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A useful Doppler radar outlier elimination algorithm based on orthogonality of innovation

机译:基于创新正交性的有用多普勒雷达异常消除算法

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In order to solve the problem that the precision and stability of Doppler radar/Fiber Optical Gyroscope Strapdown Inertial Naivgation System (FOG-SINS)/Barometer Integrated Navigation System (DFBINS) for helicopters will be highly affected if there are outliers in doppler radar, especially consecutive outliers appear, a useful method to eliminate these outliers based on orthogonality of innovation is proposed in this paper. Outliers in Doppler radar can be detected by judging whether the orthogonality of innovation in Kalman filter is lost or not, and an activation function as the weight factor to each element of observation is assigned, so it can keep innovation sequence of kalman filter orthogonal and outliers can be detected and corrected. The excellent results of digital simulation for a long distance straight line flying test show that the modified method is effectively resistant to the adverse effects on accuracy and stability of DFBINS caused by outliers in Doppler radar, the proposed algorithm is of high value in practice.
机译:为了解决多普勒雷达/光纤陀螺仪表层惯性Naivgation系统(FOG-SINS)/气流计综合导航系统(DFBINS)的精度和稳定性,如果多普勒雷达有异常值,则会受到高度影响在本文中提出了一种基于创新正交性消除这些异常值的有用方法。通过判断Kalman滤波器的创新正交性丢失或不判断创新的正交性,以及作为每个观察元素的重量因子的激活函数来检测到多普勒雷达中的异常值,因此它可以保持卡尔曼滤波器正交和异常值的创新序列可以检测和纠正。用于长距离直线飞行试验的数字仿真的优异结果表明,改性方法有效地抵抗多普勒雷达中异常值引起的对达比斯引起的达比克的准确性和稳定性的不利影响,所提出的算法在实践中具有高价值。

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