TY - JOUR
T1 - Robust Beamforming for Frequency Diverse Array Multiple-Input Multiple-Output Radar
T2 - Mitigating Steering Vector Mismatches and Suppressing Main Lobe Interference
AU - Tan, Yumei
AU - Li, Yong
AU - Cheng, Wei
AU - Dong, Limeng
AU - Geng, Langhuan
AU - Akhtar, Muhammad Moin
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/2
Y1 - 2025/2
N2 - 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.
AB - 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.
KW - diagonal loading
KW - frequency diverse array multiple-input multiple-output (FDA-MIMO) radar
KW - main lobe interference suppression
KW - transceiver steering vectors
UR - http://www.scopus.com/inward/record.url?scp=85219205114&partnerID=8YFLogxK
U2 - 10.3390/rs17040577
DO - 10.3390/rs17040577
M3 - 文章
AN - SCOPUS:85219205114
SN - 2072-4292
VL - 17
JO - Remote Sensing
JF - Remote Sensing
IS - 4
M1 - 577
ER -