Improving Detection Performance of Passive MIMO Radar by Exploiting the Preamble Information of Communications Signal

被引:9
作者
Liu, Yongjun [1 ]
Liao, Guisheng [1 ]
Xu, Jingwei [1 ]
Yang, Zhiwei [1 ]
Yin, Yingzeng [2 ]
机构
[1] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
[2] Xidian Univ, Natl Key Lab Antennas & Microwave Technol, Xian 710071, Peoples R China
来源
IEEE SYSTEMS JOURNAL | 2021年 / 15卷 / 03期
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
MIMO radar; OFDM; Transmitters; Passive radar; Receivers; Training; Radar detection; Generalized likelihood ratio test (GLRT); multiple-input multiple-output (MIMO); orthogonal frequency division multiplexing (OFDM); passive radar detection; preamble; MOVING TARGET DETECTION; OFDM INTEGRATED RADAR; WAVE-FORM DESIGN; ADAPTIVE DETECTION; SYSTEM; FILTER;
D O I
10.1109/JSYST.2020.3009752
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In passive multiple-input multiple-output (MIMO) radar, the transmit signals of the noncooperative illuminators of opportunity are usually not completely known. They are usually standard communications signals following specific protocols which stipulate the preamble format. In this article, we show that the preamble information can be exploited to improve the performance of passive MIMO radar. We have derived two generalized likelihood ratio tests (GLRTs) for passive MIMO radar detection, one for the case where the noise variance is known, and the other for the case where the noise variance is unknown. Our analysis shows that the derived two GLRTs have constant false alarm rate. Simulation results show that under the same condition the derived GLRTs outperform the GLRTs without using the preamble information. Moreover, the derived GLRTs are also compared with the GLRTs for active MIMO radar that totally knows transmit signals. These comparisons show that the performance of the derived GLRTs vary between the GLRTs for active MIMO radar and those for the passive MIMO radar with the transmit signals completely unknown.
引用
收藏
页码:4391 / 4402
页数:12
相关论文
共 63 条
  • [1] IEEE 802.11AX: CHALLENGES AND REQUIREMENTS FOR FUTURE HIGH EFFICIENCY WIFI
    Afaqui, M. Shahwaiz
    Garcia-Villegas, Eduard
    Lopez-Aguilera, Elena
    [J]. IEEE WIRELESS COMMUNICATIONS, 2017, 24 (03) : 130 - 137
  • [2] [Anonymous], 1958, An introduction to multivariate statistical analysis
  • [3] [Anonymous], 1998, FUNDEMENTALS STAT SI
  • [4] Bellalta B, 2016, IEEE WIREL COMMUN, V23, P38, DOI 10.1109/MWC.2016.7422404
  • [5] GLRT Detector in Single Frequency Multi-static Passive Radar Systems
    Chalise, Batu K.
    Himed, Braham
    [J]. SIGNAL PROCESSING, 2018, 142 : 504 - 512
  • [6] A Multistage Processing Algorithm for Disturbance Removal and Target Detection in Passive Bistatic Radar
    Colone, F.
    O'Hagan, D. W.
    Lombardo, P.
    Baker, C. J.
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2009, 45 (02) : 698 - 722
  • [7] Signal detection with noisy reference for passive sensing
    Cui, Guolong
    Liu, Jun
    Li, Hongbin
    Himed, Braham
    [J]. SIGNAL PROCESSING, 2015, 108 : 389 - 399
  • [8] Tracking in multistatic passive radar systems using DAB/DVB-T illumination
    Daun, Martina
    Nickel, Ulrich
    Koch, Wolfgang
    [J]. SIGNAL PROCESSING, 2012, 92 (06) : 1365 - 1386
  • [9] Generalized multivariate analysis of variance
    Dogandzic, A
    Nehorai, A
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 2003, 20 (05) : 39 - 54
  • [10] E. Standard, 2015, 302755 ETSI EN