Using ship radiated noise spectrum feature for data association in underwater target tracking

In multiple-target tracking problem, data association technique plays an significant role. When targets move closely or crosswise, performances of conventional data association algorithms which use kinematic information only may be degraded. Actually, beside the kinematic information, sensors always...

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Bibliographic Details
Published in2017 20th International Conference on Information Fusion (Fusion) pp. 1 - 5
Main Authors Wei Qiu, Wenke Wang, Zhiyun Zhuang, Pengzheng Lei, Le Li
Format Conference Proceeding
LanguageEnglish
Published International Society of Information Fusion (ISIF) 01.07.2017
Subjects
1 1/2-D spectrum
Feature extraction
feature-aided
Marine vehicles
posibilistic data association
Position measurement
Radar tracking
ship radiated noise spectrum
Target tracking
Time-frequency analysis
Trajectory
Online AccessGet full text
DOI10.23919/ICIF.2017.8009705

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Summary:In multiple-target tracking problem, data association technique plays an significant role. When targets move closely or crosswise, performances of conventional data association algorithms which use kinematic information only may be degraded. Actually, beside the kinematic information, sensors always can obtain feature information about the target, and incorporating the features into data association problem can improve the performance of data association. In this paper, for underwater target tracking, we propose a ship radiated noise spectrum feature aided probabilistic data association (PDA) algorithm to improve the data association and target tracking performance. Simulations are finally carried out and results show that the proposed method can improve the tracking performance over the conventional PDA algorithm in close-space-targets scenario.
DOI:10.23919/ICIF.2017.8009705