Risk-Sensitive Particle Filters for Mitigating Sample Impoverishment
نویسندگان
چکیده
منابع مشابه
Risk Sensitive Particle Filters
We propose a new particle filter that incorporates a model of costs when generating particles. The approach is motivated by the observation that the costs of accidentally not tracking hypotheses might be significant in some areas of state space, and irrelevant in others. By incorporating a cost model into particle filtering, states that are more critical to the system performance are more likel...
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during the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degeneracy and impoverishment. We are investigating methods that are particularly efficient at Particle Distribution Optimization (PDO) to fight sample degeneracy and impoverishment, with an emphasis on intelligence choices....
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A novel resampling algorithm (called Deterministic Resampling) is proposed, which avoids uncensored discarding of low weighted particles thereby avoiding sample impoverishment. The diversity of particles is maintained by deterministically sampling support particles to improve the residual resampling. A proof is given that our approach can be strictly unbiased and maintains the original state de...
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Over the last years, particle filters have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation process. The key idea of the KLD-sampling method is to bound the approximation error introduced by the sample-based represen...
متن کاملAdapting sample size in particle filters through KLD-resampling
This letter provides an adaptive resampling method. It determines the number of particles to resample so that the Kullback–Leibler distance (KLD) between distribution of particles before resampling and after resampling does not exceed a pre-specified error bound. The basis of the method is the same as Fox’s KLD-sampling but implemented differently. The KLD-sampling assumes that samples are comi...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2008
ISSN: 1053-587X
DOI: 10.1109/tsp.2008.928520