To establish a consistent target situation between different sensors, it is first necessary to address the accurate association relationship of multiple-target information observed by different sensors. Traditional association methods based on target position cannot solve the association problem under the condition of systematic bias. This paper proposes an anti-bias target association method based on topological relationships. First, the topological features of the formation structure for each target are extracted from the position information of the target groups detected by each sensor. Then, the topological distance is calculated based on the topological features of each target detected by the two sensors, and a topological distance matrix is constructed. Finally, Kuhn-Munkres algorithm is used for optimization and solving. Simulation results show that under conditions of dense formation targets, random errors, system errors, and sensor misdetections, the performance of the proposed method is significantly better than that of traditional position association methods.