학술논문

Distributed Target Tracking With Fading Channels Over Underwater Acoustic Sensor Networks
Document Type
Periodical
Source
IEEE Internet of Things Journal IEEE Internet Things J. Internet of Things Journal, IEEE. 11(8):13980-13994 Apr, 2024
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Fading channels
Target tracking
Kalman filters
Filtering
State estimation
Channel estimation
Wireless sensor networks
Channel fading
distributed state estimation (DSE)
stochastic stability
underwater acoustic sensor networks (UASNs)
unscented Kalman filtering
Language
ISSN
2327-4662
2372-2541
Abstract
This article investigates the problem of distributed target tracking via underwater acoustic sensor networks (UASNs) with fading channels. The degradation of signal quality due to wireless channel fading can significantly impact network reliability and subsequently reduce the tracking accuracy. To address this issue, we propose a modified distributed unscented Kalman filter (DUKF) named DUKF-Fc, which takes into account the effects of measurement fluctuation and transmission failure induced by channel fading. The channel estimation error is also considered when designing the estimator and a sufficient condition is established to ensure the stochastic boundedness of the estimation error. The proposed filtering scheme is versatile and possesses wide applicability to numerous scenarios, e.g., tracking a maneuvering underwater target with underwater sensor nodes (USNs) equipped with acoustic sensors. Considering the constraints of network energy resources, the issue of investigating the energy cost of DUKF-Fc is discussed in the simulation and accordingly, the results demonstrate the robustness and energy efficiency of the proposed filtering procedure.