Data Mining-Based Tracking Method for Multisource Target Data of Heterogeneous Networks

In order to solve the problem that target is easily lost in process of multisource data fusion tracking, a tracking method based on mining proposed. Multisource belongs location level fusion. Firstly, hybrid heterogeneous network model established, and then, features are extracted, source big acquisition algorithm designed compressed sensing complete preprocessing reduce amount acquisition. Based association target, get relationship between each measurement build ensure stable state results. It shows proposed can save time improve accuracy compared with methods NNDA PDA, which more conducive real-time targets.