论文部分内容阅读
弹道导弹主动段拦截中对导弹跟踪精度要求很高,如何将多种主动段探测装备得到的数据进行融合得到更加精确的数据是当前亟待解决的难题。针对此问题,文中研究了导弹预警卫星与雷达融合跟踪,提出了一种基于Bayes理论的弹道导弹主动段融合跟踪算法。该算法分别建立了导弹预警卫星和雷达对主动段探测模型和跟踪模型,应用POFACETS软件仿真了一种类型弹道导弹,并将其获得的导弹RCS数据应用到算法中,提高了算法的准确性。仿真实验表明,该融合跟踪算法可以获得比多个传感器算术平均值更精确的结果,具有较高的可靠性。
In the active segment interception of the ballistic missile, the tracking accuracy of the missile is very high. How to integrate the data obtained from a variety of active segment detection equipment to obtain more accurate data is a difficult problem to be solved urgently. In order to solve this problem, this paper studies the fusion tracking of missile early warning satellites and radar and proposes a Bayes theory based active tracking fusion algorithm for ballistic missile. The algorithm establishes the detection model and the tracking model of the missile pre-warning satellites and the radar to the active segment respectively. The application of the POFACETS software simulates a type of ballistic missile and applies the obtained missile RCS data to the algorithm, thereby improving the accuracy of the algorithm. Simulation results show that the fusion tracking algorithm can obtain more accurate results than the arithmetic average of multiple sensors and has high reliability.