DocumentCode :
1490462
Title :
Efficient Delay-Tolerant Particle Filtering
Author :
Oreshkin, Boris N. ; Liu, Xuan ; Coates, Mark J.
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Volume :
59
Issue :
7
fYear :
2011
fDate :
7/1/2011 12:00:00 AM
Firstpage :
3369
Lastpage :
3381
Abstract :
This paper proposes a novel framework for delay-tolerant particle filtering that is computationally efficient and has limited memory requirements. Within this framework the informativeness of a delayed (out-of-sequence) measurement (OOSM) is estimated using a lightweight procedure and uninformative measurements are immediately discarded. The framework requires the identification of a threshold that separates informative from uninformative; this threshold selection task is formulated as a constrained optimization problem, where the goal is to minimize state estimation error whilst controlling the computational requirements. We develop an algorithm that provides an approximate solution for the optimization problem. Simulation experiments provide an example where the proposed framework processes less than 40% of all OOSMs with only a small reduction in state estimation accuracy.
Keywords :
delays; optimisation; particle filtering (numerical methods); OOSM; constrained optimization problem; delay-tolerant particle filtering; out-of-sequence measurement; state estimation error; uninformative measurement; Atmospheric measurements; Current measurement; Markov processes; Optimization; Particle measurements; State estimation; Time measurement; Out of sequence measurement (OOSM); particle filtering; resource management; tracking;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2011.2140110
Filename :
5744131
Link To Document :
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