Method based on neural network for LFMCW radar system object range superresolution estimation

被引：0
|
作者：
Li, Y. [1 ]
Huang, J.Y. [1 ]
Feng, Z.H. [1 ]
机构：
[1] Natl. Lab. of Microwave, Dep. of Electr. Eng., Tsinghua Univ., Beijing 100084, China
来源：
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | 2000年 / 19卷 / 06期
关键词：
Computer simulation - Frequency modulation - Iterative methods - Neural networks - Signal processing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
To replace the traditional FFT method and realize the object range super-resolution estimation, an artificial neural network method was proposed to decompose signal's auto-correlation matrix into the summation of rank-1 matrices and convert the decomposition problem to an iterative one by using Hopfield neural network. The property of this method was investigated both theoretically and experimentally. The results were compared with five other typical super-resolution algorithms including MUSIC, etc.. It is found that the present method has a lower SNR threshold and higher range resolution.
引用
收藏
页码：425 / 429
相关论文
共 50 条
  • [11] Range and DOA Estimation of Micro-Doppler Target Using A LFMCW Radar
    Yan, Weizhong
    Chen, Dongzhi
    Bai, Xudong
    2020 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND NORTH AMERICAN RADIO SCIENCE MEETING, 2020, : 1287 - 1288
  • [12] A Signal Processing Practice Method Based on LFMCW Radar
    Ma, Ke
    Zhang, Kaisheng
    Zhang, Yuanan
    PROCEEDINGS OF 2017 6TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2017), 2017, : 449 - 452
  • [13] LFMCW radar multi-target acceleration and velocity estimation method
    Zhang, RQ
    Huang, YL
    Yang, JY
    Xiong, JT
    2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3, 2004, : 1989 - 1992
  • [14] Design and implementation of LFMCW radar system based on ZYNQ
    Yuan, Ye
    Xu, Qiu
    Liu, Xingyu
    Li, Heng-Chao
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (21): : 8151 - 8154
  • [15] Motion Parameter Estimation of LFMCW Radar Based on Secondary Mixing and 3-DPT Method
    Sun, Luhao
    Li, Yubai
    PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 841 - 846
  • [16] Improving range precision of LFMCW radar based on frequency domain up-sampling-interpolating method
    Zhang, RQ
    Huang, YL
    Yang, JY
    Xiong, JT
    2005 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS: VOL 1: COMMUNICATION THEORY AND SYSTEMS, 2005, : 777 - 780
  • [17] A Ship Detection Method based on Recurrent Neural Network in a Marine Radar System
    Jie, Z.
    Yufen, S.
    2019 IEEE 4TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA), 2019, : 548 - 553
  • [18] A method of faults intelligent diagnosis based on neural network and expert system for radar
    Shang, CX
    Li, HP
    Wang, XN
    Huang, YH
    ISTM/2003: 5TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-6, CONFERENCE PROCEEDINGS, 2003, : 901 - 904
  • [19] Estimation System of Human Behaviors Using a Fuzzy Neural Network Based Object Selection
    Izumi, Kiyotaka
    Kamohara, Kohei
    Watanabe, Keigo
    2008 PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-7, 2008, : 1907 - 1911
  • [20] Radar-based Object Classification Using An Artificial Neural Network
    Lee, Dajung
    Cheung, Colman
    Pritsker, Dan
    PROCEEDINGS OF THE 2019 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON), 2019, : 305 - 310
12345