基于互质阵列的阵元排布优化方法

相比于传统的线性均匀阵列，稀疏互质阵列提供了更多的自由度，但是稀疏阵列对应的差分阵列中的孔洞影响了DOA估计的性能。为了解决这个问题，该文提出了两种基于互质阵列的稀疏阵列优化方法，减少了差分阵列孔洞数量。首先，对标准互质阵列的虚拟阵列排列进行了分析，发现移除0位置阵元后，阵列可分辨信源数没有发生变化。因此，该文将这个阵元移动到了新的位置，以优化阵列设计，并且推导出两种提出的阵列虚拟阵列最大连续部分和自由度的数学表达式。仿真结果表明，两种阵列在DOA估计方面和均方根误差方面均优于标准互质阵列，具有比较优越的性能。

An Element Arrangement Optimization Method Based on Coprime Arrays

Compared with the traditional linear uniform array, the sparse coprime arrays offer more degrees of freedom, but the holes in the difference co?arrays corresponding to the sparse arrays affect the performance of DOA estimation. To solve this problem, the paper proposes two optimization methods for sparse arrays based on coprime arrays, aiming to reduce the number of holes in the difference co?array. An analysis of the virtual array arrangement for the standard coprime array reveals that the array’s ability to resolve the number of source signals remains unchanged when the element at position 0 is removed. Therefore, the paper relocates this element to a new position to optimize the array design and derives mathematical expressions for the maximum continuous segments and degrees of freedom of the proposed array configurations. Simulation results demonstrate that the two array configurations outperform the coprime arrays in terms of DOA estimation and root?mean?square error, showing superior performance.