Fully decentralised algorithm for multisensor Kalman filtering

An algorithm that achieves complete decentralisation of the Kalman filter algorithm amongst the sensing nodes of a multisensor system is preserved. This algorithm does not require any form of central processing facility or centralised communications medium. Each sensing node implements its own local Kalman filter to arrive at a partial decision which it then broadcasts to every other node. Each node then assimilates this received information to arrive at its own local estimate of the system state. The algorithm guarantees that each local estimate thus obtained is identical to the estimate that would be obtained if a conventional, completely centralised, Kalman filter were used. Because there is no single central processing node the algorithm is highly resilient to loss of one or more sensing nodes. The fully decentralised nature ensures that it is ideal for implementation on a parallel processing array, such as a transputer network. The algorithm has been tested using a simulated multiperson pursuit-evasion game to check the viability. The algorithm has also been implemented on a transputer based array of cameras to perform tracking of an object moving around a room