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针对传统DPC近似引入的近距离目标散焦问题,提出了一种有效的多子阵合成孔径声纳(SAS)CS成像算法.首先,通过泰勒级数展开并保留其高阶项,将多子阵SAS双根号形式的距离历程等效为类收发合置项与收发分置畸变项之和,并由此推导出严格解析的点目标二维谱;然后,利用多子阵数据融合的方法对收发分置畸变项进行补偿,将多子阵合成孔径声纳信号转化为单阵收发合置的形式;最后,利用单阵收发合置CS算法实现了图像重建.仿真试验和实测数据的成像试验证明了算法的有效性.
Aiming at the problem of near-target defocus caused by traditional DPC approximation, an effective multi-subarray synthetic aperture sonar (SAS) CS imaging algorithm is proposed.Firstly, the Taylor series expands and preserves its high order terms, The distance history of the SAS dual root form is equivalent to the sum of the receive / transmit combined items and the receive / transmit distorted items, and the strictly resolved point-target two-dimensional spectrum is derived. Then, the method of multi-subarray data fusion To compensate the receive / transmit distortions and transform the multi-subarray synthetic aperture sonar signals into single constellation. Finally, the image reconstructed using a single constellation transceiver CS algorithm was implemented.The simulation and the imaging of the measured data Experiments prove the effectiveness of the algorithm.