Distributed Target Tracking with Fading Channels over Underwater Wireless Sensor Networks

TL;DR

This paper presents a modified distributed unscented Kalman filter for underwater wireless sensor networks that accounts for channel fading effects, improving target tracking accuracy despite signal degradation.

Contribution

The paper introduces DUKF-Fc, a novel filtering algorithm that considers measurement fluctuations, transmission failures, and channel estimation errors in underwater target tracking.

Findings

DUKF-Fc improves tracking accuracy under fading channels.

Simulation confirms effectiveness of the proposed filter.

Trade-off analysis between tracking performance and energy consumption.

Abstract

This paper investigates the problem of distributed target tracking via underwater wireless sensor networks (UWSNs) 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 real-world scenarios, e.g., tracking a maneuvering underwater target with acoustic sensors. Simulation results demonstrate the effectiveness of the proposed filtering algorithm. In addition, considering the constraints of network energy resources, the issue of investigating a trade-off between tracking performance and energy consumption is discussed accordingly.