Kalman Filter Design for Intermittent Optical Wireless Communication Systems on Time Scales

TL;DR

This paper develops a Kalman filter on time scales to effectively estimate states in intermittent optical wireless communication systems with non-uniform measurements, demonstrating promising simulation results.

Contribution

It introduces a novel time-scale Kalman filter tailored for intermittent OWC systems, bridging continuous and discrete estimation in practical scenarios.

Findings

Time-scale Kalman filter accurately estimates states with non-uniform data.

Simulation confirms the filter's robustness in practical intermittent OWC systems.

First application of time-scale Kalman filtering to real-world optical communication data.

Abstract

Time-scale theory, due to its ability to unify the continuous and discrete cases, allows handling intractable non-uniform measurements, such as intermittent received signals. In this work, we address the state estimation problem of a vibration-induced intermittent optical wireless communication (OWC) system by designing a Kalman filter on time scales. First, the algorithm of the time-scale Kalman filter is introduced and a numerical example is given for illustration. Then the studied intermittent OWC system is presented, and experimental data are collected to determine the time scale's form, which has bounded graininess (a.k.a, bounded time jumps). Finally, we design a Kalman filter on the previously defined time scale for the intermittent OWC system and critically analyzed its estimation performance. Moreover, the obtained conclusions are further validated on a reference system. The simulation results corroborate that the time-scale Kalman filtering technique is considerably promising to solve the state estimation problem with non-uniform measurements. This study reveals for the first time the feasibility of applying the time-scale Kalman filter theory to practical applications.