Multi-sensor Targets Data Association and Track Fusion Based on Novel AWFCM

in view of the complex character of traditional JPDA algorithms to realize the data association, a novel AWFCM algorithm aiming at realizing the multi-target tracking under the cross tracks situation was proposed in this article. This new algorithm defined a new distance in new metric space in order to efficiently restrain the error range of data association clustering centers for samples with noise points and cross tracks. Also the improved weights based on the dots' density were introduced to the algorithm to reduce the negative influence of the imbalanced data sets. In this way, the improved weighted track fusion algorithm realized IR and MMW radar sensors' track fusion. Simulations have proved the validity of the AWFCM algorithm considering the advantages of the multi-sensor and the process complexity. The new system provides a reliable and valid method to make multi-target tracking data association and track fusion.