衰退
计算机科学
稳健性(进化)
卡尔曼滤波器
水声学
水声通信
估计员
传输(电信)
无线传感器网络
频道(广播)
水下
实时计算
电子工程
电信
计算机网络
工程类
人工智能
数学
生物化学
化学
海洋学
统计
基因
地质学
作者
Miaoyi Tang,Meiqin Liu,Senlin Zhang,Ronghao Zheng,Shanling Dong
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2023-12-07
卷期号:11 (8): 13980-13994
被引量:2
标识
DOI:10.1109/jiot.2023.3340415
摘要
This paper 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.
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