Computationally efficient DOA estimation for monostatic MIMO radar based on covariance matrix reconstruction. Issue 2 (1st January 2017)

• Record Type: Journal Article
• Authors: Zhang, Yu; Zhang, Gong; Wang, Xinhai
• Is Part Of: Electronics letters. Volume 53:Issue 2(2017)
• Page Start: 111
• Page End: 113
• Publication Date: 2017-01-01
• Subjects: MIMO radar -- direction‐of‐arrival estimation -- covariance matrices -- signal classification -- radar signal processing; DOA estimation -- monostatic MIMO radar -- covariance matrix reconstruction -- direction‐of‐arrival estimation algorithm -- monostatic multiple‐input multiple‐output radar -- reduced‐dimension transformation -- Toeplitz structure -- reduced‐complexity denosing covariance matrix reconstruction approach -- computational complexity -- two‐dimension multiple signal classification -- 2D‐MUSIC -- subspace‐based methods; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2016.3818
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : A computationally efficient direction‐of‐arrival (DOA) estimation algorithm for monostatic multiple‐input multiple‐output (MIMO) radar based on covariance matrix reconstruction is presented. By reduced‐dimension transformation, the transformed covariance matrix is reconstructed in the Toeplitz structure and then the DOAs are estimated by employing MUSIC. The proposed reduced‐complexity denosing covariance matrix reconstruction approach provides lower computational complexity compared with conventional two‐dimension multiple signal classification (2D‐MUSIC). Moreover, in contrast to the subspace‐based methods, the proposed method can be carried out without knowing the number of targets. Simulation results demonstrate the outperformance of the proposed method.