Paper
25 August 2003 Hybrid weighted interacting particle filter for multitarget tracking
David J. Ballantyne, Jarett Hailes, Michael A. Kouritizin, Hongwei Long, Jonathan H. Wiersma
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Abstract
A hybrid weighted interacting particle filter, the selectively resampling particle filter (SERP), is used to detect and track multiple ships maneuvering in a region of water. The ship trajectories exhibit nonlinear dynamics and interact in a nonlinear manner such that the ships do not collide. There is no prior knowledge on the number of ships in the region. The observations model a sensor tracking the ships from above the region, as in a low observable SAR or infrared problem. The SERP filter simulates particles to provide the approximated conditional distribution of the signal in the signal domain at a particular time, given the sequence of observations. After each observation, the hybrid filter uses selective resampling to move some particles with low weights to locations that have a higher likelihood of being correct, without resampling all particles or creating bias. Such a method is both easy to implement and highly computationally efficient. Quantitative results recording the capacity of the filter to determine the number of ships in the region and the location of each ship are presented. Thy hybrid filter is compared against an earlier particle filtering method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David J. Ballantyne, Jarett Hailes, Michael A. Kouritizin, Hongwei Long, and Jonathan H. Wiersma "Hybrid weighted interacting particle filter for multitarget tracking", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.488522
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CITATIONS
Cited by 6 scholarly publications and 2 patents.
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KEYWORDS
Particles

Particle filters

Electronic filtering

Nonlinear filtering

Filtering (signal processing)

Signal processing

Digital filtering

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