Results 251 to 260 of about 8,956 (287)

Radar emitter signal recognition based on atomic decomposition

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
In this paper, a novel approach based on Gaussian Chirplet Atoms is presented to automatically recognise radar emitter signals. Firstly, based on the over-completed dictionary of Gaussian Chirplet atoms, the improved matching pursuit (MP) algorithm is applied to extract the features of the time-frequency atoms from the typical radar emitter signals ...
Ming Zhu, Weidong Jin, Laizhao Hu
openaire   +1 more source

Application of pattern recognition techniques to the processing of radar signals

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
This paper presents numerous pattern recognition techniques which can be applied to radar data. In particular, nearest neighbor and linear discriminant function algorithms are discussed, as well as the use of different sets of features to represent the data.
Norberto F. Ezquerra, Linda Harkness
openaire   +1 more source

Intelligent Radar Signal Recognition and Classification

2015
This chapter investigates a classification problem for timely and reliable identification of radar signal emitters by implementing and following a neural network (NN) based approach. A large data set of intercepted generic radar signals, containing records of their pulse train characteristics (such as operational frequencies, modulation types, pulse ...
Jordanov, Ivan Nikolov, Petrov, Nedyalko
openaire   +1 more source

Wavelet Transformation and Signal Discrimination for HRR Radar Target Recognition

Multidimensional Systems and Signal Processing, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dale E. Nelson, Janusz A. Starzyk, D. David Ensley   +2 more
openaire   +1 more source

Radar Signal Recognition Based on TPOT and LIME

2018 37th Chinese Control Conference (CCC), 2018
Aiming at solving the existing problems of radar signal recognition methods, this paper presents a method based on Tree-based Pipeline Optimization Tool(TPOT) and Local Interpretable Model-agnostic Explanations(LIME). This method uses genetic programming based on the tree structure to generate the machine learning pipeline. The structure and parameters
Wenqiang Zhang, Peng Ge, Weidong Jin, Jian Guo   +3 more
openaire   +1 more source

A novel approach for radar emitter signal recognition

The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings., 2005
To enhance recognition rate of radar emitter signals (RESs) to meet the requirements of modem electronic warfare, a novel approach is proposed to recognize automatically different RESs. The main points of the introduced approach include resemblance coefficient feature extraction and support vector machine classifiers. Experimental results show that the
null Gexiang Zhang, null Laizhao Hu, null Weidong Jin   +2 more
openaire   +1 more source

A New Recognition Method of Radar Emitter Signal

Applied Mechanics and Materials, 2013
According to the problem that the existing radar signal recognition method cannot effectively identify the radar signal, a new recognition method based on kernel density estimation is proposed. First using kernel density estimation gets the probability density curve of radar emitter signal parameters, then storing the cures into database as the ...
Fei Ye, Xin Wang, Xing Rong Gao, Jun Luo
openaire   +1 more source

Modeling of multirate signal in radar target recognition

International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003, 2003
Considering the uncertain for rotating velocity of spatial target and period of radar observation, there exists sampling rate variance between radar returns and template data, which decreases the degree of matching. In this paper, the autoregressive moving average (ARMA) model in multirate is provided, through which the power spectral density (PSD) of ...
null Liu Yong-Xiang, null Li Xiang, null Zhuang Zhao-Wen   +2 more
openaire   +1 more source

Low Probability of Intercept Radar Signal Recognition Based on Semi-Supervised Support Vector Machine

Electronics (Switzerland)
Low probability of intercept (LPI) radar signal recognition under low signal-to-noise ratio (SNR) is a challenging task within electronic reconnaissance systems, particularly when faced with scarce labeled data and limited resources.
Fang Zhou, Daying Quan
exaly   +2 more sources

Radar emitter signal recognition based on support vector machines

ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004., 2005
Radar emitter signal recognition plays an important role in electronic intelligence systems and electronic support measure systems. To heighten accurate recognition rate of radar emitter signals, this paper proposes a hierarchical classifier structure to recognize radar emitter signals. The proposed structure combines resemblance coefficient classifier,
Gexiang Zhang, Weidong Jin, Laizhao Hu
openaire   +1 more source