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首页> 外文期刊>The Journal of Navigation >Loosely Coupled INS/GPS Integration with Constant Lever Arm using Marginal Unscented Kalman Filter
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Loosely Coupled INS/GPS Integration with Constant Lever Arm using Marginal Unscented Kalman Filter

机译:使用边际无味卡尔曼滤波器将INS / GPS与恒定杠杆臂松散耦合

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摘要

A loosely coupled Inertial Navigation System (INS) and Global Positioning System (GPS) are studied, particularly considering the constant lever arm effect. A five-element vector, comprising a craft's horizontal velocities in the navigation frame and its position in the earth-centred and earth-fixed frame, is observed by GPS, and in the presence of lever arm effect, the nonlinear observation equation from the state vector to the observation vector is established and addressed by the correction stage of an unscented Kalman filter (UKF). The conditionally linear substructure in the nonlinear observation equation is exploited, and a computationally efficient refinement of the UKF called marginalized UKF (MUKF) is investigated to incorporate this substructure where fewer sigma points are needed, and the computational expense is cut down while the high accuracy and good applicability of the UKF are retained. A performance comparison between UKF and MUKF demonstrates that the MUKF can achieve, if not better, at least a comparable performance to the UKF, but at a lower computational expense.
机译:研究了一种松耦合的惯性导航系统(INS)和全球定位系统(GPS),特别是考虑到恒定的杠杆臂效应。用GPS观测五元素向量,该向量包含航行器中航行器的水平速度及其在以地为中心的固定框架中的位置,并在存在杠杆臂效应的情况下从状态观察非线性观测方程建立到观测向量的向量,并通过无味卡尔曼滤波器(UKF)的校正阶段进行寻址。利用非线性观测方程中的条件线性子结构,并研究了计算效率高的UKF的改进方法,称为边缘化UKF(MUKF),以将这种子结构合并到需要较少sigma点的子结构中,从而降低了计算量,同时提高了精度并且保留了UKF的良好适用性。 UKF和MUKF之间的性能比较表明,即使不是更好,MUKF至少可以达到与UKF相当的性能,但计算成本较低。

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