基于混合特征匹配的微惯性/激光雷达组合导航方法

doi:10.7527/S1000-6893.2014.0013

Abstract

Abstract:

Usually, there are observation blind areas existing in that the distribution of land marks like angular point and line segment is parse in indoor environment. Then the locating accuracy of vehicle and the estimating precision of land marks is affected by the lack of observed quantities when using the traditional single feature matching algorithm. To solve these problems, the adaptive segmentation method of LADAR is studied, and the extraction algorithm of different types of land marks is researched, then the extended Kalman filter is presented based on the mixed feature matching observation model. At the same time, a test prototype of MEMS IMU/LADAR integrated navigation system is designed. To validate the filtering fusion algorithm, the analysis and tests are carried out in the indoor environment. The test results show that the accuracy of proposed algorithm relative to the traditional algorithm(a single point or line feature match integrated location algorithm) in the structured indoor environment increass about 60%. This indicates that the algorithm is efficient when used to improve accuracy of the MEMS IMU/LADAR integrated navigation system.

Key words: MEMS inertial measurement unit, laser radar, mix feature matched algorithm, extended Kalman filter, simultaneous localization and mapping

CLC Number:

V249.32⁺8

HANG Yijun, LIU Jianye, LI Rongbing, SUN Yongrong. MEMS IMU/LADAR Integrated Navigation Method Based on Mixed Feature Match[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(9): 2583-2592.

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MEMS IMU/LADAR Integrated Navigation Method Based on Mixed Feature Match

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