基于压缩感知的嵌套FDA 雷达距离- 角度联合估计

针对频率分集技术，与非均匀阵列、压缩感知理论相结合，实现目标距离- 角度的联合估计。通过 频率分集技术提高信号空间自由度，将距离参数引入导向矢量矩阵，实现距离- 角度参数的联合。并结合嵌套 阵列，显著提高雷达阵列孔径。该方法针对嵌套阵虚拟阵列流型矩阵的优化过程导致的秩亏缺问题，传统的空 间平滑算法会以牺牲部分阵列孔径为代价将单快拍问题转化为多快拍问题，采用正交匹配追踪算法可以实现单 快拍下的高精度参数估计，避免了空间平滑技术对阵列孔径的影响。并通过压缩感知理论的应用降低信号维度， 减小了计算复杂度。

Nested FDA Radar Range-Angle Joint Estimation Based on Compressed Sensing

With frequency diversity technology, combined with non-uniform array and compressed sensing theory, joint estimation of target distance and angle is achieved. Frequency diversity could improve the DOFs of signal and bring range into steering vector, which makes the joint of range and DOA feasible. Employing Nested array, the aperture of radar is significantly enhanced. The process of obtaining coarray will lead to rank deficiency, and spatial smoothing algorithm can resolve this problem at the cost of aperture reduction, transferring the single-snapshot problem into a muti- snapshot problem. OMP algorithm could achieve accurate estimation of parameters without aperture reduction. The application of compress sensing could achieve dimension reduction of signal, which will reduce computational complexity.