航空遥感中基于高阶INS误差模型的GPS/INS组合定位定向方法

The GPS/INS Integrated Positioning and Orientation in the Aerial Remote Sensing Based on the High-order INS Stochastic Error Model

基于随机常数、随机游走和一阶马尔可夫过程组合的高阶IMU误差模型,建立36阶卡尔曼滤波器。通过松散组合模式,最终实现位置标准差±5cm、俯仰/横滚角标准差±0.002°、航向角标准差±0.008°的定位定向精度。

Despite significant progress in GSP/INS-based direct georeferencing technology in the last decade, there is still room for improvement in terms of better accuracy. The main objective of this paper is the stochostic modeling of Inertial Measurement Unit （IMU） errors, which determines significantly the final performance of the GPS/INS integrated system. With the random constants, random walks and first-order Markov process models to characterize the stochastic errors oflMU, one Kalman Filter with 36 orders was meticulously established. The practical data was processed with the filter in the experiment and the accuracy in term of standard deviations of 5 cm in position, 0.002% in attitude and 0.008% in heading were achieved respectively.