A Novel Data Fusion of Navigation and Surveillance Facilities using Multi Dimensional Kalman Filter Algorithm in Linux Environment for Optimal Air Space Management

Abstract A compact system which takes the data from Global Positioning System(GPS), Secondary Surveillance Radar(SSR) and a communication navigation and surveillance system, namely Very High Frequency Omni Range(VOR) and reduces the errors is designed developed and realized, which can give better positional accuracy for air traffic controlling officer(ATCO), as well as to the pilot. The process of obtaining the position information onboard, which is termed as navigation can be obtained by VOR and GPS, where as the process of obtaining the aircraft position on ground by the ATCO is called surveillance, which is obtained by radar. This system can be used both for navigation and surveillance as it integrates data received by GPS, Radar(SSR) and VOR. The system can be utilized to supplement both ground based data and satellite based data. The attempt in this paper is claimed as novel, as the entire list of state variables for the aircraft can not be provided by any one sensor at normally desired level of accuracy and dependability. A multi dimensional kalman filter algorithm is applied on a Broadcom BCM2836R processor in Linux environment using mathematica10 to achieve this objective.