Weak Signal Detection Algorithm Based on Particle Filtering
In the traditional particle filter algorithm, there exist problems such as poor robustness against noise and clutter, and difficulty in balancing the detection probability and false alarm probability. In the problem of detecting weak signals, due to the noise issue, it is more prone to missed detect...
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Editorial Office of Aero Weaponry
2025-06-01
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| Series: | Hangkong bingqi |
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| Online Access: | https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2025-0004.pdf |
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| author | Mao Senpeng, Wang Pengfei, Chen Wei, Guo Lei |
| author_facet | Mao Senpeng, Wang Pengfei, Chen Wei, Guo Lei |
| author_sort | Mao Senpeng, Wang Pengfei, Chen Wei, Guo Lei |
| collection | DOAJ |
| description | In the traditional particle filter algorithm, there exist problems such as poor robustness against noise and clutter, and difficulty in balancing the detection probability and false alarm probability. In the problem of detecting weak signals, due to the noise issue, it is more prone to missed detections and false detections. Meanwhile, if there is a large amount of background clutter around the weak signal, it will lead to a decrease in tracking accuracy. To address the problems arising in the signal processing under continuous clutter scenarios and improve the weak signal detection performance of the particle filter, this paper proposes an improved particle filter algorithm. Firstly, by modifying the likelihood ratio function, the influence of clutter on the detection probability is restricted. Secondly, the Bernoulli filter is used to set the detection probability of the signal, which significantly reduces the missed detection probability. Additionally, different initial particle distributions are adjusted with or without prior probability, further enhancing the performance of the filter. Simulation results show that the detection probability of weak signals in the clutter background using the improved particle filter algorithm has been significantly enhanced compared to the processing before the improvement. |
| format | Article |
| id | doaj-art-d2758dcd42984d63b14a6e08837c2d88 |
| institution | OA Journals |
| issn | 1673-5048 |
| language | zho |
| publishDate | 2025-06-01 |
| publisher | Editorial Office of Aero Weaponry |
| record_format | Article |
| series | Hangkong bingqi |
| spelling | doaj-art-d2758dcd42984d63b14a6e08837c2d882025-08-20T02:07:09ZzhoEditorial Office of Aero WeaponryHangkong bingqi1673-50482025-06-01323869010.12132/ISSN.1673-5048.2025.0004Weak Signal Detection Algorithm Based on Particle FilteringMao Senpeng, Wang Pengfei, Chen Wei, Guo Lei01. China Airborne Missile Academy, Luoyang 471009, China;2. National Key Laboratory of Air-based Information Perception and Fusion, Luoyang 471009, ChinaIn the traditional particle filter algorithm, there exist problems such as poor robustness against noise and clutter, and difficulty in balancing the detection probability and false alarm probability. In the problem of detecting weak signals, due to the noise issue, it is more prone to missed detections and false detections. Meanwhile, if there is a large amount of background clutter around the weak signal, it will lead to a decrease in tracking accuracy. To address the problems arising in the signal processing under continuous clutter scenarios and improve the weak signal detection performance of the particle filter, this paper proposes an improved particle filter algorithm. Firstly, by modifying the likelihood ratio function, the influence of clutter on the detection probability is restricted. Secondly, the Bernoulli filter is used to set the detection probability of the signal, which significantly reduces the missed detection probability. Additionally, different initial particle distributions are adjusted with or without prior probability, further enhancing the performance of the filter. Simulation results show that the detection probability of weak signals in the clutter background using the improved particle filter algorithm has been significantly enhanced compared to the processing before the improvement.https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2025-0004.pdf|particle filter|likelihood ratio|weak signal|clutter suppression|target detection |
| spellingShingle | Mao Senpeng, Wang Pengfei, Chen Wei, Guo Lei Weak Signal Detection Algorithm Based on Particle Filtering Hangkong bingqi |particle filter|likelihood ratio|weak signal|clutter suppression|target detection |
| title | Weak Signal Detection Algorithm Based on Particle Filtering |
| title_full | Weak Signal Detection Algorithm Based on Particle Filtering |
| title_fullStr | Weak Signal Detection Algorithm Based on Particle Filtering |
| title_full_unstemmed | Weak Signal Detection Algorithm Based on Particle Filtering |
| title_short | Weak Signal Detection Algorithm Based on Particle Filtering |
| title_sort | weak signal detection algorithm based on particle filtering |
| topic | |particle filter|likelihood ratio|weak signal|clutter suppression|target detection |
| url | https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2025-0004.pdf |
| work_keys_str_mv | AT maosenpengwangpengfeichenweiguolei weaksignaldetectionalgorithmbasedonparticlefiltering |