机载/星载正侧视阵列雷达GMTI研究
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摘要
本论文针对正侧视阵列雷达(包括机载雷达和星载雷达)实现GMTI功能,开展了通道相位中心估计,通道幅度、相位误差盲均衡,SAR图像域杂波抑制和降维准最优处理,运动目标测速、定位以及重聚焦等关键技术研究。主要工作包括:
1、在通道相位中心估计过程中,通过利用通道间场景杂波相位差异与多普勒频率的特定关系,结合相位解缠绕处理和整体最小二乘方法获得高精度的通道相位中心位置估计结果。在典型机载雷达参数配置下能够获得毫米级的沿航迹基线长度估计精度,满足运动目标速度估计对相位中心位置误差的要求。针对通道幅度、相位误差盲均衡问题,在获得场景距离-多普勒图像的基础上,结合功率挑选准则和回波相位矢量相关矩阵特征分解实现通道相位误差自适应补偿;然后基于相位挑选准则剔除潜在的目标样本,通过数据相关矩阵特征分解实现通道幅度响应特性估计和自适应补偿。理论分析并结合仿真实验和某机载实测数据处理表明该方法能够有效均衡通道响应误差,对运动目标信号污染具有稳健性。
2、针对沿航迹多通道系统慢速运动目标检测问题,提出了基于广义特征空间分解的SAR图像域杂波抑制算法。理论分析证明了唯一最小广义特征值的存在性和对应特征矢量与杂波空间正交。该方法采用IIR(无限冲击响应)模型对场景杂波进行自适应预测相消,对图像配准误差和杂波起伏具有稳健性,能够有效检测出主瓣杂波区的慢速运动目标。
3、提出了一种基于SAR图像域和/差数据模型的杂波抑制降维准最优处理方法。在不损失场景信息前提下通过形成图像域和/差联合观察数据矢量达到降维处理目的。从统计意义上看:和通道包含了场景杂波在不同通道间的共同信息;差通道则包含了通道间的差异信息。对和/差通道数据进行自适应处理能够有效抑制场景杂波,并且能够保留运动目标在通道间的差异信息。理论分析和仿真数据处理表明降维准最优处理方法不仅在图像精确配准和均匀场景条件下性能良好;而且在存在图像配准误差或非均匀环境中其性能优于传统最优处理和传统全维非最优处理方法。
4、针对不具有方位扫描能力的多通道SAR系统实现运动目标测速、定位功能,首先提出了一种修正的基于单次快拍模型的目标径向速度估计算法,能够有效减小慢速运动目标的测速方差,并且具有较低的运算复杂度。然后通过测量不同方位子驻留间目标径向距离的变化获得无模糊的目标径向速度粗估计;最后结合目标导向搜索类方法对目标径向速度进行精确估计,有效解决了速度测量的模糊问题。仿真结果和实测数据处理表明该方法比传统AMF和原始单次快拍方法具有更好的运动目标定位性能。针对运动目标重聚焦问题,我们有效融合平滑伪Wigner-Ville分布、图像边缘检测、Hough变换以及最小二乘聚类处理,以较低的运算复杂度获得运动目标回波多普勒中心频率和多普勒调频率的正确估计,能够对运动目标回波获得较好的聚焦处理性能。
This doctoral dissertation addresses the key techniques, such as phase center estimation, channel gain and phase response error calibration, clutter rejection and reduced-dimension processing, moving targets radial velocity estimation and location, targets re-focusing, for ground moving target indication with side-looking multi-channel radar systems. The main topics of this dissertation are listed as follows:
1. For the purpose of phase center estimation and channel manifold calibration, a new algorithm which explores phase and amplitude relationshipe among along-track Doppler beam sharping (DBS) images is proposed. The channel manifold calibration procedure uses a power-based criterion to reject a weak clutter patch and/or target for covariance matrix estimation, on the other hand, a phase-based criterion to alleviate the strong target signal contamination problem. Thus the problem of target signal contamination can be alleviated observably. Finally, phase center among multi-channel are estimated based on fitting the linear relationship between unwrap phase of the clutter space steering vector and Doppler frequency adopting the total least square algorithm. The effectiveness for channel mismatch and phase center estimation where a millimeter estimation result can be achieved and the robustness for target signal contamination are confirmed by performance analysis and experimental data..
2. Clutter rejection is the prime problem for ground moving target indication (GMTI). We focus on clutter inner undulating which influences the performance of moving target detection. A new algorithm based on generalized noise eigen-subspace which is in existence and orthogonal to clutter subspace is presented. The robustness for clutter inner undulating and synthetic aperture radar (SAR) images registration error is proved by subspace analysis and extensive simulation.
3. A new reduced-dimensional method based on joint pixels sum-difference data for clutter rejection and GMTI is proposed. The reduced-dimensional joint pixels sum-difference data are obtained by the orthogonal projection of the joint pixels data of different synthetic aperture radar images generated by a multi-satellite radar system. In the sense of statistic expectation, the joint pixels sum-difference data contains the common and different information among SAR images. Then the objective of clutter cancellation and GMTI can be achieved by adaptive processing. Simulation results demonstrate that the performance loss induced by this method for homogeneous terrain with no co-registration error can be acceptable and better result can be achieved adopting this method in the case of heterogeneous terrain with a finite co-registration error.
4. For the purpose of overcoming the contradiction between minimum detected velocity and maximum unambiguous velocity, a new target radial velocity estimation approach which is performed in tow stages is proposed. The coarse estimation procedure uses a track-based criterion to avert the unambiguous problem. Using modified single-snapshot multiple direction of arrival estimation method, a fine estimation of target radial velocity can be achieved in the signal fitting sense. Note that the last stage is carried out at determinate range-Doppler test cell to locate moving target by azimuth searching for that one fitting best to the moving target signal, thus the location performance would not be sacrificed in order to suppress clutter and/or interference and the high resolution radial velocity estimation can be achieved. Therefore, the proposed algorithm is computationally inexpensive. A preliminary result against an airborne experimental data demonstrates the effectiveness of the proposed method. Moreover, the moving target echoes is similar with linear frequency modulation (LFM) signal, so target moving parameters can be deduced by estimating chirp rate and initial frequency. We propose a method which using spatial-frequency joined weight WVD for cross-product terms suppressing at first, and taking edge detecting in image domain followed by applying Hough transformation for line detecting and eliminating cross-product terms at the most, then giving the target moving parameter estimation by using least square algorithm. Advantages of this approach are that cross-product terms are suppressed and accurate chirp rate estimates is obtained.
1、在通道相位中心估计过程中,通过利用通道间场景杂波相位差异与多普勒频率的特定关系,结合相位解缠绕处理和整体最小二乘方法获得高精度的通道相位中心位置估计结果。在典型机载雷达参数配置下能够获得毫米级的沿航迹基线长度估计精度,满足运动目标速度估计对相位中心位置误差的要求。针对通道幅度、相位误差盲均衡问题,在获得场景距离-多普勒图像的基础上,结合功率挑选准则和回波相位矢量相关矩阵特征分解实现通道相位误差自适应补偿;然后基于相位挑选准则剔除潜在的目标样本,通过数据相关矩阵特征分解实现通道幅度响应特性估计和自适应补偿。理论分析并结合仿真实验和某机载实测数据处理表明该方法能够有效均衡通道响应误差,对运动目标信号污染具有稳健性。
2、针对沿航迹多通道系统慢速运动目标检测问题,提出了基于广义特征空间分解的SAR图像域杂波抑制算法。理论分析证明了唯一最小广义特征值的存在性和对应特征矢量与杂波空间正交。该方法采用IIR(无限冲击响应)模型对场景杂波进行自适应预测相消,对图像配准误差和杂波起伏具有稳健性,能够有效检测出主瓣杂波区的慢速运动目标。
3、提出了一种基于SAR图像域和/差数据模型的杂波抑制降维准最优处理方法。在不损失场景信息前提下通过形成图像域和/差联合观察数据矢量达到降维处理目的。从统计意义上看:和通道包含了场景杂波在不同通道间的共同信息;差通道则包含了通道间的差异信息。对和/差通道数据进行自适应处理能够有效抑制场景杂波,并且能够保留运动目标在通道间的差异信息。理论分析和仿真数据处理表明降维准最优处理方法不仅在图像精确配准和均匀场景条件下性能良好;而且在存在图像配准误差或非均匀环境中其性能优于传统最优处理和传统全维非最优处理方法。
4、针对不具有方位扫描能力的多通道SAR系统实现运动目标测速、定位功能,首先提出了一种修正的基于单次快拍模型的目标径向速度估计算法,能够有效减小慢速运动目标的测速方差,并且具有较低的运算复杂度。然后通过测量不同方位子驻留间目标径向距离的变化获得无模糊的目标径向速度粗估计;最后结合目标导向搜索类方法对目标径向速度进行精确估计,有效解决了速度测量的模糊问题。仿真结果和实测数据处理表明该方法比传统AMF和原始单次快拍方法具有更好的运动目标定位性能。针对运动目标重聚焦问题,我们有效融合平滑伪Wigner-Ville分布、图像边缘检测、Hough变换以及最小二乘聚类处理,以较低的运算复杂度获得运动目标回波多普勒中心频率和多普勒调频率的正确估计,能够对运动目标回波获得较好的聚焦处理性能。
This doctoral dissertation addresses the key techniques, such as phase center estimation, channel gain and phase response error calibration, clutter rejection and reduced-dimension processing, moving targets radial velocity estimation and location, targets re-focusing, for ground moving target indication with side-looking multi-channel radar systems. The main topics of this dissertation are listed as follows:
1. For the purpose of phase center estimation and channel manifold calibration, a new algorithm which explores phase and amplitude relationshipe among along-track Doppler beam sharping (DBS) images is proposed. The channel manifold calibration procedure uses a power-based criterion to reject a weak clutter patch and/or target for covariance matrix estimation, on the other hand, a phase-based criterion to alleviate the strong target signal contamination problem. Thus the problem of target signal contamination can be alleviated observably. Finally, phase center among multi-channel are estimated based on fitting the linear relationship between unwrap phase of the clutter space steering vector and Doppler frequency adopting the total least square algorithm. The effectiveness for channel mismatch and phase center estimation where a millimeter estimation result can be achieved and the robustness for target signal contamination are confirmed by performance analysis and experimental data..
2. Clutter rejection is the prime problem for ground moving target indication (GMTI). We focus on clutter inner undulating which influences the performance of moving target detection. A new algorithm based on generalized noise eigen-subspace which is in existence and orthogonal to clutter subspace is presented. The robustness for clutter inner undulating and synthetic aperture radar (SAR) images registration error is proved by subspace analysis and extensive simulation.
3. A new reduced-dimensional method based on joint pixels sum-difference data for clutter rejection and GMTI is proposed. The reduced-dimensional joint pixels sum-difference data are obtained by the orthogonal projection of the joint pixels data of different synthetic aperture radar images generated by a multi-satellite radar system. In the sense of statistic expectation, the joint pixels sum-difference data contains the common and different information among SAR images. Then the objective of clutter cancellation and GMTI can be achieved by adaptive processing. Simulation results demonstrate that the performance loss induced by this method for homogeneous terrain with no co-registration error can be acceptable and better result can be achieved adopting this method in the case of heterogeneous terrain with a finite co-registration error.
4. For the purpose of overcoming the contradiction between minimum detected velocity and maximum unambiguous velocity, a new target radial velocity estimation approach which is performed in tow stages is proposed. The coarse estimation procedure uses a track-based criterion to avert the unambiguous problem. Using modified single-snapshot multiple direction of arrival estimation method, a fine estimation of target radial velocity can be achieved in the signal fitting sense. Note that the last stage is carried out at determinate range-Doppler test cell to locate moving target by azimuth searching for that one fitting best to the moving target signal, thus the location performance would not be sacrificed in order to suppress clutter and/or interference and the high resolution radial velocity estimation can be achieved. Therefore, the proposed algorithm is computationally inexpensive. A preliminary result against an airborne experimental data demonstrates the effectiveness of the proposed method. Moreover, the moving target echoes is similar with linear frequency modulation (LFM) signal, so target moving parameters can be deduced by estimating chirp rate and initial frequency. We propose a method which using spatial-frequency joined weight WVD for cross-product terms suppressing at first, and taking edge detecting in image domain followed by applying Hough transformation for line detecting and eliminating cross-product terms at the most, then giving the target moving parameter estimation by using least square algorithm. Advantages of this approach are that cross-product terms are suppressed and accurate chirp rate estimates is obtained.
引文
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