The optional selection of micro-motion feature based on Support Vector Machine

Bo Li; Hongmei Ren; Zhi-he Xiao; Jing Sheng

doi:10.1117/12.2294493

15 November 2017 The optional selection of micro-motion feature based on Support Vector Machine

Bo Li, Hongmei Ren, Zhi-he Xiao, Jing Sheng

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106052X (2017) https://doi.org/10.1117/12.2294493
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

Micro-motion form of target is multiple, different micro-motion forms are apt to be modulated, which makes it difficult for feature extraction and recognition. Aiming at feature extraction of cone-shaped objects with different micro-motion forms, this paper proposes the best selection method of micro-motion feature based on support vector machine. After the time-frequency distribution of radar echoes, comparing the time-frequency spectrum of objects with different micro-motion forms, features are extracted based on the differences between the instantaneous frequency variations of different micro-motions. According to the methods based on SVM (Support Vector Machine) features are extracted, then the best features are acquired. Finally, the result shows the method proposed in this paper is feasible under the test condition of certain signal-to-noise ratio(SNR).

Citation Download Citation

Bo Li, Hongmei Ren, Zhi-he Xiao, and Jing Sheng "The optional selection of micro-motion feature based on Support Vector Machine", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106052X (15 November 2017); https://doi.org/10.1117/12.2294493

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