Anti-bias track-to-track association algorithm based on distance detection

作者：Qi, Lin^*; Dong, Kai; Liu, Yu; Liu, Jun; Jian, Tao; He, You

来源：IET Radar Sonar and Navigation, 2017, 11(2): 269-276.

DOI：10.1049/iet-rsn.2016.0139

• JOINT DATA ASSOCIATION
• SENSOR REGISTRATION
• FUSION
• PERFORMANCE

To address multi-sensor real-time track-to-track association problem of aircraft platforms in a complex environment, where sensor biases are time-varied, targets are distributed closely and different sensors report different targets, an anti-bias track-to-track association algorithm based on distance detection is proposed according to the statistical characteristics of Gaussian random vectors. First, a distance vector between homologous tracks is derived and its feature is analysed; second, the rough association based on minimum average and the refined association based X-2 distribution are illustrated according to the features of distance vectors. Adaptability experiments are established based on three factors including different target densities, random errors, and sensor biases. Monte Carlo simulations demonstrate the proposed algorithm has significant improvements of association accuracy and complex condition adaptability compared with the classical reference topology feature algorithm.

• 出版日期2017-2
• 单位北京航空航天大学; 中国人民解放军海军航空工程学院