期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 59, 期 9, 页码 4473-4477出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2011.2158427
关键词
Detection; estimation; filtering; smoothing; tracking
资金
- Australian Research Council [DP0989007, DP0880553]
- Royal Academy of Engineering/EPSRC [EP/H010866/1]
- Australian Research Council [DP0880553, DP0989007] Funding Source: Australian Research Council
- Engineering and Physical Sciences Research Council [EP/H010866/1] Funding Source: researchfish
- EPSRC [EP/H010866/1] Funding Source: UKRI
In this correspondence, we derive a forward-backward smoother for joint target detection and estimation and propose a sequential Monte Carlo implementation. We model the target by a Bernoulli random finite set since the target can be in one of two present or absent modes. Finite set statistics is used to derive the smoothing recursion. Our results indicate that smoothing has two distinct advantages over just using filtering: First, we are able to more accurately identify the appearance and disappearance of a target in the scene, and second, we can provide improved state estimates when the target exists.
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