Multiple Emitters Direct Tracking With Distributed Single-Sensors: Improved Particle Filter Based on Multiple-Frequency Fusion

Tracking the trajectory of multiple moving wideband emitters with distributed single-sensors is addressed in this article. Traditional tracking methods typically begin by collecting the positions of emitters within each observation interval and subsequently derive the tracking trajectories through trajectory correlation. However, repeated localization and multitarget data association create tremendous complexity challenges for tracking. In this article, a direct tracking method dependent on the particle filter (PF) for multiple emitters within the same frequency band is proposed. The method integrates the received data from all sensors and utilizes data segmentation and multiband division to reduce computational complexity. Subsequently, a spectral function based on multiple-frequency fusion is constructed to replace the likelihood function of the PF, which enables effective utilization of all sensor data for calculating particle weights. Finally, the weights of particles are obtained by utilizing multiple frequency bands, enabling the tracking of multiple emitters based on multiple sets of particles. In comparison to state-of-the-art methods, the proposed method avoids trajectory correlation and demonstrates better tracking performance. The effectiveness of the proposed method is substantiated by both numerical and experimental results.

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Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-03-29
DOI
https://doi.org/10.1109/taes.2025.3555214
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Multiple Emitters Direct Tracking With Distributed Single-Sensors: Improved Particle Filter Based on Multiple-Frequency Fusion

Xinjian Yin, Ming‐Yi You, Jianfeng Li, Tong Hu et al.
IEEE Transactions on Aerospace and Electronic Systems
Advanced Algorithms and Applications
article

Multiple Emitters Direct Tracking With Distributed Single-Sensors: Improved Particle Filter Based on Multiple-Frequency Fusion

Xinjian Yin, Ming‐Yi You, Jianfeng Li, Tong Hu, Xiaofei Zhang
article en

Abstract

Tracking the trajectory of multiple moving wideband emitters with distributed single-sensors is addressed in this article. Traditional tracking methods typically begin by collecting the positions of emitters within each observation interval and subsequently derive the tracking trajectories through trajectory correlation. However, repeated localization and multitarget data association create tremendous complexity challenges for tracking. In this article, a direct tracking method dependent on the particle filter (PF) for multiple emitters within the same frequency band is proposed. The method integrates the received data from all sensors and utilizes data segmentation and multiband division to reduce computational complexity. Subsequently, a spectral function based on multiple-frequency fusion is constructed to replace the likelihood function of the PF, which enables effective utilization of all sensor data for calculating particle weights. Finally, the weights of particles are obtained by utilizing multiple frequency bands, enabling the tracking of multiple emitters based on multiple sets of particles. In comparison to state-of-the-art methods, the proposed method avoids trajectory correlation and demonstrates better tracking performance. The effectiveness of the proposed method is substantiated by both numerical and experimental results.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(4)
ETC International (NL), Nanjing University of Aeronautics and Astronautics (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Affordable and clean energy
Openalex Percentile: Top 94%
Advanced Algorithms and Applications
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Multiple Emitters Direct Tracking With Distributed Single-Sensors: Improved Particle Filter Based on Multiple-Frequency Fusion — Xinjian Yin, Ming‐Yi You, et al. · IEEE Transactions on Aerospace and Electronic Systems (2025) | TGRS Research Map | TGRS