惯性/卫星组合导航数据后处理算法研究

Research on High-Precision INS/GPS Integrated Navigation Offline Data-processing Algorithm

针对航空测绘、SAR雷达成像等场合,传统的实时卡尔曼滤波组合导航精度无法满足工程需求的问题。提出了双向滤波和RTS固定区间平滑算法,用集中式卡尔曼滤波器实现了惯性/卫星实时组合导航系统,设计了组合导航数据后处理算法,分别用双向滤波算法和RTS算法对导航参数进行了平滑处理。用模拟轨迹数据对算法进行验证,仿真结果表明,双向滤波和RTS平滑算法的解算精度相比常规卡尔曼实时滤波有明显提高,尤其是在卫星信号失锁情况下可以显著改善导航效果。

On the occasions such as aerial photogrammetry and SAR imaging, traditional Kalman fiber fails to a- chieve desired precision in engineering. TFS and RTS fixed-interval smoothing algorithm has been investigated. While traditional Kalman filter system based on INS/GPS was employed to give real-time integration results, TFS and RTS smoothing was utilized as the post-processing methodology for better navigation solutions. The results of evaluation show that TFS and RTS substantially improved the position and velocity estimation accuracy compared wirh traditional Kalman filter.