The track correlation algorithm should be able to adjust its control parameter to adapt the complicated and changing track data with unknown system error and other unknown features.The concept of the local track correlation uncertainty was proposed in this paper

two types of local track correlation uncertainty was defined and an adaptive track correlation algorithm was proposed based on traditional sequential track correlation algorithm

which included a new anti-system-error method of calculating correlation probability

a method to adaptively adjust the length of sequence according to the first local track correlation uncertainty

and a method to adaptively adjust correlation threshold according to the second local track correlation uncertainty.The simulation results show that with the new algorithm

the system error has little effect on the correlation probability under certain conditions

the sequence length the range of correlation threshold can be adaptively adjusted according to the change of average distance of targets and random error of sensors

and the correct correlation rate can be effectively improved in complicated conditions.