In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of general nonlinear systems with stochastic uncertainties under communication protocols. A modified unscented transformation is put forward to account for stochastic uncertainties caused by modeling errors. For preventing data collisions and mitigating communication burden, the round-robin protocol and the weighted try-once-discard protocol are, respectively, introduced to regulate the data transmission order from sensors to the filter. Then, by employing two kinds of data-holding strategies (i.e., zero-order holder and zero input) for those nodes without transmission privilege, two novel protocol-based measurement models are formulated. Subsequently, by resorting to the sigma point approximation method, two resource-saving UKF algorithms are developed, where the impact from the underlying protocols on the filter design is explicitly quantified. Finally, compared with the protocol-based extended Kalman filtering algorithms, a simulation example is presented to demonstrate the effectiveness of the proposed protocol-based UKF algorithms.

中文翻译：

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存在随机不确定性时基于协议的无迹卡尔曼滤波


本文研究了通信协议下一类具有随机不确定性的一般非线性系统的无迹卡尔曼滤波（UKF）问题。提出了一种改进的无味变换来解决建模误差引起的随机不确定性。为了防止数据冲突并减轻通信负担，分别引入循环协议和加权尝试一次丢弃协议来调节从传感器到过滤器的数据传输顺序。然后，通过对没有传输权限的节点采用两种数据保存策略（即零阶保存和零输入），制定了两种新颖的基于协议的测量模型。随后，通过采用西格玛点近似方法，开发了两种资源节约型 UKF 算法，其中底层协议对滤波器设计的影响被明确量化。最后，通过仿真实例与基于协议的扩展卡尔曼滤波算法进行比较，验证了所提出的基于协议的UKF算法的有效性。