ADS-B-Based Algorithm for Real-Time Optimal Estimation of Radar Biases

In order to improve the surveillance accuracy of radars in China's central and western regions,where multiple coverage does not come true and majority airplanes are not equipped with ADS-B(automatic dependent surveillance-broadcast),an ADS-B-based algorithm for real-time optimal estimation of radar biases was proposed on the basis of the radar biases theory.The algorithm can achieve a real-time optimal estimation of radar biases by the data fusion based on the difference between ADS-B data and radar data at the same time as well as the real-time calibration of the radar.The simulation of a case study shows that the root mean square of biases between calibrated and real range values is about 50 m,the root mean square of biases between calibrated and real angle values is about 0.04°,and the calibrated radar trajectories are essentially coincident with actual trajectories.