基于两级扩展Kalman滤波的海上多平台误差配准算法

为了建立统一态势图，利用平台的低精度导航信息和相互测量的位置信息来进行海上多平台传感器数据位置对准，避免了对高精度导航设备的依赖以及将地表近似为平面所带来的误差。分析数据位置对准过程中的主要误差来源，给出对准的坐标变换模型，分别构建关于导航系统误差和传感器系统误差的测量方程和状态方程，设计两级扩展Kalman滤波配准算法对两种系统误差进行在线估计和补偿，完成海上多平台的误差配准，为后续数据关联和融合提供更高精度的传感器数据。仿真实验结果验证了算法的正确性和有效性。

Error registration algorithm for maritime multi-platforms based on two-stage extended Kalman filtering

To establish the uniform situation map, the platforms’ low precision navigation information and the location information measured mutually are used to carry out the sensor data alignment for martime multi platforms. This method can avoid the dependences on high precision navigation equipment and the errors introduced by assuming the earth’s surface to be the plane. The error sources in data alignment are analyzed, and the models of coordinate conversion for aligning are presented. Then the measure equations and the state equations with regard to navigation systematic error and sensor systematic error are built respectively, and a registration algorithm based on two stage extended Kalman filtering is designed for estimating online and compensating those two systematic errors. Consequently, the error registration for martime multi platforms is achieved, and the higher precision sensor data can be provided for the subsequent data association and data fusion. Simulation results demonstrate the correctness and validity of the algorithm.