多尺度小波变换提取趋向的异步航迹关联方法

传统的航迹关联方法都是基于雷达同步工作方式,但在实际的空中监视系统中,不同位置的雷达不可能同步工作。因此异步雷达目标航迹的关联更接近于实际。目标航迹数据序列实际上是一个含有多项式趋势的非平稳随机过程,利用小波变换提取这种趋势,比较两条航迹趋势的接近程度,进行异步航迹关联。理论分析和仿真实验表明,这种方法的关联正确率高,同步和异步方式下均可应用。

Asynchronous Tracks Association Based on Tendency with Wavelet Transform

Traditional tracks association algorithms all are depend on the synchronous mode of radar working, but the radars in the air surveillance system at the different positions are impossible to start work at the same time. So the asynchronous tracks association is more approach to practical situation. The target track can be decoupled to two nonstationary random sequences that contains polynomial tendency on the X and Y directions. Using the wavelet transform to extract the tendencies from those nonstationary sequences and then to compare them. According to the degree of approach each other to decide if they come from the same target and then to associate them.