With increasing air traffic flow

TCAS Ⅱ can’t meet growing demand for collision avoidance

data fusion algorithm based on the maximum eigenvalue weighting of estimation error covariance is proposed. Principle and characteristics of TCAS Ⅱ and ADS-B are analyzed

the necessity of development of combining monitoring combined with advantages of ADS-B is expounded

and combined monitoring area is introduced. Kalman filtering is used for target tracking of aircraft

and the optimal estimation is obtained by weighted fusion of tracks obtained by local filtering. The algorithm is simulated and the results show that the algorithm can get higher precision of data

improve monitoring ability

and enhance performance of collision avoidance.