Track-before-detect algorithm-based optimized interactive multiple model particle filtering for tracking maneuvering weak target

Xiaojia Wu; Jinlong Yang

doi:10.1117/12.3035452

19 July 2024 Track-before-detect algorithm-based optimized interactive multiple model particle filtering for tracking maneuvering weak target

Xiaojia Wu, Jinlong Yang

Author Affiliations +

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132132I (2024) https://doi.org/10.1117/12.3035452
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

This paper proposes an optimized algorithm for tracking maneuvering weak radar targets in complex sea environments. In the proposal, we first preprocesses radar echo images using the fractional Fourier transform (FrFT) to reduce clutter interference. Then, Feedback factor and residual resampling are introduced to optimize the interactive multiple model particle filtering (IMMPF) algorithm to achieve effective tracking of maneuvering targets. Additionally, the optimized IMMPF is combined with track before detect algorithm (TBD) to suppress clutter and accumulate target trajectory. Simulation experiment results demonstrate that the proposed algorithm can effectively track targets compared to other TBD algorithms.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaojia Wu and Jinlong Yang "Track-before-detect algorithm-based optimized interactive multiple model particle filtering for tracking maneuvering weak target", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132132I (19 July 2024); https://doi.org/10.1117/12.3035452

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