MULTI SENSOR DATA FUSION

Abstract

The objective of our research is to design a multi radar data fusion algorithm which accepts the input from multiple disparate radars and fuse them to generate a precise and reliable picture for air traffic controllers. Data fusion is a technique used for efficiently combining the relevant information coming from multiple sources. The purpose is to achieve estimates and assure better results than those attainable by depending on a single source. Multi radar data fusion can be separated into two sub-problems: 1) State estimation 2) Data Association. Our proposed algorithm efficiently uses gating and data association techniques to solve the multi radar data fusion problem. Uninterrupted updates of the radars are the most crucial part of the multi radar data fusion. Therefore, Kalman filter is used for the prediction of the target if updates are not received from the radars. When the number of radar increases, the amount of information and data association complexity also increases. This results in confusion, because single target is observed multiple times. This phenomenon is known as clutter. Air traffic controlling is a critical job. Hence, if clutter is observed, it affects the controlling and decision making process for the operator. The proposed algorithm is evaluated by using real world data of domestic and international flights. Different operational scenarios are discussed with air traffic controllers and three live scenarios are selected for the testing of the algorithm. The results of the proposed method are compared with the data of Automatic Dependent Surveillance Broadcast (ADS–B). It is a modern tracking system in which aircraft uses satellite navigation system to decide its current position and regularly transmits to its ground bases controlling station. The air traffic controller uses ADS-B receivers as a replacement of the secondary radars because no interrogation signal is needed from the ground. The results of the proposed algorithm are compared with the ADS-B data as a true reference because of its precision and reliability.