基于Kalman滤波的分段积分闭环回溯快速粗对准方法

快速启动能力是惯导系统的重要性能指标。为应对车辆与武器系统等在短时间内完成初始对准的需求，在基于Kalman滤波的闭环粗对准基础上提出了一种闭环回溯粗对准方法，并设计了一种分段积分矢量构建方法，使得算法能够在多次回溯的过程中构建更多不共线矢量，进一步减少粗对准所需的数据量并提升对准精度。经三轴转台及车载惯导30 s和50 s对准实验验证，本算法在短时间内的对准精度优于优化对准方法和基于Kalman滤波的闭环粗对准方法，能够满足载体进行快速初始对准的需求。

Kalman-filtering-based piecewise-integration closed-loop backtracking fast coarse alignment

Rapid start-up capability is an important indicator for inertial navigation systems. In order to meet the requirement of rapid initial alignment for vehicles and weapon systems, a closed-loop backtracking coarse alignment method is proposed based on Kalman-filtering-based coarse alignment, and a pricewise integration vector construction method is designed, which can construct more non-collinear vectors during multiple backtracking processes, further reducing the amount of data required for coarse alignment and improving accuracy. Through experiments of 30 s and 50 s coarse alignment on a three-axis turntable and a vehicle, the accuracy of this algorithm is better than that of optimization-based alignment and Kalman-filtering-based coarse alignment in a short period of time, which can meet the requirement of rapid initial alignment.