基于滑动窗口的新息自适应组合导航算法

针对新息自适应滤波算法噪声跟踪精度和跟踪灵敏度相互矛盾导致的窗口宽度选取困难问题,提出了一种基于滑动窗口的新息自适应组合导航算法,该方法通过设计噪声统计特性梯度检测函数、敏感噪声统计特性的实际变化情况,利用窗口自适应函数实时计算窗口宽度,使得窗口在预设区间内自适应滑动,以适应实际噪声的变化。仿真实验表明,基于滑动窗口的新息自适应组合导航算法可以有效跟踪噪声统计特性的实时变化,可同时兼顾自适应跟踪精度和跟踪灵敏度。

Innovation-based adaptive Kalman filter with sliding window for integrated navigation

Considering that it is difficult to select window width of the innovation-based adaptive Kalman filter for the reason that tracking accuracy and tracking sensitivity of noise are contradictory to each other, an innovation-based adaptive Kalman filter with sliding window for integrated navigation is proposed. This method designs the gradient detection function of noise statistical characteristic to sense real-time variation of noise statistical characteristics. The window width obtained in real time by using window adaptation function makes the window slide in the preset range to adapt to the actual noise. Simulation results show that the innovation-based adaptive Kalman filter with sliding window for integrated navigation can track real-time variation of noise statistical characteristics effectively, and adaptive tracking accuracy and tracking sensitivity is considered simultaneously.