Robust Beamforming for Frequency Diverse Array Multiple-Input Multiple-Output Radar: Mitigating Steering Vector Mismatches and Suppressing Main Lobe Interference

Yumei Tan, Yong Li, Wei Cheng, Limeng Dong, Langhuan Geng, Muhammad Moin Akhtar

科研成果: 期刊稿件文章同行评审

摘要

Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) radar introduces range-dependent beamforming capabilities, enhancing its ability to differentiate true targets from main lobe jammers. However, this innovation also introduces new challenges, particularly when errors disrupt the transceiver steering vectors, leading to performance degradation in main lobe interference suppression. To this end, a robust beamforming method tailored for FDA-MIMO radar systems is proposed to address signal mismatches caused by range–angle errors, array element position errors, frequency offsets, and coherent local scattering. Initially, a logarithmic function is used to decouple range and angle, enabling the design of a stable beampattern. The desired steering vector is then computed by addressing an optimization problem that leverages the interference-plus-noise covariance matrix alongside the signal-plus-noise covariance matrix. This estimation process, combined with mismatch correction through the diagonal loading method, significantly stabilizes the covariance matrix and enhances the robustness of FDA-MIMO systems. Extensive simulations validate the proposed approach across various error scenarios specific to FDA-MIMO radars, demonstrating superior robustness in main lobe interference suppression. These findings contribute to advancing robust beamforming techniques for FDA-MIMO radar systems, paving the way for enhanced performance in complex and error-prone environments.

源语言英语
文章编号577
期刊Remote Sensing
17
4
DOI
出版状态已出版 - 2月 2025

指纹

探究 'Robust Beamforming for Frequency Diverse Array Multiple-Input Multiple-Output Radar: Mitigating Steering Vector Mismatches and Suppressing Main Lobe Interference' 的科研主题。它们共同构成独一无二的指纹。

引用此