Paper
12 March 1999 Single-model multiple-process noise soft-switching filter
Ali T. Alouani, Theodore R. Rice
Author Affiliations +
Abstract
This paper presents a new tracking filter capable of soft switching between two kinematic target models without requiring any a prior knowledge of the target state's transition probability matrix. The target models used are both constant velocity models, one with a low state process noise and one with a high state process noise. Simulations are performed to show the soft switching capability of the new filter as well as its performance. The newly derived filter significantly outperforms a well-known variable dimension filter. The result of this paper constitute a first step toward designing a new class of filters that are capable of soft switching between different target kinematic models without requiring a priori knowledge of the target state's transition likelihoods.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ali T. Alouani and Theodore R. Rice "Single-model multiple-process noise soft-switching filter", Proc. SPIE 3719, Sensor Fusion: Architectures, Algorithms, and Applications III, (12 March 1999); https://doi.org/10.1117/12.341348
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Switching

Monte Carlo methods

Kinematics

Process modeling

Sensors

Electronic filtering

Motion models

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