期刊
IEEE INTERNET OF THINGS JOURNAL
卷 10, 期 18, 页码 16427-16439出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2023.3268151
关键词
Observers; Transmitters; Location awareness; Receivers; Doppler shift; Trajectory optimization; Delay effects; Bistatic sonar; Doppler shift; Internet of Underwater Things (IoUT); target localization; time delay; trajectory optimization
Efficient target localization is crucial for marine applications in the Internet of Underwater Things (IoUT). A-optimality criterion-based observer trajectory optimization problem is formulated to improve localization performance based on time delay and Doppler shift measurements. The proposed method addresses the conflict between the nonaccessible zone constraint and observer dynamics constraint using a warning zone-based augmented Lagrange multiplier approach. Extensive simulations demonstrate the improved target localization accuracy achieved by trajectory optimization.
Efficient target localization is critical to many marine applications in the Internet of Underwater Things (IoUT). Doppler effect becomes more predominant in the underwater environment when the relative speed of the moving object, i.e., the observer, to the signal propagation speed in water is much larger than that in the air. This along with the observer-target geometry will bring in a notable impact on the localization performance. In this article, we derive the Cramer-Rao lower bound (CRLB) and formulate the A-optimality criterion-based observer trajectory optimization problem to improve the localization performance based on time delay and Doppler shift measurements. We show that in the worst case scenario, there will be a conflict between the nonaccessible zone constraint and the observer dynamics constraint, which will lead to an erroneous result. To address this problem, we propose a warning zone-based augmented Lagrange multiplier method (ALMM) where the nonaccessible zone constraint is relaxed to resolve the conflict and ensure the nonaccessible requirement of the targeted zone is maintained. Performance evaluations are conducted through extensive simulations for different scenarios, and the results are compared to other methods with or without trajectory optimization. We demonstrate that trajectory optimization using time delays and Doppler shifts can greatly improve the target localization accuracy in underwater networks.
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