宽带雷达目标时域检测算法研究
|
摘要
宽带雷达与窄带雷达相比,优势主要体现在:可提高雷达对杂波中目标的检测能力;可更灵活地设计发射波形和雷达系统;具有更高的距离分辨力;具有更好的电磁兼容性能;具有更低的截获性能等。宽带雷达的潜能使它成为雷达发展的一个重要方向。但目前对宽带雷达的应用主要集中在目标成像、识别和分类等方面,如何在宽带雷达体制下完成目标检测,跟踪等雷达传统任务具有重要的理论意义和工程价值。本论文围绕宽带雷达目标时域检测问题展开,主要内容分为五部分:
(1).从目标散射点模型出发,对宽带雷达目标回波的物理特性进行了深入研究。详细分析了宽带雷达检测中的两个难点:由目标转动引起的回波相位变化,和由平动引起的相参处理期间目标的越距离单元走动,并介绍了目标回波平动补偿的方法:包络对齐和初相校正,为后续的工作奠定了基础。
(2).研究了均匀高斯噪声中基于单次脉冲回波的宽带雷达目标检测问题。首先分析了宽带雷达对目标进行检测的优势和存在的问题,而后介绍了几种已有的单次回波宽带雷达目标检测算法,并分析了它们的优缺点。指出实际中提高单次回波雷达目标检测性能的难点在于无法获取目标散射中心分布的先验信息。从解决这一问题入手,提出了一种基于多量化门限的二进制积累检测算法,理论分析和实测数据的仿真实验证明,在无法获取目标散射中心分布先验信息条件下,对于散射中心分布稀疏的目标,该算法与能量积累、基于散射点密度的广义似然比等检测算法相比,计算简单,易于硬件实现,并具有更稳健的检测性能。
(3).研究了均匀高斯噪声中,基于多次脉冲回波的宽带雷达运动目标特征检测问题。首先根据宽带雷达目标回波的特点,指出匀速直线运动的宽带雷达目标,其距离-慢时间域的轨迹由若干条斜率相等的直线组成。由这一特征入手,设计一种基于哈夫变换的检测算法,对其性能进行了完整的理论分析,最后通过实测数据验证了该检测算法可对宽带雷达目标回波进行有效的非相参积累,与各种已有算法相比,显著提高了宽带雷达的检测性能。
(4).研究了均匀高斯噪声中,基于多次脉冲回波的宽带雷达目标相参检测问题。首先针对低信噪比环境中包络对齐精度低的难点,提出一种基于概率积累函数映射和约束时延平移量的包络对齐新方法。在此基础上,从脉间和脉内信号能量积累的思路出发,设计了两种检测算法。前者从观测数据中估计初相,用估计出的导向矢量对脉间信号进行相参积累;后者采用目标数据库的基于主分量分析的子空间对脉内信号进行次优匹配接收。理论说明了两种算法的恒虚警率性。实验结果表明,与非相参积累检测算法相比,这两种算法显著地提高了宽带雷达的检测性能。
(5).研究了宽带雷达目标的稳健检测问题。分析了目标在相参处理时间内导向矢量误差给相参积累带来的影响,针对这一问题,提出了一种基于凸规划的改进稳健广义似然比检测算法。详细的理论分析和实测数据仿真实验证明,在保证检测性能的前提下,该检测算法可有效地降低稳健广义似然比检测算法的计算复杂度。在导向矢量严重失配的情况下,该算法检测性能相对于传统的广义似然比算法有明显的提高。
Compared with narrowband radars, wideband radars can provide many advantages, such as, better target detection performance in clutter, more flexible design for waveforms and systems, better spatial resolution, better electromagnetic compatibility and lower probability of interception. Wideband radars become the trend of radar development for its potential applications. However, nowadays the applications of wideband radar are mainly for target imaging, recognition and classification, how to use wideband radar to fulfill the conventional radar task (such as target detection and tracking etc) is of significance in both the theory and application.
The work of this dissertation mainly focuses on issues of the wideband radar target detection in the time domain. The main content can be summarized as the following five aspects:
(1). Based on a scattering center model, the physical property of wideband radar target return is discussed. We point out that how to deal with the target-scattering function changing caused by rotational motion and scatters’migration through range cells caused by translational motion is a challenging task for wideband radar target detection. The translational motion compensation can be obtained by envelope alignment and initial phase correction. This forms the basis for the following study.
(2). The problem of wideband radar target detection in Gaussian noise by one pulse is researched. Firstly, the advantage and problem of detecting targets by wideband radar are discussed; several existing algorithms are reviewed with their advantages and disadvantages analyzed in detail; then we point out that the difficulty of wideband radar detection is the absence of the knowledge about the spatial distribution of the target scattering centers in real applications; To overcome this difficulty we design a novel binary integrator using multiple quantization thresholds, which we term as the modified binary integrator (MBI). Theoretical analyses and simulation results show that MBI is easily implemented and can achieve a more robust performance than the present algorithms(such as energy integration detector and scatter density dependent GLRT detector etc) for sparse scattering target when the prior knowledge of the targets’scattering centers distribution is absent.
(3). The problem of wideband radar moving target detection in Gaussian noise based on feature of multiple adjacent pulses is researched. Based on the characteristics of the wideband target return, we point out that the tracks of target with a constant velocity in range-time data space are composed of several straight lines with the same slope. Based on the target and noise models we design a wideband radar Hough detector using Hough transform. The statistical properties of the detector are discussed completely and rigorously. Experimental results show that the detector can integrate the target returns from multiple pulses efficiently, and has a much better performance than the existing noncoherent detectors.
(4). The problem of wideband radar target coherent integration detection in Gaussian noise by the returns of multiple adjacent pulses is researched. The conventional envelope alignment method suffers severe performance degradation under low signal-to-noise ratio. To overcome this problem we design a novel envelope alignment scheme based on cumulative distribution function mapping and constrained misalignment. After envelope alignment we propose two detection schemes. In the first one, we integrate the signal from every pulse by the initial phase steering vector estimated from the observed data. In the latter one, we integrate the signal from every range cells using prior training target data based on principal component analysis. Theoretical analyses show that the proposed detection schemes achieve constant false alarm rate (CFAR). Furthermore, in the detection experiments based on measured data, the proposed schemes can obtain better detection performance than the existing coherent detectors.
(5). The problem of robust detection in wideband radar is investigated. The steering mismatches during the coherent processing interval and its impact on coherent integration are introduced firstly; then we propose a new detector based on convex programming, which we refer to as improved robust generalized likelihood ratio test (IRGLRT).A detailed analysis on IRGLRT shows that compare with the existing robust generalized likelihood ratio test (RGLRT) detector, it can greatly reduce the computation complexity without loss of detection performance. Finally, experimental results for measured data of three planes show that the proposed algorithm achieves a visible performance improvement with respect to the conventional GLRT, especially in the presence of severe steering vector mismatches.
(1).从目标散射点模型出发,对宽带雷达目标回波的物理特性进行了深入研究。详细分析了宽带雷达检测中的两个难点:由目标转动引起的回波相位变化,和由平动引起的相参处理期间目标的越距离单元走动,并介绍了目标回波平动补偿的方法:包络对齐和初相校正,为后续的工作奠定了基础。
(2).研究了均匀高斯噪声中基于单次脉冲回波的宽带雷达目标检测问题。首先分析了宽带雷达对目标进行检测的优势和存在的问题,而后介绍了几种已有的单次回波宽带雷达目标检测算法,并分析了它们的优缺点。指出实际中提高单次回波雷达目标检测性能的难点在于无法获取目标散射中心分布的先验信息。从解决这一问题入手,提出了一种基于多量化门限的二进制积累检测算法,理论分析和实测数据的仿真实验证明,在无法获取目标散射中心分布先验信息条件下,对于散射中心分布稀疏的目标,该算法与能量积累、基于散射点密度的广义似然比等检测算法相比,计算简单,易于硬件实现,并具有更稳健的检测性能。
(3).研究了均匀高斯噪声中,基于多次脉冲回波的宽带雷达运动目标特征检测问题。首先根据宽带雷达目标回波的特点,指出匀速直线运动的宽带雷达目标,其距离-慢时间域的轨迹由若干条斜率相等的直线组成。由这一特征入手,设计一种基于哈夫变换的检测算法,对其性能进行了完整的理论分析,最后通过实测数据验证了该检测算法可对宽带雷达目标回波进行有效的非相参积累,与各种已有算法相比,显著提高了宽带雷达的检测性能。
(4).研究了均匀高斯噪声中,基于多次脉冲回波的宽带雷达目标相参检测问题。首先针对低信噪比环境中包络对齐精度低的难点,提出一种基于概率积累函数映射和约束时延平移量的包络对齐新方法。在此基础上,从脉间和脉内信号能量积累的思路出发,设计了两种检测算法。前者从观测数据中估计初相,用估计出的导向矢量对脉间信号进行相参积累;后者采用目标数据库的基于主分量分析的子空间对脉内信号进行次优匹配接收。理论说明了两种算法的恒虚警率性。实验结果表明,与非相参积累检测算法相比,这两种算法显著地提高了宽带雷达的检测性能。
(5).研究了宽带雷达目标的稳健检测问题。分析了目标在相参处理时间内导向矢量误差给相参积累带来的影响,针对这一问题,提出了一种基于凸规划的改进稳健广义似然比检测算法。详细的理论分析和实测数据仿真实验证明,在保证检测性能的前提下,该检测算法可有效地降低稳健广义似然比检测算法的计算复杂度。在导向矢量严重失配的情况下,该算法检测性能相对于传统的广义似然比算法有明显的提高。
Compared with narrowband radars, wideband radars can provide many advantages, such as, better target detection performance in clutter, more flexible design for waveforms and systems, better spatial resolution, better electromagnetic compatibility and lower probability of interception. Wideband radars become the trend of radar development for its potential applications. However, nowadays the applications of wideband radar are mainly for target imaging, recognition and classification, how to use wideband radar to fulfill the conventional radar task (such as target detection and tracking etc) is of significance in both the theory and application.
The work of this dissertation mainly focuses on issues of the wideband radar target detection in the time domain. The main content can be summarized as the following five aspects:
(1). Based on a scattering center model, the physical property of wideband radar target return is discussed. We point out that how to deal with the target-scattering function changing caused by rotational motion and scatters’migration through range cells caused by translational motion is a challenging task for wideband radar target detection. The translational motion compensation can be obtained by envelope alignment and initial phase correction. This forms the basis for the following study.
(2). The problem of wideband radar target detection in Gaussian noise by one pulse is researched. Firstly, the advantage and problem of detecting targets by wideband radar are discussed; several existing algorithms are reviewed with their advantages and disadvantages analyzed in detail; then we point out that the difficulty of wideband radar detection is the absence of the knowledge about the spatial distribution of the target scattering centers in real applications; To overcome this difficulty we design a novel binary integrator using multiple quantization thresholds, which we term as the modified binary integrator (MBI). Theoretical analyses and simulation results show that MBI is easily implemented and can achieve a more robust performance than the present algorithms(such as energy integration detector and scatter density dependent GLRT detector etc) for sparse scattering target when the prior knowledge of the targets’scattering centers distribution is absent.
(3). The problem of wideband radar moving target detection in Gaussian noise based on feature of multiple adjacent pulses is researched. Based on the characteristics of the wideband target return, we point out that the tracks of target with a constant velocity in range-time data space are composed of several straight lines with the same slope. Based on the target and noise models we design a wideband radar Hough detector using Hough transform. The statistical properties of the detector are discussed completely and rigorously. Experimental results show that the detector can integrate the target returns from multiple pulses efficiently, and has a much better performance than the existing noncoherent detectors.
(4). The problem of wideband radar target coherent integration detection in Gaussian noise by the returns of multiple adjacent pulses is researched. The conventional envelope alignment method suffers severe performance degradation under low signal-to-noise ratio. To overcome this problem we design a novel envelope alignment scheme based on cumulative distribution function mapping and constrained misalignment. After envelope alignment we propose two detection schemes. In the first one, we integrate the signal from every pulse by the initial phase steering vector estimated from the observed data. In the latter one, we integrate the signal from every range cells using prior training target data based on principal component analysis. Theoretical analyses show that the proposed detection schemes achieve constant false alarm rate (CFAR). Furthermore, in the detection experiments based on measured data, the proposed schemes can obtain better detection performance than the existing coherent detectors.
(5). The problem of robust detection in wideband radar is investigated. The steering mismatches during the coherent processing interval and its impact on coherent integration are introduced firstly; then we propose a new detector based on convex programming, which we refer to as improved robust generalized likelihood ratio test (IRGLRT).A detailed analysis on IRGLRT shows that compare with the existing robust generalized likelihood ratio test (RGLRT) detector, it can greatly reduce the computation complexity without loss of detection performance. Finally, experimental results for measured data of three planes show that the proposed algorithm achieves a visible performance improvement with respect to the conventional GLRT, especially in the presence of severe steering vector mismatches.
引文
[1]丁鹭飞,耿富录.雷达原理.西安:西安电子科技大学,2002.
[2] Wehner D R . High-resolution radar, 2 nd. Boston, MA: Artech House, 1995.
[3] James D, Taylor P E. Ultra-wideband radar technology. New York: CRC Press, 2001.
[4] Camp W W, Mayhan J T, Odonnell R M. Wideband radar for ballistic missile defense and range-Doppler imaging of satellites. Lincoln Laboratory Journal. 2000, vol.12 (2):267-279.
[5]刘宏伟,杜兰,保铮等.雷达高分辨距离像目标识别研究进展.电子与信息学报.2005, vol.27 (8) :1328-1334.
[6]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[7]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[8] Trees H L V, Detection, estimation, and modulation theory (Part III):radar-sonar signal processing and Gaussian signals in noise. New York: John Wiley and Sons, 2001.
[9] Delisle G Y, Haiqing W. Moving target imaging and trajectory computation using ISAR. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol.37 (3): 887-899.
[10] Jiang N Z, Wu R B, Li J. Super resolution feature extraction of moving targets. IEEE Transactions on Aerospace and Electronic Systems. 2001, vol.37 (3):781-793.
[11] Hughes P K. A high-resolution radar detection strategy. IEEE Transactions on Aerospace and Electronic Systems. 1983, vol.19 (5) :663-667.
[12] Conte E, Maio A D, Ricci G.. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7): 1336-1348.
[13] Shirman Y D, Leshchenko S P, Orlenko V M. Advantages and problems of wideband radar. Proceedings of International Radar-2003 Conference, Adwlaide.
[14] Taylor J D. Introduction to ultra-wideband radar technology. New York: CRC Press, 1995.
[15] Haykin S. Cognitive radar: a way of the future. IEEE Signal Processing Magazine. 2006, vol. 23 (1):30-40.
[16] Bell M R. Information theory and radar waveform design. IEEE Transactions on Information Technology. 1993, vol. 39(9): 1578-1597.
[17] Leshem A, Naparstek O, Nehorai A. Information theoretic adaptive radar waveform design for multiple extended targets. IEEE Journal of Selected Topics in Signal Processing. 2007, vol.1 (1):42-55.
[18] Pillai S U, Oh H S, Guerci J R, et al. Optimum transmit-receiver design in the presence of signal-dependent interference and channel noise. IEEE Transactions on Information Technology. 2000, vol. 46(3):577-584.
[19] Sowelam S M, Tewfik A H. Waveform selection in radar target classification. IEEE Transactions on Information Technology. 2000, vol. 46(5) :1014-1029.
[20]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[21] Cuomo K M, Piou J E, Mayhan J T. Ultra-wideband coherent processing, Lincoln Laboratory Journal. 1997, vol.10 (2): 203-222.
[22] Hoffman A, Kogon S. Subband STAP in wideband radar systems. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 256-260.
[23] Steinhardt A O, Nicholas B. Pulsone. Subband STAP processing, the fifth generation. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 1-6.
[24] Rabinkin D V, Nguyen T. Optimum subband filterbank design for radar array signal processing with pulse compression. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 315-321.
[25] Raz G. An approach to adaptive beamforming for wideband systems using subband decomposition. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 300-305.
[26] Cuomo K M, Coutts S D, Mcharg J C, et al. Wideband aperture coherent processing for next generation radar. Project report NG-3, Lincoln Laboratory.
[27] Coutts S, Cuomo K, Mcharg J, Robey F, et al. Distributed coherent aperture measurements for next generation BMS radar. Sensor array and multichannel signal processing, 2006, IEEE Workshop: 390-393.
[28] Vanderspek G A. Detection of a distributed target. IEEE Transactions on Aerospace and Electronic Systems. 1971, vol.7(5) :922-931.
[29] Gerlach K, Steiner M, Lin F C. Detection of a spatially distributed target in white noise. IEEE Signal Processing Letter. 1997, vol.4(7) :198-200.
[30] Gerlach K, Steiner M J. Adaptive Detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7) :1844-1850.
[31] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed Targets. IEEE Transactions on Signal Processing. 2000, vol.48(9) :2686-2670.
[32] Conte E, Maio A D. CFAR Detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(2) : 612-621.
[33] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests, IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[34] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference. IEEE Transactions on Signal Processing.2007,vol.55(4) :1223-1237.
[35] Bon N, Khencharf A, Garello R. GLRT subspace detection for range and Doppler distributed targets. IEEE Transactions on Signal Processing. 2008, vol.44(2) : 678-696.
[36] Farina A, Studer F A. Detection with high resolution radar: great promise, big challenge, Microwave Journal. 1991, vol.34(5): 263-273.
[37] Guerci J R, Pillai S U. Adaptive transmission radar: the next‘wave’?. Proceedings of the IEEE 2000 National Aerospace and Electronics Conference, Dayton, OH, USA: IEEE: 779-786.
[38] Yang Y, Blum R S. MIMO radar waveform design based on mutual information and minimum mean-square error estimation. IEEE Transactions on Aerospace and Electronic Systems. 2007, vol. 43(1): 1-12.
[39] Goodman N A, Venkata P R, Neifeld M A. Adaptive waveform design and sequential hypothesis testing for target recognition with active sensors. IEEE Journal of Selected Topics in Signal Processing.2007, vol.1(1) :105-113.
[40] Sira S P, Cochran D, Suppappola A P, et al. Adaptive waveform design for improved detection of low-RCS targets in heavy sea clutter. IEEE Journal of Selected Topics in Signal Processing. 2007, vol.1(1) :56-66.
[41] Chen C Y, Vaidyanathan P P. MIMO radar waveform optimization with prior information of the extended target and clutter. IEEE Transactions on Signal Processing. 2009,vol.57(9) :3533-3544.
[42] Kay S. Waveform design for multistatic radar detection. IEEE Transactions on Aerospace and Electronic Systems. 2009, vol.45(3) :1153-1166.
[43]刘永坦.雷达成像技术.北京:国防工业出版社,1999.
[44]戴奉周.宽带雷达信号处理—检测、杂波抑制与认知跟踪.博士研究生学位论文.西安电子科技大学.2007.
[45]黄德双.高分辨雷达智能信号处理.北京:机械工业出版社,2001.
[46] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57(10) :3733-3745.
[47]孙文峰,何松华,郭桂蓉等.自适应距离单元积累检测方法及其应用.电子学报.1999, vol.27(2) :111-112.
[48]黎海涛,徐继麟.基于广义似然比的高分辨雷达目标检测.系统工程与电子技术.2000, vol. 22(11) :5-7.
[49]黄巍,贺知明,向敬成.宽带雷达能量积累与信号检测方法研究.系统工程与电子技术.2004, vol.26(7) :889-892.
[50]王彩云,许小剑,毛士艺.高分辨雷达中带宽对信号检测影响的研究.宇航学报.2006, vol.27 (5) :915-919.
[51]胡文明,关键,何友.基于二维积累的雷达分布式目标检测新方法[J].系统工程与电子技术.2006,28(9):1335-1337.
[52]顾新锋,简涛,何友.一种基于散射中心密度的距离扩展目标检测方法.信号处理.2009, vol.25(12) :1941-1945.
[53]孟祥伟,曲东才,何友.高斯背景下距离扩展目标的恒虚警率检测.系统工程与电子技术.2005, vol. 27(6) :1012-1015.
[54] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1) :66-78.
[55]戴奉周,刘宏伟,吴顺君.最大相关系数准则下的子带域宽带雷达杂波抑制与距离像增强.电子与信息学报.2009,vol.31(7) :1701-1705.
[56]戴奉周,刘宏伟,吴顺君.一种基于顺序统计量的距离扩展目标检测器.电子与信息学报.2009,vol.31(10) :2488-2492.
[57] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010) :16-23.
[58] Dai F Z, Liu H W, Wu S J. Subband implementation for wideband radar clutter suppression and target HRRP enhancement. Chinese Journal of Electronics. 2010, vol.19(2) :381-385.
[59] Dai F Z, Liu H W, Wang P H, et al.Adaptive waveform design for range-spread target tracking. IET electronics letters. 2010, vol. 46(11) :394-395.
[60] Dai F Z, Wang P H, Liu H W, et al. Detection performance comparison for wideband and narrowband radar in Noise. IEEE International Radar Coference, Washington DC, May, 10-14, 2010:794-798.
[1]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[2]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[3]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[4]袁莉.基于高分辨距离像的雷达目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[5]叶炜.逆合成孔径雷达运动补偿与成像研究.博士研究生学位论文.西安电子科技大学.1996.
[6]廖学军.基于高分辨距离像的雷达目标识别.博士研究生学位论文.西安电子科技大学.1999.
[7] Carlson S Z. An adaptive array detector with mismatched signal rejection. IEEE Transactions on Aerospace and Electronic Systems. 2002,vol. 28(1): 195-207.
[8] Maio A D. Robust adaptive radar detection in the presence of steering vector mismatches. IEEE Transactions on Aerospace and Electronic Systems. 2005,vol.41(4) : 1322-1337.
[9] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(2) : 612–621.
[10] Conte E, Maio A D, Ricci G. GLRT-Based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7) :1336-1348.
[11] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007,vol.55(4): 1223-1237.
[12] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010) :16-23.
[13] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests. IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[14] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7) :1844-1850.
[15] Gerlach K, Steiner M J. Fast Convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48(9) :2686-2670.
[16] Guan J, Zhang Y F, Yong H. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1): 66-78.
[17]邢孟道.基于实测数据的雷达成像方法研究.博士研究生学位论文.西安电子科技大学.2002.
[18] Ye W, Yeo T S, Bao Z. Weighed least-squares estimation of phase errors for SAR/ISAR autofocus. IEEE Transactions on Geoscience and Remote Sensing. 1999, vol.37(5): 2487-2494.
[19]刘永坦.雷达成像技术.北京:国防工业出版社.1999.
[20]戴奉周.宽带雷达信号处理—检测、杂波抑制与认知跟踪.博士研究生学位论文.西安电子科技大学.2010.
[21] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57 (10): 3733-3745.
[1] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[2] Trees H L V, Detection, estimation, and modulation theory (Part III):radar-sonar signal processing and Gaussian signals in noise. New York: John Wiley and Sons, 2001.
[3] Gerlach K, Steiner M, Lin F C. Detection of a spatially distributed target in white noise. IEEE Signal Processing Letter. 1997, vol.4(7):198-200.
[4] Gerlach K, Steiner M, Lin F C. Spatially distributed target detection in non-Gaussian clutter. IEEE Transactions on Aerospace and Electronic Systems. 1999,vol.35(3):926-934.
[5] Worley R. Optimum thresholds for binary integration. IEEE Transactions on Information Theory. 1968, IT-4:349-352.
[6] Weiner M A. Binary integration for fluctuating targets. IEEE Transactions on Aerospace and Electronic Systems. 1991, vol.27(1) :11-17.
[7] Frey T L. An approximation for the optimum binary integration threshold for Swerling II targets. IEEE Transactions on Aerospace and Electronic Systems.1996, vol.32(3) :1181 -1185.
[8] Shnidman H L. Binary integration for Swerling target fluctuations. IEEE Transactions on Aerospace and Electronic Systems. 1998, vol.34(3): 1043 -1053.
[9]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[10] Hughes P K. A high-resolution radar detection strategy. IEEE Transactions on Aerospace and Electronic Systems. 1983, vol.19(5): 663-667.
[11]郭启俊,刘劲,刘宏伟.基于时频融合的分布式目标的恒虚警率检测.雷达科学与技术.2007, vol.5(1): 65-68.
[12] Papoulis A, Pillai S U. Probability, random variables and stochastic process, 4th ed. New York: McGraw-Hill. 2002.
[13] Gini F, Lombardini F, Verrazzni L. Decentralized CFAR detection with binaryintegration in Weibull clutter. IEEE Transactions on Aerospace and Electronic Systems. 1997,vol.33(2): 396-407.
[14] Maio A D, Nicola S D, Huang Y W, et al. Code design to optimize radar detection performance under accuracy and similarity constraints. IEEE Transactions on Signal Processing. 2008, vol.56(11): 5618-5629.
[15]赵树杰,赵建勋.信号检测与估值理论.北京:清华大学出版社,2005.
[1] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57(10): 3733-3745.
[2] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part I: system concept. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 102-108.
[3] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part II: detection statistics. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 109-115.
[4] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part III: detection performance with binary integration. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 116-125.
[5] Zeng J K, He Z S, Mathini S, et al. Modified Hough transform for searching radar detection. IEEE Geoscience and Remote Sensing Letters. 2008, vol.5(4): 683-686.
[6] Behar V, Vassileva B, Kabakchiev C. Adaptive Hough detector with binary integration in pulse jamming. Proceedings ECCTD'97, Budapest, 1997: 885-889.
[7] Behar V, Kabakchiev C. Hough detector with adaptive non-coherent integration for target detection in pulse jamming. Proceedings ISSSTA'98, South Africa, 1998:1003-1008.
[8] Kabakchiev C, Doukovska L, Garvanov I. Hough radar detectors in conditions of intensive pulse jamming, S&Te-Didest, ISSN 1726-5479, 2005:381-389.
[9]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[10]廖学军.基于高分辨距离像的雷达目标识别.博士研究生学位论文.西安电子科技大学.1999.
[11]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[12]戴奉周,刘宏伟,吴顺君.一种基于顺序统计量的距离扩展目标检测器.电子与信息学报.2009,vol.31(10) :2488-2492.
[13]李玉山.数字视觉和视频技术.西安:西安电子科技大学.2006.
[14] Leung S W, Minett J W, Siu Y M, et al. A fuzzy approach to signal integration. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(1): 346-350.
[15] Marichala J L, Kojadinovicb I. Distribution functions of linear combinations of lattice polynomials from the uniform distribution. Statistics and Probability Letters. 2008, vol.78(8): 985-991.
[16] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[1]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[2] Conte E, Maio A D, Ricci G. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7): 1336-1348.
[3] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007, vol.55(4): 1223-1237.
[4] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol. 38(2): 612-621.
[5] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010): 16-23.
[6] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests, IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[7] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7): 1844-1850.
[8] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48 (9) :2686-2670.
[9] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributedtarget in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1): 66-78.
[10]胡文明,关键,何友.基于二维积累的雷达分布式目标检测新方法[J].系统工程与电子技术.2006,vol.28(9): 1335-1337.
[11] Leung S W, Minett J W, Siu Y M, et al. A fuzzy approach to signal integration. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(1): 346-350.
[12] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[13]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[14]张贤达,矩阵分析与应用,北京:清华大学出版社,2004.
[15] Duda R O, Hart P E, Stork D G. Pattern Classification. 2rd ed. New York:John Wiley and Sons.2001.
[16]袁莉.基于高分辨距离像的雷达目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[1] Maio A D. Robust adaptive radar detection in the presence of steering vector mismatches. IEEE Transactions on Aerospace and Electronic Systems. 2005, vol.41(4): 1322-1337.
[2]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[3]赵树杰,赵建勋.信号检测与估值理论.北京:清华大学出版社,2005.
[4] Conte E, Maio A D, Ricci G. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol. 49(7): 1336-1348.
[5] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007,vol.55 (4): 1223-1237.
[6] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol. 38(2): 612-621.
[7] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010): 16-23.
[8] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests. IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2): 568-582.
[9] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing.1999, vol.47(7): 1844-1850.
[10] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48 (9): 2686-2670.
[11] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol. 19(1): 66-78.
[12]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[13]张贤达.矩阵分析与应用.北京:清华大学出版社,2004.
[14] Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2003.
[15] Sturm J F. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. Optimization Method Software.1999,vol. 18(7): 625-653.
[16] Lobo M, Vandenberghe L, Boyd S. H. Lebret.Applications of second-order cone programming. Linear Algebra and its Applications.1998,vol. 19(2): 193-228.
[2] Wehner D R . High-resolution radar, 2 nd. Boston, MA: Artech House, 1995.
[3] James D, Taylor P E. Ultra-wideband radar technology. New York: CRC Press, 2001.
[4] Camp W W, Mayhan J T, Odonnell R M. Wideband radar for ballistic missile defense and range-Doppler imaging of satellites. Lincoln Laboratory Journal. 2000, vol.12 (2):267-279.
[5]刘宏伟,杜兰,保铮等.雷达高分辨距离像目标识别研究进展.电子与信息学报.2005, vol.27 (8) :1328-1334.
[6]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[7]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[8] Trees H L V, Detection, estimation, and modulation theory (Part III):radar-sonar signal processing and Gaussian signals in noise. New York: John Wiley and Sons, 2001.
[9] Delisle G Y, Haiqing W. Moving target imaging and trajectory computation using ISAR. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol.37 (3): 887-899.
[10] Jiang N Z, Wu R B, Li J. Super resolution feature extraction of moving targets. IEEE Transactions on Aerospace and Electronic Systems. 2001, vol.37 (3):781-793.
[11] Hughes P K. A high-resolution radar detection strategy. IEEE Transactions on Aerospace and Electronic Systems. 1983, vol.19 (5) :663-667.
[12] Conte E, Maio A D, Ricci G.. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7): 1336-1348.
[13] Shirman Y D, Leshchenko S P, Orlenko V M. Advantages and problems of wideband radar. Proceedings of International Radar-2003 Conference, Adwlaide.
[14] Taylor J D. Introduction to ultra-wideband radar technology. New York: CRC Press, 1995.
[15] Haykin S. Cognitive radar: a way of the future. IEEE Signal Processing Magazine. 2006, vol. 23 (1):30-40.
[16] Bell M R. Information theory and radar waveform design. IEEE Transactions on Information Technology. 1993, vol. 39(9): 1578-1597.
[17] Leshem A, Naparstek O, Nehorai A. Information theoretic adaptive radar waveform design for multiple extended targets. IEEE Journal of Selected Topics in Signal Processing. 2007, vol.1 (1):42-55.
[18] Pillai S U, Oh H S, Guerci J R, et al. Optimum transmit-receiver design in the presence of signal-dependent interference and channel noise. IEEE Transactions on Information Technology. 2000, vol. 46(3):577-584.
[19] Sowelam S M, Tewfik A H. Waveform selection in radar target classification. IEEE Transactions on Information Technology. 2000, vol. 46(5) :1014-1029.
[20]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[21] Cuomo K M, Piou J E, Mayhan J T. Ultra-wideband coherent processing, Lincoln Laboratory Journal. 1997, vol.10 (2): 203-222.
[22] Hoffman A, Kogon S. Subband STAP in wideband radar systems. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 256-260.
[23] Steinhardt A O, Nicholas B. Pulsone. Subband STAP processing, the fifth generation. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 1-6.
[24] Rabinkin D V, Nguyen T. Optimum subband filterbank design for radar array signal processing with pulse compression. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 315-321.
[25] Raz G. An approach to adaptive beamforming for wideband systems using subband decomposition. In Proceedings of the IEEE SAM Signal Processing Workshop, Cambridge, MA, March 2000: 300-305.
[26] Cuomo K M, Coutts S D, Mcharg J C, et al. Wideband aperture coherent processing for next generation radar. Project report NG-3, Lincoln Laboratory.
[27] Coutts S, Cuomo K, Mcharg J, Robey F, et al. Distributed coherent aperture measurements for next generation BMS radar. Sensor array and multichannel signal processing, 2006, IEEE Workshop: 390-393.
[28] Vanderspek G A. Detection of a distributed target. IEEE Transactions on Aerospace and Electronic Systems. 1971, vol.7(5) :922-931.
[29] Gerlach K, Steiner M, Lin F C. Detection of a spatially distributed target in white noise. IEEE Signal Processing Letter. 1997, vol.4(7) :198-200.
[30] Gerlach K, Steiner M J. Adaptive Detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7) :1844-1850.
[31] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed Targets. IEEE Transactions on Signal Processing. 2000, vol.48(9) :2686-2670.
[32] Conte E, Maio A D. CFAR Detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(2) : 612-621.
[33] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests, IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[34] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference. IEEE Transactions on Signal Processing.2007,vol.55(4) :1223-1237.
[35] Bon N, Khencharf A, Garello R. GLRT subspace detection for range and Doppler distributed targets. IEEE Transactions on Signal Processing. 2008, vol.44(2) : 678-696.
[36] Farina A, Studer F A. Detection with high resolution radar: great promise, big challenge, Microwave Journal. 1991, vol.34(5): 263-273.
[37] Guerci J R, Pillai S U. Adaptive transmission radar: the next‘wave’?. Proceedings of the IEEE 2000 National Aerospace and Electronics Conference, Dayton, OH, USA: IEEE: 779-786.
[38] Yang Y, Blum R S. MIMO radar waveform design based on mutual information and minimum mean-square error estimation. IEEE Transactions on Aerospace and Electronic Systems. 2007, vol. 43(1): 1-12.
[39] Goodman N A, Venkata P R, Neifeld M A. Adaptive waveform design and sequential hypothesis testing for target recognition with active sensors. IEEE Journal of Selected Topics in Signal Processing.2007, vol.1(1) :105-113.
[40] Sira S P, Cochran D, Suppappola A P, et al. Adaptive waveform design for improved detection of low-RCS targets in heavy sea clutter. IEEE Journal of Selected Topics in Signal Processing. 2007, vol.1(1) :56-66.
[41] Chen C Y, Vaidyanathan P P. MIMO radar waveform optimization with prior information of the extended target and clutter. IEEE Transactions on Signal Processing. 2009,vol.57(9) :3533-3544.
[42] Kay S. Waveform design for multistatic radar detection. IEEE Transactions on Aerospace and Electronic Systems. 2009, vol.45(3) :1153-1166.
[43]刘永坦.雷达成像技术.北京:国防工业出版社,1999.
[44]戴奉周.宽带雷达信号处理—检测、杂波抑制与认知跟踪.博士研究生学位论文.西安电子科技大学.2007.
[45]黄德双.高分辨雷达智能信号处理.北京:机械工业出版社,2001.
[46] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57(10) :3733-3745.
[47]孙文峰,何松华,郭桂蓉等.自适应距离单元积累检测方法及其应用.电子学报.1999, vol.27(2) :111-112.
[48]黎海涛,徐继麟.基于广义似然比的高分辨雷达目标检测.系统工程与电子技术.2000, vol. 22(11) :5-7.
[49]黄巍,贺知明,向敬成.宽带雷达能量积累与信号检测方法研究.系统工程与电子技术.2004, vol.26(7) :889-892.
[50]王彩云,许小剑,毛士艺.高分辨雷达中带宽对信号检测影响的研究.宇航学报.2006, vol.27 (5) :915-919.
[51]胡文明,关键,何友.基于二维积累的雷达分布式目标检测新方法[J].系统工程与电子技术.2006,28(9):1335-1337.
[52]顾新锋,简涛,何友.一种基于散射中心密度的距离扩展目标检测方法.信号处理.2009, vol.25(12) :1941-1945.
[53]孟祥伟,曲东才,何友.高斯背景下距离扩展目标的恒虚警率检测.系统工程与电子技术.2005, vol. 27(6) :1012-1015.
[54] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1) :66-78.
[55]戴奉周,刘宏伟,吴顺君.最大相关系数准则下的子带域宽带雷达杂波抑制与距离像增强.电子与信息学报.2009,vol.31(7) :1701-1705.
[56]戴奉周,刘宏伟,吴顺君.一种基于顺序统计量的距离扩展目标检测器.电子与信息学报.2009,vol.31(10) :2488-2492.
[57] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010) :16-23.
[58] Dai F Z, Liu H W, Wu S J. Subband implementation for wideband radar clutter suppression and target HRRP enhancement. Chinese Journal of Electronics. 2010, vol.19(2) :381-385.
[59] Dai F Z, Liu H W, Wang P H, et al.Adaptive waveform design for range-spread target tracking. IET electronics letters. 2010, vol. 46(11) :394-395.
[60] Dai F Z, Wang P H, Liu H W, et al. Detection performance comparison for wideband and narrowband radar in Noise. IEEE International Radar Coference, Washington DC, May, 10-14, 2010:794-798.
[1]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[2]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[3]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[4]袁莉.基于高分辨距离像的雷达目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[5]叶炜.逆合成孔径雷达运动补偿与成像研究.博士研究生学位论文.西安电子科技大学.1996.
[6]廖学军.基于高分辨距离像的雷达目标识别.博士研究生学位论文.西安电子科技大学.1999.
[7] Carlson S Z. An adaptive array detector with mismatched signal rejection. IEEE Transactions on Aerospace and Electronic Systems. 2002,vol. 28(1): 195-207.
[8] Maio A D. Robust adaptive radar detection in the presence of steering vector mismatches. IEEE Transactions on Aerospace and Electronic Systems. 2005,vol.41(4) : 1322-1337.
[9] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(2) : 612–621.
[10] Conte E, Maio A D, Ricci G. GLRT-Based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7) :1336-1348.
[11] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007,vol.55(4): 1223-1237.
[12] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010) :16-23.
[13] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests. IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[14] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7) :1844-1850.
[15] Gerlach K, Steiner M J. Fast Convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48(9) :2686-2670.
[16] Guan J, Zhang Y F, Yong H. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1): 66-78.
[17]邢孟道.基于实测数据的雷达成像方法研究.博士研究生学位论文.西安电子科技大学.2002.
[18] Ye W, Yeo T S, Bao Z. Weighed least-squares estimation of phase errors for SAR/ISAR autofocus. IEEE Transactions on Geoscience and Remote Sensing. 1999, vol.37(5): 2487-2494.
[19]刘永坦.雷达成像技术.北京:国防工业出版社.1999.
[20]戴奉周.宽带雷达信号处理—检测、杂波抑制与认知跟踪.博士研究生学位论文.西安电子科技大学.2010.
[21] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57 (10): 3733-3745.
[1] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[2] Trees H L V, Detection, estimation, and modulation theory (Part III):radar-sonar signal processing and Gaussian signals in noise. New York: John Wiley and Sons, 2001.
[3] Gerlach K, Steiner M, Lin F C. Detection of a spatially distributed target in white noise. IEEE Signal Processing Letter. 1997, vol.4(7):198-200.
[4] Gerlach K, Steiner M, Lin F C. Spatially distributed target detection in non-Gaussian clutter. IEEE Transactions on Aerospace and Electronic Systems. 1999,vol.35(3):926-934.
[5] Worley R. Optimum thresholds for binary integration. IEEE Transactions on Information Theory. 1968, IT-4:349-352.
[6] Weiner M A. Binary integration for fluctuating targets. IEEE Transactions on Aerospace and Electronic Systems. 1991, vol.27(1) :11-17.
[7] Frey T L. An approximation for the optimum binary integration threshold for Swerling II targets. IEEE Transactions on Aerospace and Electronic Systems.1996, vol.32(3) :1181 -1185.
[8] Shnidman H L. Binary integration for Swerling target fluctuations. IEEE Transactions on Aerospace and Electronic Systems. 1998, vol.34(3): 1043 -1053.
[9]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[10] Hughes P K. A high-resolution radar detection strategy. IEEE Transactions on Aerospace and Electronic Systems. 1983, vol.19(5): 663-667.
[11]郭启俊,刘劲,刘宏伟.基于时频融合的分布式目标的恒虚警率检测.雷达科学与技术.2007, vol.5(1): 65-68.
[12] Papoulis A, Pillai S U. Probability, random variables and stochastic process, 4th ed. New York: McGraw-Hill. 2002.
[13] Gini F, Lombardini F, Verrazzni L. Decentralized CFAR detection with binaryintegration in Weibull clutter. IEEE Transactions on Aerospace and Electronic Systems. 1997,vol.33(2): 396-407.
[14] Maio A D, Nicola S D, Huang Y W, et al. Code design to optimize radar detection performance under accuracy and similarity constraints. IEEE Transactions on Signal Processing. 2008, vol.56(11): 5618-5629.
[15]赵树杰,赵建勋.信号检测与估值理论.北京:清华大学出版社,2005.
[1] Shui P L, Liu H W, Bao Z. Range-spread target detection based on cross time-frequency distribution features of two adjacent received signals. IEEE Transactions on Signal Processing. 2009, vol.57(10): 3733-3745.
[2] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part I: system concept. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 102-108.
[3] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part II: detection statistics. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 109-115.
[4] Carlson B D, Evans E D, Wilson S L. Search radar detection and track with the Hough transform, part III: detection performance with binary integration. IEEE Transactions on Aerospace and Electronic Systems. 1994, vol. 30(1): 116-125.
[5] Zeng J K, He Z S, Mathini S, et al. Modified Hough transform for searching radar detection. IEEE Geoscience and Remote Sensing Letters. 2008, vol.5(4): 683-686.
[6] Behar V, Vassileva B, Kabakchiev C. Adaptive Hough detector with binary integration in pulse jamming. Proceedings ECCTD'97, Budapest, 1997: 885-889.
[7] Behar V, Kabakchiev C. Hough detector with adaptive non-coherent integration for target detection in pulse jamming. Proceedings ISSSTA'98, South Africa, 1998:1003-1008.
[8] Kabakchiev C, Doukovska L, Garvanov I. Hough radar detectors in conditions of intensive pulse jamming, S&Te-Didest, ISSN 1726-5479, 2005:381-389.
[9]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[10]廖学军.基于高分辨距离像的雷达目标识别.博士研究生学位论文.西安电子科技大学.1999.
[11]黄培康,殷红成,徐小剑.雷达目标特性.北京:电子工业出版社,2005.
[12]戴奉周,刘宏伟,吴顺君.一种基于顺序统计量的距离扩展目标检测器.电子与信息学报.2009,vol.31(10) :2488-2492.
[13]李玉山.数字视觉和视频技术.西安:西安电子科技大学.2006.
[14] Leung S W, Minett J W, Siu Y M, et al. A fuzzy approach to signal integration. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(1): 346-350.
[15] Marichala J L, Kojadinovicb I. Distribution functions of linear combinations of lattice polynomials from the uniform distribution. Statistics and Probability Letters. 2008, vol.78(8): 985-991.
[16] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[1]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[2] Conte E, Maio A D, Ricci G. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol.49(7): 1336-1348.
[3] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007, vol.55(4): 1223-1237.
[4] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol. 38(2): 612-621.
[5] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010): 16-23.
[6] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests, IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2) :568-582.
[7] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing. 1999, vol.47(7): 1844-1850.
[8] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48 (9) :2686-2670.
[9] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributedtarget in compound-Gaussian clutter. Digital Signal Processing. 2009, vol.19(1): 66-78.
[10]胡文明,关键,何友.基于二维积累的雷达分布式目标检测新方法[J].系统工程与电子技术.2006,vol.28(9): 1335-1337.
[11] Leung S W, Minett J W, Siu Y M, et al. A fuzzy approach to signal integration. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol.38(1): 346-350.
[12] Skolnik M I. Radar Handbook. New York: McGraw-Hill, 1990.
[13]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[14]张贤达,矩阵分析与应用,北京:清华大学出版社,2004.
[15] Duda R O, Hart P E, Stork D G. Pattern Classification. 2rd ed. New York:John Wiley and Sons.2001.
[16]袁莉.基于高分辨距离像的雷达目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[1] Maio A D. Robust adaptive radar detection in the presence of steering vector mismatches. IEEE Transactions on Aerospace and Electronic Systems. 2005, vol.41(4): 1322-1337.
[2]杜兰.雷达高分辨距离像目标识别方法研究.博士研究生学位论文.西安电子科技大学.2007.
[3]赵树杰,赵建勋.信号检测与估值理论.北京:清华大学出版社,2005.
[4] Conte E, Maio A D, Ricci G. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Transactions on Signal Processing. 2001, vol. 49(7): 1336-1348.
[5] Bandiera F, Maio A D, Gerco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference.IEEE Transactions on Signal Processing. 2007,vol.55 (4): 1223-1237.
[6] Conte E, Maio A D. CFAR detection of distributed targets in non-Gaussian disturbance. IEEE Transactions on Aerospace and Electronic Systems. 2002, vol. 38(2): 612-621.
[7] Shuai X F, Kong L J, Yang J Y. Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing. 90(2010): 16-23.
[8] Conte E, Maio A D. Distributed target detection in compound-Gaussian noise with Rao and Wald tests. IEEE Transactions on Aerospace and Electronic Systems. 2003, vol.39(2): 568-582.
[9] Gerlach K, Steiner M J. Adaptive detection of range distributed targets. IEEE Transactions on Signal Processing.1999, vol.47(7): 1844-1850.
[10] Gerlach K, Steiner M J. Fast convergence adaptive detection of Doppler-shifted range-distributed targets. IEEE Transactions on Signal Processing. 2000, vol.48 (9): 2686-2670.
[11] Guan J, Zhang Y F, Huang Y. Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing. 2009, vol. 19(1): 66-78.
[12]保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[13]张贤达.矩阵分析与应用.北京:清华大学出版社,2004.
[14] Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2003.
[15] Sturm J F. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. Optimization Method Software.1999,vol. 18(7): 625-653.
[16] Lobo M, Vandenberghe L, Boyd S. H. Lebret.Applications of second-order cone programming. Linear Algebra and its Applications.1998,vol. 19(2): 193-228.