自适应GPS/INS组合导航系统研究

Wang Bin, Wang Jian, Wu Jianping, Cai Baigen
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引用次数: 21

摘要

提出了一种基于多传感器数据融合理论的GPS/INS组合导航系统。建立了惯性测量单元的误差模型,并将其纳入惯性惯性系统的扩展卡尔曼滤波中。为了消除GPS数据的明显误差,减少计算量,提出了一种改进的分散卡尔曼滤波方法。采用自适应联邦卡尔曼滤波器对GPS和INS数据进行融合,以提供平滑连续的定位数据,避免GPS阻塞或通信中断以及随时间增长的无界INS误差。结果表明,自适应GPS/INS组合导航系统的性能优于仅使用GPS/INS的组合导航系统。
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Study on adaptive GPS/INS integrated navigation system
A GPS/INS integrated navigation system based on the theory of multi-sensor data fusion is presented in this paper. Error models for the inertial measurement unit are generated and included in the extended Kalman filter for INS. An improved decentralized Kalman filter is developed to eliminate obvious error of GPS data and reduce the load of calculation. An adaptive federal Kalman filter is used to fuse the data from GPS and INS to provide smoothed and continuous positioning data against the presence of GPS blockages or communication dropouts and the unbounded INS errors growing with time. The results demonstrate that the performance of the adaptive GPS/INS integrated navigation system is better than that of using only GPS of INS.
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