Liu Yong-xiang, Li Xiang, Zhuang Zhao-wen. Scaled Model for Recognizing the Spatial Rotating Target[J]. Journal of Electronics & Information Technology, 2004, 26(9): 1509-1512.
Citation:
Liu Yong-xiang, Li Xiang, Zhuang Zhao-wen. Scaled Model for Recognizing the Spatial Rotating Target[J]. Journal of Electronics & Information Technology, 2004, 26(9): 1509-1512.
Liu Yong-xiang, Li Xiang, Zhuang Zhao-wen. Scaled Model for Recognizing the Spatial Rotating Target[J]. Journal of Electronics & Information Technology, 2004, 26(9): 1509-1512.
Citation:
Liu Yong-xiang, Li Xiang, Zhuang Zhao-wen. Scaled Model for Recognizing the Spatial Rotating Target[J]. Journal of Electronics & Information Technology, 2004, 26(9): 1509-1512.
Considering the uncertain for rotating velocity of spatial target and sample 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 ARMA model in multirate is provided, through which the model parameters of radar turns in the scale of template data can be gotten, and then data can be matched in the same scale. Experimental result shows the validity of proposed method.
宗孔德.多抽样率信号处理.北京:清华大学出版社,1996:21-31. ［2］Wei W W S, Stram D O. Disaggregation of time series models. J. Royal Stat. Soc., 1990, 52(2):453-467. ［3］Eom M B, Chellappa R. Noncooperative target classification using hierarchical modeling of highrange resolution radar signatures. IEEE Trans. on Signal Processing, 1997, 24(9): 2318-2327.
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