Decentralized Multi Passive Sensor System for 3D TargetTracking

Decentralized Kalman filter architecture for tracking a target in 3D Cartesian coordinates using acoustic and optical sensor data is presented. The performance of the algorithm is evaluated with numerical simulation and performance check metrics. This architecture is very simple and easily adaptable since there is no fed back from the global Kalman filter stage to local Kalman filter stage. It is robust even during the measurement loss and it is suitable for real time applications. This architecture is very easy for parallel implementation and it allows adding sensor on the fly.