车载激光多普勒测速仪的卡尔曼滤波算法研究

发布时间：2018-01-25 03:29

本文关键词： 激光光学车载测速仪卡尔曼滤波多普勒　出处：《中国激光》2014年11期 　论文类型：期刊论文

【摘要】：为了减小随机误差和野值对车载激光多普勒测速仪测速精度的影响,提出了一种自适应卡尔曼滤波算法。以"当前"统计模型为基础,结合车载测速仪实际特点建立了系统的状态空间模型,并利用速度观测值与预测值之间的偏差进行加速度方差自适应调整,同时根据卡尔曼滤波算法中新息的正交特性和速度估计误差,给出了能够剔除野值并实时反映路面特征的观测噪声方差自适应算法。仿真结果表明该算法的滤波收敛速度和估计精度都明显优于"当前"统计模型算法,实验结果证明该算法能够显著提高测速仪的测速精度与稳健性。
[Abstract]:In order to reduce the influence of random errors and outliers on the accuracy of vehicle laser Doppler velocimetry, an adaptive Kalman filter algorithm is proposed, which is based on the "current" statistical model. Combined with the actual characteristics of the vehicle velocimeter, the state space model of the system is established, and the acceleration variance is adjusted adaptively by the deviation between the velocity observation value and the predicted value. At the same time, according to the orthogonal characteristic of innovation and the error of velocity estimation in Kalman filter algorithm. An adaptive algorithm of observation noise variance which can eliminate outliers and reflect pavement characteristics in real time is presented. The simulation results show that the filter convergence speed and estimation accuracy of the algorithm are obviously better than the current statistical model algorithm. Experimental results show that the algorithm can significantly improve the accuracy and robustness of the velocimeter.
【作者单位】：北京航空航天大学仪器科学与光电工程学院;
【基金】：国家自然科学基金(61101007)
【分类号】：TN96.2;TN249
【正文快照】： 1引言激光多普勒测速仪(LDV)利用多普勒效应直接测量载体的地速和航偏角,具有完全自主、反应快、抗干扰性能好、测速精度高等优点,已成为组合导航中重要的速度传感器[1-3]。然而未经滤波的LDV测速数据往往包含较大的随机误差和野值,这不仅会降低组合导航系统的定位精度,而且还

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