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Multiple-model cardinality balanced multitarget multi-bernoulli filter for tracking maneuvering targets
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نویسنده
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yuan x. ,lian f. ,han c.
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منبع
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journal of applied mathematics - 2013 - دوره : 2013 - شماره : 0
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چکیده
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By integrating the cardinality balanced multitarget multi-bernoulli (cbmember) filter with the interacting multiple models (imm) algorithm,an mm-cbmember filter is proposed in this paper for tracking multiple maneuvering targets in clutter. the sequential monte carlo (smc) method is used to implement the filter for generic multi-target models and the gaussian mixture (gm) method is used to implement the filter for linear-gaussian multi-target models. then,the extended kalman (ek) and unscented kalman filtering approximations for the gm-mm-cbmember filter to accommodate mildly nonlinear models are described briefly. simulation results are presented to show the effectiveness of the proposed filter. © 2013 xianghui yuan et al.
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آدرس
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ministry of education key laboratory for intelligent networks and network security (moe klinns),school of electronics and information engineering,xi'an jiaotong university, China, ministry of education key laboratory for intelligent networks and network security (moe klinns),school of electronics and information engineering,xi'an jiaotong university, China, ministry of education key laboratory for intelligent networks and network security (moe klinns),school of electronics and information engineering,xi'an jiaotong university, China
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Authors
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