Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar

Sensors

Xianpeng Wang²  Wei Wang¹  Xin Li²  Jing Liu² 

[1] College of Automation, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China;

关键词: MIMO radar;    DOA estimation;    sparse representation;    unitary transformation;    Khatri–Rao product;   

DOI  :  10.3390/s151128271

来源: mdpi

【 摘 要 】

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.