Journal of Shanghai Jiao Tong University ›› 2022, Vol. 56 ›› Issue (2): 231-241.doi: 10.16183/j.cnki.jsjtu.2020.432

Previous Articles     Next Articles

A High Quality Algorithm of Time-Frequency Analysis and Its Application in Radar Signal Target Detection via LMSCT

HAO Guocheng1,2,3, ZHANG Bichao1, GUO Juan1, ZHANG Yabing1, SHI Guangyao1, WANG Panpan1, ZHANG Wei1()   

  1. 1.School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan), Wuhan 430074, China
    2.Department of Mathematics, Duke University, Durham 27708, USA
    3.Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences (Wuhan), Wuhan 430074, China
  • Received:2020-12-19 Online:2022-02-28 Published:2022-03-03
  • Contact: ZHANG Wei


Aimed at the fact that the chirplet rate parameter of the chirplet transform (CT) cannot match the instantaneous frequency of the signal completely, and that the anti-noise performance of the algorithm is poor, this paper proposes a high-quality local maximum synchrosqueezing chirplet transform (LMSCT) algorithm to improve the deviation of energy diffusion amplitude in CT time-frequency (TF)distribution. The main idea of this algorithm is to reallocate CT frequency points by local maximum synchrosqueezing operation. The experiment results show that the LMSCT algorithm has a higher TF concentration and a strong ability to suppress the interference of noise. The method can maintain a better resolution of TF representation at a low signal-to-noise ratio. In the application analysis of IPIX processing radar signals, the LMSCT algorithm can clearly describe the TF joint distribution characteristic of target signal and determine the distance unit of target, which provides the judgement basis for small target detection of IPIX radar signal in the background of sea clutter.

Key words: time-frequency (TF) analysis, chirplet transform (CT), local maximum synchrosqueezing transform, IPIX processing radar signal

CLC Number: