测绘通报 ›› 2018, Vol. 0 ›› Issue (12): 52-58.doi: 10.13474/j.cnki.11-2246.2018.0383

• 学术研究 • 上一篇    下一篇

ADAS导航地图多源数据高程异常修正算法研究

黄鹤1,2, 陈志锋1, 衣鹏军1   

  1. 1. 北京建筑大学测绘与城市空间信息学院, 北京 102616;
    2. 未来城市设计北京市高精尖创新中心, 北京 102616
  • 收稿日期:2018-05-07 出版日期:2018-12-25 发布日期:2019-01-03
  • 作者简介:黄鹤(1977-),男,博士,副教授,主要研究方向为大地测量。E-mail:huanghe@bucea.edu.cn
  • 基金资助:
    国家重点研发计划(2017YFB0503702)

Study on Multi-source Data Height Anomaly Correction Algorithm in ADAS Navigation Map

HUANG He1,2, CHEN Zhifeng1, YI Pengjun1   

  1. 1. School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China;
    2. Beijing Advanced Innovation Center for Future Urban Design, Beijing 102616, China
  • Received:2018-05-07 Online:2018-12-25 Published:2019-01-03

摘要: 因ADAS导航地图多采用多源数据融合及ADAS导航地图数据采集方式等因素造成ADAS数据中高程出现不符合实际的异常,不同时期采集的数据因为采集过程中系统误差的改变(采集方式、采集环境、人员)导致了目前ADAS导航地图数据中普遍存在LINK层面高程不连续的问题。限于篇幅限制,本文只讨论了控制层处理问题,提出建立在整体水准网平差思想上的ADAS高程异常附带约束修正算法。试验证明,该方法可以实现对整个ADAS数据高程不连续和高程异常问题的处理,具有整体符合性好(与实际情况高度符合)、对原数据高程改动幅度小(在达到高程异常修正目标的同时尽量保护实采数据)、整体合理(全部LINK结点均不存在异常)的优点。

关键词: ADAS, 高程异常, 最小独立闭合环, 整体最优估计, 数据重建

Abstract: In ADAS navigation maps, multi-source data fusion and ADAS navigation map data collection methods often cause elevations in the ADAS data that do not conform to actual anomalies. The data collected in different periods are different because of various systematic errors in the collection process (collection mode, collection environment, and personnel). This has led to the problem of the discontinuity of LINK level elevation that is currently prevalent in ADAS navigation map data. Due to space limitations, this article only discusses control layer processing issues. The ADAS elevation anomaly constraint correction algorithm based on the idea of global level network adjustment is proposed. Experiments show that this method can realize the processing of elevation discontinuity and elevation abnormality of the whole ADAS data. It has the advantages of good overall conformance, small change of original data elevation, and reasonable overall (all LINK nodes are not abnormal).

Key words: ADAS, abnormal elevation, minimum independent closed loop, overall best estimate, data reconstruction

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