Robust Sensor Registration Based on Ridge Least Trimmed Squares
TIAN Wei1, PENG Hua-fu1,2, HUANG Gao-ming1, LIN Xiao-hong1, WANG Xue-bao1
1. College of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430033, China;
2. Unit 92773 of the PLA, Wenzhou, Zhejiang 325807, China
Abstract: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.
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