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基于形态学滤波的惯导里程定位方法研究 被引量:2

Research oninertial navigation range location method based on morphological filtering
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摘要 针对于捷联惯导系统(SINS)测量过程中异常数据对测试精度影响的问题,文中提出了一种基于形态学滤波的高精度惯导里程定位方法。系统利用所提出的三角形形态学滤波的方法对惯性测量单元(IMU)的测量数据进行修正,减少测量数据中的异常值,利用基于里程计校准的惯导定位方法对经过形态学滤波预处理的数据进行计算,实现对被测管道路径的精确定位。为了了解经三角形形态学滤波后的惯性导航定位效果,对104 m的管道进行了模拟对比试验。由试验结果分析表明,经三角形形态学滤波预处理后,系统水平方向的测量精度由原来的0.58%提高到0.29%,增长了1倍;高度方向的测量精度由原来的0.096%提高到0.077%,提高了24.6%,取得了良好的效果。 For reducing the influence of abnormal data on the test accuracy during the SINS measurement process,this paper proposes a high-precision inertial navigation method based on morphological filtering.The system firstly adopts the proposed triangular morphology filtering method to modify the measurement data of the inertial measurement unit(IMU)to reduce the abnormal value.And then,the astigmatism calibration method based on the odometer calibration is used to calculate the data preprocessed by morphological filtering to realize accurate positioning of the pipeline path under test.In order to verify the effect of the proposed method,a simulation comparison test was carried out on 104 m pipeline.The analysis of the test results shows that the measurement accuracy of the horizontal direction of the system is increased from 0.58%to 0.29%,which is doubled by the morphological filtering of the triangle.And the accuracy in the height direction is increased from 0.096%to 0.077%,which achieves an increase of 24.6%.
作者 张乔林 崔昊杨 宋辰羊 王超迪 Zhang Qiaolin;Cui Haoyang;Song Chenyang;Wang Chaodi(School of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 200090,China;State Grid Shanghai Electric Power Corporation Economic and Technological Research Institute,Shanghai 200001,China;East China Power Transmission and Transformation Engineering Co.,Ltd.,Shanghai 201803,China)
出处 《电测与仪表》 北大核心 2021年第4期78-83,共6页 Electrical Measurement & Instrumentation
基金 国家自然科学基金资助项目(61107081) 上海市地方能力建设项目(15110500900)。
关键词 路径定位 捷联惯导 里程计 形态学滤波 自适应Kalman滤波 cable path location Strapdown inertial navigation odometer morphological filtering adaptive kalman filter
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