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high range resolution profile Automatic Target Recognition Using Sparse Representation

Chinese Journal of Aeronautics 2010年第5期23卷 556-562页

作者：周诺陈炜北京航空航天大学电子信息工程学院

Sparse representation is a new signal analysis method which is receiving increasing attention in recent years. In this article, a novel scheme solving high range resolution profile automatic target recognition for ground moving targets is proposed. The sparse representation theory is applied to analyzing the components of high range resolution profiles and sparse coefficients are used to describe their features. Numerous experiments with the target type number ranging from 2 to 6 have been implemented. Results show that the proposed scheme not only provides higher recognition preciseness in real time, but also achieves more robust performance as the target type number increases.

关键词： automatic target recognition high range resolution profile sparse representation feature extraction dictionary generation

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A Target Recognition Approach to Projecting HRR profiles onto Subspace

引用

Journal of Systems Engineering and Electronics 2003年第1期14卷 36-40页

作者： Pei Bingnan & Bao ZhengKey Lab. of Radar Signal Processing, Xidian University, Xi’an 710071, P. R. China Dept. of Electronic Engineering, Zhengzhou University, Zhengzhou 450052, P.R. China Key Lab. of adar Signal Processing Xidian University. Xi'an 710071 P. R. China Dept. of Electronic Engineering Zhengzhou University Zhengzhou 450052 P. R. China

Abstract: A array of the azimuthally averaged range-profile vectors and the inter-class and intra-class divergence matrixesare constructed iwth many frames of the high resolution range profiles which result from radar echoes of airplanes. Takingthe methods of whitening transformation and SVD produces a system of subspace vectors for target recognition. Where-upon, a template library for target recognition is built by the projection of a class-mean vector made from the radar dataonto the subspace for recognition. By Euclidean distance, a comparison is made between the above projection and eachtemplate in the library, to decide which class the target belongs to. Finally, simulations with the experimental radar dataarte given to show that the proposed method is robust to variation in azimuth and immune to additive Gaussian noisewhen SNR≥5dB.

关键词： Automatic target recognition high range resolution profile Distance classifier SVD Computer simulation

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