This paper is concerned with the target tracking problem for a class of wireless localization systems with unknown but bounded noises. Since the energy supply of wireless sensor nodes is rather scarce, a component-based event-triggered mechanism is utilized to reduce the signal transmission frequency by discarding the unnecessary information transmissions. The objective of the addressed problem is to design an event-triggered set-membership filter for target tracking with guaranteed performance. An estimate-based linearization approach is employed to reconstruct the innovation and a particle swarm optimization (PSO) algorithm is adopted to determine the uncertain scaling matrix generated by the linearization. The desired time-varying filter gain matrix is derived by solving a convex optimization problem. Finally, the personnel safety monitoring problem in a mine industrial site is considered in the simulation experiment to demonstrate the effectiveness of the proposed filtering algorithm.

本文关注的是一类具有未知但有界噪声的无线定位系统的目标跟踪问题。由于无线传感器节点的能量供应较为匮乏，因此采用基于组件的事件触发机制，通过丢弃不必要的信息传输来降低信号传输频率。所解决问题的目标是设计一个事件触发的集合成员过滤器，用于具有保证性能的目标跟踪。采用基于估计的线性化方法重构创新，并采用粒子群优化（PSO）算法确定线性化产生的不确定缩放矩阵。所需的时变滤波器增益矩阵是通过求解一个凸优化问题。最后，通过仿真实验考虑了某矿山工业现场人员安全监控问题，验证了所提滤波算法的有效性。