Paper
17 May 2012 MeMBer filter for manoeuvring targets
Author Affiliations +
Abstract
This paper will introduce a new Multitarget Multi-Bernoulli (MeMBer) recursion for tracking targets traveling under multiple motion models. The proposed interacting multiple model MeMBer (IMM-MeMBer) filter uses Jump Markov Models (JMM) to extended the basic MeMBer recursion to allow for multiple motion models. This extension is implemented using both the SMC and GM based MeMBer approximations. The recursive prediction and update equations are presented for both implementations. Each multiple model implementation is validated against its respective standard MeMBer implementation as well as against each other. This validation is done using a simulated scenario containing multiple maneuvering targets. A variety of metrics are observed including target detection capability, estimate accuracy and model likelihood determination.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Darcy Dunne and T. Kirubarajan "MeMBer filter for manoeuvring targets", Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 839205 (17 May 2012); https://doi.org/10.1117/12.921069
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Motion models

Berkelium

Digital filtering

Nonlinear filtering

Target detection

Electronic filtering

Filtering (signal processing)

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