Sensor registration is the key precondition of the performance advantages of the multisensor data fusion system.In the presence of random errors

sensor biases

false alarms and missed detections

sensor registration usually works in a nonideal association envrionment.Traditional registration approches relying on the ideal association condition degrade seriously.On the other hand

traditional registration methods are sensitive to the target distribution.When targets are densely distributed

the registration problem is ill-conditioned and the estimation encounters the numerical instability phenomena.Focusing on sensor registration in the context of nonideal association and ill-condition

this paper presents the robust registration approach based on ridge least trimmed squares (RLTS).The proposed approach combines the advantages of the ridge regression (RR) and the least trimmed squares (LTS) estimation.The RLTS can deal with nonideal association and ill-condition simultaneously.Simulation results verify the robust performance of the RLTS method.