A sparse direction-of-arrival estimation algorithm for MIMO radar in the presence of gain-phase errors

Jing Liu, Weidong Zhou, Xianpeng Wang, Defeng David Huang

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)

    Abstract

    In this paper, the problem of direction-of-arrival (DOA) estimation for monostatic multiple-input multiple-output (MIMO) radar with gain-phase errors is addressed, by using a sparse DOA estimation algorithm with fourth-order cumulants (FOC) based error matrix estimation. Useful cumulants are designed and extracted to estimate the gain and the phase errors in the transmit array and the receive array, thus a reliable error matrix is obtained. Then the proposed algorithm reduces the gain-phase error matrix to a low dimensional one. Finally, with the updated gain-phase error matrix, the FOC-based reweighted sparse representation framework is introduced to achieve accurate DOA estimation. Thanks to the fourth-order cumulants based gain-phase error matrix estimation, and the reweighted sparse representation framework, the proposed algorithm performs well for both white and colored Gaussian noises, and provides higher angular resolution and better angle estimation performance than reduced-dimension MUSIC (RD-MUSIC), adaptive sparse representation (adaptive-SR) and ESPRIT-based algorithms. Simulation results verify the effectiveness and advantages of the proposed method. © 2017 Elsevier Inc. 

    Original languageEnglish
    Pages (from-to)193-203
    Number of pages11
    JournalDigital Signal Processing
    Volume69
    Early online date10 Jul 2017
    DOIs
    Publication statusPublished - 1 Oct 2017

    Fingerprint

    Dive into the research topics of 'A sparse direction-of-arrival estimation algorithm for MIMO radar in the presence of gain-phase errors'. Together they form a unique fingerprint.

    Cite this