星载多通道SAR高分辨宽测绘带成像方法研究
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摘要
地球遥感和军事侦察大多要求星载SAR同时具备高分辨和宽测绘带(HRWS : High Resolution and Wide Swath)成像能力。传统的单通道星载SAR受“最小天线面积约束”的限制,分辨率和测绘带这两个指标相互制约,难以满足当前的应用需求。多通道体制可以有效缓解这个矛盾,在相同分辨率下,多通道体制SAR可以获得远大于单通道体制SAR的测绘带宽度。
本文主要研究多通道体制SAR HRWS成像中的关键问题。首先,研究了一发多收(SIMO : Single Input Multiple Output)SAR距离/多普勒模糊抑制的问题,根据接收天线相对位置的差异,分为“单星SIMO-SAR”和“分布式SIMO-SAR”,它们的数据处理具有不同的特点。然后在一发多收研究成果的基础上,研究了多发多收SAR特有的正交波形设计和对应的成像处理等关键问题。具体研究内容安排如下:
第二章对“单星一发多收SAR”的多种实现模式进行了系统的对比研究。首先根据“最小天线面积约束”给出了品质因子的定义,用于评价系统的HRWS成像能力。然后从品质因子、距离/多普勒模糊抑制能力、信噪比、数据量、信号处理复杂度、盲区等方面分析对比了五类多通道接收SAR系统的优劣异同,得出了综合性能最优的系统方案—距离多通道接收的多相位中心方位多波束(DPC-MAB)系统。
第三章研究了单星距离多通道接收的DPC-MAB系统实现HRWS成像的问题。建立了一发多收DPC-MAB系统的信号模型,提出“谱分解法”完成回波的无模糊重构,并采用传统成像算法完成成像。在分析重构后回波的方位模糊比和信噪比的基础上,指出方位模糊比、信噪比与系统PRF的矛盾,提出利用相控阵天线并采用接收子阵列交叠接收以及宽发窄收两种方案予以妥善解决。给出了距离多通道接收的实现方案和信号处理方法,分析了其对信噪比的改善程度。
第四章研究了分布式SAR实现HRWS成像的问题。针对只存在沿航向基线的“SAR-Train”构形,提出一种回波预处理方案,可消除由沿航向基线引起的回波去相关,将构形转化为“DPC-MAB”模式,进而利用谱分解法解多普勒模糊;针对类似“TanDEM-X”的双站多相位中心SAR系统,提出在进行相位补偿之后,将双站多通道回波转化为双站回波,继而可采用双站成像算法进行成像;针对接收通道间存在切航向基线的分布式卫星SAR系统,提出将通道间回波历程差进行二阶近似、再分别补偿的方法。特别指出回波历程差随目标距离迁徙曲线空变的特性并提出了频域补偿方法。
第五章研究了多发多收(MIMO: Multiple Input Multiple Output)SAR改善HRWS成像性能的问题,主要集中在正交波形设计和相对应的成像算法。通过理论分析和仿真实验指出,同频带的相位编码信号和离散频率编码信号无法克服自相关函数和互相关函数积分旁瓣比之间的矛盾,不适合用于对地观测的MIMO-SAR;将正交性优良的步进频率LFM信号用于MIMO-SAR,给出了成像的信号处理方法和结果;进一步针对步进频率LFM信号各子带之间不能进行方位联合处理的缺点,将顺序发射的空-时正交波形用于MIMO-SAR,可获得更多的等效相位中心,显著改善系统的HRWS成像性能,同时避免了同频信号并发造成的相干暗斑,分析了空-时正交波形MIMO-SAR的模糊抑制性能,并给出了成像处理方法和仿真结果。
The capability of high resolution and wide swath (HRWS) imaging is desired by space based remote sensing and military reconnaissance. But for minimum antenna area constraint, there is an irreconcilable conflict between azimuth resolution and swath in single-channel SAR. This conflict can be mitigated via receiving with multiple channels. With the same resolution, multi-channel SAR can achieve much wider swath than single-channel SAR.
Several key problems for multiple-channel SAR imaging are investigated in this paper. Firstly , with regard to single-input and multiple-output (SIMO) SAR, suppression means for range-Doppler ambiguities are studied for the two formation of single platform and distributed satellite SAR respectively because they have different characteristics of distinct baselines among phase centers. Secondly, to multiple-input and multiple-output (MIMO) SAR, problems such as orthogonal waveform design are researched based on studies above for SIMO SAR.
Implementation form for SIMO SAR on single platform is comprehensively studied in Chapter 2. Firstly, merit factor for HRWS imaging evaluation is presented according to minimum antenna area constraint. Next, five multi-channel SAR systems are contrastively analyzed on several aspects, such as merit factor, capability for range-Doppler ambiguity suppression, signal to noise rate(SNR), data volume, complexity of signal processing, and blind swath. Conclusively, a reasonable system scheme, with displaced phase centers multiple azimuthal beam (DPC-MAB) and multiple receiving channel in range, is chosen as issue studied below.
DPC-MAB SAR with multiple receivers in range is studied in Chapter 3. After building signal model of SIMO SAR, decomposition spectrum algorithm is proposed to ambiguity-free reconstruction for multi-channel SAR echo, by which conventional imaging algorithms can be carried out to achieve HRWS imaging. SNR and azimuth ambiguity signal rate (AASR) of reconstructed data are analyzed and conclusion is drawn that there is conflict among SNR, AASR and PRF. So application of multiple overlapped receiving subapertures with phased array antenna is presented to handle this problem.
Distributed satellites SAR for HRWS imaging is studied in Chapter 4. For SAR-Train without cross-track baseline, preprocessing method is proposed for compensation for mutuality losing in echoes from multiple satellites. Then, the SAR-Train formation can be transformed to DPC-MAB and method given in Chapter 3 can be implemented in this formation. For the formation as“TanDEM-X”, an idea is presented to transform echoes from bistatic SAR multiple channels into echo from bistatic SAR with single channel equally. As regard to distributed SAR system with cross-track baseline, Phase history difference of two receiving channels is approximated by the second taylor expansion and compensated respectively. Range-dependent characteristic for phase histroy difference is analyzed and frequency compensation method is presented.
MIMO-SAR is researched to improve performance of HRWS imaging in Chapter 5. Based on theory analysis and simulation, an impartant conclusion is drawn that phase-coded waveforms and Costas waveforms will fail to fulfill land mapping MIMO-SAR for the constraint between autocorrelation function and cross-correlation function. Stepped frequency LFM signal is proved to have ideal orthogonal performance and can be adapted to MIMO-SAR. Signal processing method for this kind of waveform and simulation results are presented. To break up the limitation of failing to jointly processing in azimuth dimension with different frequency band stepped frequency LFM signals, space-time orthogonal waveform is proposed to achieve more equivalent phase centers and better HRWS imaging performance. Besides these advantages, space-time waveform can avoid interference dark speckle on the ground scene brought by transmitting signals simultaneously at the same frequency. Performance for range-Doppler ambiguity suppression is analyzed and signal processing method is also researched.
本文主要研究多通道体制SAR HRWS成像中的关键问题。首先,研究了一发多收(SIMO : Single Input Multiple Output)SAR距离/多普勒模糊抑制的问题,根据接收天线相对位置的差异,分为“单星SIMO-SAR”和“分布式SIMO-SAR”,它们的数据处理具有不同的特点。然后在一发多收研究成果的基础上,研究了多发多收SAR特有的正交波形设计和对应的成像处理等关键问题。具体研究内容安排如下:
第二章对“单星一发多收SAR”的多种实现模式进行了系统的对比研究。首先根据“最小天线面积约束”给出了品质因子的定义,用于评价系统的HRWS成像能力。然后从品质因子、距离/多普勒模糊抑制能力、信噪比、数据量、信号处理复杂度、盲区等方面分析对比了五类多通道接收SAR系统的优劣异同,得出了综合性能最优的系统方案—距离多通道接收的多相位中心方位多波束(DPC-MAB)系统。
第三章研究了单星距离多通道接收的DPC-MAB系统实现HRWS成像的问题。建立了一发多收DPC-MAB系统的信号模型,提出“谱分解法”完成回波的无模糊重构,并采用传统成像算法完成成像。在分析重构后回波的方位模糊比和信噪比的基础上,指出方位模糊比、信噪比与系统PRF的矛盾,提出利用相控阵天线并采用接收子阵列交叠接收以及宽发窄收两种方案予以妥善解决。给出了距离多通道接收的实现方案和信号处理方法,分析了其对信噪比的改善程度。
第四章研究了分布式SAR实现HRWS成像的问题。针对只存在沿航向基线的“SAR-Train”构形,提出一种回波预处理方案,可消除由沿航向基线引起的回波去相关,将构形转化为“DPC-MAB”模式,进而利用谱分解法解多普勒模糊;针对类似“TanDEM-X”的双站多相位中心SAR系统,提出在进行相位补偿之后,将双站多通道回波转化为双站回波,继而可采用双站成像算法进行成像;针对接收通道间存在切航向基线的分布式卫星SAR系统,提出将通道间回波历程差进行二阶近似、再分别补偿的方法。特别指出回波历程差随目标距离迁徙曲线空变的特性并提出了频域补偿方法。
第五章研究了多发多收(MIMO: Multiple Input Multiple Output)SAR改善HRWS成像性能的问题,主要集中在正交波形设计和相对应的成像算法。通过理论分析和仿真实验指出,同频带的相位编码信号和离散频率编码信号无法克服自相关函数和互相关函数积分旁瓣比之间的矛盾,不适合用于对地观测的MIMO-SAR;将正交性优良的步进频率LFM信号用于MIMO-SAR,给出了成像的信号处理方法和结果;进一步针对步进频率LFM信号各子带之间不能进行方位联合处理的缺点,将顺序发射的空-时正交波形用于MIMO-SAR,可获得更多的等效相位中心,显著改善系统的HRWS成像性能,同时避免了同频信号并发造成的相干暗斑,分析了空-时正交波形MIMO-SAR的模糊抑制性能,并给出了成像处理方法和仿真结果。
The capability of high resolution and wide swath (HRWS) imaging is desired by space based remote sensing and military reconnaissance. But for minimum antenna area constraint, there is an irreconcilable conflict between azimuth resolution and swath in single-channel SAR. This conflict can be mitigated via receiving with multiple channels. With the same resolution, multi-channel SAR can achieve much wider swath than single-channel SAR.
Several key problems for multiple-channel SAR imaging are investigated in this paper. Firstly , with regard to single-input and multiple-output (SIMO) SAR, suppression means for range-Doppler ambiguities are studied for the two formation of single platform and distributed satellite SAR respectively because they have different characteristics of distinct baselines among phase centers. Secondly, to multiple-input and multiple-output (MIMO) SAR, problems such as orthogonal waveform design are researched based on studies above for SIMO SAR.
Implementation form for SIMO SAR on single platform is comprehensively studied in Chapter 2. Firstly, merit factor for HRWS imaging evaluation is presented according to minimum antenna area constraint. Next, five multi-channel SAR systems are contrastively analyzed on several aspects, such as merit factor, capability for range-Doppler ambiguity suppression, signal to noise rate(SNR), data volume, complexity of signal processing, and blind swath. Conclusively, a reasonable system scheme, with displaced phase centers multiple azimuthal beam (DPC-MAB) and multiple receiving channel in range, is chosen as issue studied below.
DPC-MAB SAR with multiple receivers in range is studied in Chapter 3. After building signal model of SIMO SAR, decomposition spectrum algorithm is proposed to ambiguity-free reconstruction for multi-channel SAR echo, by which conventional imaging algorithms can be carried out to achieve HRWS imaging. SNR and azimuth ambiguity signal rate (AASR) of reconstructed data are analyzed and conclusion is drawn that there is conflict among SNR, AASR and PRF. So application of multiple overlapped receiving subapertures with phased array antenna is presented to handle this problem.
Distributed satellites SAR for HRWS imaging is studied in Chapter 4. For SAR-Train without cross-track baseline, preprocessing method is proposed for compensation for mutuality losing in echoes from multiple satellites. Then, the SAR-Train formation can be transformed to DPC-MAB and method given in Chapter 3 can be implemented in this formation. For the formation as“TanDEM-X”, an idea is presented to transform echoes from bistatic SAR multiple channels into echo from bistatic SAR with single channel equally. As regard to distributed SAR system with cross-track baseline, Phase history difference of two receiving channels is approximated by the second taylor expansion and compensated respectively. Range-dependent characteristic for phase histroy difference is analyzed and frequency compensation method is presented.
MIMO-SAR is researched to improve performance of HRWS imaging in Chapter 5. Based on theory analysis and simulation, an impartant conclusion is drawn that phase-coded waveforms and Costas waveforms will fail to fulfill land mapping MIMO-SAR for the constraint between autocorrelation function and cross-correlation function. Stepped frequency LFM signal is proved to have ideal orthogonal performance and can be adapted to MIMO-SAR. Signal processing method for this kind of waveform and simulation results are presented. To break up the limitation of failing to jointly processing in azimuth dimension with different frequency band stepped frequency LFM signals, space-time orthogonal waveform is proposed to achieve more equivalent phase centers and better HRWS imaging performance. Besides these advantages, space-time waveform can avoid interference dark speckle on the ground scene brought by transmitting signals simultaneously at the same frequency. Performance for range-Doppler ambiguity suppression is analyzed and signal processing method is also researched.
引文
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