1- https://doi.org/10.1117/12.886937
The Set IMMJPDA filter for multitarget tracking
- May 13, 2011
- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
- Daniel Svensson +4 more
The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relationbetween the density of a random finite set and the ordinary density of a state vector to improve on the JointProbabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of theGaussian approximations of the JPDA, which results in avoidance of track coalescence. Another advantage is animproved estimation accuracy in terms of a measure which disregards target identity. In this paper we extend thefilter to also consider multiple motion models. As a basis for the extension we use the Interacting Multiple Model(IMM) algorithm. We derive three alternative filters that we jointly refer to as Set IMMJPDA (SIMMJPDA).They are based on two alternative descriptions of the IMMJPDA filter. In the paper, we also present simulationresults for a two-target tracking scenario, which show improved tracking performance for the Set IMMJPDAfilter when evaluated with a measure that disregards target identity.
- # JointProbabilistic Data Association
- # JointProbabilistic Data Association Filter
- # Multiple Motion Models
- # Interacting Multiple Model
- # Alternative Filters
- # Multi-target Tracking
- # Interacting Multiple Model Algorithm
- # Data Association Filter
- # Multiple Model Algorithm
- # Density Of Vector
