Results 251 to 260 of about 235,258 (299)

Open Set Recognition With Incremental Learning for SAR Target Classification

IEEE Transactions on Geoscience and Remote Sensing, 2023
Synthetic aperture radar (SAR) target classification is an important application in SAR image interpretation. In practical applications, the battlefield is open and dynamic, and the SAR target classification model often encounters the targets of unknown ...
Xiaojie Ma, K. Ji, Sijia Feng, Linbin Zhang, Boli Xiong, Gangyao Kuang   +5 more
semanticscholar   +1 more source

Bispectrum-based radar target classification

ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344), 2002
With the good performance of higher-order spectra (HOS) techniques for non-Gaussian signal processing and Gaussian noise suppression capability, an AR model parametric bispectrum estimation is presented for conventional radar target return analysis. A reasonable selection of target bispectrum features is made with a formation of target feature vector ...
null Ji Hongbing, null Li Jie, null Xie Weixin, null He Wei   +3 more
openaire   +1 more source

Radar-camera Fusion for Road Target Classification

International Radar Conference, 2020
This paper presents a radar and camera sensor fusion framework as a vulnerable road user (VRU) perception system that can automatically detect, track and classify different targets on the road.
Kheireddine Aziz, E. De Greef, M. Rykunov, A. Bourdoux, H. Sahli   +4 more
semanticscholar   +1 more source

Waveform Adaptation for Target Classification Using HRRP in a Cognitive Framework

IEEE Transactions on Aerospace and Electronic Systems, 2023
Waveform adaptation is a key-feature for modern radar systems and essential for cognitive radar. In this article, we present a concept for the enhancement of the classification performance by using optimized transmit waveforms and a Gaussian template ...
M. Warnke, S. Brüggenwirth
semanticscholar   +1 more source

An efficient method of radar target classification

2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559), 2002
An efficient method of choosing the mother wavelet for classification is proposed, and an efficient classifier based on genetic wavelet neural network is designed and applied to classify two types of radar targets. The classification experiment results are encouraging, which shows the method proposed is superior.
null Yanning Zhang, null Jiangbin Zheng, null Huarui Liu, null Licheng Jiao   +3 more
openaire   +1 more source

Mixed Loss Graph Attention Network for Few-Shot SAR Target Classification

IEEE Transactions on Geoscience and Remote Sensing, 2022
Restricted by the observation condition, synthetic aperture radar (SAR) automatic target classification based on deep learning usually suffers from insufficient training samples.
Minjia Yang, Xueru Bai, Li Wang, Feng Zhou   +3 more
semanticscholar   +1 more source

Target Discrimination and Classification in Through-the-Wall Radar Imaging

IEEE Transactions on Signal Processing, 2011
In this paper, a scheme for target discrimination and classification is proposed. The proposed scheme is applied to through-the-wall microwave images obtained by using a wideband radar implementing frequency-domain back-projection. We consider stationary targets where Doppler and change-detection based techniques are inapplicable.
Christian Debes, Jürgen T. Hahn, Abdelhak M. Zoubir, Moeness G. Amin   +3 more
openaire   +1 more source

Background classification method based on deep learning for intelligent automotive radar target detection

Future generations computer systems, 2019
Automotive radar is becoming an important sensor of automotive with many advantages, and its target detection is easily affected by clutter and noise. In order to solve this problem, this paper introduces the deep learning model into one-dimensional (1D)
Ningbo Liu, Yanan Xu, Yonghua Tian, H. Ma, S. Wen   +4 more
semanticscholar   +1 more source

Few-Shot SAR Target Classification via Metalearning

IEEE Transactions on Geoscience and Remote Sensing, 2021
The state-of-the-art deep neural networks have made a great breakthrough in remote sensing image classification. However, the heavy dependence on large-scale data sets limits the application of the deep learning to synthetic aperture radar (SAR ...
Kun Fu, Tengfei Zhang, Yue Zhang, Zhirui Wang, Xian Sun   +4 more
semanticscholar   +1 more source

Small Target Classification of Maritime Radars Using Standardized Time-Frequency Distribution Images and Residual Networks With Improved Focal Loss

IEEE Transactions on Instrumentation and Measurement
Small target classification is an important but difficult task in maritime surveillance radar measurements. Due to the small sizes of small targets, no spatial scattering structural information is available for classification.
Jing-Yi Li, Xiaojun Zhang, Zi-Jian Zhao, P. Shui, Shuwen Xu   +4 more
semanticscholar   +1 more source