Abstract
Target rejection using high resolution range profile (HRRP) means reject the unknown target which not belongs to any class of the database while maintaining a high accuracy in recognition. In radar automatic target recognition (RATR), lacking complete training database is a main problem in unknown target rejection. In this paper, a novel method which generates training samples based on Gamma model is proposed. The paper firstly analyzed the statistical characteristics of echoes of range cells. Then it derived the parameters estimation process of Gamma model. Compared with uniform distributed model, the proposed method can achieve better rejection performance. The experimental results of measured data demonstrate its effectiveness.
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References
Li HJ, Yang SH (1993) Using rang profiles as feature vectors to identify aerospace objects. IEEE Trans Antennas Propag 41(3):261–268
Du L, Liu HW, Bao Z (2005). Radar HRRP target recognition based on higher order spectra. IEEE Trans Signal Processing 53(7)
Liao K, Fu JS, Yang WL (2010) A refuse-recognition method for radar HRRP target recognition based on Mahalanobis distance. In: Proceedings of the IEEE ICCASM, pp 503–506
Li Q, Li B (2011) Plane HRRP rejection based on SVDD technology. In: Proceedings of the IEEE APSAR, pp 1–4
Tax D, Duin R (2004) Support vector data description. Mach Learn 54:45–66
Chai J, Liu HW, Bao Z (2010) Application of a weighted KNN classifier for HRRP out-of-database target rejection. Syst Eng Electron 32(4):718–723 (in Chinese)
Jiang WL, Tang BY, Xu KB, Ke YA (1998) Modeling of high frequency inverse scatterings and estimation of parameters. Acta Electronica Sinica 26(3):70–74 (in Chinese)
Evans M, Hastings N, Peacock B (1993) Statistical distributions seconded. Wiley, New York
Du L, Liu HW, Bao Z (2006) A two-distribution compounded statistical model for radar HRRP target recognition. IEEE Trans Signal Process 54(6):2226–2238
Huang J, Ling CX (2003) Comparing naive Bayes, decision trees, and SVM with AUC and accuracy. In: Proceedings of the IEEE ICDM, pp 553–556
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© 2013 Springer-Verlag Berlin Heidelberg
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Zhou, D., Wang, R., Zheng, C., Su, J., Liu, X. (2013). Gamma Model-Based Target HRRP Rejection. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34522-7_38
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DOI: https://doi.org/10.1007/978-3-642-34522-7_38
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