高距离分辨海杂波背景下目标检测方法
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摘要
本文主要研究高分辨海杂波背景下的若干目标检测技术。海杂波中的目标检测一直是重要的研究课题，也是雷达信号处理中最复杂的问题之一，在军事、民用领域均有广阔的应用前景。高距离分辨海杂波表现出空时非平稳特性和非高斯特性，这些特性严重影响了海面上空的空中目标和海面漂浮目标的检测。
基于实测IPIX雷达采集的海杂波数据，研究了海面上空的低空目标和海表面的漂浮目标的检测算法。针对目前广泛应用在海杂波背景下的自适应归一化匹配滤波检测器，分析了该检测器的内在矛盾，并提出了多种解决方案缓解这一矛盾，主要包括使用距离过采样样本、杂波抑制算法、块自适应归一化匹配滤波检测器和子带自适应归一化匹配滤波检测器，这些算法均建立在加性模型的基础上，适用于检测海面上空的低空目标。最后，为了更好地检测海面漂浮小目标，提出了非加性模型下的三特征检测算法。
本文的主要研究成果可概括为以下五部分：
第一部分，介绍了海杂波的模型，明确了海杂波的空间均匀性，描述了相干检测算法的发展历程，指出了长的积累时间与有限的参考样本数量之间的矛盾是自适应归一化匹配滤波检测器的内在矛盾，最后，介绍了IPIX雷达采集的实测数据，为后续的研究奠定基础。
第二部分，研究了自适应归一化匹配滤波检测器在距离过采样背景下的性能增益。自适应归一化匹配滤波检测器的检测性能与估计的协方差矩阵密切相关。样本协方差矩阵估计器作为一种最常见的协方差估计算法，已经在独立同分布的高斯参考样本下有了彻底研究，但是在距离过采样的样本情况下却没有被研究。现役雷达系统的接收机采用距离过采样技术，参考样本在空间上是相关的。我们参考气象和海洋雷达中的距离过采样模型，建立了距离过采样杂波向量的空间相关模型，分析了样本协方差矩阵估计器的误差，得出了过采样增益。过采样增益是与过采样因子和雷达接收机带宽密切相关的。过采样增益评价自适应归一化匹配滤波检测器的性能改善。实测的雷达数据实验结果显示，距离过采样技术使得自适应归一化匹配滤波检测器的性能有了显著的改善。
第三部分，研究了高分辨海杂波背景下的杂波抑制算法和目标检测算法。该内容分为两部分：杂波抑制和目标检测。在杂波抑制部分，利用邻近的距离单元和邻近的时间区间里的时间序列计算功率谱，提出了一个基于中值的估计器来估计高分辨海杂波的功率谱，该估计器对少量异常变化的时间序列是稳健的。基于估计的功率谱，设计了一个块自适应杂波抑制滤波器来抑制积累前的杂波。在目标检测部分，由于滤波后的残余杂波服从球不变随机向量模型，将自适应归一化匹配滤波检测器延伸到残余杂波中，得到了残余杂波的自适应归一化匹配滤波检测器。紧接着，注意到高分辨海杂波和残余杂波的近似平稳时间远小于目标回波的相干处理时间，为了积累更多的脉冲，并且同时提高检测性能，我们又提出了一个具有启发式的块自适应归一化匹配滤波检测器。最后，在实测海杂波背景下，实验结果表明，当仿真目标不位于强杂波区时，自适应归一化匹配滤波检测器和块自适应归一化匹配滤波检测器在残余杂波环境下获得了更好的检测性能，鉴于此，提出了双通道检测机制。
第四部分，研究了高分辨海杂波背景下子带自适应归一化匹配滤波检测器。高距离分辨海杂波的空时非平稳特性限制了自适应归一化匹配滤波检测器的检测性能，具体表现在：杂波的空间非平稳性限制了可获得的参考空间样本数，杂波的时间非平稳性限制了积累时间。为了解除这个限制，提出了子带自适应归一化匹配滤波检测器，它包括一个DFT调制滤波器组和紧跟其后的一系列自适应归一化匹配滤波检测器。滤波器组的功能是将接收的时间序列低速率地分解成子带时间序列，它具有如下的优点：子带分解抑制通带外的杂波和改善杂波的短期平稳性。由于子带杂波具有更好的短期平稳性和更低的速率，子带自适应归一化匹配滤波检测器比自适应归一化匹配滤波检测器拥有更长的积累时间。实测的杂波数据实验结果显示子带自适应归一化匹配滤波检测器优于自适应归一化匹配滤波检测器。
第五部分，研究了海面漂浮小目标的特征检测算法。海面目标改变了周围海面的散射几何结构，高分辨雷达的散射回波不再满足传统的加性模型，而是满足非加性模型。基于这个非加性模型，我们将目标检测问题转化为一种特殊的只含有一类的分类问题：纯杂波模式。提取平均功率、多普勒偏移以及多普勒带宽组成一个三维的特征向量，在三维特征空间里设计三特征检测算法。利用提出的凸包训练算法训练纯杂波模式下三维空间的检测区域，该检测区域由具有多面体结构的凸包构成，它存在快速的设计算法。利用IPIX雷达数据的实验结果表明在检测海面漂浮小目标时，三特征检测算法比已有的检测算法具有更优越的性能。
The main research in the dissertation is several target detection methods in high rangeresolution sea clutter. Detection in sea clutter is an important issue, and it is one of themost complex problems in radar signal processing. Target detection in sea clutter canpotentially be utilized in military and civil field. Due to the spatial-temporal non-stationarity and non-Gaussian property of high range resolution sea clutter, targetdetection methods become complicated for the aircrafts over the sea and the floatingtargets on the sea surface.
Based on the real IPIX radar sea clutter, the paper focuses on the target detections forthe aircrafts over the sea and the floating targets on the sea surface. Adaptivenormalized matched filter (ANMF) detector is widely used in sea clutter for targetdetection. We analyze the intrinsic conflict in the ANMF detector, and propose someschemes to alleviate the conflict. The main work includes the utilization of range-oversampled samples, clutter suppression algorithm, B-ANMF detector, and subbandANMF detector. All the algorithms mentioned above are based on the traditionaladditive model, and are applied to detecting aircrafts over the sea. Finally, atri-features-based detection algorithm is proposed for better detecting the floatingtargets on the sea surface.
The main content of this dissertation is summarized as follows.
The first part introduces the model of sea clutter, defines the homogeneous sea clutter,makes a detailed analysis on the development of coherent detectors, and points out thatthe intrinsic conflict in the ANMF detector is between the long integration duration andthe finite secondary samples. Finally, we introduce the real sea clutter data collected byIPIX radar, which forms the basis for the following study.
The second part focuses on the performance gain of ANMF detector in range-oversampling case. The performance of ANMF detector depends on the estimation ofclutter covariance matrix. As an average estimator, the sample covariance matrix (SCM)estimator has been thoroughly analyzed for independent and identically distributedGaussian clutter vectors, but not for the range-oversampled secondary samples. Manyradar systems on service use range-oversampled receivers. Thus, the secondary samplesare correlated in spatially. Referred to the range-oversampled model in the weather andoceanic radars, the spatial correlation model of range-oversampled clutter vectors isestablished, the error of the SCM estimator is analyzed, and the range-oversampling gain, relevant to the oversampling factor and the receiver’s bandwidth, is derived. Therange-oversampling gain is used to evaluate the gain of performance of ANMF detector.The experiments using real radar clutter data are made to verify the range-oversamplinggain, showing that the range-oversampling improves the performance of ANMFdetector.
The third part is contributed to clutter suppression algorithm and target detection inhigh range resolution sea clutter. The thesis basically consists of two parts: cluttersuppression and target detection. In the part of clutter suppression, it commences with aproposal of median-based estimator to estimate the power spectrum of high resolutionsea clutter by the time series observed in adjacent range cells and time intervals. Theestimator provides a robust estimation when just a few aberrant time series happen inobservation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF)is designed to suppress the clutter prior to the pulse integration. In the part of targetdetection, due to that the residual clutter, the output of the BACSF, is modeled asspherically invariant random vector (SIRV), upon applying an ANMF detector to theresidual clutter, a residual clutter’s ANMF detector is derived. Moreover, in highresolution radar background, considering that the approximately stationary intervals ofsea clutter and residual clutter are much shorter than the coherent processing interval(CPI), another heuristic B-ANMF detector is proposed. It can integrate more pulses andachieve better performance than the ANMF detector does. The chapter concludes withexperiments of simulated target against the real sea clutter. Experimental resultsdemonstrate that, when target’s Doppler frequency is beyond strong clutter region, theANMF detector and B-ANMF detector perform better in residual clutter than in clutter.Hence, a double-channel scheme is given.
The fourth part focuses on the subband ANMF detector in high range resolution seaclutter which is spatial-temporally non-stationary. The ANMF detector is limited inperformance, because the non-stationarity in spatially of the clutter restricts the spatialsamples available and the non-stationarity in temporally restricts the integrationduration. In order to overcome this limitation, a subband ANMF detector is proposed. Itconsists of a forward DFT modulated filter bank followed by a set of ANMF detectorsin individual subbands. The forward filter bank is used to decompose received signals ofhigh rate into subband signals of low rate. The subband decomposition via the filterbank realizes clutter suppression outside each subband and improves the short-termstationarity of sea clutter. Improved short-term stationarity and the low rate of subbandsignals allow the subband ANMF detector to have much longer integration durations than the traditional ANMF detector to do. The experimental results using real sea clutterdata show that the subband ANMF detector attains a much better detection performancethan the traditional ANMF detector does.
The fifth part is contributed to the feature detection for floating small targets on seasurface. Presence of a surface target alters the scattering geometry of the sea surfacearound the target. It is shown that the observation in the high range resolution followsthe non-additive model rather than the traditional additive one. Under the non-additivemodel, target detection boils down to a special classification problem of the clutter-onlypattern. The average power, the Doppler offset and bandwidth are extracted andarranged into a three-dimensional feature vector. The tri-features-based detector isdesigned in the three-dimensional feature space. A convex-hull training algorithm isproposed to determine a three-dimensional decision region of the clutter-only patternfrom clutter-only data. The convex-hull’s polyhedron structure of the decision regionsupports a fast decision. The experimental results using the IPIX datasets show that thetri-features-based detector attains an excellent performance than available detectors doin detecting floating small targets on sea surface.
基于实测IPIX雷达采集的海杂波数据，研究了海面上空的低空目标和海表面的漂浮目标的检测算法。针对目前广泛应用在海杂波背景下的自适应归一化匹配滤波检测器，分析了该检测器的内在矛盾，并提出了多种解决方案缓解这一矛盾，主要包括使用距离过采样样本、杂波抑制算法、块自适应归一化匹配滤波检测器和子带自适应归一化匹配滤波检测器，这些算法均建立在加性模型的基础上，适用于检测海面上空的低空目标。最后，为了更好地检测海面漂浮小目标，提出了非加性模型下的三特征检测算法。
本文的主要研究成果可概括为以下五部分：
第一部分，介绍了海杂波的模型，明确了海杂波的空间均匀性，描述了相干检测算法的发展历程，指出了长的积累时间与有限的参考样本数量之间的矛盾是自适应归一化匹配滤波检测器的内在矛盾，最后，介绍了IPIX雷达采集的实测数据，为后续的研究奠定基础。
第二部分，研究了自适应归一化匹配滤波检测器在距离过采样背景下的性能增益。自适应归一化匹配滤波检测器的检测性能与估计的协方差矩阵密切相关。样本协方差矩阵估计器作为一种最常见的协方差估计算法，已经在独立同分布的高斯参考样本下有了彻底研究，但是在距离过采样的样本情况下却没有被研究。现役雷达系统的接收机采用距离过采样技术，参考样本在空间上是相关的。我们参考气象和海洋雷达中的距离过采样模型，建立了距离过采样杂波向量的空间相关模型，分析了样本协方差矩阵估计器的误差，得出了过采样增益。过采样增益是与过采样因子和雷达接收机带宽密切相关的。过采样增益评价自适应归一化匹配滤波检测器的性能改善。实测的雷达数据实验结果显示，距离过采样技术使得自适应归一化匹配滤波检测器的性能有了显著的改善。
第三部分，研究了高分辨海杂波背景下的杂波抑制算法和目标检测算法。该内容分为两部分：杂波抑制和目标检测。在杂波抑制部分，利用邻近的距离单元和邻近的时间区间里的时间序列计算功率谱，提出了一个基于中值的估计器来估计高分辨海杂波的功率谱，该估计器对少量异常变化的时间序列是稳健的。基于估计的功率谱，设计了一个块自适应杂波抑制滤波器来抑制积累前的杂波。在目标检测部分，由于滤波后的残余杂波服从球不变随机向量模型，将自适应归一化匹配滤波检测器延伸到残余杂波中，得到了残余杂波的自适应归一化匹配滤波检测器。紧接着，注意到高分辨海杂波和残余杂波的近似平稳时间远小于目标回波的相干处理时间，为了积累更多的脉冲，并且同时提高检测性能，我们又提出了一个具有启发式的块自适应归一化匹配滤波检测器。最后，在实测海杂波背景下，实验结果表明，当仿真目标不位于强杂波区时，自适应归一化匹配滤波检测器和块自适应归一化匹配滤波检测器在残余杂波环境下获得了更好的检测性能，鉴于此，提出了双通道检测机制。
第四部分，研究了高分辨海杂波背景下子带自适应归一化匹配滤波检测器。高距离分辨海杂波的空时非平稳特性限制了自适应归一化匹配滤波检测器的检测性能，具体表现在：杂波的空间非平稳性限制了可获得的参考空间样本数，杂波的时间非平稳性限制了积累时间。为了解除这个限制，提出了子带自适应归一化匹配滤波检测器，它包括一个DFT调制滤波器组和紧跟其后的一系列自适应归一化匹配滤波检测器。滤波器组的功能是将接收的时间序列低速率地分解成子带时间序列，它具有如下的优点：子带分解抑制通带外的杂波和改善杂波的短期平稳性。由于子带杂波具有更好的短期平稳性和更低的速率，子带自适应归一化匹配滤波检测器比自适应归一化匹配滤波检测器拥有更长的积累时间。实测的杂波数据实验结果显示子带自适应归一化匹配滤波检测器优于自适应归一化匹配滤波检测器。
第五部分，研究了海面漂浮小目标的特征检测算法。海面目标改变了周围海面的散射几何结构，高分辨雷达的散射回波不再满足传统的加性模型，而是满足非加性模型。基于这个非加性模型，我们将目标检测问题转化为一种特殊的只含有一类的分类问题：纯杂波模式。提取平均功率、多普勒偏移以及多普勒带宽组成一个三维的特征向量，在三维特征空间里设计三特征检测算法。利用提出的凸包训练算法训练纯杂波模式下三维空间的检测区域，该检测区域由具有多面体结构的凸包构成，它存在快速的设计算法。利用IPIX雷达数据的实验结果表明在检测海面漂浮小目标时，三特征检测算法比已有的检测算法具有更优越的性能。
The main research in the dissertation is several target detection methods in high rangeresolution sea clutter. Detection in sea clutter is an important issue, and it is one of themost complex problems in radar signal processing. Target detection in sea clutter canpotentially be utilized in military and civil field. Due to the spatial-temporal non-stationarity and non-Gaussian property of high range resolution sea clutter, targetdetection methods become complicated for the aircrafts over the sea and the floatingtargets on the sea surface.
Based on the real IPIX radar sea clutter, the paper focuses on the target detections forthe aircrafts over the sea and the floating targets on the sea surface. Adaptivenormalized matched filter (ANMF) detector is widely used in sea clutter for targetdetection. We analyze the intrinsic conflict in the ANMF detector, and propose someschemes to alleviate the conflict. The main work includes the utilization of range-oversampled samples, clutter suppression algorithm, B-ANMF detector, and subbandANMF detector. All the algorithms mentioned above are based on the traditionaladditive model, and are applied to detecting aircrafts over the sea. Finally, atri-features-based detection algorithm is proposed for better detecting the floatingtargets on the sea surface.
The main content of this dissertation is summarized as follows.
The first part introduces the model of sea clutter, defines the homogeneous sea clutter,makes a detailed analysis on the development of coherent detectors, and points out thatthe intrinsic conflict in the ANMF detector is between the long integration duration andthe finite secondary samples. Finally, we introduce the real sea clutter data collected byIPIX radar, which forms the basis for the following study.
The second part focuses on the performance gain of ANMF detector in range-oversampling case. The performance of ANMF detector depends on the estimation ofclutter covariance matrix. As an average estimator, the sample covariance matrix (SCM)estimator has been thoroughly analyzed for independent and identically distributedGaussian clutter vectors, but not for the range-oversampled secondary samples. Manyradar systems on service use range-oversampled receivers. Thus, the secondary samplesare correlated in spatially. Referred to the range-oversampled model in the weather andoceanic radars, the spatial correlation model of range-oversampled clutter vectors isestablished, the error of the SCM estimator is analyzed, and the range-oversampling gain, relevant to the oversampling factor and the receiver’s bandwidth, is derived. Therange-oversampling gain is used to evaluate the gain of performance of ANMF detector.The experiments using real radar clutter data are made to verify the range-oversamplinggain, showing that the range-oversampling improves the performance of ANMFdetector.
The third part is contributed to clutter suppression algorithm and target detection inhigh range resolution sea clutter. The thesis basically consists of two parts: cluttersuppression and target detection. In the part of clutter suppression, it commences with aproposal of median-based estimator to estimate the power spectrum of high resolutionsea clutter by the time series observed in adjacent range cells and time intervals. Theestimator provides a robust estimation when just a few aberrant time series happen inobservation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF)is designed to suppress the clutter prior to the pulse integration. In the part of targetdetection, due to that the residual clutter, the output of the BACSF, is modeled asspherically invariant random vector (SIRV), upon applying an ANMF detector to theresidual clutter, a residual clutter’s ANMF detector is derived. Moreover, in highresolution radar background, considering that the approximately stationary intervals ofsea clutter and residual clutter are much shorter than the coherent processing interval(CPI), another heuristic B-ANMF detector is proposed. It can integrate more pulses andachieve better performance than the ANMF detector does. The chapter concludes withexperiments of simulated target against the real sea clutter. Experimental resultsdemonstrate that, when target’s Doppler frequency is beyond strong clutter region, theANMF detector and B-ANMF detector perform better in residual clutter than in clutter.Hence, a double-channel scheme is given.
The fourth part focuses on the subband ANMF detector in high range resolution seaclutter which is spatial-temporally non-stationary. The ANMF detector is limited inperformance, because the non-stationarity in spatially of the clutter restricts the spatialsamples available and the non-stationarity in temporally restricts the integrationduration. In order to overcome this limitation, a subband ANMF detector is proposed. Itconsists of a forward DFT modulated filter bank followed by a set of ANMF detectorsin individual subbands. The forward filter bank is used to decompose received signals ofhigh rate into subband signals of low rate. The subband decomposition via the filterbank realizes clutter suppression outside each subband and improves the short-termstationarity of sea clutter. Improved short-term stationarity and the low rate of subbandsignals allow the subband ANMF detector to have much longer integration durations than the traditional ANMF detector to do. The experimental results using real sea clutterdata show that the subband ANMF detector attains a much better detection performancethan the traditional ANMF detector does.
The fifth part is contributed to the feature detection for floating small targets on seasurface. Presence of a surface target alters the scattering geometry of the sea surfacearound the target. It is shown that the observation in the high range resolution followsthe non-additive model rather than the traditional additive one. Under the non-additivemodel, target detection boils down to a special classification problem of the clutter-onlypattern. The average power, the Doppler offset and bandwidth are extracted andarranged into a three-dimensional feature vector. The tri-features-based detector isdesigned in the three-dimensional feature space. A convex-hull training algorithm isproposed to determine a three-dimensional decision region of the clutter-only patternfrom clutter-only data. The convex-hull’s polyhedron structure of the decision regionsupports a fast decision. The experimental results using the IPIX datasets show that thetri-features-based detector attains an excellent performance than available detectors doin detecting floating small targets on sea surface.
引文
[1]丁鹭飞,耿富录.雷达原理.西安:西安电子科技大学出版社,1984.
[2] K. D. Ward, R. J. A. Tough, S. Watts. Sea clutter: scattering, the K distributionand radar performance. Published by the institution of engineering and technique,London, United Kingdom,(Chapter4),2006.
[3] D. Walker. Doppler modelling of radar sea clutter. IEE Proc. Radar, Sonar Navig.,2001, March,148(2):73-80.
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