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首页> 外文期刊>The Journal of Navigation >Adaptive Two-stage Kalman Filter for SINS/Odometer Integrated Navigation Systems
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Adaptive Two-stage Kalman Filter for SINS/Odometer Integrated Navigation Systems

机译：用于SINS /里程表组合导航系统的自适应两级卡尔曼滤波器

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摘要

In Strapdown Inertial Navigation System (SINS)/Odometer (OD) integrated navigation systems, OD scale factor errors change with roadways and vehicle loads. In addition, the random noises of gyros and accelerometers tend to vary with time. These factors may cause the Kalman filter to be degraded or even diverge. To address this problem and reduce the computation load, an Adaptive Two-stage Kalman Filter (ATKF) for SINS/OD integrated navigation systems is proposed. In the Two-stage Kalman Filter (TKF), only the innovation in the bias estimator is a white noise sequence with zero-mean while the innovation in the bias-free estimator is not zero-mean. Based on this fact, a novel algorithm for computing adaptive factors is presented. The proposed ATKF is evaluated in a SINS/OD integrated navigation system, and the simulation results show that it is effective in estimating the change of the OD scale factor error and robust to the varying process noises. A real experiment is carried out to further validate the performance of the proposed algorithm.
机译：在捷联惯性导航系统（SINS）/里程表（OD）集成导航系统中，OD比例因子误差随道路和车辆负载而变化。另外，陀螺仪和加速度计的随机噪声倾向于随时间变化。这些因素可能导致卡尔曼滤波器降级甚至发散。为了解决这个问题并减少计算量，提出了一种用于SINS / OD组合导航系统的自适应两级卡尔曼滤波器（ATKF）。在两级卡尔曼滤波器（TKF）中，只有偏差估计器的创新是零均值的白噪声序列，而无偏差估计器的创新却不是零均值。基于这一事实，提出了一种新的自适应因子计算算法。在SINS / OD组合导航系统中对拟议的ATKF进行了评估，仿真结果表明，该方法可有效地估计OD比例因子误差的变化，并且对变化的过程噪声具有鲁棒性。进行了实际实验以进一步验证所提出算法的性能。

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