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.

翻译：本文研究了在存在信道衰落的水下无线传感器网络(UWSNs)中实现分布式目标跟踪的问题。无线信道衰落导致的信号质量下降会显著影响网络可靠性，进而降低跟踪精度。为解决这一问题，我们提出了一种改进的分布式无迹卡尔曼滤波器(DUKF)——DUKF-Fc，该滤波器充分考虑了信道衰落引发的测量波动和传输失败效应。在估计器设计中还纳入了信道估计误差，并建立了确保估计误差随机有界性的充分条件。所提出的滤波方案具有普适性，能够广泛应用于众多实际场景，例如利用声学传感器跟踪机动水下目标。仿真结果验证了所提滤波算法的有效性。此外，考虑到网络能量资源的约束，论文还探讨了跟踪性能与能量消耗之间的权衡问题。