Decentralized and Distributed Information Filter for Autonomous Intelligent Multisensor Systems

Abstract

This research paper is on development of distributed and decentralized multisensor data estimation and fusion algorithm with linear information filter for fusing the information from these various sensors and embedded in the developed system. The estimation technique is modified Kalman filter that provides estimates of the information about a certain state. Consequently the developed system is Radar Tracking System (RTS); comprising of array of antennae, and GPS mounted on a Digital Rate Gyroscope (DRG), for accurate and effective Information Gathering and Processing (IGP). The system was simulated to determine the stability and drift error rate of the trajectory over a period of 300secs. The results are also derived under usual methods and proof procedure of some existing literature. The advantage of this algorithm is that the transmission of new information can be done asynchronously only when the amount of information, measure with its randomness, is larger than a fixed threshold level.