A Reduction Algorithm Based on Rough Set and Information Granulation Theory for Multi-radar Data

To solve the problem that the Multi-radar Surveillance System for Air Traffic Control System receives too much redundant data at some point, the paper proposes a data reduction algorithm based on Rough Set theory. Traditionally, rough set theory is applied in reduction of attributes and attributes´ value. In this paper, we combine Rough Set theory with Information Granulation theory to reduce the multi-radar data on attribute and universe. Simulation results show that the algorithm can reduce redundant data effectively. Compared with the original data, the coordinate estimated after reducing data is closer to the true location of the civil aircraft.