Efficient delay-tolerant particle filtering

TitleEfficient delay-tolerant particle filtering
Publication TypeJournal Article
Year of Publication2011
AuthorsOreshkin, B. N., X. Liu, and M. J. Coates
JournalIEEE Transactions on Signal Processing
Pagination3369 - 3381
Date Published04/2011
Keywordsout of sequence measurement (OOSM), particle filtering, resource management, Tracking

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.

Refereed DesignationRefereed