識(shí)別空間旋轉(zhuǎn)目標(biāo)的尺度模型
Scaled Model for Recognizing the Spatial Rotating Target
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摘要: 由于空間目標(biāo)旋轉(zhuǎn)速率和雷達(dá)采樣周期的不確定，雷達(dá)回波數(shù)據(jù)與模板數(shù)據(jù)存在著采樣率不一致,影響匹配效果。該文通過多抽樣率下自回歸滑動(dòng)平均(ARMA)混合模型建模，得到回波數(shù)據(jù)在模板尺度下的模型參數(shù)，實(shí)現(xiàn)同一尺度下的信號(hào)匹配。實(shí)驗(yàn)結(jié)果表明了該方法的有效性。Abstract: 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.
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宗孔德.多抽樣率信號(hào)處理.北京:清華大學(xué)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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