Abstract
The problem of two-dimensional bearings-only multisensor-multitarget tracking is addressed in this work. For this type of target tracking problem, the multidimensional assignment (MDA) is crucial for identifying measurements originating from the same targets. However, the computation of the assignment cost of all possible associations is extremely high. To reduce the computational complexity of MDA, a new coarse gating strategy is proposed. This is realized by comparing the Mahalanobis distance between the current estimate and initial estimate in an iterative process for the maximum likelihood estimation of the target position with a certain threshold to eliminate potential infeasible associations. When the Mahalanobis distance is less than the threshold, the iteration will exit in advance so as to avoid the expensive computational costs caused by invalid iteration. Furthermore, the proposed strategy is combined with the two-stage multiple hypothesis tracking framework for bearings-only multisensor-multitarget tracking. Numerical experimental results verify its effectiveness.
Funder
National Key Research and Development Plan under Grants
National Natural Science Foundation of China
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
4 articles.
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1. Optimal Geometry and Motion Coordination for Multisensor Target Tracking with Bearings-Only Measurements;Sensors;2023-07-14
2. Measurement-to-Measurement Association for MDA with A Practical Coarse Gating Strategy;2023 26th International Conference on Information Fusion (FUSION);2023-06-28
3. Revisiting the Bearings-only Filtering Problem;2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS);2022-11-21
4. GNN-Guided Track Branch Formation For Multiple Hypothesis Tracking;2022 4th International Conference on Communications, Information System and Computer Engineering (CISCE);2022-05-27