杂波环境下基于距离航速航向信息的多目标跟踪

针对杂波环境下的多目标数据互联问题，提出了基于距离、航速和航向信息的多目标数据互联算法。该算法首先以不同目标状态更新向量中的位置元素为中心，基于距离门限对测量数据进行选择，然后在此基础上利用目标航速和航向信息对选择的测量数据做进一步判断，具体方法是由当前时刻目标测量数据和前一时刻目标的状态来估计相应目标的航速和航向，并通过设定的航速和航向门限对保留的测量数据进行选择，实现复杂环境下的多目标数据的有效关联；然后计算有效回波是正确量测的概率，并以这些概率值作为权值对目标状态进行加权融合，实现杂波环境下多目标的可靠跟踪;最后通过仿真实验对算法的有效性和可行性进行了验证。

Multiple target tracking in clutter based on distance speed and course

A multiple target tracking algorithm in clutter is studied, and a new method is adopted to solve the data association problem based on distance, speed and course. Firstly, the position element of the state update estimates is used as the center to conduct the distance statistical test, which is used to select the measurements of the targets. Then the selected data are needed to make further judgement through speed and course. The steps are as follow: The current measurements and the state update estimate a moment ago are used to estimate the speed and course of the target, which are compared with the speed and course threshold respectively. And those measurements which fall in to the two thresholds are preserved. The probabilities of the retained data are calculated, and which are used as weights to obtain the weighted fusion state. The simulation results reveal the feasibility and validity of the proposed algorithm.