子阵分级处理与稀疏恢复联合的抗主副瓣干扰方法

传统的抗干扰方法在低信噪比条件下性能恶化，对此本文提出了子阵分级处理与稀疏恢复联合的抗干扰方法。新方法首先按照一定规则将全阵列划分为多个子阵列；然后利用自适应波束形成（ADBF）技术抑制各子阵接收信号中的副瓣干扰信号，并将各子阵ADBF后的输出数据联合，构建新的阵列数据；最后通过新构建的阵列数据构建稀疏表示，改进了多测量向量降维提升法（ReMBo），并与交叉方向乘子法（ADMM）联合进行稀疏恢复，分离得到目标回波信号，并得到了波达角（DOA）的估计。仿真实验表明，新方法能有效对抗主副瓣干扰，与其它方法相比，具有更好的目标检测和DOA估计性能，特别是在低信噪比的条件下。 

Combination of subarray processing and sparse recovery for mainlobe and sidelobes interference suppression

The performance of traditional anti-jamming methods deteriorated under the condition of low signal-to-noise ratio (SNR). In order to improve the anti-jamming ability of radar under the condition of low SNR, in this paper, we proposed an anti-jamming method combining subarray processing and sparse recovery. In this paper, subarray Adaptive Digitial Beam Forming (ADBF) and sparse recovery are used to suppress the mainlobe interference and sidelobe interference. Firstly, the whole array was divided into several subarrays according to certain rules. Then, the ADBF technique was used to suppress the sidelobe interference signals of each subarray, and the output data of each subarray were combined to construct new array data. Finally, the sparse representation was constructed from the newly constructed array data, the Reduce Multiple measurement vectors and Boost (ReMBo) was improved to reduce computation in the condition of low SNR, and the Alternating Direction Method of Multiplier (ADMM) was used to perform the sparse recovery, the target signals were separated and the Direction of Arrival (DOA) estimation was obtained. Simulation results show that the proposed method can effectively suppress the mainlobe and sidelobe interference, and this method has better performance in target detection and DOA estimation compared with other methods, especially under the condition of low SNR. Under the condition of low SNR, the new method can effectively suppress the mainlobe and sidelobe interference and achieve better results than traditional methods.