基于信息融合的机动多目标单站无源跟踪关键技术研究

Key Techniques of Passive Tracking of Multiple Maneuvering Targets by Single Observer Based on Information Fusion

跟踪起始与数据关联是机动多目标单站无源跟踪的关键技术。提出了一种基于目标多特征信息融合的自适应跟踪起始算法,通过构造多维动态可变的跟踪门,进行自适应跟踪起始检测,然后根据序列概率比检验准则进行轨迹确认。同时提出了一种基于多目标多特征信息融合的数据关联算法,首先通过定义多个特征数据关联度,将单个有效观测的多特征信息进行融合,再对多目标进行综合数据关联。计算机仿真表明,该跟踪起始算法能够快速有效地进行航迹起始,数据关联算法的性能要优于传统的最近邻(NN)方法。

Tracking initiation and data association are key techniques of multi-target passive tracking by single observer. A new adaptive passive tracking initiation algorithm based on information fusion was proposed. First, according to multiple features of the target, multidimensional dynamically variable tracking gate was built for adaptive detection. Further, the Sequential Probability Ratio Test （SPRT） rule was used to confirm the track. And also a new data association algorithm based on information fusion was proposed. Based on the information fusion of multiple features of a single valid observation, the decision of synthetic data association of all the targets was made. With the help of computer simulations, the tracking initiation algorithm is proven to be correct and effective, and the data association algorithm is proven to be superior to the NN method.