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29 October 1997 Large-scale air traffic surveillance using an IMM estimator with assignment
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Abstract
In this paper we present the development and implementation of a multisensor-multitarget tracking algorithm for large scale air traffic surveillance based on the IMM state estimator combined with a 2-dimensional assignment for data association. The algorithm can be used to track a large umber of targets from measurements obtained with a large number of radars. The use of the algorithm is illustrated on measurements obtained from 5 FAA radars, which are asynchronous, heterogeneous and geographically distributed over a large area. Both secondary radar data (beacon returns from cooperative targets) as well as primary radar data (skin returns from non-cooperative targets) are used. The target IDs from the beacon returns are not used in the data association. The surveillance region includes about 800 targets that exhibit different types of motion. The performance of the IMM estimator is compared with that of the Kalman filter. A number of performance measures that can be used on real data without knowledge of the ground truth are presented for this purpose. It is shown that the IMM estimator performs better than the Kalman filter. The advantage of fusing multisensor data is quantified. It is also shown that the computational requirements in the multisensor case are lower than in single sensor case.
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Hui Wang, Thiagalingam Kirubarajan, Yicong Li, and Yaakov Bar-Shalom "Large-scale air traffic surveillance using an IMM estimator with assignment", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.283965
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