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针对单站合成孔径雷达(SAR)实现海面场景高分辨率宽测绘带(HRWS)成像问题,结合海面目标相对整个场景的稀疏特性,提出了一种基于马尔科夫链的单站SAR宽幅高分成像算法。算法将宽幅的海面场景分为不同子测绘带,首先发射少量脉冲对各子测绘带进行距离向成像,利用距离向成像结果获取场景内感兴趣目标的数量信息。然后计算雷达波束指向的马尔科夫状态转移概率,并按此概率控制雷达对不同测绘带进行扫描。获得不同测绘带的稀疏子孔径后进行压缩感知成像。提出的算法可以在相同合成孔径时间内实现多个测绘带的宽幅高分成像,最后的仿真实验验证了所提算法的有效性。
In order to solve the problem of high resolution wide swath (HRWS) imaging in single scene synthetic aperture radar (SAR), a single station SAR based on Markov chain Sub-imaging algorithm. The algorithm divides a wide range of submarine scenes into different sub-bands. First, a small number of pulses are transmitted to carry out range imaging of each sub-band, and the distance to the imaging result is used to obtain the number of interested targets in the scene. Then the Markov transition probability of the radar beam is calculated, and the radar is used to scan the different zones according to this probability. After obtaining the sparse sub-aperture of different swaths, compressed sensing imaging was performed. The proposed algorithm can realize wideband high-resolution imaging of multiple swaths within the same synthetic aperture time. Finally, the simulation results show the effectiveness of the proposed algorithm.