An Improved Optimal Measurement Data Correlation Algorithm Based on Multi-Source Information

An improved optimal 3-Dimensional (3-D) assignment algorithm based on Multi-source Information (IMFOA) is proposed. The algorithm firstly gets the correlation degree between multi-source measurements of single-sensor and target track through fusing multi-source information by using grey relational analysis algorithm and then a 3-D assignment model based on multi-source information fusion can be got. Further, an improved point- track optimal assignment algorithm is used to complete point-track correlations. In comparison with the Optimal 3- D Assignment (OA) algorithm based on dynamic information and the Improved Optimal Assignment (IOA) algorithm which implements point-track correlation through using marginal correlation probability on the basis of OA algorithm, IMFOA algorithm improves the tracking accuracy of multi-target in varying degrees under different detection scenarios and is an optimal measurement data correlation algorithm with stronger anti-interference.