动目标检测、成像与参数估计方法研究
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摘要
运动目标探测是雷达系统的最重要功能之一提高动目标检测性能，主要依赖于两点：一是有效地抑制杂波，二是对目标进行有效地聚焦借助多个天线的自由度信息能够有效地实现杂波抑制，这样，如何提高各天线通道的一致性以及更加有效的杂波抑制算法就成为动目标检测的重要内容之一随着动目标探测技术研究的不断深入和发展，实现动目标检测的同时估计得到目标的运动参数及位置和目标的SAR成像也成为重要的系统要求和研究内容
本论文主要围绕两方面内容进行了相关研究：一是提高目标检测性能的方法：如何有效抑制杂波以及如何对目标进行良好聚焦；二是在目标检测后，如何有效估计目标的运动参数，具体如下：
1.多通道SAR-GMTI通道均衡及动目标检测定位方法
通道一致性问题是实现多通道SAR-GMTI系统杂波抑制和动目标检测的关键问题针对多通道SAR-GMTI系统，提出了一种新的通道均衡方法和基于该均衡的动目标检测定位方法该方法先利用泄漏信号进行电路中信号均衡，后进行通道间快时间和慢时间校准并在距离压缩后通过迭代补偿通道差异，再经杂波对消和方位压缩实现动目标检测，最后通过估计动目标多普勒偏移的方法完成参数估计该通道均衡方法不需要天线参数平台运动参数等先验信息，避免了图像配准过程和自适应杂波相消处理，因而计算量小，易于实现实测数据实验结果证明该方法杂波对消比能够达到20dB，检测和定位性能好
2.基于总体最小二乘的多通道SAR-GMTI方法
针对多通道SAR-GMTI处理中噪声导致杂波相关性差而使杂波抑制性能降低的问题，提出了一种基于总体最小二乘的SAR-GMTI方法该方法利用检测单元周围的相邻像素杂波信息在整体最小二乘意义下拟合检测单元杂波特性，消除了噪声影响，提高了多个通道杂波之间的相关性，改善了杂波抑制性能，而且该方法具有很好的通道误差稳健性，仿真数据处理和实测数据处理验证了该方法的有效性
3.多通道SAR多目标高概率检测与高精度成像方法
在多通道SAR-GMTI系统中，目标运动会导致目标的越距离单元走动和方位调频率偏移由于目标的运动参数未知，传统的SAR-GMTI处理方法利用静止场景参数对目标进行聚焦，这会导致目标散焦检测概率下降等问题另外，传统的方法只能在目标检测并进行目标逐一提取以后逐一对目标进行参数估计，这将带来很大的运算复杂度针对这些问题，本论文提出了一种不需要动目标运动参数等先验知识的多目标高概率检测和成像方法该方法首先利用Keystone变换和相位补偿滤波器组消除目标距离走动，后利用LVD变换对多个目标在LVD平面同时进行聚焦在该平面对目标进行目标检测后，可以得到这些目标的多普勒调频率，最后可以实现目标SAR成像实测数据处理证明该方法能够克服目标越距离单元走动和调频率偏移导致的散焦问题，从而有效提高了动目标的检测概率
4.机载双基正侧阵雷达杂波抑制方法
机载双基雷达收发分置的双基结构使杂波二维分布呈现距离依赖性，导致空时自适应处理很难得到独立同分布的距离样本来估计杂波统计特性，因而杂波抑制性能很差针对此问题，提出了利用MIMO或者重叠子阵交替发射的机载双基正侧阵雷达杂波抑制方法这两种方法利用发射端空间自由度信息使机载双基正侧阵雷达的杂波脊落在发射和接收空间频率以及多普勒频率构成的三维频率空间的一个平面上，并且目标通常具有一定径向速度而不落在该平面由于该杂波平面具有距离平稳性，这保证了空时自适应处理可以有效地抑制该杂波平面，进而能够有效抑制距离非平稳杂波
5.运动目标空时参数快速估计方法
常规的运动目标空时参数估计方法需要参数精细搜索，估计精度和搜索的步长有关，计算量很大针对此问题，提出了两种目标空时参数快速估计方法：基于多项式求根的目标空时参数最大似然估计方法利用目标所在频率附近的3个频率通道的导向矢量做自适应滤波得到3个不同的自适应权矢量和输出响应，用多项式求根方法估计得到目标的空时频率；基于二阶多项式拟合的目标空时参数最大似然估计算法利用对目标频率滤波后响应主瓣附近的三个频率的输出，进行二阶多项式拟合，通过求解极值得到目标空时频率的最大似然估计值这两种方法大大降低了目标空时参数估计的计算复杂度，且在得到与参数搜索方法类似的估计精度时计算量均远远小于参数搜索方法
The moving target detection (MTD) is one of the most important functions of radarsystem. The MTD performance is mainly dominated by the performances of cluttersuppression and target focusing. Clutter suppression can be realized effectivelyexploiting the degrees of freedom (DOF) of multiple antennas. Therefore, how toimprove the coherence of different channels and how to suppress the clutter effectivelybecome the most important subjects of MTD technique. Along with the development ofthe MTD research, the motion parameters estimation and the imaging of the movingtarget also become an important demand and a researching subject.
This dissertation is mainly devoted to two subjects: one is how to improve the MTDperformance containing how to suppress the clutter and focus the targets effectively;one is how to estimate the target parameters effectively. The main research results are asfollows:
1. The channel equalization and moving target detection and location formulti-channel SAR-GMTI,
Improving the coherence of different channels is the key problem in MTD forairborne multi-channel SAR-GMTI system. Aiming at the problem, a novel channelequalization method is presented, and a technique for moving target detection (MTD)and location based on which is further proposed. This method first realizes circuitscalibration utilizing the leaking signals, then implements fast and slow time calibrationand compensates the channel differences via iteration after range compression, after thatrealizes MTD by clutter cancellation and imaging, finally obtains target parameters byestimating moving target Doppler shift. The channel equalization method needs nopriori knowledge such as the parameters of antenna and the plane’s movement, andavoids image registration and auto adaptive clutter cancellation method. Thus it’s ofless computation and easy to realize. The experiment result of real data proved that themethod can achieve a clutter cancellation ratio of more than20dB, and it has gooddetection and location performance.
2. Multi-channel SAR-GMTI based on total least squares method
Aiming at the poor clutter suppression performance induced by noise and poorclutter coherence in multi-channel SAR-GMTI, a method for SAR-GMTI based on totalleast squares is presented. The method adopts adjacent pixels around detection pixel tofit it under total least squares criterion, which can eliminate the influence of noise andimprove clutter coherence, thus lead to performance improvement on clutter suppression. Besides, the method is robust to error. Finally, simulation results and realdata processing are given to demonstrate the effectiveness of the method.
3. The detection with high detection probability and the imaging with highaccuracy for multiple targets in multi-channel SAR
For Multi-channel SAR-GMTI system, the movement of the targets leads to rangecell movement (RCM) and the shift of their Doppler rates. As the motion parameters ofthe targets are unknown, they are focused using the parameters of the stationary scene,which will induce their defocus and the degrade of their detection probability. Inaddition, the targets are extracted from SAR image and processed to obtain their motionparameters singly, which brings great computation complexity. To solve the problems, anew method to moving target imaging and detection with high detection probability ispresented. It first corrects RCM using Keystone transform and filter group whichcompensating phases of the target. Then LVD transform is performed to focusing thetargets. After detecting the moving targets in the LVD plane, the Doppler rates of themultiple targets are obtained. At last, targets imaging is realized in SAR image. Theprocessing of real data testifies that it can overcome RCM and the defocus induced bychirp rate shift, therefore improves the detection probability of targets efficiently.
4. Clutter suppression algorithm for airborne bistatic sidelooking radar
A simultaneous transmitter and receiver motion of the bistatic radar complicatesthe clutter spectra over range and makes the clutter spectra range-dependent [1].Range-dependent clutter makes space time adaptive processing (STAP) difficult toobtain independently and identically distributed (i.i.d.) secondary data used forcovariance matrix estimation, which will lead to the decline of the clutter suppressionperformance. To solve the problem, two clutter suppression algorithms for airbornebistatic sidelooking radar using MIMO or overlapped subarray alternate transmitting aredeveloped. In the methods, by incorporating the transmit degree of freedom (DOF), thebistatic clutter ridge turns to be a three-dimensional ridge. Moreover, the clutter ridgesof all range bins locate in the same plane of the three-dimensional space, while themoving targets don’t because of their radial velocity. For the clutter in the plane isrange-independent, it can be suppressed effectively by3-dimensional STAP.
5. Fast algorithm for moving target space-time parameters estimation
The traditional method for moving target space-time parameters estimation needsrefined parameter searching, which leads to heavy computation burden. And itsestimation accuracy is related to the searching pace. To overcome the problem, two fastalgorithms for target space-time parameters estimation are developed: The maximum likelihood estimation based on polynomial rooting performs adaptive processing usingthe steering vectors of the three frequency channels neighbor to that of the target. In thisway, three adaptive weights and three response output are obtained. Then the space-timeparameters of the target are estimated by rooting a polynomial; the maximum likelihoodestimation based on quadratic polynomial approximation performs the quadraticpolynomial approximation of the spectrum of the frequency response using the outputof the three channels round which of the target. Then the space-time parameters of thetarget are estimated by calculating the extremum. The two methods effectively lower thecomputation complexity of the target space-time parameters estimation. Compared toparameter grid searching methods, their computation complexity is much decreasedwhile in the same accuracy.
本论文主要围绕两方面内容进行了相关研究：一是提高目标检测性能的方法：如何有效抑制杂波以及如何对目标进行良好聚焦；二是在目标检测后，如何有效估计目标的运动参数，具体如下：
1.多通道SAR-GMTI通道均衡及动目标检测定位方法
通道一致性问题是实现多通道SAR-GMTI系统杂波抑制和动目标检测的关键问题针对多通道SAR-GMTI系统，提出了一种新的通道均衡方法和基于该均衡的动目标检测定位方法该方法先利用泄漏信号进行电路中信号均衡，后进行通道间快时间和慢时间校准并在距离压缩后通过迭代补偿通道差异，再经杂波对消和方位压缩实现动目标检测，最后通过估计动目标多普勒偏移的方法完成参数估计该通道均衡方法不需要天线参数平台运动参数等先验信息，避免了图像配准过程和自适应杂波相消处理，因而计算量小，易于实现实测数据实验结果证明该方法杂波对消比能够达到20dB，检测和定位性能好
2.基于总体最小二乘的多通道SAR-GMTI方法
针对多通道SAR-GMTI处理中噪声导致杂波相关性差而使杂波抑制性能降低的问题，提出了一种基于总体最小二乘的SAR-GMTI方法该方法利用检测单元周围的相邻像素杂波信息在整体最小二乘意义下拟合检测单元杂波特性，消除了噪声影响，提高了多个通道杂波之间的相关性，改善了杂波抑制性能，而且该方法具有很好的通道误差稳健性，仿真数据处理和实测数据处理验证了该方法的有效性
3.多通道SAR多目标高概率检测与高精度成像方法
在多通道SAR-GMTI系统中，目标运动会导致目标的越距离单元走动和方位调频率偏移由于目标的运动参数未知，传统的SAR-GMTI处理方法利用静止场景参数对目标进行聚焦，这会导致目标散焦检测概率下降等问题另外，传统的方法只能在目标检测并进行目标逐一提取以后逐一对目标进行参数估计，这将带来很大的运算复杂度针对这些问题，本论文提出了一种不需要动目标运动参数等先验知识的多目标高概率检测和成像方法该方法首先利用Keystone变换和相位补偿滤波器组消除目标距离走动，后利用LVD变换对多个目标在LVD平面同时进行聚焦在该平面对目标进行目标检测后，可以得到这些目标的多普勒调频率，最后可以实现目标SAR成像实测数据处理证明该方法能够克服目标越距离单元走动和调频率偏移导致的散焦问题，从而有效提高了动目标的检测概率
4.机载双基正侧阵雷达杂波抑制方法
机载双基雷达收发分置的双基结构使杂波二维分布呈现距离依赖性，导致空时自适应处理很难得到独立同分布的距离样本来估计杂波统计特性，因而杂波抑制性能很差针对此问题，提出了利用MIMO或者重叠子阵交替发射的机载双基正侧阵雷达杂波抑制方法这两种方法利用发射端空间自由度信息使机载双基正侧阵雷达的杂波脊落在发射和接收空间频率以及多普勒频率构成的三维频率空间的一个平面上，并且目标通常具有一定径向速度而不落在该平面由于该杂波平面具有距离平稳性，这保证了空时自适应处理可以有效地抑制该杂波平面，进而能够有效抑制距离非平稳杂波
5.运动目标空时参数快速估计方法
常规的运动目标空时参数估计方法需要参数精细搜索，估计精度和搜索的步长有关，计算量很大针对此问题，提出了两种目标空时参数快速估计方法：基于多项式求根的目标空时参数最大似然估计方法利用目标所在频率附近的3个频率通道的导向矢量做自适应滤波得到3个不同的自适应权矢量和输出响应，用多项式求根方法估计得到目标的空时频率；基于二阶多项式拟合的目标空时参数最大似然估计算法利用对目标频率滤波后响应主瓣附近的三个频率的输出，进行二阶多项式拟合，通过求解极值得到目标空时频率的最大似然估计值这两种方法大大降低了目标空时参数估计的计算复杂度，且在得到与参数搜索方法类似的估计精度时计算量均远远小于参数搜索方法
The moving target detection (MTD) is one of the most important functions of radarsystem. The MTD performance is mainly dominated by the performances of cluttersuppression and target focusing. Clutter suppression can be realized effectivelyexploiting the degrees of freedom (DOF) of multiple antennas. Therefore, how toimprove the coherence of different channels and how to suppress the clutter effectivelybecome the most important subjects of MTD technique. Along with the development ofthe MTD research, the motion parameters estimation and the imaging of the movingtarget also become an important demand and a researching subject.
This dissertation is mainly devoted to two subjects: one is how to improve the MTDperformance containing how to suppress the clutter and focus the targets effectively;one is how to estimate the target parameters effectively. The main research results are asfollows:
1. The channel equalization and moving target detection and location formulti-channel SAR-GMTI,
Improving the coherence of different channels is the key problem in MTD forairborne multi-channel SAR-GMTI system. Aiming at the problem, a novel channelequalization method is presented, and a technique for moving target detection (MTD)and location based on which is further proposed. This method first realizes circuitscalibration utilizing the leaking signals, then implements fast and slow time calibrationand compensates the channel differences via iteration after range compression, after thatrealizes MTD by clutter cancellation and imaging, finally obtains target parameters byestimating moving target Doppler shift. The channel equalization method needs nopriori knowledge such as the parameters of antenna and the plane’s movement, andavoids image registration and auto adaptive clutter cancellation method. Thus it’s ofless computation and easy to realize. The experiment result of real data proved that themethod can achieve a clutter cancellation ratio of more than20dB, and it has gooddetection and location performance.
2. Multi-channel SAR-GMTI based on total least squares method
Aiming at the poor clutter suppression performance induced by noise and poorclutter coherence in multi-channel SAR-GMTI, a method for SAR-GMTI based on totalleast squares is presented. The method adopts adjacent pixels around detection pixel tofit it under total least squares criterion, which can eliminate the influence of noise andimprove clutter coherence, thus lead to performance improvement on clutter suppression. Besides, the method is robust to error. Finally, simulation results and realdata processing are given to demonstrate the effectiveness of the method.
3. The detection with high detection probability and the imaging with highaccuracy for multiple targets in multi-channel SAR
For Multi-channel SAR-GMTI system, the movement of the targets leads to rangecell movement (RCM) and the shift of their Doppler rates. As the motion parameters ofthe targets are unknown, they are focused using the parameters of the stationary scene,which will induce their defocus and the degrade of their detection probability. Inaddition, the targets are extracted from SAR image and processed to obtain their motionparameters singly, which brings great computation complexity. To solve the problems, anew method to moving target imaging and detection with high detection probability ispresented. It first corrects RCM using Keystone transform and filter group whichcompensating phases of the target. Then LVD transform is performed to focusing thetargets. After detecting the moving targets in the LVD plane, the Doppler rates of themultiple targets are obtained. At last, targets imaging is realized in SAR image. Theprocessing of real data testifies that it can overcome RCM and the defocus induced bychirp rate shift, therefore improves the detection probability of targets efficiently.
4. Clutter suppression algorithm for airborne bistatic sidelooking radar
A simultaneous transmitter and receiver motion of the bistatic radar complicatesthe clutter spectra over range and makes the clutter spectra range-dependent [1].Range-dependent clutter makes space time adaptive processing (STAP) difficult toobtain independently and identically distributed (i.i.d.) secondary data used forcovariance matrix estimation, which will lead to the decline of the clutter suppressionperformance. To solve the problem, two clutter suppression algorithms for airbornebistatic sidelooking radar using MIMO or overlapped subarray alternate transmitting aredeveloped. In the methods, by incorporating the transmit degree of freedom (DOF), thebistatic clutter ridge turns to be a three-dimensional ridge. Moreover, the clutter ridgesof all range bins locate in the same plane of the three-dimensional space, while themoving targets don’t because of their radial velocity. For the clutter in the plane isrange-independent, it can be suppressed effectively by3-dimensional STAP.
5. Fast algorithm for moving target space-time parameters estimation
The traditional method for moving target space-time parameters estimation needsrefined parameter searching, which leads to heavy computation burden. And itsestimation accuracy is related to the searching pace. To overcome the problem, two fastalgorithms for target space-time parameters estimation are developed: The maximum likelihood estimation based on polynomial rooting performs adaptive processing usingthe steering vectors of the three frequency channels neighbor to that of the target. In thisway, three adaptive weights and three response output are obtained. Then the space-timeparameters of the target are estimated by rooting a polynomial; the maximum likelihoodestimation based on quadratic polynomial approximation performs the quadraticpolynomial approximation of the spectrum of the frequency response using the outputof the three channels round which of the target. Then the space-time parameters of thetarget are estimated by calculating the extremum. The two methods effectively lower thecomputation complexity of the target space-time parameters estimation. Compared toparameter grid searching methods, their computation complexity is much decreasedwhile in the same accuracy.
引文
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