摘要
针对粒子滤波算法在室内地磁分布的连续性变化中会发生滤波发散,加之算法中重采样步骤使该现象恶化,直接导致室内定位过程中目标丢失的问题。该文受Hausdorff距离度量法中点集匹配思想的启发,提出了一种利用初定位误差作为最大粒子匹配距离的约束思想,通过缩小匹配空间的区域范围的方法来解决传统算法的发散问题。最后实验表明,此方法解决了粒子滤波器在地磁匹配中出现的滤波发散现象,同时使得定位结果更加快速收敛。
According to the problem of particle filter algorithm has the phenomenon of filtering divergence in the continuous variation of the indoor magnetic distribution,and the resampling step of implementation makes the phenomenon worse,which directly lead to the loss of indoor positioning solution.Based on the idea of Hausdorff distance metric method,this paper propose a method of using the initial positioning error as the constraint of the maximum particle matching distance,and solve the divergence problem of the traditional algorithm by narrowing the region of the matching space.Finally,the experimental results show that this method solves the filtering divergence phenomenon of the particle filter in the geomagnetic matching,and makes the positioning result more rapid convergence.
作者
李维
黄鹤
罗德安
LI Wei;HUANG He;LUO Dean(School of Geomatics and Urban Spatial Information,Beijing University of Civil Engineering and Architecture,Beijing 102616,China;Beijing Advanced Innovation Center for Future Urban Design,Beijing 100044,China)
出处
《测绘科学》
CSCD
北大核心
2018年第7期109-114,120,共7页
Science of Surveying and Mapping
基金
国家重点研发计划项目(2017YFB0503702)
现代城市测绘国家地理信息局重点实验室开放基金项目(20131201NZ)
关键词
室内定位
粒子滤波
定位误差
HAUSDORFF距离
地磁匹配
定位误差约束
indoor positioning
particle filter
positioning error
Hausdorff metric distance
geomagnetic matching
positioning error constraints
