高频地波雷达背景感知与目标检测技术研究
|
摘要
大范围、全天候、实时超视距探测能力使高频地波雷达(High Frequency Surface Wave Radar, HFSWR)广泛应用于海态遥感、海面目标检测和经济专属区监视等军民两用领域。垂直极化电磁波沿海面绕射传播的超视距探测机理使HFSWR舰船目标的检测不同于传统微波雷达中的检测。多种杂波与噪声(如海洋表面回波、电离层杂波、电台干扰、流星余迹、大气噪声等)的同时存在造成了HFSWR检测背景的复杂化和多样化特征。分辨单元内多源散射造成同质(亦称均匀,homogenous)/异质(亦称非均匀,nonhomogenous)回波共存,导致检测背景不仅包含高斯类杂波,而且包含时变起伏的非高斯类杂波。这些都给舰船目标检测造成了很大困难。
为此,本文通过对HFSWR检测环境的深入分析,总结了HFSWR检测环境的特点和检测难点,并根据实际系统需求提出了一种HFSWR背景感知信息处理系统。该系统包括背景感知信息提取(亦称检测场景分析)和多策略/参数检测两部分。前者通过特征提取或者模型的建立,从而完成对目标所在检测环境信息的提取和认知。包括对已有杂波的识别,对检测区域的分割和评价,检测背景分类及其统计特性分析等。后者则利用获得的背景感知信息,针对目标所处的不同环境,通过选择相应的检测策略、设置不同的检测参数实现优化检测的目的。本文将针对上述几个关键技术展开研究,主要内容如下:
1.一阶海杂波(亦称Bragg峰)的识别对HFSWR具有重要意义:一方面,在海态遥感中,其位置参数可用于海洋参数反演;另一方面,在海面动目标检测中,由于一阶海杂波具有类目标特征,因此常常造成船目标检测结果中的虚警和漏警。针对上述问题,本文提出了一种提取距离-多普勒(Range-Doppler, RD)谱脊特征作为Bragg峰位置指示信息,并结合特征知识的高频一阶海杂波及其分裂谱峰的识别方法。通过实测数据验证表明,与经典的峰值检测和仅使用特征知识的方法相比,本文提出的方法无论在船目标干扰条件下还是在强/弱洋流切变环境下,都可以获得更好的识别效果。
2.介绍了一种基于最大类间差的HFSWR检测区域分割方法。该方法利用检测背景在RD谱中的统计特性,将检测区域分割为强散射回波区、中等散射回波区、弱散射回波区和参考噪声区4个部分。该结果的一个重要应用是对扩展E层、F层电离层杂波的识别。由于覆盖范围广、强度大、时变起伏并具有不规则分布,扩展E层、F层电离层杂波对HFSWR性能造成很大威胁。为此,本文提出了一种基于区域分割结果并结合杂波区域特征的扩展E层、F层电离层杂波识别方法。首先,使用卷积模板确定杂波边缘,然后利用分割区域类型的采样占有率作为杂波区域的限定门限,从而成功的实现了对扩展电离层杂波区域的识别。实测数据结果表明,该方法可以准确的描述扩展电离层杂波对雷达检测背景的影响,对其定量的评价分析结果与实测结果相符。这一结果对杂波抑制、选频和雷达系统性能的评价有重要的参考和应用价值。
3.使用检测区域分割结果并结合检测背景的物理特征,实现了对HFSWR检测背景的分类。为了剔除各类检测背景中的异质采样,使用一元非线性回归分析方法对实际检测背景进行了预检测处理,并对处理后的各类检测背景的统计特性进行了分析。实测数据结果表明,经过预检测处理后的各类非大气噪声背景,其统计分布分别服从形状参数不同的Weibull分布,并且具有比预检测处理前更好的似然效果;而对于成分单一的大气噪声类检测背景,无需进行预检测处理即可获得其背景统计分布信息。该结果是多策略/参数检测的重要依据。
4.提出了基于背景感知信息的HFSWR多策略/参数检测方法。该方法利用前文所述技术,通过在线获取检测场景信息,经过杂波剔除、检测区域分割、检测背景分类、概率分布估计、峰值检测和Weibull双参数归一化处理等过程,实现了多策略/参数检测任务。由于根据不同类型背景的特点选择不同的检测策略/参数,本文提出的方法避免了以往检测过程中由于检测模型失配造成的检测损失。文中使用仿真目标加实测背景数据的方法进行了Monte Carlo仿真实验,并使用含有非合作目标的实测数据处理结果进一步验证了算法的性能。通过与国际上经典的和最新的高频雷达检测方法比较发现,基于背景感知信息的多策略/参数检测方法在保证虚警概率的前提下,具有更好的小目标发现能力。
与经典的和基于知识的(Knowledge-Based, KB)检测结构不同,本文通过单一类型传感器在线实时提取检测环境信息,提高了对目标所处检测环境的感知能力,从而为不同环境下的多策略/参数检测提供决策依据,可为雷达检测性能的提高、系统评价和智能管理提供有力的帮助。
High Frequency Surface Wave Radar (HFSWR) is widely used in both millitary and civilian areas such as sea state sensing, surface target detection and the surveilance of the Exlusive Economic Zone (EEZ) for its excellent capability of long range, all weather and real-time surveilance. Its mechanism utilizing a vertical polarization electromagnetic wave that follows the curvature of the earth along the air-water interface with low propagation loss on highly conductive ocean surface makes ship target detection in HFSWR different from that in microwave radar. Clutter such as sea echo, ionospheric clutter, radio frequency interference, meteor, and environment noise cause the complexity and diversity of the detection environment. Multi-source scatter makes homogenous and non-homogenous echoes coexistent which results in the detection background consists of not only Gaussian clutter but also unknown, time-variant, and fluctuated non-Gaussian clutter. All of these lead to great difficulties in ship target detection for HFSWR.
Thus, by deeply analyzing the detection environment, this dissertation summarizes detection characteristics and difficulties of HFSWR. Then an architecture of background cognitive information processing system for HFSWR is presented according to these requirements. The system consists of background cognitive information extraction (namely detection scene analysis) and multiple strategies/parameters detection. The former extracts and cognizes the environment information of the detection background by characteristics extraction and model establition, which includes clutter identification, detection region segmentation and evaluation, detection background classification and statistical analysis. The latter utilizes the background cognitive information for selecting proper detection strategies or setting parameters to optimize the detection performance. This dissertation is composed of the studies on the above-mentioned key techniques, and the outline is as follows:
1. First-order sea clutter (namely Bragg peaks) plays an important role in HFSWR. On the one hand, its location paramter can be inversion tools for sea state sensing. On the other hand, its quasi-target features often result in false alarm and missing alarm in ship target detection. To solve these problems, this dissertation proposes an algorithm to identification single and splitting first-order sea cluter in HF band which combines characteristic knowledge with the location indicative information extracted from ridge feature of Bragg peaks in Range-Doppler (RD) map. Real data experiments show that the proposed algorithm, comparing with the classical peak detection method and the characteristic- knowledge-based method, can have a better identification performance even in the environment with ship targets as interference or in the strong/weak current shear condition.
2. A detection region segmentation method is intorduced based on maximizing the separability of the resultant classes. This method uses statistics of the detection background in RD map to segment the detection region into four parts: strong scattering area, medium scattering area, weak scattering area and reference noise area. One of its most significant applications is to identificate the spread E, F layer ionospheric clutter. Wide range covering, strong intensity, time-variant, flucuated and irregular distribution of the spread E, F layer ionospheric clutter badly affects the system performance of HFSWR. A spread E, F layer ionospheric clutter identification method is proposed based on the region segmentation results and region characteristics of the clutter. First of all, convolution template is used for locating the edge of the clutter, then the ratio of the number of the samples belonging to some segmented region and the total number of the samples in the region of interest is used for setting the determinative threshold of the clutter region. Experiments manifest that the proposed method can describe the effect of the spread ionospheric clutter to HFSWR. The quantitative analysis is consistent with the real data observation. The result can be used as a worthwhile reference for clutter mitigation, carrier frequency selection or radar system evaluation.
3. Detection background classification is achieved by combining the region segmentation results and the physical features of the detection background. Unary non-linear regression analysis method is utilized for pre-detection which elimites the non-homogenous samples in the detection background. Then, statistical analysis is operated on the different types of the detection background. Experiments with real data show that the statistical distribution in the pre-detected non-atmospheric noise background follows Weibull distribution with different shape parameters with a better likelihood than that without pre-detection. While the statistical distribution information of atmospheric noise background consisting of single component can be got without pre-detection. The result is an important basic for multiple strategies/parameters detection method.
4. Background-cognitive-information-based multiple strategies/ parameters detection method for HFSWR is proposed. Multiple strtegies/parameters detection method is implemented by utilizing on-line accessed detection scene information, including clutter elimination, detection region segementation, detection background classification, statistical distribution estimation, peak detection, and 2-parameter normalization of Weibull distribution, etc. Selecting proper detection stategies/ parameters according to the different characteristics of the background help this method reduce the detection loss which often happens in the classical detectors because of model mismatch. Monte Carlo simulation with sythetic targets in real data as background is operated and experiments with real data is used for further verifying the performance of the algorithm. Comparing the proposed method with the classical and latest HF detection algorithms, it’s found that the background-cognitive-information-based multiple strategies/paramters method has a better capability of detecting weak targets within a proper false alarm rate.
In summary, compared with the classical and the Knowledge-Based (KB) detector, the proposed methods can extract the information of detection environment on-line by a single type of sensor. The capability of being aware of target’s surrounding environment is improved which is the decision basis for multiple strategies/parameters detection in different environment and can provide effective help in detection optimization, system performance evaluation and intelligent management.
为此,本文通过对HFSWR检测环境的深入分析,总结了HFSWR检测环境的特点和检测难点,并根据实际系统需求提出了一种HFSWR背景感知信息处理系统。该系统包括背景感知信息提取(亦称检测场景分析)和多策略/参数检测两部分。前者通过特征提取或者模型的建立,从而完成对目标所在检测环境信息的提取和认知。包括对已有杂波的识别,对检测区域的分割和评价,检测背景分类及其统计特性分析等。后者则利用获得的背景感知信息,针对目标所处的不同环境,通过选择相应的检测策略、设置不同的检测参数实现优化检测的目的。本文将针对上述几个关键技术展开研究,主要内容如下:
1.一阶海杂波(亦称Bragg峰)的识别对HFSWR具有重要意义:一方面,在海态遥感中,其位置参数可用于海洋参数反演;另一方面,在海面动目标检测中,由于一阶海杂波具有类目标特征,因此常常造成船目标检测结果中的虚警和漏警。针对上述问题,本文提出了一种提取距离-多普勒(Range-Doppler, RD)谱脊特征作为Bragg峰位置指示信息,并结合特征知识的高频一阶海杂波及其分裂谱峰的识别方法。通过实测数据验证表明,与经典的峰值检测和仅使用特征知识的方法相比,本文提出的方法无论在船目标干扰条件下还是在强/弱洋流切变环境下,都可以获得更好的识别效果。
2.介绍了一种基于最大类间差的HFSWR检测区域分割方法。该方法利用检测背景在RD谱中的统计特性,将检测区域分割为强散射回波区、中等散射回波区、弱散射回波区和参考噪声区4个部分。该结果的一个重要应用是对扩展E层、F层电离层杂波的识别。由于覆盖范围广、强度大、时变起伏并具有不规则分布,扩展E层、F层电离层杂波对HFSWR性能造成很大威胁。为此,本文提出了一种基于区域分割结果并结合杂波区域特征的扩展E层、F层电离层杂波识别方法。首先,使用卷积模板确定杂波边缘,然后利用分割区域类型的采样占有率作为杂波区域的限定门限,从而成功的实现了对扩展电离层杂波区域的识别。实测数据结果表明,该方法可以准确的描述扩展电离层杂波对雷达检测背景的影响,对其定量的评价分析结果与实测结果相符。这一结果对杂波抑制、选频和雷达系统性能的评价有重要的参考和应用价值。
3.使用检测区域分割结果并结合检测背景的物理特征,实现了对HFSWR检测背景的分类。为了剔除各类检测背景中的异质采样,使用一元非线性回归分析方法对实际检测背景进行了预检测处理,并对处理后的各类检测背景的统计特性进行了分析。实测数据结果表明,经过预检测处理后的各类非大气噪声背景,其统计分布分别服从形状参数不同的Weibull分布,并且具有比预检测处理前更好的似然效果;而对于成分单一的大气噪声类检测背景,无需进行预检测处理即可获得其背景统计分布信息。该结果是多策略/参数检测的重要依据。
4.提出了基于背景感知信息的HFSWR多策略/参数检测方法。该方法利用前文所述技术,通过在线获取检测场景信息,经过杂波剔除、检测区域分割、检测背景分类、概率分布估计、峰值检测和Weibull双参数归一化处理等过程,实现了多策略/参数检测任务。由于根据不同类型背景的特点选择不同的检测策略/参数,本文提出的方法避免了以往检测过程中由于检测模型失配造成的检测损失。文中使用仿真目标加实测背景数据的方法进行了Monte Carlo仿真实验,并使用含有非合作目标的实测数据处理结果进一步验证了算法的性能。通过与国际上经典的和最新的高频雷达检测方法比较发现,基于背景感知信息的多策略/参数检测方法在保证虚警概率的前提下,具有更好的小目标发现能力。
与经典的和基于知识的(Knowledge-Based, KB)检测结构不同,本文通过单一类型传感器在线实时提取检测环境信息,提高了对目标所处检测环境的感知能力,从而为不同环境下的多策略/参数检测提供决策依据,可为雷达检测性能的提高、系统评价和智能管理提供有力的帮助。
High Frequency Surface Wave Radar (HFSWR) is widely used in both millitary and civilian areas such as sea state sensing, surface target detection and the surveilance of the Exlusive Economic Zone (EEZ) for its excellent capability of long range, all weather and real-time surveilance. Its mechanism utilizing a vertical polarization electromagnetic wave that follows the curvature of the earth along the air-water interface with low propagation loss on highly conductive ocean surface makes ship target detection in HFSWR different from that in microwave radar. Clutter such as sea echo, ionospheric clutter, radio frequency interference, meteor, and environment noise cause the complexity and diversity of the detection environment. Multi-source scatter makes homogenous and non-homogenous echoes coexistent which results in the detection background consists of not only Gaussian clutter but also unknown, time-variant, and fluctuated non-Gaussian clutter. All of these lead to great difficulties in ship target detection for HFSWR.
Thus, by deeply analyzing the detection environment, this dissertation summarizes detection characteristics and difficulties of HFSWR. Then an architecture of background cognitive information processing system for HFSWR is presented according to these requirements. The system consists of background cognitive information extraction (namely detection scene analysis) and multiple strategies/parameters detection. The former extracts and cognizes the environment information of the detection background by characteristics extraction and model establition, which includes clutter identification, detection region segmentation and evaluation, detection background classification and statistical analysis. The latter utilizes the background cognitive information for selecting proper detection strategies or setting parameters to optimize the detection performance. This dissertation is composed of the studies on the above-mentioned key techniques, and the outline is as follows:
1. First-order sea clutter (namely Bragg peaks) plays an important role in HFSWR. On the one hand, its location paramter can be inversion tools for sea state sensing. On the other hand, its quasi-target features often result in false alarm and missing alarm in ship target detection. To solve these problems, this dissertation proposes an algorithm to identification single and splitting first-order sea cluter in HF band which combines characteristic knowledge with the location indicative information extracted from ridge feature of Bragg peaks in Range-Doppler (RD) map. Real data experiments show that the proposed algorithm, comparing with the classical peak detection method and the characteristic- knowledge-based method, can have a better identification performance even in the environment with ship targets as interference or in the strong/weak current shear condition.
2. A detection region segmentation method is intorduced based on maximizing the separability of the resultant classes. This method uses statistics of the detection background in RD map to segment the detection region into four parts: strong scattering area, medium scattering area, weak scattering area and reference noise area. One of its most significant applications is to identificate the spread E, F layer ionospheric clutter. Wide range covering, strong intensity, time-variant, flucuated and irregular distribution of the spread E, F layer ionospheric clutter badly affects the system performance of HFSWR. A spread E, F layer ionospheric clutter identification method is proposed based on the region segmentation results and region characteristics of the clutter. First of all, convolution template is used for locating the edge of the clutter, then the ratio of the number of the samples belonging to some segmented region and the total number of the samples in the region of interest is used for setting the determinative threshold of the clutter region. Experiments manifest that the proposed method can describe the effect of the spread ionospheric clutter to HFSWR. The quantitative analysis is consistent with the real data observation. The result can be used as a worthwhile reference for clutter mitigation, carrier frequency selection or radar system evaluation.
3. Detection background classification is achieved by combining the region segmentation results and the physical features of the detection background. Unary non-linear regression analysis method is utilized for pre-detection which elimites the non-homogenous samples in the detection background. Then, statistical analysis is operated on the different types of the detection background. Experiments with real data show that the statistical distribution in the pre-detected non-atmospheric noise background follows Weibull distribution with different shape parameters with a better likelihood than that without pre-detection. While the statistical distribution information of atmospheric noise background consisting of single component can be got without pre-detection. The result is an important basic for multiple strategies/parameters detection method.
4. Background-cognitive-information-based multiple strategies/ parameters detection method for HFSWR is proposed. Multiple strtegies/parameters detection method is implemented by utilizing on-line accessed detection scene information, including clutter elimination, detection region segementation, detection background classification, statistical distribution estimation, peak detection, and 2-parameter normalization of Weibull distribution, etc. Selecting proper detection stategies/ parameters according to the different characteristics of the background help this method reduce the detection loss which often happens in the classical detectors because of model mismatch. Monte Carlo simulation with sythetic targets in real data as background is operated and experiments with real data is used for further verifying the performance of the algorithm. Comparing the proposed method with the classical and latest HF detection algorithms, it’s found that the background-cognitive-information-based multiple strategies/paramters method has a better capability of detecting weak targets within a proper false alarm rate.
In summary, compared with the classical and the Knowledge-Based (KB) detector, the proposed methods can extract the information of detection environment on-line by a single type of sensor. The capability of being aware of target’s surrounding environment is improved which is the decision basis for multiple strategies/parameters detection in different environment and can provide effective help in detection optimization, system performance evaluation and intelligent management.
引文
1 D. D. Crombie. Doppler Spectrum of Sea Echo at 13.67MHz. Nature. 1955, 175: 681~682
2 L. Sevgi, A. Ponsford, H. C. Chan. An Integrated Maritime Surveillance System Based on High-Frequency Surface-Wave Radars, Part 1: Theoretical Background and Numerical Simulations. IEEE Antennas and Propagation Magazine. 2001, 43(4): 28~43
3 M. I. Skolnik. Radar Handbook. 3rd Edition. Artech House, 2008: 20.43~20.45, 7.1~7.2, 7.22, 7.11
4 M. Roughan, E. J. Terrill, J. L. Largier, etc. Observations of Divergence and Upwelling around Point Loma, California. Journal of Geophysical Research. 2005, 110: 1~13
5 B. Lipa, B. Nyden. Directional Wave Information from the SeaSonde. IEEE Journal of Oceanic Engineering. 2005, 30(1): 221~231
6 B. K. Haus, M. Wang, L. K. Shay, etc. HF Radar Observation of Wave Directional Spectra in a Strong Current Regime. Oceans-Europe 2007, 18-21 June 2007: 1~5
7 L. R. Wyatt, J. J. Green, A. Middleditch, etc. Operational Wave, Current, and Wind Measurements with the Pisces HF Radar. IEEE Journal of Oceanic Engineering. 2006, 31(4): 819~834
8 M. Skolnik. Opportunities in Radar-2002. Electronics & Communication Engineering Journal. 2002.12: 263~272
9 K. W. Gurget, T. Schlick. HF radar wave measurements in the presence of ship echoes-problems and solutions. Oceans-Europe 2005: 937~941
10 T. Thayaparan, L. J. Stankovic, M. Dakovic. A Novel Approach for the Detection of Maneuvering Air Targets in Sea-Clutter using High-Frequency Surface-Wave Radar. Defence R&D Canada-Ottawa Technical Report. Dec. 2005: 1~68
11 D. Trizna, L. Xu. Target Classification and Remote Sensing of Ocean Current Shear Using a Dual-Use Multifrequency HF Radar. IEEE Journal of Oceanic Engineering. 2006, 31(4): 904~918
12 M. L. Heron, B. Willis. HF Ocean Surface Radar Monitoring for Coral Bleaching in the Great Barrier Reef. OCEANS 2006: 1~5
13 J. F. Vesecky, J. Drake, K. Laws, etc. Coastal Eddies in the Ocean Wind Field as Observed by Single and Multifrequency HF Radars on Monterey Bay, California. OCEANS 2007 EUROPE, Jun. 18-21, 2007: 1~5
14 J. S. Bathgate, M. L. Heron, A. Prytz. A Method of Swell-Wave Parameter Extraction from HF Ocean Surface Radar Spectra. IEEE Journal of Oceanic Engineering. 2006, 31(4): 812~818
15 K-W Gurgel, H-H Essen, T. Schlick. An Empirical Method to Derive Ocean Waves from Second-Order Bragg Scattering Prospects and Limitations. IEEE Journal of Oceanic Engineering, 2006, 31(4): 804~811
16 M. L. Parkinson. Observations of the broadening and coherence of MF lower HF surface-radar ocean echoes. IEEE Journal of Oceanic Engineering, 1997, 2(2): 347~363
17 R. Guinvarc’h, M. Lesturgie, R. Durand, etc. On the Use of HF Surface Wave Radar in Congested Waters Influence of Masking Effect on Detection of Small Ships. IEEE Journal of Oceanic Engineering. 2006, 31(4): 894~903
18 H. Leong, A. Ponsford. The Effects of Sea Clutter on The performance of HF Surface Wave Radar in Ship Detection. 2008 Radar Conference. May 2008: 1~6
19 D. J. Emery. The Choice of Operating Frequency in HF Surface Wave Radar Design. Ninth International Conference on HF Radio Systems and Techniques. Jun. 23-26, 2003: 278~281
20 L. Sevgi, A. Ponsford, H. C. Chan. An Integrated Maritime Surveillance System Based on High-Frequency Surface-Wave Radars, Part 2: Operational Status and System Performance. IEEE Antennas and Propagation Magazine. 2001, 43(5): 52~63
21 D. J. Emery. Some Aspects of Design and Enviromental Management in HF Surface Wave Radar. Radar 2002: 51~55
22强勇.高频雷达抗干扰与目标检测方法.西安电子科技大学博士学位论文. 2004: 7~8
23 T. Thayaparan, J. MacDougall. Evaluation of ionospheric sporadic-E clutter in an arctic environment for the assessment of high-frequency surface-wave radar surveillance. IEEE Transactions on Geoscience and Remote Sensing. 2005, 43(5): 1180~1188
24黄亮,文必洋,吴立明等. HFSWR电离层干扰抑制研究.电波科学学报. 2007, 22(4): 626~630
25 X. Wan, F. Chen, H. Ke. Experimental trials on ionospheric clutter suppression for high-frequency surface wave radar. IEE Proc.-Radar Sonar Navig. 2006, 153(1): 23~29
26 F. Jangal, S. Saillant, M. Helier. Ionospheric clutter mitigation using one-dimensional or two-dimensional wavelet processing. IET Radar, Sonar and Navigation. 2009, 3(2): 112~121
27 A. L. Dzvonkovskaya, H. Rohling. Target Detection with Adaptive Power Regression Thresholding for HF Radar. 2006 International Radar Conference. Oct. 2006: 1~4
28强勇,侯彪,焦李成,保铮.天波超视距雷达抑制流星余迹干扰方法的研究.电波科学学报. 2003, 18(1): 23~27
29权太范,李建巍,于长军.高频雷达抑制冲击干扰的研究和实验.电子学报. 1999, 27(12): 23~25.
30 H. Zhou, B. Wen, S. Wu. Dense Radio Frequency Interference Suppression in HF Radars. IEEE Signal Processing Letters, 2005, 12(5): 361~364
31 G. A. Fabrizio, G. J. Frazer, M. D. Turley. STAP For Clutter And Interference Cancellation in A HF Radar System: ICASSP2006: 1033~1036
32 L. Huang, B. Wen. Impulsive Interference Mitigation in High Frequency Radar. IEEE Conference on Industrial Electronics and Applications. ICIEA 2006: 1~4
33周文瑜,焦培南等.超视距雷达技术.电子工业出版社, 2008: 1, 95~98, 358~370
34王金荣,张宁.高频地波超视距雷达.雷达与对抗. 1994.3: 1~6
35 J. M. Headrick, J. F. Thomason. Applications of High-Frequency Radar. Radio Science. 1998, 33(4): 1045~1054
36 D. Barrick, D. James, J. Isaacson. Marrying Quantitative and Graphic Tidal Analysis Tools with HF Radar Current Map Outputs. Proceedings of the IEEE/OES Seventh Working Conference on Current Measurement Technology. Mar. 13-15, 2003: 105~110
37 D. Barrick. History Present Status and Future Directions of HF Surface Wave Radar in the US. Proceedings of International Conference on Radar 2003: 652~655
38 http://www.codar.com/support_doc.htm: Seasonde_sellsheet
39 L. Wyatt, J. Venn, G. Burrows, etc. HF radar measurements of ocean wave parameters during NURWEC. IEEE Journal of Oceanic Engineering. 1986, 11(2): 219~221
40 S. J. Anderson, P. J. Edwards, P. Marrone, etc. Investigations with SECAR: a bistatic HF surface wave radar. Radar 2003. 2003: 717~722
41 B. A. Johnson, P. F. Amey, Shane Braendler, Michael D.E. Turley. In-Service Enhancements of the Jindalee Over-The-Horizon Radars. Proceedings of International Conference on Radar 2008. Oct. 2008: 218~223
42 H. C. Chan. Charaterization of ionospheric clutter in HF surface wave radar. Defence R&D Canada- Ottawa Technical Report. DRDC Ottawa TR 2003-114. Sep. 2003: 1~70
43 C. Kenny, N. K. Atkins, T. Banks, etc. Canadian Security Guide book, 2007: 14~47
44 K. W. Gurgel, H. H. Essen, T. Sclick. HF Surface Wave Radar for Oceanography: A Review of Activities in Germany. Proceedings of International Conference on Radar 2003. Sep. 2003: 700~705
45 A. L. Dzvonkovskaya, H. Rohling, K.-W. Gurgel. First Results of Ship Detection and Tracking Using WERA HF Radar System. Proceedings of International Radar Symposium IRS 2007. Sep. 2007: 249~254
46 M. Lesturgie, J. P. Eglizeaud, G. Auffray. The Last Decades and The Future of Low Frequency Radar Concepts in France. Proceedings of International Conference on Radar 2004: 1~2
47 Y. Hisaki. Development of HF Ocean Radar in Japan. Proceedings of International Conference on Radar. Sep. 2003: 510~514
48 Y. Liu, R. Xu, N. Zhang. Progress in HFSWR Research at Harbin Institute of Technology. Proceedings of International Conference on Radar 2003. Sep. 2003: 522~528
49文必洋,黄为民,王小华. OSMAR2000探测海面风浪场原理与实现.武汉大学学报(理学版). 2001, 47(5): 642~644
50苏洪涛,张守宏,保铮.空时超分辨方法在高频地波超视距雷达中的应用.电子学报. 2003, 34(3):437~440
51郭佩芳.地波雷达要干资料的反演及应用研究.中国科学院研究生院博士学位论文. 2006: 10~13
52 H. L.范特里斯著.检测、估计和调制理论:卷Ⅰ检测、估计和线性调制理论.张其善,毛士艺,周荫清译.电子工业出版社, 2007: 5~8, 226~234
53 M. O. Kolawo. Radar System, Peak Detection and Tracking. Newnes Publications, 2002: 275~281
54 S. M. Kay.统计信号处理基础——估计与检测理论.罗鹏飞,张文明,刘忠等译.电子工业出版社, 2006: 501~505
55 M. A. Richards. Fundamentals of Radar Signal Processing. McGraw-Hill Companies, 2005:285~286
56伊伏斯·里迪著.现代雷达原理.卓荣邦等译.电子工业出版社, 1991: 384
57段凤增编.信号检测理论(第二版).哈尔滨工业大学出版社, 2002: 188
58 J. Guan, Y. N. Peng, Y. He, Proof of CFAR by the Use of the Invariant Test. IEEE Transactions on Aerospace and Electronic Systems. 2000, 36(1): 336~339
59 H. M. Finn, R. S. Johnson. Adaptive detection mode with threshold control as a function of spatially sampled clutter level estimates. RCA Review. 1968, 29: 414~463
60 H. Rohling. Radar CFAR Resolution of Targets Using Automatic Detectors. IEEE Transactions on Aerospace and Electronic Systems. 1983, 19(4): 608~621
61 J. T. Rickard, G. M. Dillard. Adaptive detection algorithms for multiple target situations. IEEE Transactions on Aerospace and Electronic Systems. 1977, 13(4): 338~343
62 P. P. Gandhi, S. A. Kassam. Analysis of CFAR Processors in Nonhomogeneous Background. IEEE Transactions on Aerospace and Electronic Systems. 1988, 24(4): 427~445
63 J. A. Ritcey, J. L. Hines. Performance of MAX family of order-statistic CFAR detectors. IEEE Transactions on Aerospace and Electronic Systems. 1991, 27(1): 48~57
64 M. B. ElMashade. Detection analysis of linearly combined order statistic CFAR algorithms in nonhomogeneous background environments. Signal Process. 1998, 68: 59~719
65 C. J. Kim, D. S. Han, H. S. Lee. Generalized OSCFAR detector with noncoherent integration. Signal Process. 1993, 31(1): 43~56
66 S. D. Himonas, M. Barkat. Automatic censored CFAR detection for nonhomogeneous environments. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(1): 286~304
67 R. Srinivasan. Robust radar detection using ensemble CFAR processing. IEEProc.-Radar Sonar Navig. 2000,147(6): 291~297
68 M. E. Smith, P. K. Varshney. Intelligent CFAR processor based on data variability. IEEE Transactions on Aerospace and Electronic Systems. 2000, 36(3): 837~847
69 A. Farrouki, M. Barkat. Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments. IEE Proc.-Radar Sonar Navig. 2005, 162(1): 43~51
70 T. V. Cao. Constant False-Alarm Rate Algorithm Based on Test Cell Information. IET Radar Sonar Navig. 2008, 2(3): 200~213
71 V. G. Hansen. A. Olsen. Nonparametric radar extraction using a generalized sign test. IEEE Transactions on Aerospace and Electronic Systems. 1971, 7(5): 942~952
72何友,关键,彭应宁等著.雷达自动检测与恒虚警处理.清华大学出版社, 1999: 34~39, 172
73 S. D. Himonas. A Robust Automatic Censored CFAR Detection for Non-Homogeneous Environments. IEEE International Radar Conference. 1991: 117~121
74 R. Srinivasan. Robust Radar Detedtion Using Ensemble CFAR Processing. IEE Proc-F. 2000, 147: 291~297
75 H. Wang. Robust CFAR Detect in Nonhomeeneous Correlated Interference. Proceedings of IEEE Internation Radar Conference. 1992: 373~376
76 M. Greco, F. Gini. Robust CFAR Detection of Randeom Signals in Compound Gaussian Clutter Plus Thermal Noise. IEEE Proc-F. 2001, 148: 227~232
77 Mark G. Rutten, Branko Ristic, Neil J. Gordon. A Comparison of Particle Filters or Recursive Track-before-detect. 2005 7th International Conference on Information Fusion (FUSION). 2005: 169~175
78 H. IM, T. Kim. Optimization of Multiframe Target Dtection Schemes. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(1): 176~187
79 J. D. R. Jr. Kramer, W. S. Reid. Track-before-detect processing for an airborne type radar. IEEE International Radar Conference 1990. 1990: 422~427.
80 K. Punithakumar, T. Kirubarajan, A.Sinha. A Sequential Monte Carlo Probability Hypothesis Density Algorithm for Multitarget Track-Before-Detect. Signal and Data Processing of Small Targets 2005. Proc. of SPIE Vol. 59131S: 1~8
81 Y. Borers, H. Driessen. A Particle-Filter-Based Detection Scheme. IEEE SignalProcessing Letters. 2003, 10: 300~302
82 B-N Vo, S. Singh, A. Doucet. Sequential Monte Carlo implementation of the PHD filter for multitarget tracking. Proceedings of the Sixth International Conference of Information Fusion, Vol.2, July 2003: 792~799
83 K. Punithakumar, T. Kirubarajan, A. Sinha. A Sequential Monte Carlo Probability Hypothesis Density Algorithm for Multitarget Track-Before-Detect. Signal and Data Processing of Small Targets 2005. Proc. of SPIE Vol. 59131S: 1~8
84 W. Ng, J. Li, S. Godsill, etc. A Hybrid Approach for Online Joint Detection and Tracking for Multiple Targets. Aerospace 2005 IEEE Conference: 1~16
85 S. C. A. Thomopoulos, R. Viswanathan, D. K. Bougoulias. Optimal Decision Fusion in Multiple Sensor Systems. IEEE Transactions on Aerospace and Electronic Systems. 1987, 23: 644~653
86 M. Xiang, J. Zhao. New Results on the Performance of Distributed Bayesian Detection Systems. IEEE Transactions Syst., Man, Cybern., 2001,31(1): 73~78
87 E. Coiras, P.-Y. Mignotte, Y. Petillot, J. Bell, K. Lebart. Supervised Target Detection and Classification by Training on Augmented Reality Data. IET Radar Sonar Navig. 2007, 1(1): 83~90
88 S. López-Estrada, R. Cumplido. Fusion Center with Neural Network For Target Detection in Background Clutter. IEEE Proceedings of the Sixth Mexican International Conference on Computer Science (ENC’05), 2005: 189~196
89 A. L. Chan, S. Z. Der, N. M. Nasrabadi. A Joint Compression-Discrimination Neural Transformation Applied to Target Detection. IEEE Transactions Syst., Man, Cybern.—Part B: Cyber Netics. 2005, 35(4): 670~681
90 P. Willett, W. Chen. Wavelets in the Frequency Domain for Narrowband Process Detection. 2001 IEEE International Conference on Acoustics, Speech and Signal Processing. 2001: 3193~3196
91 X. Ma, C. Zhou. Automated Wavelet Selection and Thresholding for PD Detection. IEEE Electrical Insulation Magazine. 2002, 38: 202~216
92 S. Haykin, Y. Xue, T. N. Davidson. Optimal Waveform Design for Cognitive Radar. 42nd Asilomar Conference on Signals, Systems and Computers. Oct. 2008, Pacific Grove, CA. 2008: 3~7
93 D. Gan, S. H. Zeng. High-Order Fractal Characteristion of Sea-Scattered Signals and Detection of Sea-Surface Targets. Electronics Letters. 1999, 35: 424~425
94梁宗闯,刘兴钊,郑薇.基于高阶谱技术地波超视距雷达信号检测算法.系统工程与电子技术. 1999, 21(5): 128~133
95 B. T. Root. Joint Time-Frequency Analysis of Over-The-Horizon Radar Data. Proceedings of SPIE Vol. 4738 2002: 217~229
96 L. Jubisa Stankovic, Thayananthan Thayaparan, Milos Dakovic. Signal Decomposition by Using the S-Method Application to the Analysis of HF Radar Signal Sea-Clutter. IEEE Transactions on Signal Processing. 2006, 54(11): 4332~4342
97 D. Gan, S. H. Zeng. Detection of Sea-surface Radar Targets Based on Multifractal Analysis. Electronics Letters. 2000, 36(13): 1144~1145
98 L. M. Kaplan. Improved SAR Target Detection Via Extended Fractal Features. IEEE Transactions on Aerospace and Electronic Systems. 2001, 37(2): 436~451
99 M. A. Khabou, P. D. Gader. Automatic Target Detection using Entropy Optimized Shared-weight Neural Networks. IEEE Transactions on Neural Networks. 2001, 11(1): 186~193
100 A. Nelander. Model-based Adaptive Detection of Fluctuating Targets. 2000 IEEE International Radar Conference. 2000: 231~386
101杨强,刘永坦. HFSWR目标识别检测方法.高技术通讯. 2000.10: 37~41
102 Y. F. Vincent. Radar Target Detection using Feature Extraction. IRS 1998 International Symposium on Radar. 1998: 705~714
103 A. D. Maio. Rao Test for Adaptive Detection in Gaussian Interference with Unknown Covariance Matrix. IEEE Transactions on Signal Processing, 2007, 55(7): 3577~3584
104 F. Bandiera, A. D. Maio. Adaptive Radar Detection of Distributed Targets in Homogeneous and Partially Homogeneous Noise Plus Subspace Interference. IEEE Transactions on Signal Processing, 2007, 55(4): 1223~1237
105 L. Sevgi. Target Reflectivity and RCS Interactions in Integrated Maritime Surveillance Systems Based on Surface-wave High-frequency Radars. IEEE Antennas and PropagationMagazine. 2001, 42: 36~51
106 G. Jones, S. Haykin. Higher-dimension Detection of Targets form Scanned Radar. IEE Proc-F. 1996, 143(5): 313~320
107杨强,刘永坦.复杂背景下的二维检测研究.系统工程与电子技术. 2002, 24(1): 34~37
108 S. Russell, P. Norvig. Artificial Intelligence: A Modern Approach. 2nd Edition.Prentice Hall, 2003: 724~725
109 G. T. Capraro, A. Frina, H. Griffiths, etc. Knowledge-based Radar signal and Data Processing: A Tutorial Review. IEEE Signal Processing Magazine. 2006, 23(1): 18~29
110 E. Conte, A. D. Maio, A. Farina, etc. Design and Analysis of a Knowledge-aided Radar Detector for Doppler Processing. IEEE Trasaction on Aerospace and Electronic Systems. 2006, 42(1): 1058~1079
111 G. Gini, M. Rangaswamy. Knowledge-Based Radar Detection, Tracking, and Classification. John Wiley & Sons, 2008: 103~126
112 S. Haykin. Cognitive Radar Networks. IEEE International Workshop on Computational Advanced in Multisensor Adaptive Processing. 13-15 Dec. 2005: 1~3
113 S. Haykin. Cognitive Radar: A Way of the Future. IEEE Signal Processing Magazine. 2006.1: 30~40
114 S. B. Gelfand, T. E. Fortmann, Y Bar-Shalom. Adaptive Detection Threshold Optimization for Tracking in Clutter. IEEE Transaction on Aerospace and Electronic Systems, 1996, 55(7): 514~523
115 A. Vizinho, L. R. Wyatt. Modern spectral analysis in HF radar remote sensing. OCEANS '96. MTS/IEEE. Sep. 1996: 1500~1503
116 A. Vizinho, L. R. Wyatt. Evaluation of the Use of The Modified-Covariance Method in HF Radar Ocean Measurement. IEEE Journal of Oceanic Engineering. 2001, 26(4): 832~840
117 R. J. Martin, M. J. Kearney. Remote sea current sensing using HF radar: an autoregressive approach. IEEE Journal of Oceanic Engineering. 1997, 22(1): 151~155
118 Z. Liang, X. Liu, Y. Liu. A Signal Detection Algorithm Based on Higher-Order Statistics for HFSW-OTH radar. 2001 CIE International Conference on Radar. 15-18 Oct. 2001: 996 ~1000
119 R. James. Ship Detection with high-resolution HF Sky-wave radar. IEEE Journal Oceanic Engineering. 1986, 11(2): 196~209
120 S. J. Anderson, A. R. Mahoney. Application of Superresolution Techniques to HF Radar Sea Echo Analysis. The Pacific Ocean Remote Sensing Conference. Melbourne, Australia, March,1994: 1~4
121 T. Ponsford, R. Dizaji. System and method for spectral generation in radar.United States Patent Application Publication. Pub, No: Us 2004/0178951 A1. Sep, 2004
122 R. Dizaji, T. Ponsford. Adaptive system and method for radar detection. United States Patent Application Publication. Pub, NO: Us 2003/0174088 A1, Sep, 2003
123 H. Leong. Adaptive Nulling of Skywave Interference Using Horiziontal Diplole Antennas in a Coastal Surveillance HF Surface Wave Radar System. Proceedings of IET Radar 97. Oct. 1997: 26~30
124 X. Wan, H. Ke, B. Wen. Adaptive Ionospheric Clutter Suppression Based on Subarrays in Monostatic HF Surface Wave Radar. IEE Proceedings of Radar, Sonar and Navigation. 2005, 152(2): 89~96
125 X. Mao, Y. Liu, W. Deng. Radio Disturbance of High Frequency Surface Wave Radar. Electronc Letters. 2004, 40(3): 202~203
126 H. Leong, A. Ponsford. The advantage of dual-frequency operation in ship tracking by HF surface wave radar. Radar 2004, International conference on Radar system. Toulouse, France. Oct, 2004: 233~237
127 D. E. Barrick. First-order theory and analysis of MF/HF/VHF scatter from the sea. IEEE Transactions on Antennas Propagation. 1972, 20(1): 2~10.
128 D. E. Barrick, J. M. Headrick, R. W. Bogle, D. D. Crombie. Sea backscatter at HF: interpretation and utilization of the echo. Proceedings of IEEE. 1974, 62(6): 673~687
129 L. R. Wyatt. High-Frequency Radar Measurements of the Ocean Wave -Directional Spectrum. IEEE Journal of Oceanic Engineering. 1991, 16(1): 163~169
130 R. H. Khan. Ocean-clutter model for high frequency radar. IEEE Journal of Oceanic eigineering. 1991, 16(2): 181~188
131 M. W. Y. Poon, R. H. Khan, S. L. Ngoc. A singular value decomposition (SVD) based method for suppressing ocean clutter in high frequency radar. IEEE Trans on signal processing. 1993, 41(3): 1421~1425
132 J. Wang. High resolution methods for small target detection and estimation in high frequency radar. Ph.D. dissertation. University of Victoria, Canada. 2004: 1~20
133 C. W. Anderson, S. D. Green, S.P. Kingsley. HF Skywave Radar: Estimating Aircraft Heights Using Super-Resolution in Range. Radar, Sonar andNavigation, IEE Proceedings, 1996, 143(4): 281~285
134谢俊好.舰载高频地波雷达目标检测与估值研究.哈尔滨工业大学博士学位论文. 2000: 29~47
135郭欣.天波超视距雷达信号处理技术研究.南京理工大学博士学位论文. 2003: 31~51
136 B. T. Root. Joint Time-Frequency Analysis of Over-The-Horizon Radar Data. Proceedings of SPIE Vol. 4738, 2002: 217~229
137 R. Gui, R. Weigel. Detecting targets of variable acceleration with High Frequency Surface Wave Radar. International Radar Symposium 2008. May 2008: 1~4
138桂任舟,杨子杰.基于信号分解的时频分析方法在HFSWR目标监测中的应用研究.武汉大学学报(信息科学版). 2006.7: 653~656
139周浩,文必洋,吴世才等.基于时频分析的高频雷达目标检测与定向.电子学报. 2005.12: 2265~2268
140 X. Wan, H. Ke, B. Wen. Adaptive Cochannel Interference Suppression Based on Subarrays for HFSWR. IEEE signal processing letters. 2005, 12(2): 162~165
141 D. Ramakrishnan, J. Krolik. Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter. IEEE Transactions on Aerospace and Electronic Systems. 2009, 45(2): 484~500
142 S. J Anderson, J. M. Fan, P. Jiao. Enhanced OTHR ship detection via dual frequency operation. 2001 IEEE CIE International Radar Conference. 2001: 85~89
143 P. K. Jeans, R. Donnelly. Four element CODAR beamforming. IEEE Journal of Ocean Engineering. 1986, 11(2): 296~303
144 J. Arnold, S. W. Shaw, H. Pasternack. Efficient Target Tracking Using Dynamic Programming. IEEE Transactions on Aerospace and Electronic Systems. 1993, 29(1): 44 ~56
145乔晓林.高频地波超视距雷达中的检测问题.哈尔滨工业大学博士学位论文. 1991: 20~30
146王威.高频地波超视距雷达目标检测与估值的研究.哈尔滨工业大学博士学位论文. 1997: 21~22
147沈一鹰.高频地波超视距雷达信号检测器的设计.哈尔滨工业大学博士学位论文. 2000: 4~20
148杨强.高频地波雷达检测器研究.哈尔滨工业大学博士学位论文. 2002: 7~11, 17~29
149 R. K. Jarrott, T. A. Soame. The Processing of HF Skywave Radar Signals. 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, 19-22 April, 1994: VI/165~VI/168
150 F. E. Nathaanson, J. P. Reilly, M. N. Cohen. Radar Design Principles. McGraw-Hill. 1991: 143~144
151 M. D. E. Turley. Hybrid CFAR techniques for HF radar. 1997 IEEE International Conference on Radar, 1997: 36~40
152 A. M. Zoubir. Statistical Signal Processing For Application to Over-The-Horizon Radar. 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1994. ICASSP-94 , 19-22 April 1994: VI/113 ~VI/116
153 X. Lu, J. Wang, R. Dizaji, etc. A Switching Constant False Alarm Rate Technique for High Frequency Surface Wave Radar. CCECE 2004-CCGEI: 2081~2084
154 A. Dzvonkovskaya, H. Rohling. CFAR Target Detection Based on Gumbel Distribution for HF Radar. 2006 International Radar Symposium. May 24-26, 2006: 1~4
155 M. D. E. Turley. Signal Processing Techniques for Maritime Surveillance with Skywave Radar. 2008 International Conference on Radar, Adelaide, Australia, Sep. 2008: 241~246
156 A. Dzvonkovskaya, K-W Gurgel, H. Rohling, etc. Low Power High Frequency Surface Wave Radar Application for Ship Detection and Tracking. 2008 International Conference on Radar. Adelaide, Australia, Sep. 2008: 627~632
157 D. G. Money, D. J. Emery, G. Dickel. Intelligent Radar Management Techniques in High Frequency Surface Wave Radar. 2007 3rd Institution of Engineering and Technology Seminar on Intelligent Sensor Management. May 2007: 1~11
158 I. D. Longstaff. New Technologies and New Techniques-Radar Developments in Australia. 2008 International Radar Conference. May 2008: 19~24
159 D. J. Emery, G. Dickel. The operation and performance of a multi-frequency HF Surface wave Radar. 2008 International Radar Conference. May 2008: 1~6
160 D. E. Barrick, J. M. Headrick, R. W. Bogle, etc. Sea Backscatter at HF:Interpretation and Utilization of the Echo. Proceedings of IEEE. 1974, 62(6): 673~680
161 M. L. Heron, E. W. Gill, A. Prytz. An Investigation of Double-peaked HF Radar Spectra via A Convolution/De-convolution Algorithm. OCEANS 2008: IEEE, 2008: 1~5
162 J. W. Maresca, J. R. Barnum. Measurement of Oceanic Wind Speed from HF Sea Scatter by Skywave Radar. IEEE Transaction on Antennas and Propagation. 1971.1: 132~136
163 T. M. Georges, J. A. Harlan. New horizos for over-the-horizon radar. IEEE Antennas and Propagation Magazine. 1994, 36(4): 14~24
164 Y. Abramovich, S. Anderson, Y. Lyudviga, etc. Space time adaptive techniques for ionospheric clutter mitigation in HF surface wave radar systems. Radar 2004, International conference on Radar system. Toulouse, France. Oct, 2004: 203~207
165李雷.高频雷达自适应抗干扰技术研究.哈尔滨工业大学博士学位论文. 2007: 6~7, 24~30
166 Y. I. Abramovich, N. K. Spencer, S. J. Anderson, etc. Stochastic-constraints method in nonstationary hot-clutter cancellation-Part 1: Fundamentals and supervised training applications. IEEE Transactions on Aerospace and Electronic Systems. 1998, 34: 1271~1292
167 G. A. Fabrizio, D. A. Gray,M. D. Turley. Experimental Evaluation of adaptive beamforming methods and interference modes for high frequency Over-the-horizon radar systems. Multidimensional systems and signal processing. 2003, 14: 241~263
168 T. Ponsford, R. Dizaji. System and method for spectral generation in radar. United States Patent Application Publication. Pub, No: US 2004/0178951 A1. Sep, 2004
169 R. Dizaji, T. Ponsford. Adaptive system and method for radar detection. United States Patent Application Publication. Pub, NO: US 2003/0174088 A1, Sep, 2003
170 A. D. Maio, A. Farina, G. Foglia. Design and experimental validation of knowledge-based CFAR detectors. Radar 2006 IEEE Conference. Apr. 2006: 128~135
171 K. J. Hickey, E. W. Gill, J. A. Helbig, etc. Measurement of ocean surfacecurrents using a long-range, high-frequency ground wave radar. IEEE Journal of Oceanic Engineering. 1994, 19(4): 549~554
172 D. E. Barrick. Accuracy of parameter extraction from sample-averaged sea-echo Doppler spectra. IEEE Transactions on Antennas and Propagation, 1980, 28(1): 1~11
173 R. Khan, D. Power, J. Walsh. Ocean Clutter Suppression for HF Ground Wave Radar. IEEE 1997 Canadian Conference on Electrical and Computer Engineering. Feb. 1997: 512~515
174 J. Wang, R. L. Kirlin. Improvement of high frequency ocean surveillance radar using subspace methods based on sea clutter suppression. Sensor Array and Multichannel Signal Processing Workshop Proceedings. 2002: 557~560
175高兴斌,宗成阁,袁业术.高频地波舰载超视距雷达的海杂波对消.电子学报. 2000, 28(3): 5~8
176冀振元,孟宪德,周和秘.高频地波超视距雷达海杂波号分析.系统工程与电子技术. 2000,22(5): 12~16
177童健,文必洋,王颂.强海杂波背景下的舰船目标检测.武汉大学学报(理学版). 2005, 51(3): 370~374
178 http://www.etl.noaa.gov/technology/archive/surface/
179 M. L. Heron, E. W. Gill, A. Prytz. An Investigation of Double-peaked HF Radar Spectra via a Convolution/De-convolution Algorithm. OCEANS 2008: IEEE, 2008: 1~5
180 T. Lindeberg. Edge Detection and Ridge Detection with Automatic Scale Selection. International Journal of Computer Vision. 1998, 30(2): 107~153
181 A. P. Ralph. Data Processing for a Ground Wave Radar. The GEC Journal of Research. 1988, 6(2): 96~105
182 R. C. Gonzalez, R. E. Woods.数字图像处理(第二版).阮秋琦,阮宇智等译.电子工业出版社, 2003: 446, 482
183 M. Sezgin. Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging. 2004, 13(1): 146~168
184蔚明,王典洪. Otsu法的多阈值推广及其快速实现.中国体视学与图像分析. 2004, 9(4): 219~223
185 N. Otsu. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics. 1979, 9(1): 62~66
186侯格贤,毕笃彦.图像分割质量评价方法研究.中国图象图形学报. 2000,5(1): 39~43
187 Y. J. Zhang, J. J. Gerbrands. Objective and Quantitative Segmentation Evaluation and Comparison. Signal Processing. 1994, 39(1): 43~54
188 G. Galati. Advanced radar techniques and systems. Peter Peregrinus Ltd, 1993: 188~207
189 H. Gao, G. Li, Y. Li, etc. Ionospheric effect of HF surface wave over-the-horizion radar. Radio Science. 2006, 41(11): 1~10
190贾沛璋.误差分析与数据处理.国防工业出版社, 1992: 206~223
191 L. B. Victor. An Approach to Outiler Detection Based on Bayesian Probalilistic Model. IEEE Proceedings of ICPR. 1996: 70~74
192 A. G. Bruce, D. L. Donoho. Denoising and Robust Nonlinear Wavelet Analysis. Proceedings of SPIE-The Intenational Society for Optical Engineering. 1994: 325~336
193王黎明,陈颖,杨楠.应用回归分析.复旦大学出版社, 2008: 47~52
194 S. J. Davey, S. B. Colegrove, D. Mudge. Advanced Jindalee Tracker: Enhanced Peak Detector. DSTO-TR-0765. 1999.6: 2~7
195 A. R. Elia-Fuste, M. G. G. de Mercado, E. de los Reyes Davo. Analysis of Some Modified Ordered Statistic CFAR: OSGO and OSSO CFAR. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26(1): 197~202
196丁宗华.电离层频高图自动度量与分析的方法研究.中国科学院研究生院博士学位论文. 2006: 11~14
2 L. Sevgi, A. Ponsford, H. C. Chan. An Integrated Maritime Surveillance System Based on High-Frequency Surface-Wave Radars, Part 1: Theoretical Background and Numerical Simulations. IEEE Antennas and Propagation Magazine. 2001, 43(4): 28~43
3 M. I. Skolnik. Radar Handbook. 3rd Edition. Artech House, 2008: 20.43~20.45, 7.1~7.2, 7.22, 7.11
4 M. Roughan, E. J. Terrill, J. L. Largier, etc. Observations of Divergence and Upwelling around Point Loma, California. Journal of Geophysical Research. 2005, 110: 1~13
5 B. Lipa, B. Nyden. Directional Wave Information from the SeaSonde. IEEE Journal of Oceanic Engineering. 2005, 30(1): 221~231
6 B. K. Haus, M. Wang, L. K. Shay, etc. HF Radar Observation of Wave Directional Spectra in a Strong Current Regime. Oceans-Europe 2007, 18-21 June 2007: 1~5
7 L. R. Wyatt, J. J. Green, A. Middleditch, etc. Operational Wave, Current, and Wind Measurements with the Pisces HF Radar. IEEE Journal of Oceanic Engineering. 2006, 31(4): 819~834
8 M. Skolnik. Opportunities in Radar-2002. Electronics & Communication Engineering Journal. 2002.12: 263~272
9 K. W. Gurget, T. Schlick. HF radar wave measurements in the presence of ship echoes-problems and solutions. Oceans-Europe 2005: 937~941
10 T. Thayaparan, L. J. Stankovic, M. Dakovic. A Novel Approach for the Detection of Maneuvering Air Targets in Sea-Clutter using High-Frequency Surface-Wave Radar. Defence R&D Canada-Ottawa Technical Report. Dec. 2005: 1~68
11 D. Trizna, L. Xu. Target Classification and Remote Sensing of Ocean Current Shear Using a Dual-Use Multifrequency HF Radar. IEEE Journal of Oceanic Engineering. 2006, 31(4): 904~918
12 M. L. Heron, B. Willis. HF Ocean Surface Radar Monitoring for Coral Bleaching in the Great Barrier Reef. OCEANS 2006: 1~5
13 J. F. Vesecky, J. Drake, K. Laws, etc. Coastal Eddies in the Ocean Wind Field as Observed by Single and Multifrequency HF Radars on Monterey Bay, California. OCEANS 2007 EUROPE, Jun. 18-21, 2007: 1~5
14 J. S. Bathgate, M. L. Heron, A. Prytz. A Method of Swell-Wave Parameter Extraction from HF Ocean Surface Radar Spectra. IEEE Journal of Oceanic Engineering. 2006, 31(4): 812~818
15 K-W Gurgel, H-H Essen, T. Schlick. An Empirical Method to Derive Ocean Waves from Second-Order Bragg Scattering Prospects and Limitations. IEEE Journal of Oceanic Engineering, 2006, 31(4): 804~811
16 M. L. Parkinson. Observations of the broadening and coherence of MF lower HF surface-radar ocean echoes. IEEE Journal of Oceanic Engineering, 1997, 2(2): 347~363
17 R. Guinvarc’h, M. Lesturgie, R. Durand, etc. On the Use of HF Surface Wave Radar in Congested Waters Influence of Masking Effect on Detection of Small Ships. IEEE Journal of Oceanic Engineering. 2006, 31(4): 894~903
18 H. Leong, A. Ponsford. The Effects of Sea Clutter on The performance of HF Surface Wave Radar in Ship Detection. 2008 Radar Conference. May 2008: 1~6
19 D. J. Emery. The Choice of Operating Frequency in HF Surface Wave Radar Design. Ninth International Conference on HF Radio Systems and Techniques. Jun. 23-26, 2003: 278~281
20 L. Sevgi, A. Ponsford, H. C. Chan. An Integrated Maritime Surveillance System Based on High-Frequency Surface-Wave Radars, Part 2: Operational Status and System Performance. IEEE Antennas and Propagation Magazine. 2001, 43(5): 52~63
21 D. J. Emery. Some Aspects of Design and Enviromental Management in HF Surface Wave Radar. Radar 2002: 51~55
22强勇.高频雷达抗干扰与目标检测方法.西安电子科技大学博士学位论文. 2004: 7~8
23 T. Thayaparan, J. MacDougall. Evaluation of ionospheric sporadic-E clutter in an arctic environment for the assessment of high-frequency surface-wave radar surveillance. IEEE Transactions on Geoscience and Remote Sensing. 2005, 43(5): 1180~1188
24黄亮,文必洋,吴立明等. HFSWR电离层干扰抑制研究.电波科学学报. 2007, 22(4): 626~630
25 X. Wan, F. Chen, H. Ke. Experimental trials on ionospheric clutter suppression for high-frequency surface wave radar. IEE Proc.-Radar Sonar Navig. 2006, 153(1): 23~29
26 F. Jangal, S. Saillant, M. Helier. Ionospheric clutter mitigation using one-dimensional or two-dimensional wavelet processing. IET Radar, Sonar and Navigation. 2009, 3(2): 112~121
27 A. L. Dzvonkovskaya, H. Rohling. Target Detection with Adaptive Power Regression Thresholding for HF Radar. 2006 International Radar Conference. Oct. 2006: 1~4
28强勇,侯彪,焦李成,保铮.天波超视距雷达抑制流星余迹干扰方法的研究.电波科学学报. 2003, 18(1): 23~27
29权太范,李建巍,于长军.高频雷达抑制冲击干扰的研究和实验.电子学报. 1999, 27(12): 23~25.
30 H. Zhou, B. Wen, S. Wu. Dense Radio Frequency Interference Suppression in HF Radars. IEEE Signal Processing Letters, 2005, 12(5): 361~364
31 G. A. Fabrizio, G. J. Frazer, M. D. Turley. STAP For Clutter And Interference Cancellation in A HF Radar System: ICASSP2006: 1033~1036
32 L. Huang, B. Wen. Impulsive Interference Mitigation in High Frequency Radar. IEEE Conference on Industrial Electronics and Applications. ICIEA 2006: 1~4
33周文瑜,焦培南等.超视距雷达技术.电子工业出版社, 2008: 1, 95~98, 358~370
34王金荣,张宁.高频地波超视距雷达.雷达与对抗. 1994.3: 1~6
35 J. M. Headrick, J. F. Thomason. Applications of High-Frequency Radar. Radio Science. 1998, 33(4): 1045~1054
36 D. Barrick, D. James, J. Isaacson. Marrying Quantitative and Graphic Tidal Analysis Tools with HF Radar Current Map Outputs. Proceedings of the IEEE/OES Seventh Working Conference on Current Measurement Technology. Mar. 13-15, 2003: 105~110
37 D. Barrick. History Present Status and Future Directions of HF Surface Wave Radar in the US. Proceedings of International Conference on Radar 2003: 652~655
38 http://www.codar.com/support_doc.htm: Seasonde_sellsheet
39 L. Wyatt, J. Venn, G. Burrows, etc. HF radar measurements of ocean wave parameters during NURWEC. IEEE Journal of Oceanic Engineering. 1986, 11(2): 219~221
40 S. J. Anderson, P. J. Edwards, P. Marrone, etc. Investigations with SECAR: a bistatic HF surface wave radar. Radar 2003. 2003: 717~722
41 B. A. Johnson, P. F. Amey, Shane Braendler, Michael D.E. Turley. In-Service Enhancements of the Jindalee Over-The-Horizon Radars. Proceedings of International Conference on Radar 2008. Oct. 2008: 218~223
42 H. C. Chan. Charaterization of ionospheric clutter in HF surface wave radar. Defence R&D Canada- Ottawa Technical Report. DRDC Ottawa TR 2003-114. Sep. 2003: 1~70
43 C. Kenny, N. K. Atkins, T. Banks, etc. Canadian Security Guide book, 2007: 14~47
44 K. W. Gurgel, H. H. Essen, T. Sclick. HF Surface Wave Radar for Oceanography: A Review of Activities in Germany. Proceedings of International Conference on Radar 2003. Sep. 2003: 700~705
45 A. L. Dzvonkovskaya, H. Rohling, K.-W. Gurgel. First Results of Ship Detection and Tracking Using WERA HF Radar System. Proceedings of International Radar Symposium IRS 2007. Sep. 2007: 249~254
46 M. Lesturgie, J. P. Eglizeaud, G. Auffray. The Last Decades and The Future of Low Frequency Radar Concepts in France. Proceedings of International Conference on Radar 2004: 1~2
47 Y. Hisaki. Development of HF Ocean Radar in Japan. Proceedings of International Conference on Radar. Sep. 2003: 510~514
48 Y. Liu, R. Xu, N. Zhang. Progress in HFSWR Research at Harbin Institute of Technology. Proceedings of International Conference on Radar 2003. Sep. 2003: 522~528
49文必洋,黄为民,王小华. OSMAR2000探测海面风浪场原理与实现.武汉大学学报(理学版). 2001, 47(5): 642~644
50苏洪涛,张守宏,保铮.空时超分辨方法在高频地波超视距雷达中的应用.电子学报. 2003, 34(3):437~440
51郭佩芳.地波雷达要干资料的反演及应用研究.中国科学院研究生院博士学位论文. 2006: 10~13
52 H. L.范特里斯著.检测、估计和调制理论:卷Ⅰ检测、估计和线性调制理论.张其善,毛士艺,周荫清译.电子工业出版社, 2007: 5~8, 226~234
53 M. O. Kolawo. Radar System, Peak Detection and Tracking. Newnes Publications, 2002: 275~281
54 S. M. Kay.统计信号处理基础——估计与检测理论.罗鹏飞,张文明,刘忠等译.电子工业出版社, 2006: 501~505
55 M. A. Richards. Fundamentals of Radar Signal Processing. McGraw-Hill Companies, 2005:285~286
56伊伏斯·里迪著.现代雷达原理.卓荣邦等译.电子工业出版社, 1991: 384
57段凤增编.信号检测理论(第二版).哈尔滨工业大学出版社, 2002: 188
58 J. Guan, Y. N. Peng, Y. He, Proof of CFAR by the Use of the Invariant Test. IEEE Transactions on Aerospace and Electronic Systems. 2000, 36(1): 336~339
59 H. M. Finn, R. S. Johnson. Adaptive detection mode with threshold control as a function of spatially sampled clutter level estimates. RCA Review. 1968, 29: 414~463
60 H. Rohling. Radar CFAR Resolution of Targets Using Automatic Detectors. IEEE Transactions on Aerospace and Electronic Systems. 1983, 19(4): 608~621
61 J. T. Rickard, G. M. Dillard. Adaptive detection algorithms for multiple target situations. IEEE Transactions on Aerospace and Electronic Systems. 1977, 13(4): 338~343
62 P. P. Gandhi, S. A. Kassam. Analysis of CFAR Processors in Nonhomogeneous Background. IEEE Transactions on Aerospace and Electronic Systems. 1988, 24(4): 427~445
63 J. A. Ritcey, J. L. Hines. Performance of MAX family of order-statistic CFAR detectors. IEEE Transactions on Aerospace and Electronic Systems. 1991, 27(1): 48~57
64 M. B. ElMashade. Detection analysis of linearly combined order statistic CFAR algorithms in nonhomogeneous background environments. Signal Process. 1998, 68: 59~719
65 C. J. Kim, D. S. Han, H. S. Lee. Generalized OSCFAR detector with noncoherent integration. Signal Process. 1993, 31(1): 43~56
66 S. D. Himonas, M. Barkat. Automatic censored CFAR detection for nonhomogeneous environments. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(1): 286~304
67 R. Srinivasan. Robust radar detection using ensemble CFAR processing. IEEProc.-Radar Sonar Navig. 2000,147(6): 291~297
68 M. E. Smith, P. K. Varshney. Intelligent CFAR processor based on data variability. IEEE Transactions on Aerospace and Electronic Systems. 2000, 36(3): 837~847
69 A. Farrouki, M. Barkat. Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments. IEE Proc.-Radar Sonar Navig. 2005, 162(1): 43~51
70 T. V. Cao. Constant False-Alarm Rate Algorithm Based on Test Cell Information. IET Radar Sonar Navig. 2008, 2(3): 200~213
71 V. G. Hansen. A. Olsen. Nonparametric radar extraction using a generalized sign test. IEEE Transactions on Aerospace and Electronic Systems. 1971, 7(5): 942~952
72何友,关键,彭应宁等著.雷达自动检测与恒虚警处理.清华大学出版社, 1999: 34~39, 172
73 S. D. Himonas. A Robust Automatic Censored CFAR Detection for Non-Homogeneous Environments. IEEE International Radar Conference. 1991: 117~121
74 R. Srinivasan. Robust Radar Detedtion Using Ensemble CFAR Processing. IEE Proc-F. 2000, 147: 291~297
75 H. Wang. Robust CFAR Detect in Nonhomeeneous Correlated Interference. Proceedings of IEEE Internation Radar Conference. 1992: 373~376
76 M. Greco, F. Gini. Robust CFAR Detection of Randeom Signals in Compound Gaussian Clutter Plus Thermal Noise. IEEE Proc-F. 2001, 148: 227~232
77 Mark G. Rutten, Branko Ristic, Neil J. Gordon. A Comparison of Particle Filters or Recursive Track-before-detect. 2005 7th International Conference on Information Fusion (FUSION). 2005: 169~175
78 H. IM, T. Kim. Optimization of Multiframe Target Dtection Schemes. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(1): 176~187
79 J. D. R. Jr. Kramer, W. S. Reid. Track-before-detect processing for an airborne type radar. IEEE International Radar Conference 1990. 1990: 422~427.
80 K. Punithakumar, T. Kirubarajan, A.Sinha. A Sequential Monte Carlo Probability Hypothesis Density Algorithm for Multitarget Track-Before-Detect. Signal and Data Processing of Small Targets 2005. Proc. of SPIE Vol. 59131S: 1~8
81 Y. Borers, H. Driessen. A Particle-Filter-Based Detection Scheme. IEEE SignalProcessing Letters. 2003, 10: 300~302
82 B-N Vo, S. Singh, A. Doucet. Sequential Monte Carlo implementation of the PHD filter for multitarget tracking. Proceedings of the Sixth International Conference of Information Fusion, Vol.2, July 2003: 792~799
83 K. Punithakumar, T. Kirubarajan, A. Sinha. A Sequential Monte Carlo Probability Hypothesis Density Algorithm for Multitarget Track-Before-Detect. Signal and Data Processing of Small Targets 2005. Proc. of SPIE Vol. 59131S: 1~8
84 W. Ng, J. Li, S. Godsill, etc. A Hybrid Approach for Online Joint Detection and Tracking for Multiple Targets. Aerospace 2005 IEEE Conference: 1~16
85 S. C. A. Thomopoulos, R. Viswanathan, D. K. Bougoulias. Optimal Decision Fusion in Multiple Sensor Systems. IEEE Transactions on Aerospace and Electronic Systems. 1987, 23: 644~653
86 M. Xiang, J. Zhao. New Results on the Performance of Distributed Bayesian Detection Systems. IEEE Transactions Syst., Man, Cybern., 2001,31(1): 73~78
87 E. Coiras, P.-Y. Mignotte, Y. Petillot, J. Bell, K. Lebart. Supervised Target Detection and Classification by Training on Augmented Reality Data. IET Radar Sonar Navig. 2007, 1(1): 83~90
88 S. López-Estrada, R. Cumplido. Fusion Center with Neural Network For Target Detection in Background Clutter. IEEE Proceedings of the Sixth Mexican International Conference on Computer Science (ENC’05), 2005: 189~196
89 A. L. Chan, S. Z. Der, N. M. Nasrabadi. A Joint Compression-Discrimination Neural Transformation Applied to Target Detection. IEEE Transactions Syst., Man, Cybern.—Part B: Cyber Netics. 2005, 35(4): 670~681
90 P. Willett, W. Chen. Wavelets in the Frequency Domain for Narrowband Process Detection. 2001 IEEE International Conference on Acoustics, Speech and Signal Processing. 2001: 3193~3196
91 X. Ma, C. Zhou. Automated Wavelet Selection and Thresholding for PD Detection. IEEE Electrical Insulation Magazine. 2002, 38: 202~216
92 S. Haykin, Y. Xue, T. N. Davidson. Optimal Waveform Design for Cognitive Radar. 42nd Asilomar Conference on Signals, Systems and Computers. Oct. 2008, Pacific Grove, CA. 2008: 3~7
93 D. Gan, S. H. Zeng. High-Order Fractal Characteristion of Sea-Scattered Signals and Detection of Sea-Surface Targets. Electronics Letters. 1999, 35: 424~425
94梁宗闯,刘兴钊,郑薇.基于高阶谱技术地波超视距雷达信号检测算法.系统工程与电子技术. 1999, 21(5): 128~133
95 B. T. Root. Joint Time-Frequency Analysis of Over-The-Horizon Radar Data. Proceedings of SPIE Vol. 4738 2002: 217~229
96 L. Jubisa Stankovic, Thayananthan Thayaparan, Milos Dakovic. Signal Decomposition by Using the S-Method Application to the Analysis of HF Radar Signal Sea-Clutter. IEEE Transactions on Signal Processing. 2006, 54(11): 4332~4342
97 D. Gan, S. H. Zeng. Detection of Sea-surface Radar Targets Based on Multifractal Analysis. Electronics Letters. 2000, 36(13): 1144~1145
98 L. M. Kaplan. Improved SAR Target Detection Via Extended Fractal Features. IEEE Transactions on Aerospace and Electronic Systems. 2001, 37(2): 436~451
99 M. A. Khabou, P. D. Gader. Automatic Target Detection using Entropy Optimized Shared-weight Neural Networks. IEEE Transactions on Neural Networks. 2001, 11(1): 186~193
100 A. Nelander. Model-based Adaptive Detection of Fluctuating Targets. 2000 IEEE International Radar Conference. 2000: 231~386
101杨强,刘永坦. HFSWR目标识别检测方法.高技术通讯. 2000.10: 37~41
102 Y. F. Vincent. Radar Target Detection using Feature Extraction. IRS 1998 International Symposium on Radar. 1998: 705~714
103 A. D. Maio. Rao Test for Adaptive Detection in Gaussian Interference with Unknown Covariance Matrix. IEEE Transactions on Signal Processing, 2007, 55(7): 3577~3584
104 F. Bandiera, A. D. Maio. Adaptive Radar Detection of Distributed Targets in Homogeneous and Partially Homogeneous Noise Plus Subspace Interference. IEEE Transactions on Signal Processing, 2007, 55(4): 1223~1237
105 L. Sevgi. Target Reflectivity and RCS Interactions in Integrated Maritime Surveillance Systems Based on Surface-wave High-frequency Radars. IEEE Antennas and PropagationMagazine. 2001, 42: 36~51
106 G. Jones, S. Haykin. Higher-dimension Detection of Targets form Scanned Radar. IEE Proc-F. 1996, 143(5): 313~320
107杨强,刘永坦.复杂背景下的二维检测研究.系统工程与电子技术. 2002, 24(1): 34~37
108 S. Russell, P. Norvig. Artificial Intelligence: A Modern Approach. 2nd Edition.Prentice Hall, 2003: 724~725
109 G. T. Capraro, A. Frina, H. Griffiths, etc. Knowledge-based Radar signal and Data Processing: A Tutorial Review. IEEE Signal Processing Magazine. 2006, 23(1): 18~29
110 E. Conte, A. D. Maio, A. Farina, etc. Design and Analysis of a Knowledge-aided Radar Detector for Doppler Processing. IEEE Trasaction on Aerospace and Electronic Systems. 2006, 42(1): 1058~1079
111 G. Gini, M. Rangaswamy. Knowledge-Based Radar Detection, Tracking, and Classification. John Wiley & Sons, 2008: 103~126
112 S. Haykin. Cognitive Radar Networks. IEEE International Workshop on Computational Advanced in Multisensor Adaptive Processing. 13-15 Dec. 2005: 1~3
113 S. Haykin. Cognitive Radar: A Way of the Future. IEEE Signal Processing Magazine. 2006.1: 30~40
114 S. B. Gelfand, T. E. Fortmann, Y Bar-Shalom. Adaptive Detection Threshold Optimization for Tracking in Clutter. IEEE Transaction on Aerospace and Electronic Systems, 1996, 55(7): 514~523
115 A. Vizinho, L. R. Wyatt. Modern spectral analysis in HF radar remote sensing. OCEANS '96. MTS/IEEE. Sep. 1996: 1500~1503
116 A. Vizinho, L. R. Wyatt. Evaluation of the Use of The Modified-Covariance Method in HF Radar Ocean Measurement. IEEE Journal of Oceanic Engineering. 2001, 26(4): 832~840
117 R. J. Martin, M. J. Kearney. Remote sea current sensing using HF radar: an autoregressive approach. IEEE Journal of Oceanic Engineering. 1997, 22(1): 151~155
118 Z. Liang, X. Liu, Y. Liu. A Signal Detection Algorithm Based on Higher-Order Statistics for HFSW-OTH radar. 2001 CIE International Conference on Radar. 15-18 Oct. 2001: 996 ~1000
119 R. James. Ship Detection with high-resolution HF Sky-wave radar. IEEE Journal Oceanic Engineering. 1986, 11(2): 196~209
120 S. J. Anderson, A. R. Mahoney. Application of Superresolution Techniques to HF Radar Sea Echo Analysis. The Pacific Ocean Remote Sensing Conference. Melbourne, Australia, March,1994: 1~4
121 T. Ponsford, R. Dizaji. System and method for spectral generation in radar.United States Patent Application Publication. Pub, No: Us 2004/0178951 A1. Sep, 2004
122 R. Dizaji, T. Ponsford. Adaptive system and method for radar detection. United States Patent Application Publication. Pub, NO: Us 2003/0174088 A1, Sep, 2003
123 H. Leong. Adaptive Nulling of Skywave Interference Using Horiziontal Diplole Antennas in a Coastal Surveillance HF Surface Wave Radar System. Proceedings of IET Radar 97. Oct. 1997: 26~30
124 X. Wan, H. Ke, B. Wen. Adaptive Ionospheric Clutter Suppression Based on Subarrays in Monostatic HF Surface Wave Radar. IEE Proceedings of Radar, Sonar and Navigation. 2005, 152(2): 89~96
125 X. Mao, Y. Liu, W. Deng. Radio Disturbance of High Frequency Surface Wave Radar. Electronc Letters. 2004, 40(3): 202~203
126 H. Leong, A. Ponsford. The advantage of dual-frequency operation in ship tracking by HF surface wave radar. Radar 2004, International conference on Radar system. Toulouse, France. Oct, 2004: 233~237
127 D. E. Barrick. First-order theory and analysis of MF/HF/VHF scatter from the sea. IEEE Transactions on Antennas Propagation. 1972, 20(1): 2~10.
128 D. E. Barrick, J. M. Headrick, R. W. Bogle, D. D. Crombie. Sea backscatter at HF: interpretation and utilization of the echo. Proceedings of IEEE. 1974, 62(6): 673~687
129 L. R. Wyatt. High-Frequency Radar Measurements of the Ocean Wave -Directional Spectrum. IEEE Journal of Oceanic Engineering. 1991, 16(1): 163~169
130 R. H. Khan. Ocean-clutter model for high frequency radar. IEEE Journal of Oceanic eigineering. 1991, 16(2): 181~188
131 M. W. Y. Poon, R. H. Khan, S. L. Ngoc. A singular value decomposition (SVD) based method for suppressing ocean clutter in high frequency radar. IEEE Trans on signal processing. 1993, 41(3): 1421~1425
132 J. Wang. High resolution methods for small target detection and estimation in high frequency radar. Ph.D. dissertation. University of Victoria, Canada. 2004: 1~20
133 C. W. Anderson, S. D. Green, S.P. Kingsley. HF Skywave Radar: Estimating Aircraft Heights Using Super-Resolution in Range. Radar, Sonar andNavigation, IEE Proceedings, 1996, 143(4): 281~285
134谢俊好.舰载高频地波雷达目标检测与估值研究.哈尔滨工业大学博士学位论文. 2000: 29~47
135郭欣.天波超视距雷达信号处理技术研究.南京理工大学博士学位论文. 2003: 31~51
136 B. T. Root. Joint Time-Frequency Analysis of Over-The-Horizon Radar Data. Proceedings of SPIE Vol. 4738, 2002: 217~229
137 R. Gui, R. Weigel. Detecting targets of variable acceleration with High Frequency Surface Wave Radar. International Radar Symposium 2008. May 2008: 1~4
138桂任舟,杨子杰.基于信号分解的时频分析方法在HFSWR目标监测中的应用研究.武汉大学学报(信息科学版). 2006.7: 653~656
139周浩,文必洋,吴世才等.基于时频分析的高频雷达目标检测与定向.电子学报. 2005.12: 2265~2268
140 X. Wan, H. Ke, B. Wen. Adaptive Cochannel Interference Suppression Based on Subarrays for HFSWR. IEEE signal processing letters. 2005, 12(2): 162~165
141 D. Ramakrishnan, J. Krolik. Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter. IEEE Transactions on Aerospace and Electronic Systems. 2009, 45(2): 484~500
142 S. J Anderson, J. M. Fan, P. Jiao. Enhanced OTHR ship detection via dual frequency operation. 2001 IEEE CIE International Radar Conference. 2001: 85~89
143 P. K. Jeans, R. Donnelly. Four element CODAR beamforming. IEEE Journal of Ocean Engineering. 1986, 11(2): 296~303
144 J. Arnold, S. W. Shaw, H. Pasternack. Efficient Target Tracking Using Dynamic Programming. IEEE Transactions on Aerospace and Electronic Systems. 1993, 29(1): 44 ~56
145乔晓林.高频地波超视距雷达中的检测问题.哈尔滨工业大学博士学位论文. 1991: 20~30
146王威.高频地波超视距雷达目标检测与估值的研究.哈尔滨工业大学博士学位论文. 1997: 21~22
147沈一鹰.高频地波超视距雷达信号检测器的设计.哈尔滨工业大学博士学位论文. 2000: 4~20
148杨强.高频地波雷达检测器研究.哈尔滨工业大学博士学位论文. 2002: 7~11, 17~29
149 R. K. Jarrott, T. A. Soame. The Processing of HF Skywave Radar Signals. 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, 19-22 April, 1994: VI/165~VI/168
150 F. E. Nathaanson, J. P. Reilly, M. N. Cohen. Radar Design Principles. McGraw-Hill. 1991: 143~144
151 M. D. E. Turley. Hybrid CFAR techniques for HF radar. 1997 IEEE International Conference on Radar, 1997: 36~40
152 A. M. Zoubir. Statistical Signal Processing For Application to Over-The-Horizon Radar. 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1994. ICASSP-94 , 19-22 April 1994: VI/113 ~VI/116
153 X. Lu, J. Wang, R. Dizaji, etc. A Switching Constant False Alarm Rate Technique for High Frequency Surface Wave Radar. CCECE 2004-CCGEI: 2081~2084
154 A. Dzvonkovskaya, H. Rohling. CFAR Target Detection Based on Gumbel Distribution for HF Radar. 2006 International Radar Symposium. May 24-26, 2006: 1~4
155 M. D. E. Turley. Signal Processing Techniques for Maritime Surveillance with Skywave Radar. 2008 International Conference on Radar, Adelaide, Australia, Sep. 2008: 241~246
156 A. Dzvonkovskaya, K-W Gurgel, H. Rohling, etc. Low Power High Frequency Surface Wave Radar Application for Ship Detection and Tracking. 2008 International Conference on Radar. Adelaide, Australia, Sep. 2008: 627~632
157 D. G. Money, D. J. Emery, G. Dickel. Intelligent Radar Management Techniques in High Frequency Surface Wave Radar. 2007 3rd Institution of Engineering and Technology Seminar on Intelligent Sensor Management. May 2007: 1~11
158 I. D. Longstaff. New Technologies and New Techniques-Radar Developments in Australia. 2008 International Radar Conference. May 2008: 19~24
159 D. J. Emery, G. Dickel. The operation and performance of a multi-frequency HF Surface wave Radar. 2008 International Radar Conference. May 2008: 1~6
160 D. E. Barrick, J. M. Headrick, R. W. Bogle, etc. Sea Backscatter at HF:Interpretation and Utilization of the Echo. Proceedings of IEEE. 1974, 62(6): 673~680
161 M. L. Heron, E. W. Gill, A. Prytz. An Investigation of Double-peaked HF Radar Spectra via A Convolution/De-convolution Algorithm. OCEANS 2008: IEEE, 2008: 1~5
162 J. W. Maresca, J. R. Barnum. Measurement of Oceanic Wind Speed from HF Sea Scatter by Skywave Radar. IEEE Transaction on Antennas and Propagation. 1971.1: 132~136
163 T. M. Georges, J. A. Harlan. New horizos for over-the-horizon radar. IEEE Antennas and Propagation Magazine. 1994, 36(4): 14~24
164 Y. Abramovich, S. Anderson, Y. Lyudviga, etc. Space time adaptive techniques for ionospheric clutter mitigation in HF surface wave radar systems. Radar 2004, International conference on Radar system. Toulouse, France. Oct, 2004: 203~207
165李雷.高频雷达自适应抗干扰技术研究.哈尔滨工业大学博士学位论文. 2007: 6~7, 24~30
166 Y. I. Abramovich, N. K. Spencer, S. J. Anderson, etc. Stochastic-constraints method in nonstationary hot-clutter cancellation-Part 1: Fundamentals and supervised training applications. IEEE Transactions on Aerospace and Electronic Systems. 1998, 34: 1271~1292
167 G. A. Fabrizio, D. A. Gray,M. D. Turley. Experimental Evaluation of adaptive beamforming methods and interference modes for high frequency Over-the-horizon radar systems. Multidimensional systems and signal processing. 2003, 14: 241~263
168 T. Ponsford, R. Dizaji. System and method for spectral generation in radar. United States Patent Application Publication. Pub, No: US 2004/0178951 A1. Sep, 2004
169 R. Dizaji, T. Ponsford. Adaptive system and method for radar detection. United States Patent Application Publication. Pub, NO: US 2003/0174088 A1, Sep, 2003
170 A. D. Maio, A. Farina, G. Foglia. Design and experimental validation of knowledge-based CFAR detectors. Radar 2006 IEEE Conference. Apr. 2006: 128~135
171 K. J. Hickey, E. W. Gill, J. A. Helbig, etc. Measurement of ocean surfacecurrents using a long-range, high-frequency ground wave radar. IEEE Journal of Oceanic Engineering. 1994, 19(4): 549~554
172 D. E. Barrick. Accuracy of parameter extraction from sample-averaged sea-echo Doppler spectra. IEEE Transactions on Antennas and Propagation, 1980, 28(1): 1~11
173 R. Khan, D. Power, J. Walsh. Ocean Clutter Suppression for HF Ground Wave Radar. IEEE 1997 Canadian Conference on Electrical and Computer Engineering. Feb. 1997: 512~515
174 J. Wang, R. L. Kirlin. Improvement of high frequency ocean surveillance radar using subspace methods based on sea clutter suppression. Sensor Array and Multichannel Signal Processing Workshop Proceedings. 2002: 557~560
175高兴斌,宗成阁,袁业术.高频地波舰载超视距雷达的海杂波对消.电子学报. 2000, 28(3): 5~8
176冀振元,孟宪德,周和秘.高频地波超视距雷达海杂波号分析.系统工程与电子技术. 2000,22(5): 12~16
177童健,文必洋,王颂.强海杂波背景下的舰船目标检测.武汉大学学报(理学版). 2005, 51(3): 370~374
178 http://www.etl.noaa.gov/technology/archive/surface/
179 M. L. Heron, E. W. Gill, A. Prytz. An Investigation of Double-peaked HF Radar Spectra via a Convolution/De-convolution Algorithm. OCEANS 2008: IEEE, 2008: 1~5
180 T. Lindeberg. Edge Detection and Ridge Detection with Automatic Scale Selection. International Journal of Computer Vision. 1998, 30(2): 107~153
181 A. P. Ralph. Data Processing for a Ground Wave Radar. The GEC Journal of Research. 1988, 6(2): 96~105
182 R. C. Gonzalez, R. E. Woods.数字图像处理(第二版).阮秋琦,阮宇智等译.电子工业出版社, 2003: 446, 482
183 M. Sezgin. Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging. 2004, 13(1): 146~168
184蔚明,王典洪. Otsu法的多阈值推广及其快速实现.中国体视学与图像分析. 2004, 9(4): 219~223
185 N. Otsu. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics. 1979, 9(1): 62~66
186侯格贤,毕笃彦.图像分割质量评价方法研究.中国图象图形学报. 2000,5(1): 39~43
187 Y. J. Zhang, J. J. Gerbrands. Objective and Quantitative Segmentation Evaluation and Comparison. Signal Processing. 1994, 39(1): 43~54
188 G. Galati. Advanced radar techniques and systems. Peter Peregrinus Ltd, 1993: 188~207
189 H. Gao, G. Li, Y. Li, etc. Ionospheric effect of HF surface wave over-the-horizion radar. Radio Science. 2006, 41(11): 1~10
190贾沛璋.误差分析与数据处理.国防工业出版社, 1992: 206~223
191 L. B. Victor. An Approach to Outiler Detection Based on Bayesian Probalilistic Model. IEEE Proceedings of ICPR. 1996: 70~74
192 A. G. Bruce, D. L. Donoho. Denoising and Robust Nonlinear Wavelet Analysis. Proceedings of SPIE-The Intenational Society for Optical Engineering. 1994: 325~336
193王黎明,陈颖,杨楠.应用回归分析.复旦大学出版社, 2008: 47~52
194 S. J. Davey, S. B. Colegrove, D. Mudge. Advanced Jindalee Tracker: Enhanced Peak Detector. DSTO-TR-0765. 1999.6: 2~7
195 A. R. Elia-Fuste, M. G. G. de Mercado, E. de los Reyes Davo. Analysis of Some Modified Ordered Statistic CFAR: OSGO and OSSO CFAR. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26(1): 197~202
196丁宗华.电离层频高图自动度量与分析的方法研究.中国科学院研究生院博士学位论文. 2006: 11~14