A Low Computational Complexity JPDA Filter With Superposition
| Autor: | Roy L. Streit, Robert Blair Angle, Murat Efe |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computational complexity theory
Computer science Applied Mathematics Bayesian probability Probabilistic logic Estimator 020206 networking & telecommunications 02 engineering and technology Machine epsilon Superposition principle Filter (video) Video tracking Signal Processing 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Algorithm |
| Zdroj: | IEEE Signal Processing Letters. 28:1031-1035 |
| ISSN: | 1558-2361 1070-9908 |
| DOI: | 10.1109/lsp.2021.3082040 |
| Popis: | Object superposition is a way to derive Bayesian estimators for multiple object tracking using point processes. A low computational complexity Bayesian multiple target tracking filter, based on target superposition, is presented. The concept of superposition is introduced and applied to the well-known Joint Probabilistic Data Association (JPDA) filter to derive the JPDA with superposition (JPDAS) filter. The JPDAS intensity function is evaluated to machine precision “for free” by computing the generating functional of the posterior process using complex arithmetic. A simulated example with eight targets is presented. |
| Databáze: | OpenAIRE |
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