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Radar HRRP target recognition with deep networks
Pattern Recognition, 2017Abstract Feature extraction is the key technique for radar automatic target recognition (RATR) based on high-resolution range profile (HRRP). Traditional feature extraction algorithms usually utilize shallow architectures, which result in the limited capability to characterize HRRP data and restrict the generalization performance for RATR.
Bo Chen, Hongwei Liu
exaly +2 more sources
One-Shot HRRP Generation for Radar Target Recognition
IEEE Geoscience and Remote Sensing Letters, 2022Insufficient data of a noncooperative target seriously affect the performance of radar automatic target recognition (RATR) using the high-resolution range profile (HRRP), especially when the noncooperative target has only one sample. To this end, we propose an unsupervised data generation method to generate noncooperative HRRP signals.
Yi Wen, Yihong Zhuang, Yue Huang
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Radar HRRP statistical recognition based on hypersphere model
Signal Processing, 2008The theoretical analysis and experimental results in this paper show that the independence assumption regarding elements in a radar high-resolution range profile (HRRP) sample, under which some statistical recognition methods were proposed, is not true.
Lan Du, Hongwei Liu
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Natural Scene Recognition Based on HRRP Statistical Modeling
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021Natural scene classification based on high resolution one-dimensional range profile (HRRP) has significant value in the field of target recognition and environmental monitoring. Statistical modeling of HRRP has been widely used to extract useful information from clutter-like signals.
Shu-Qi Lei +2 more
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