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- W2384389541 abstract "To improve the filtering precision when dealing with the state estimation problem of moving target tracking,A particle optimal combination particle filtering(POCPF) algorithm is proposed according to particle degradation and particle impoverishment caused by particle-resample.The new particle algorithm uses a likelihood function to improve the location of particles.And the likelihood function can make particles move towards regions where they have larger values of posterior density function.Then it reassesses the weights of particles and maintains the particle diversity.As a result,the impoverishment of particle filter is overcome and the sample size necessary for accuracy state estimation is reduced dramatically so the running time shortened.Experimental results show that POCPF algorithm is effective,furthermore,on the condition of the same particle amount,POCPF algorithm is better than PF algorithm." @default.
- W2384389541 created "2016-06-24" @default.
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- W2384389541 date "2011-01-01" @default.
- W2384389541 modified "2023-09-24" @default.
- W2384389541 title "A Study on Particle Filtering Tracking Algorithm of Particle Optimal Combination" @default.
- W2384389541 hasPublicationYear "2011" @default.
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