利用测距值优化的室内三维定位算法

doi:10.13190/j.jbupt.2017.03.004

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (3): 37-42.doi: 10.13190/j.jbupt.2017.03.004

利用测距值优化的室内三维定位算法

何杰¹, 吴得泱², 李希飞¹, 徐丽媛¹, 齐悦¹

1. 北京科技大学计算机与通信工程学院, 北京 100083;
2. 北京科技大学数理学院, 北京 100083

收稿日期:2016-08-31 出版日期:2017-06-28 发布日期:2017-05-25
作者简介:何杰(1983-),男,博士,副教授,E-mail:hejie@ustb.edu.cn.
基金资助:
国家自然科学基金项目（61671056）；北京市自然科学基金项目（4152036）；天津市科技重大专项与工程项目（16ZXCXSF00150）

A 3-D Indoor Localization AlgorithmUsing Distance Optimization

HE Jie¹, WU De-yang², LI Xi-fei¹, XU Li-yuan¹, QI Yue¹

1. School of Computer and Communication Engineering, University of Science and Technology, Beijing 100083, China;
2. School of Mathematics and Physics, University of Science and Technology, Beijing 100083, China

Received:2016-08-31 Online:2017-06-28 Published:2017-05-25

摘要/Abstract

摘要： 为了解决实际误差分布与假设误差分布不匹配导致最小二乘三维定位算法精度较低的问题，提出一种基于测距值优化的最小二乘室内三维定位算法.结合残差修正、Cayley-Menger行列式及空间四面体几何约束，利用非线性规划方法优化测距值，使测距误差符合高斯分布特性，从而提高最小二乘三维定位算法的定位精度.实验对比分析结果显示，所提算法具有较高的定位精度及稳定性.

关键词: 三维定位, 最小二乘算法, 测距值优化, 几何约束

Abstract: Least Square is a typical three-dimensional location algorithm for time of arrival based indoor positioning system. The precondition of traditional LS algorithm is that the measurement error meets the zero mean and the equal variance. However, the multipath and non-line of sight significant in realistic indoor environment leads TOA ranging error to be non-Gaussian distribution and cannot meet the hypothesis. This conflict leads low localization accuracy. This article presents a distance optimization based least square 3-D indoor localization algorithm. The nonlinear programming method with Cayley-Menger determinant and tetrahedral geometry constraints was adopted by the proposed algorithm to optimize measured distance, which makes the ranging error fit Gaussian distribution and thus improves the localization accuracy of least square. Experiments demonstrate that the proposed distance optimization based least square 3-D localization algorithm achieves better localization accuracy and stability.

Key words: 3-D localization, least square algorithm, distance optimization, geometric constraints

中图分类号:

TN911.22

何杰, 吴得泱, 李希飞, 徐丽媛, 齐悦. 利用测距值优化的室内三维定位算法[J]. 北京邮电大学学报, 2017, 40(3): 37-42.

HE Jie, WU De-yang, LI Xi-fei, XU Li-yuan, QI Yue. A 3-D Indoor Localization AlgorithmUsing Distance Optimization[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(3): 37-42.

参考文献

[1] Rantakokko J, Rydell J, Strömbäck P, et al. Accurate and reliable soldier and first responder indoor positioning:multisensor systems and cooperative localization[J]. IEEE Wireless Communications, 2011, 18(2):10-18.
[2] 王鹏, 张晓彤, 徐丽媛, 等. 基于自适应时延估计的室内近场测距算法[J]. 计算机学报,2016, 39(32):1-19. Wang Peng, Zhang Xiaotong, Xu Liyuan, et al. Indoor near field ranging algorithm based on adaptive time delay estimation[J]. Chinese Journal of Computers, 2016, 39(32):1-19.
[3] Gandhi S R, Ganz A, Mullett G. FIREGUIDE:firefighter guide and tracker[C]//EMBC 2010. Buenos Aires:IEEE, 2010:2037-2040.
[4] Ghidary S S, Nakata Y, Takamori T, et al. Localization and approaching to the human by mobile home robot[C]//RO-MAN 2000. Osaka:IEEE, 2000:63-68.
[5] Li Zeyuan. Constrained weighted least squares location algorithm using received signal strength measurements[J]. China Communications, 2016, 13(4):81-88.
[6] Akgul F O. Modeling the behavior of multipath components pertinent to indoor geolocation[M].[S.l.]:Worcester Polytechnic Institute, 2010.
[7] Bialer O, Raphaeli D, Weiss A J. Efficient time of arrival estimation algorithm achieving maximum likelihood performance in dense multipath[J]. IEEE Transactions on Signal Processing, 2012, 60(3):1241-1252.
[8] Erkmen B I, Moision B. Maximum likelihood time-of-arrival estimation of optical pulses via photon-counting photodetectors[C]//2009 IEEE International Symposium on Information Theory.[S.l.]:IEEE, 2009:1909-1913.
[9] Liang S C, Liao L H, Lee Y C. Localization algorithm based on improved weighted centroid in wireless sensor networks[J]. Journal of Networks, 2014, 9(1):183-189.
[10] Chu Y, Ganz A. A UWB-based 3D location system for indoor environments[C]//2^nd International Conference on Broadband Networks. Boston:IEEE, 2005:1147-1155.
[11] Cao Ming, Anderson B D O, Morse A S. Sensor network localization with imprecise distances[J]. Systems & control letters, 2006, 55(11):887-893.
[12] Crippen G M, Havel T F. Distance geometry and molecular conformation[M]. Taunton:Research Studies Press, 1988.
[13] 曾中君. 六正数构成四面体六棱长的充要条件. 数学教学通讯[J]:教师阅读, 2008(12):38-39. Zhongjun Zeng. A sufficient and necessary condition for six positive numbers to form six sides of a tetrahedron, mathematics teaching communication[J]. Teacher Reading, 2008(12):38-39.
[14] Chai T, Draxler R R. Root mean square error (RMSE) or mean absolute error (MAE)-arguments against avoiding RMSE in the literature[J]. Geoscientific Model Development, 2014, 7(3):1247-1250.

利用测距值优化的室内三维定位算法

A 3-D Indoor Localization AlgorithmUsing Distance Optimization

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 3

编辑推荐

Metrics

本文评价

[1]	胡中栋, 王俊岭, 王振东, 曾珽. 山区复杂地形的无线传感器网络节点定位算法[J]. 北京邮电大学学报, 2019, 42(5): 113-118.
[2]	任侃, 王伟杰, 钱惟贤, 汪鹏程, 陈钱. 移动相机下的地面运动目标分割技术[J]. 北京邮电大学学报, 2017, 40(1): 42-45.
[3]	杨卓，郭黎利，李万臣. UWB信道盲估计的频域递归最小二乘实现[J]. 北京邮电大学学报, 2011, 34(1): 121-125.