Decorrelation-Based Data Association Algorithm for Heterogeneous Sensors System

A decorrelation-based data association algorithm for heterogeneous sensors system is proposed, which first fusions multiple measurements to estimate a target position using the pseudo linear estimation method, then a decorrelation-based data association model is built and the unscented transform is proposed to compute the mutual covariance between measurements and the pseudo ones. Meanwhile, taking the real-time problem into consideration, when calculating the cross covariance, the minimum skew simplex sample is used to reduce the complexity of the algorithm.