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Description: Abstract:W e analyze the degeneracy phenomenon of sequen t ialMon te Carlo part icle f ilters based on
bayesian theo rem , pu t focu s on the key techn iques ( good cho ice of impo rtance den sity and u se of
resamp ling ) to reduce it s effect s. Several imp roving schemes such as the U n scen ted Part icle F ilters
(U PF) , the A ux iliary Samp ling Impo rtance Resamp ling (A S IR ) and the Samp ling Impo rtance Resamp ling
(S IR ) algo rithm s are in t roduced to illu st rate th rough increasing the likelihood of the impo rtance den sity o r
inco rpo rat ing new measu remen t, o r rep licat ing part icles w ith large w eigh t s w ith in the generic f rame of
part icle f ilters, the convergence accu racy and robu stness behavio rs of the algo rithm can be effect ively
imp roved. A typ ical passive detect ion and locat ion p rob lem is simu lated to p rove above conclu sion s.
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粒子滤波算法的关键技术应用.pdf
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