机载雷达恒虚警率检测方法研究
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摘要
干扰背景下的恒虚警率(CFAR)检测一直是雷达信号处理研究的热点和难点问题,而机载雷达采用的多工作模式及其所处的复杂的地、海杂波环境使其CFAR检测面临的困难尤为突出。本文结合某型机载雷达具体体制,系统地研究了该雷达在地、海杂波背景下的CFAR检测问题。主要工作包括:
(1)分布参数估计算法研究。准确地获取杂波的分布信息是机载雷达最优或准最优CFAR检测的基础。针对K分布参数最大似然估计求解计算量大的缺点,本文从算法的估计精度和实现复杂度两个方面对现有的七种基于矩方法的K分布参数估计算法进行了比较分析,并证明了几种算法之间的关系,在此基础上提出了一种基于zlog(z)期望的K分布参数估计算法,该算法同时应用了对数变换和分数阶矩,因此获得了更高的估计精度。本文同时给出了适宜机载雷达CFAR检测应用背景的参数估计算法的选择方案。
(2)分布模型辨识方法研究。在分布参数估计的基础上,本文接着对机载雷达分布模型辨识方法进行了研究。针对常用的Chi-Square检验受样本区间划分影响大和KS检验通用性差的缺点,提出了一种新的杂波分布辨识方法—PDF变换法,该方法利用了正态分布检验精度高,实现简单的优点,同时,该方法在分布模型解析表达式已知的情况下即可进行PDF变换,因此辨识精度和通用性都得到了较大的提高。随后,分析了各类杂波分布模型的偏度和峰度特征及其它们的相似性,为杂波分布模型辨识的精度分析提供了理论依据。
(3)在分布模型不确定或变化的地杂波环境中,针对基于单一分布模型的CFAR检测器信杂比损失较大的缺点,提出了一种适应于机载雷达多分布类型杂波环境的CFAR检测器—杂波分布检验CFAR(CT-CFAR)检测器,该CFAR检测器较为准确地利用了背景杂波的分布信息,且同时具有较好的虚警控制能力。接着,本文针对Smith等人提出的VI-CFAR检测器在多个干扰目标同时存在于参考窗两侧时检测性能下降的不足,提出了一种基于有序统计的可变性指示CFAR(OSVI-CFAR)检测器,该CFAR检测器结合OS类算法,同时在多目标干扰、杂波边缘和均匀背景下获得了较好的检测能力和虚警控制能力,在实际应用中具有更强的鲁棒性。
(4)海杂波的强相关性是影响CFAR检测性能的重要因素。本文在对海杂波相关性模型合理假设的基础上,分析了杂波结构分量空间相关长度不同时,CA-CFAR的虚警概率和检测概率在空间上的分布特性,理论分析和仿真实验结果表明,CA-CFAR检测器在逼近最优检测时,其参考窗长度应自适应于杂波空间相关长度的变化。但在实际的CFAR处理中,结构分量的空间相关长度需要估计获得,而现有的幅度域相关系数拟合估计法计算量大,针对这一缺点,本文利用近似的方法对其进行了简化。仿真实验结果表明,用简化前、后的幅度域相关系数拟合法获得的相关系数基本一致,证明了简化方法的有效性。
(5)本文最后基于机载雷达实测数据对第五章提出的CT-CFAR检测器和OSVI-CFAR检测器的检测性能进行了分析,实验结果验证了第五章提出的CFAR检测理论与仿真分析的正确性和有效性。
The constant false alarm rate (CFAR) detection in the presence of interfering background is always the hotspot and difficulty on the study of radar signal processing. Since the airborne radar adopts the multiple modes and confronts with complicated land and sea clutter, so the CFAR detection for airborne radar is especially difficult. Based on a certain airborne radar system, the theory and technique of CFAR detection for airborne radar in the presence of land and sea clutter environment are investigated in this dissertation. The main works of this dissertation can be summarized as follows:
First, the distribution parameter estimation algorithm is studied, since it is the foundation of the optimal or quasi-optimal CFAR detection. In view of the deficiency of extremely time consuming of the maximum likelihood (ML) estimation for K-distribution parameter, the existing seven parameter estimation algorithms based on method of moment (MOM) are analyzed by comparing their estimation accuracy and implementation complexity, and the relations of them are proved, then, a new parameter estimation algorithm based on z~rlog(z) expectation for K-distribution is proposed. The proposed algorithm applies both log transformation and fractional order moment, so its estimation precision is improved evidently. At the same time, a scheme of application of parameter estimation algorithms to airborne radar CFAR detection is presented.
Next, the methods of distribution model identification are studied in this dissertation. Aiming at the deficiencies that the common Chi-Square test is affected badly by sample interval division, and the KS test has poor universality, a new clutter distribution identification method, namely, PDF transform method is proposed. The proposed method has the virtues of high identification accuracy and realization simplification of the normal test, moreover, as long as the analytic expression of the distribution model is known, the PDF transform for the clutter sample could be done, so both the identification accuracy and universality are improved evidently. And then, the similarity of four distributions is analyzed by their Skewness and Kurtosis characteristics, and it offers an important academic gist for the precision analysis of the distribution model identification.
Thirdly, in the presence of ground clutter environment which the distribution model is uncertain or varying, in view of the deficiency of larger signal-to-noise ratio(SCR) loss with the CFAR detector based on single distribution model, a CFAR detector called CT-CFAR detector which adapt to multi-distribution clutter environment is proposed. The new CFAR detector applies the distribution information of clutter well, so it has better controlling capability of false alarm peak, simultaneity, it achieves certain CFAR gain compared to that for the general rayleigh-based CFAR detector in low SCR. And then, aiming at the deficiencies that the detection performanc of VI-CFAR detector may be seriously degraded when the interfering targets are present in both the halves of the reference window, a new adaptive CFAR detector, i.e. OSVI-CFAR detector is proposed, combining with OS algorithm, this detector achieves better detection performance and false alarm peak controlling capability in multiple interfering targets, clutter edge and homogeneous environment respectively, so it is more robust in practice.
Fourthly, the strong correlation of sea clutter has an important influence upon the CFAR detection performance. Based on rational hypothesis of the clutter correlation model, the spatial distribution characteristics of the false alarm probability and detection probability of CA-CFAR is analysed in this dissertation when the spatially correlation length of the clutter structure component is varying. Theoretical analysis and simulation results indicate that the reference window length of CA-CFAR detector should adapt to the change of clutter spatially correlation length when it approaches the optimal detection. But in practical CFAR process, the spatially correlation length of the structure component needs to be estimated. In view of extremely time consuming of the correlation coefficient fitting estimation method in amplitude domain, an approximate method is applied to simplify it. Simulation results prove the efficiency of the approximate method.
Finally, the detection performance of CT-CFAR and OSVI-CFAR which proposed in chapter 5 is analyzed basd on measured data. Experiment results demonstrate the correctness and validity of the CFAR detection theory proposed in chapter 5.
(1)分布参数估计算法研究。准确地获取杂波的分布信息是机载雷达最优或准最优CFAR检测的基础。针对K分布参数最大似然估计求解计算量大的缺点,本文从算法的估计精度和实现复杂度两个方面对现有的七种基于矩方法的K分布参数估计算法进行了比较分析,并证明了几种算法之间的关系,在此基础上提出了一种基于zlog(z)期望的K分布参数估计算法,该算法同时应用了对数变换和分数阶矩,因此获得了更高的估计精度。本文同时给出了适宜机载雷达CFAR检测应用背景的参数估计算法的选择方案。
(2)分布模型辨识方法研究。在分布参数估计的基础上,本文接着对机载雷达分布模型辨识方法进行了研究。针对常用的Chi-Square检验受样本区间划分影响大和KS检验通用性差的缺点,提出了一种新的杂波分布辨识方法—PDF变换法,该方法利用了正态分布检验精度高,实现简单的优点,同时,该方法在分布模型解析表达式已知的情况下即可进行PDF变换,因此辨识精度和通用性都得到了较大的提高。随后,分析了各类杂波分布模型的偏度和峰度特征及其它们的相似性,为杂波分布模型辨识的精度分析提供了理论依据。
(3)在分布模型不确定或变化的地杂波环境中,针对基于单一分布模型的CFAR检测器信杂比损失较大的缺点,提出了一种适应于机载雷达多分布类型杂波环境的CFAR检测器—杂波分布检验CFAR(CT-CFAR)检测器,该CFAR检测器较为准确地利用了背景杂波的分布信息,且同时具有较好的虚警控制能力。接着,本文针对Smith等人提出的VI-CFAR检测器在多个干扰目标同时存在于参考窗两侧时检测性能下降的不足,提出了一种基于有序统计的可变性指示CFAR(OSVI-CFAR)检测器,该CFAR检测器结合OS类算法,同时在多目标干扰、杂波边缘和均匀背景下获得了较好的检测能力和虚警控制能力,在实际应用中具有更强的鲁棒性。
(4)海杂波的强相关性是影响CFAR检测性能的重要因素。本文在对海杂波相关性模型合理假设的基础上,分析了杂波结构分量空间相关长度不同时,CA-CFAR的虚警概率和检测概率在空间上的分布特性,理论分析和仿真实验结果表明,CA-CFAR检测器在逼近最优检测时,其参考窗长度应自适应于杂波空间相关长度的变化。但在实际的CFAR处理中,结构分量的空间相关长度需要估计获得,而现有的幅度域相关系数拟合估计法计算量大,针对这一缺点,本文利用近似的方法对其进行了简化。仿真实验结果表明,用简化前、后的幅度域相关系数拟合法获得的相关系数基本一致,证明了简化方法的有效性。
(5)本文最后基于机载雷达实测数据对第五章提出的CT-CFAR检测器和OSVI-CFAR检测器的检测性能进行了分析,实验结果验证了第五章提出的CFAR检测理论与仿真分析的正确性和有效性。
The constant false alarm rate (CFAR) detection in the presence of interfering background is always the hotspot and difficulty on the study of radar signal processing. Since the airborne radar adopts the multiple modes and confronts with complicated land and sea clutter, so the CFAR detection for airborne radar is especially difficult. Based on a certain airborne radar system, the theory and technique of CFAR detection for airborne radar in the presence of land and sea clutter environment are investigated in this dissertation. The main works of this dissertation can be summarized as follows:
First, the distribution parameter estimation algorithm is studied, since it is the foundation of the optimal or quasi-optimal CFAR detection. In view of the deficiency of extremely time consuming of the maximum likelihood (ML) estimation for K-distribution parameter, the existing seven parameter estimation algorithms based on method of moment (MOM) are analyzed by comparing their estimation accuracy and implementation complexity, and the relations of them are proved, then, a new parameter estimation algorithm based on z~rlog(z) expectation for K-distribution is proposed. The proposed algorithm applies both log transformation and fractional order moment, so its estimation precision is improved evidently. At the same time, a scheme of application of parameter estimation algorithms to airborne radar CFAR detection is presented.
Next, the methods of distribution model identification are studied in this dissertation. Aiming at the deficiencies that the common Chi-Square test is affected badly by sample interval division, and the KS test has poor universality, a new clutter distribution identification method, namely, PDF transform method is proposed. The proposed method has the virtues of high identification accuracy and realization simplification of the normal test, moreover, as long as the analytic expression of the distribution model is known, the PDF transform for the clutter sample could be done, so both the identification accuracy and universality are improved evidently. And then, the similarity of four distributions is analyzed by their Skewness and Kurtosis characteristics, and it offers an important academic gist for the precision analysis of the distribution model identification.
Thirdly, in the presence of ground clutter environment which the distribution model is uncertain or varying, in view of the deficiency of larger signal-to-noise ratio(SCR) loss with the CFAR detector based on single distribution model, a CFAR detector called CT-CFAR detector which adapt to multi-distribution clutter environment is proposed. The new CFAR detector applies the distribution information of clutter well, so it has better controlling capability of false alarm peak, simultaneity, it achieves certain CFAR gain compared to that for the general rayleigh-based CFAR detector in low SCR. And then, aiming at the deficiencies that the detection performanc of VI-CFAR detector may be seriously degraded when the interfering targets are present in both the halves of the reference window, a new adaptive CFAR detector, i.e. OSVI-CFAR detector is proposed, combining with OS algorithm, this detector achieves better detection performance and false alarm peak controlling capability in multiple interfering targets, clutter edge and homogeneous environment respectively, so it is more robust in practice.
Fourthly, the strong correlation of sea clutter has an important influence upon the CFAR detection performance. Based on rational hypothesis of the clutter correlation model, the spatial distribution characteristics of the false alarm probability and detection probability of CA-CFAR is analysed in this dissertation when the spatially correlation length of the clutter structure component is varying. Theoretical analysis and simulation results indicate that the reference window length of CA-CFAR detector should adapt to the change of clutter spatially correlation length when it approaches the optimal detection. But in practical CFAR process, the spatially correlation length of the structure component needs to be estimated. In view of extremely time consuming of the correlation coefficient fitting estimation method in amplitude domain, an approximate method is applied to simplify it. Simulation results prove the efficiency of the approximate method.
Finally, the detection performance of CT-CFAR and OSVI-CFAR which proposed in chapter 5 is analyzed basd on measured data. Experiment results demonstrate the correctness and validity of the CFAR detection theory proposed in chapter 5.
引文
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