基于空间平滑多重信号分类算法的低角目标探测

基于阵列信号处理的目标回波到达方向（DOA）估计算法具有分辨力强、估计精度高、抗干扰能力强的特点，是目标测向的研究热点。多重信号分类（MUSIC）算法就是基于阵列信号处理的目标测向算法之一，传统的多重信号分类算法假设目标回波是互不相关的，这导致其应用效果受到较大的限制。在传统多重信号分类算法的基础上，采用空间平滑多重信号分类算法进行目标回波解相干处理，推导给出了估计目标回波到达角度的表达式以及该算法的实现流程框图，并结合数值模拟结果以及实际应用场景对该算法的优缺点进行了对比分析。空间平滑多重信号分类算法在低角目标探测、单目标多径问题、多目标到达角度与多目标数量估计等方面具有一定优势。

Low Angle Target Detection Based on Spatial Smoothing MUSIC Algorith

The target echo Directing of Arrival (DOA) estimation algorithm based on array signal processing has the characteristics of strong resolution, high estimation accuracy and strong anti-interference ability. These algorithms are also research hotspots in target direction finding. The Multiple Signal Classification (MUSIC) algorithm is one of the DOA estimation algorithms, and the traditional MUSIC algorithm assumes that the target echoes are not correlated with each other, which leads to its application effect being greatly limited. Based on the traditional MUSIC algorithm, the spatial smoothing MUSIC algorithm is used to decoherence the target echo, and the expression for estimating the target DOA and the implementation flow block diagram of the algorithm are derived. The advantages and disadvantages of the algorithm are compared and analyzed based on the numerical simulation results. The MUSIC algorithm has certain advantages in low-DOA, single target multipath problem, multi-target DOA and targets number estimation.