Double-threshold CFAR detector in presence of subspace interference for MIMO radar

被引:2
作者
Li, Zhihua [1 ]
Su, Hongtao [1 ]
Zhou, Shenghua [1 ]
Hu, Qinzhen [1 ]
机构
[1] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Shaanxi, Peoples R China
关键词
MIMO communication; maximum likelihood estimation; signal detection; radar detection; object detection; covariance matrices; radar clutter; MIMO radar; frequency diversity multiple-input-multiple-output radar; unstructured disturbance; double threshold detector; DT-MGLRT; modified generalised likelihood ratio test algorithm; stage deals; unknown parameters; unknown spectral properties; structured interference distribution; detection algorithm; 2 dB signal-to-interference-plus-noise power ratio improvement; conventional detection algorithms; threshold CFAR detector; subspace interference; constant false alarm rate decision scheme; noise figure 2; 0; dB; DISTRIBUTED TARGETS; ADAPTIVE DETECTION;
D O I
10.1049/iet-spr.2018.5226
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, a constant false alarm rate (CFAR) decision scheme is devised for frequency diversity multiple-input-multiple-output (MIMO) radar. Under the assumption that there exists not only the unstructured disturbance but also the structured interference, a double threshold detector (DT-MGLRT) based on the modified generalised likelihood ratio test (MGLRT) algorithm is proposed, of which the first stage deals with the unknown parameters and the second stage determines the final decision. It is proved that the proposed detector possesses a CFAR with respect not only to the unknown spectral properties of the unstructured disturbance but also to the structured interference distribution. Finally, some experiment results indicate that the proposed detection algorithm has 2 dB signal-to-interference-plus-noise power ratio improvement on average in detection performance at a low computation and communication cost over conventional detection algorithms.
引用
收藏
页码:72 / 80
页数:9
相关论文
共 27 条
  • [1] [Anonymous], 1997, Distributed Detection and Data Fusion
  • [2] Adaptive Detection of Point-Like Targets in the Presence of Homogeneous Clutter and Subspace Interference
    Aubry, A.
    De Maio, A.
    Orlando, D.
    Piezzo, M.
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2014, 21 (07) : 848 - 852
  • [3] Radar Detection of Distributed Targets in Homogeneous Interference Whose Inverse Covariance Structure is Defined via Unitary Invariant Functions
    Aubry, Augusto
    De Maio, Antonio
    Pallotta, Luca
    Farina, Alfonso
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2013, 61 (20) : 4949 - 4961
  • [4] Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference
    Bandiera, Francesco
    De Maio, Antonio
    Greco, Antonio Stefano
    Ricci, Giuseppe
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2007, 55 (04) : 1223 - 1237
  • [5] Adaptive Detection and Diversity Order in Multistatic Radar
    Bruyere, Donald P.
    Goodman, Nathan A.
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2008, 44 (04) : 1615 - 1623
  • [6] Ziv-Zakai Bound for Joint Parameter Estimation in MIMO Radar Systems
    Chiriac, Vlad M.
    He, Qian
    Haimovich, Alexander M.
    Blum, Rick S.
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (18) : 4956 - 4968
  • [7] Improving MIMO radar's performance through receivers' positioning
    Chitgarha, Mohammad Mahdi
    Radmard, Mojtaba
    Majd, Mohammad Nazari
    Nayebi, Mohammad Mahdi
    [J]. IET SIGNAL PROCESSING, 2017, 11 (05) : 622 - 630
  • [8] MIMO radar: An idea whose time has come
    Fishler, E
    Haimovich, A
    Blum, R
    Chizhik, D
    Cimini, L
    Valenzuela, R
    [J]. PROCEEDINGS OF THE IEEE 2004 RADAR CONFERENCE, 2004, : 71 - 78
  • [9] Bayesian generalised likelihood ratio tests for distributed target detection in interference and noise
    Gao, Yongchan
    Liao, Guisheng
    Liu, Weijian
    Zuo, Lei
    [J]. IET RADAR SONAR AND NAVIGATION, 2017, 11 (05) : 752 - 758
  • [10] Grenander U., 1981, ABSTRACT INFERENCE P