Adaptive Kernel Kalman Filter Based Belief Propagation Algorithm for Maneuvering Multi-Target Tracking
نویسندگان
چکیده
This letter incorporates the adaptive kernel Kalman filter (AKKF) into belief propagation (BP) algorithm for multi-target tracking (MTT) in single-sensor systems. The is capable of an unknown and time-varying number targets, presence false alarms, clutter measurement-to-target association uncertainty. Experiment results reveal that proposed method has a favourable performance using generalized optimal sub-patten assignment (GOSAP) metrics at substantially less computation cost than particle (PF) based BP algorithm.
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ژورنال
عنوان ژورنال: IEEE Signal Processing Letters
سال: 2022
ISSN: ['1558-2361', '1070-9908']
DOI: https://doi.org/10.1109/lsp.2022.3184534