In this paper, the particle filtering problem is investigated for a class of nonlinear/non-Gaussian systems with energy harvesting sensors subject to randomly occurring sensor saturations (ROSSs). The random occurrences of the sensor saturations are characterized by a series of Bernoulli distributed stochastic variables with known probability distributions. The energy harvesting sensor transmits its measurement output to the remote filter only when the current energy level is sufficient, where the transmission probability of the measurement is recursively calculated by using the probability distribution of the sensor energy level. The effects of the ROSSs and the possible measurement losses induced by insufficient energies are fully considered in the design of filtering scheme, and an explicit expression of the likelihood function is derived. Finally, the numerical simulation examples (including a benchmark example for nonlinear filtering and the applications in moving target tracking problem) are provided to demonstrate the feasibility and effectiveness of the proposed particle filtering algorithm.

中文翻译：

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带有随机发生的传感器饱和的能量采集传感器的非线性/非高斯系统的粒子滤波

在本文中，研究了一类具有能量收集传感器的非线性/非高斯系统的粒子滤波问题，该系统受到随机发生的传感器饱和（ROSS）的影响。传感器饱和度的随机出现的特征是一系列具有已知概率分布的伯努利分布随机变量。仅当当前能量水平足够时，能量采集传感器才将其测量输出发送到远程滤波器，其中，通过使用传感器能量水平的概率分布来递归计算测量的传输概率。在滤波方案的设计中，充分考虑了ROSS的影响以及由于能量不足而引起的可能的测量损失，并推导了似然函数的明确表示。