Increasing FastSLAM accuracy for radar data by integrating the Doppler information
Increasing FastSLAM accuracy for radar data by integrating the Doppler information
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通过集成多普勒信息提高雷达数据的 FastSLAM 精度
DOI：
10.1109/icmim.2017.7918867
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
J. Dickmann
中科院分区：
文献类型：
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作者：
Stefanie Lupfer;M. Rapp;K. Dietmayer;Peter Broßeit;Jakob Lombacher;Markus Hahn;J. Dickmann
本文针对雷达传感器的具体应用，提出了一种改进的FastSLAM方法，利用多普勒信息来提高定位和地图精度。该方法基于FastSLAM 2.0算法。它显示了FastSLAM 2.0方法如何通过考虑多普勒信息来显着改进。因此，对每次探测的模拟，即所谓的期望多普勒和实测多普勒进行比较。在真实世界数据上的模拟和实验都表明，通过结合汽车雷达传感器的多普勒测量，改进的FastSLAM方法的精度有所提高。提出的算法与最先进的FastSLAM 2.0算法和车辆里程计进行了比较，而汽车动态运动分析仪的配置文件作为参考。
This paper presents a modified FastSLAM approach for the specific application of radar sensors using the Doppler information to increase the localization and map accuracy. The developed approach is based on the FastSLAM 2.0 algorithm. It is shown how the FastSLAM 2.0 approach can be significantly improved by taking the Doppler information into account. Therefore, the modelled, so-called expected Doppler, and the measured Doppler are compared for every detection. Both, simulations and experiments on real world data show the increase in accuracy of the modified FastSLAM approach by incorporating the Doppler measurements of automotive radar sensors. The proposed algorithm is compared to the state-of-the-art FastSLAM 2.0 algorithm and the vehicle odometry, whereas profiles of an Automotive Dynamic Motion Analyzer serve as the reference.