Research on multisource track fusion algorithm based on regional discriminant fusion

Civil aircraft track monitoring relies on various signals, including primary radar, secondary radar, ADS-B signal, etc. Beidou short message signal has the advantages of wide coverage and low use cost, and has been gradually applied in the field of civil aviation track monitoring. The fusion of the above multi-source trace signals can make use of the advantages of each signal to improve the accuracy of track estimation and obtain high-quality fusion tracks. To enhance flight monitoring accuracy and reliability, multi-source track fusion algorithms are crucial. Therefore, it is very necessary to study the multi-source track fusion algorithm. This paper focuses on the integration of radar, ADS-B, and Beidou short message track signals. A weighted track fusion algorithm combining Mosaic method and track covariance method is presented, combining the strengths of the Mosaic method and track covariance approach. The algorithm is implemented and validated using actual signal data.