Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (2): 49-54.doi: 10.19665/j.issn1001-2400.2021.02.007

• Special Issue: Advances in Radar Technology • Previous Articles     Next Articles

Radar HRRP target recognition based on the multiplicative RNN model

XU Bin1(),ZHANG Yongshun1(),ZHANG Qin1(),WANG Fuping2(),ZHENG Guimei1()   

  1. 1. Air and Missile Defence college,Air Force Engineering University,Xi’an 710051,China
    2. School of Communication and Information Engineering,Xi’an University of Posts & Telecommunications,Xi’an 710121,China
  • Received:2020-09-30 Revised:2020-11-11 Online:2021-04-20 Published:2021-04-28


The traditional HRRP recognition methods do not consider the temporal correlation,and the azimuth sensitivity of HRRP results in the temporal variation of the samples.This paper proposes a multiplicative recurrent neural network.In this paper,HRRP samples are converted into the sequence form first,which is used to consider the correlation between range cells.In order to alleviate the mismatch between the HRRP sequence variation caused by azimuth sensitivity and the model with fixed parameters,the model adaptively selects the corresponding parameters according to the input data,and extracts robust features from the HRRP sequence.Finally,the voting strategy is adopted to fuse the information at all time steps and predict the sample categories.Experimental results with measured data show that the current model can effectively extract discriminative features and identify targets.

Key words: radar automatic target recognition, multiplicative recurrent neural network, high resolution range profile, target-aspect sensitivity, temporal correlation

CLC Number: 

  • TN957.52