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低脉冲重复频率(PRF)雷达是解决多目标多普勒模糊的关键技术之一,基于此雷达工作体制,提出一种基于压缩感知(CS)理论的多普勒超分辨处理方法,利用该方式下回波信号在相参积累时间内的时域欠采样特性及多普勒域的稀疏特性,构建了多普勒超分辨的CS模型,并采用正交匹配追踪算法对多目标进行超分辨处理。同时,提出了一种改进算法,即基于SVD分解的二次测量及动态感知联合优化算法模型,仿真结果验证了算法的有效性及可靠性。
Low pulse repetition frequency (PRF) radar is one of the key technologies to solve the multi-objective Doppler ambiguity. Based on this radar working system, a Doppler super-resolution method based on the CS theory is proposed. Under the time-domain undersampled characteristics and Doppler domain sparseness of the coherent signal, the Doppler super-resolution CS model is built and the orthogonal matching pursuit algorithm is used to perform multiresolution super-resolution . At the same time, an improved algorithm is proposed, that is, the joint measurement and dynamic perception optimization model based on SVD decomposition. The simulation results verify the effectiveness and reliability of the algorithm.