分布式数据链的定周期自适应时间对准

分布式数据链航迹处理对时间对准提出了更高要求。为此，提出了一种定周期的自适应处理模型。通过建立数据校正模型，将多源数据统一到固定的时间点上，通过卡尔曼滤波算法将数据外推到相应时间点，并可有效根据其数据消息质量进行动态调整有效数据融合策略，从而为后续数据链航迹融合提供支持。通过仿真实验验证了算法的有效性和可行性，为后续数据链无中心数据处理提供了基础支撑。

Fixed period adaptive time-alignment for distributed datalink

Higher accuracy of time synchronization is required in the distributed datalink track processing. This paper introduces a fixed period adaptive algorithm model in which multiple source data is firstly adjusted to the uniform time line,and then extrapolated to the correlated time spot by Kalman filter algorithm. The data fusing policy can be dynamically adjusted according to the information so that it can effectively support the further datalink track processing. The efficiency and feasibility of the algorithm is simulated and it provides the basic guide for the datalink distributed track processing.