SAR-GMTI处理方法研究
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摘要
合成孔径雷达地面运动目标检测(SAR-GMTI)技术综合了高分辨对地观测和运动目标检测、测速定位能力,具有重要的军事和民用价值。SAR借助平台运动增加方位带宽以实现对地面静止目标高分辨成像,然而静止目标对GMTI而言就是杂波,杂波抑制后才可以提取动目标信号及其运动参数和位置信息。SAR在运动过程中发射重复脉冲的特性引起运动目标回波的多普勒模糊,同时目标的高速运动引起目标越距离单元徙动,导致运动目标回波不能得到相干积累,这在很大程度上制约了SAR对快速运动目标的探测能力。论文围绕实测数据处理过程中遇到的问题,对SAR-GMTI多通道杂波抑制,快速运动目标检测和成像等技术进行了研究。论文具体内容概括如下:
     1、提高通道间复图像的相干性,是多通道SAR系统实现强杂波背景下地面运动目标检测的必要条件和重要保证。各通道间天线波束方向图的差异导致SAR图像幅相不一致,论文提出了一种在两个不同的SAR原始数据域进行两步滤波的通道均衡方法。在距离频域方位时域进行幅相滤波解决距离频率响应差异,在距离多普勒域上进行幅相滤波解决方位多普勒谱的差异。第一步滤波操作中,在高相干性区域构造自适应滤波器消除通道间的确定性差异,对噪声区域则采用非自适应滤波。第二步滤波操作进一步抑制噪声,通道均衡后对消杂波得到运动目标信号。机载实测数据处理结果验证了原始数据域通道均衡方法的有效性。
     2、为突破SAR方位脉冲重复频率(PRF)对运动目标最大可检测速度的限制,提出了两种基于解PRF模糊的快速目标检测方法。第一种方法在距离频率方位压缩域(RFAC)利用目标轨迹斜率与模糊数成比例的关系,通过直线斜率推导模糊数。第二种方法在距离压缩方位时间域(RCAT)将目标信号作Keystone变换后,直线斜率与模糊数成比例,根据这一关系可以解动目标速度模糊。这两种方法都是通过二维匹配滤波实现动目标的成像。仿真和实测数据结果均验证了该方法的有效性。
     3、对检测到的目标进行成像是运动目标识别的基础,具有重要的军事应用价值。快速运动目标径向速度分量会引起越距离单元徙动和方位多普勒模糊,沿航向速度分量引起多普勒调频率的变化,从而导致回波信号不能得到相干积累,SAR成像后动目标在距离与方位上存在散焦。提出了一种结合Keystone-Wigner变换(KWT)的快速运动目标成像方法,首先在距离压缩方位原始数据域校正动目标距离走动,方位粗聚焦后检测运动目标,接着将动目标信号变换回RCAT域进行KWT分析,得到动目标调频率参数的同时进行成像。该方法在对检测到的快速目标进行重聚焦的同时,解决了快速目标的运动参数估计问题。实测数据处理结果表明该方法能够实现快速目标的成像、测速和准确定位。
     4、稀疏理论近几年在信号处理领域引起了国内外学者的广泛关注,鉴于它在稀疏信号表示方面的良好性能,论文提出了基于稀疏信号表示的地面运动目标成像方法。在雷达回波中地面运动目标分量相对于杂波背景占极少数,杂波抑制后其回波可建模为稀疏线性调频信号,可构造线性调频超完备基对回波信号进行稀疏表示,该方法具有超分辨成像特性。仿真与实测数据验证了该方法的有效性。
     5、宽测绘带方位高分辨SAR成像是地球观测卫星的重要性能指标。论文提出了单通道SAR系统低脉冲重复频率条件下地/海面运动目标检测的方法,考虑了多普勒中心模糊和频谱模糊同时存在的情况。利用多视拍频技术估计运动目标径向速度,该方法可以提高最大可检测速度,不受脉冲重复频率限制。利用信号时频特征估计目标的位置,从而完成不同速度的目标的定位与参数估计问题。仿真和实测数据处理结果证明了所提出算法的有效性。
     6、双基SAR对目标进行观测可以得到比单基更丰富的散射特性,更有利于目标识别。星机双基多通道SAR-GMTI同时具备多通道SAR杂波抑制和双基SAR构型灵活性的优势。提出了一种星机广义双基构型下多通道SAR-GMTI处理方法,推导了该构型下SAR-GMTI公式,并讨论相干性增强方法及杂波特性,针对方位空变性,给出了相应的相位补偿方法。最后通过仿真实验表明所提出的算法的有效性。
Synthetic aperture radar and ground moving target indication (SAR-GMTI) combines the capability of high resolution earth observation and moving target detection and relocation, which is critical to military and civil application. High resolution imaging of stationary targets is achieved depending on the motion of platform, while the stationary targets are just regarded as clutter for GMTI mission, and clutter suppression is a prerequisite for moving target indication. The raw echoes cannot be coherently integrated due to two factors. On one hand, SAR transmits pulses repeatedly during the motion, which can be treated as discrete sampling in slow time and causes Doppler ambiguity. On the other hand, the fast moving targets will cause large range cell migration. Thus the detection performance of fast moving targets is limited. This thesis exploits a few kinds of strategies to deal with the problems resulting from real data processing, such as multi-channel SAR-GMTI clutter suppression and fast moving target detection as well as imaging. The outline of the thesis is listed as follows:
     1. The coherence enhancement is the prerequisite of multi-channel SAR moving target detection under strong clutter condition. A channel balancing technique based on the two-stage filters in different raw data domain is presented to overcome the differences in amplitude and phase. The amplitude and phase filtering in range frequency and azimuth time domain is used for range frequency response difference, while the amplitude-phase filtering in range-Doppler domain for Doppler spectrum difference. The first step of filtering removes the deterministic difference by using an adaptive filter in district with high coherence, and a non-adaptive one in the noisy district. The second step of filtering is used to suppress the noise further. After the channel balancing the clutter can be well cancelled and the moving target is obtained. The effectiveness of the channel balancing algorithm carried out in the raw data domain is demonstrated with the measured airborne data.
     2. In order to break through the maximum detectable velocity limitation due to the limited SAR pulse repetition frequency (PRF), two fast moving target indication methods are developed. One method utilizes the relation that the line slope of target trajectory is proportional to the ambiguity number of fast moving target in the range frequency and azimuth compressed time (RFAC) domain, and the ambiguity number can be obtained from Radon transform. The other method exploits the relation between range envelope and the ambiguity number in range compressed and azimuth time domain, following with the Keystone transform. Both the approaches acquire moving target imaging via 2-D matched filtering. The results of simulation and real data processing show the efficiency of the approaches.
     3. SAR imaging of the detected moving target is fundamental for target identification and very significant for military application. The radial velocity of fast moving target will cause the migration through range cell as well as Doppler ambiguity in azimuth, and the along-track velocity will cause the variation of the Doppler chirp rate. Both factors will make the echoes hardly be integrated coherently and the point spread function (PSF) of moving target in SAR image will become defocused. An approach based on Keystone-Wigner transform is proposed to implement the fast moving target imaging. Firstly, the large range cell migration is corrected in range compressed and azimuth time domain, detection is carried out after the coarse focusing in azimuth. Then the moving target signal is transformed back into RCAT domain, where the KWT is performed. Lastly, the image of fast moving target and the Doppler parameters are obtained. The motion parameters are estimated simultaneously with the fast moving target refocused. The proposed method can robustly estimate the motion parameters of the fast moving targets, which are illustrated with both simulated and real data.
     4. The development of sparsity theory has attracted wide public concern in the field of signal processing in recent years. Due to the perfect performance of sparse signal representation, a ground moving target imaging method based on sparse signal representation is proposed. In radar echoes the moving target signals take up the minority compared with the background clutter scatterers, so after clutter rejection the moving target signals can be treated as sparse LFM signals, which can be reconstructed via sparse representation on the overcomplete basis. A super-resolution imaging can be achieved by this method. The simulation and real data experiments show the validity of the approach.
     5. The capability of SAR high-resolution imaging with wide swath is an important aspect for earth observation satellites. A ground/sea surface moving target indication approach is developed with single channel SAR system under low PRF condition. This approach takes both the Doppler centroid and Doppler spectrum ambiguities into account. It can increase the maximum detectable velocity without the limitation of the PRF by using the multi-look beat frequency technique to finish radial velocity estimation of the moving target. The time-frequency property is used to estimate the target location. Thus the mission of the parameter estimation and target relocation can be achieved. The effectiveness of the proposed method is validated by the simulation and real data processing.
     6. The main advantage of bistatic SAR over monostatic one is that it can obtain more rich scattering information, thus more available for target identification. Space-surface multi-channel SAR-GMTI system has the capabilities of both clutter suppression and viewing angle flexibility. A multi-channel SAR-GMTI processing method under the space-surface generalized bistatic configuration is proposed. The basic moving target indication equations are presented, and the coherence enhancement method between the SAR images derived from different channels and the clutter character are discussed. The translation variant is dealt with using a phase compensation method. Simulation result shows the feasibility of the proposed method.
引文
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