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Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system

机译:用于集成GPS / SINS导航系统的基于奇异值分解的鲁棒库曼滤波

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摘要

A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) navigation system. The influence of different design parameters for an H∞ cubature Kalman filter is analysed. It is found that when the design parameter is small, the robustness of the filter is stronger. However, the design parameter is easily out of step in the Riccati equation and the filter easily diverges. In this respect, a singular value decomposition algorithm is employed to replace the Cholesky decomposition in the robust cubature Kalman filter. With large conditions for the design parameter, the new filter is more robust. The test results demonstrate that the proposed filter algorithm is more reliable and effective in dealing with the outliers in the data sets produced by the integrated GPS/SINS system.
机译:本文提出了一种新的非线性鲁棒滤波器,以解决集成的全球定位系统/捷联惯性导航系统(GPS / SINS)导航系统的异常情况。分析了不同设计参数对H∞库尔曼卡尔曼滤波器的影响。发现当设计参数小时,滤波器的鲁棒性更强。但是,设计参数在Riccati方程中很容易失调,并且滤波器容易发散。在这方面,采用奇异值分解算法来代替鲁棒的库尔曼卡尔曼滤波器中的Cholesky分解。在较大的设计参数条件下,新的滤波器更加坚固。测试结果表明,所提出的滤波算法在处理由GPS / SINS集成系统产生的数据集中的异常值时,更加可靠有效。

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