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首页> 外文会议>2011 IEEE International Conference on Information and Automation >A useful Doppler radar outlier elimination algorithm based on orthogonality of innovation
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A useful Doppler radar outlier elimination algorithm based on orthogonality of innovation

机译：一种基于创新正交性的有用多普勒雷达离群值消除算法

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摘要

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中存在离群值的问题，直升机的多普勒雷达/光纤陀螺捷联惯性导航系统（FOG-SINS）/气压计集成导航系统（DFBINS）的精度和稳定性会受到严重影响。连续出现离群值，本文提出了一种基于创新正交性的有效消除这些离群值的方法。通过判断卡尔曼滤波器的创新正交性是否丢失，可以检测多普勒雷达中的离群值，并为每个观测要素分配权重因子作为激活函数，从而可以保持卡尔曼滤波器的创新序列正交和离群值可以被检测和纠正。远距离直线飞行试验数字仿真的优异结果表明，改进的方法有效地抵抗了多普勒雷达离群值对DFBINS精度和稳定性的不利影响，该算法在实践中具有较高的应用价值。

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