基于改进解耦原子范数最小化的l型阵列声速无关DOA估计

Gengin Ning, Yu Wang
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引用次数: 1

摘要

本文提出了一种水下应用的DOA估计方法。首先,利用解耦原子范数最小化原理,建立了l形阵列互协方差矩阵(MCM)上的半正定规划模型;该模型可以更精确地重建l型阵列的MCM。在第二阶段,提出了一种全向速度无关(VI)方法来消除声速因素。数值仿真结果表明,该方法不仅能在声速未知的环境下实现有效的DOA估计,而且在高信噪比条件下,其性能得到了显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acoustic Velocity-Independent DOA Estimation for L-Shaped Array via Modified Decoupled Atomic Norm Minimization
In this paper, a DOA estimation method for underwater application is proposed. In the first stage, a semi-positive definite programming (SDP) model on the L-shaped array mutual covariance matrix (MCM) is constructed with the principle of decoupled atomic norm minimization (DANM). This model allows a more accurate reconstruction of the MCM for the L-shaped array. In the second stage, an omnidirectional velocity independence (VI) method is proposed to eliminate the acoustic velocity factor. Numerical simulations show that the proposed method not only achieves effective DOA estimation in the environment of the unknown acoustic velocity but also its performance, especially under high SNR conditions, is significantly improved.
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