Noise robust recognition method based on scatterer pattern for radar HRRP data
Hua He, Lan Du, Penghui Wang, Hongwei Liu
Abstract
In this paper, a novel noise-robust recognition method for high-resolution range profile (HRRP) data is proposed based on target scatterer pattern to enhance its recognition performance under the test condition of low SNR. The target dominant scatterers are first extracted based on the scattering center model of complex HRRP data via the orthogonal matching pursuit (OMP) algorithm to realize noise reduction. Then a scatterer matching recognition algorithm based on Hausdorff distance (HD) is developed with the magnitudes and locations of extracted dominant scatterers used as the feature patterns. Experimental results on the measured HRRP data demonstrate that the proposed method can improve the recognition performance under the relatively low SNR condition for both orthogonal and superresolution representations of scattering center model.
BibTeX
@inproceedings{icassp2016_noiserobustrecog,
title = {Noise robust recognition method based on scatterer pattern for radar HRRP data},
author = {Hua He and Lan Du and Penghui Wang and Hongwei Liu},
booktitle = {ICASSP 2016},
year = {2016}
}