马尔可夫蒙特卡罗的室内定位算法

doi:10.3969/j.issn.1001-2400.2016.02.025

Abstract

Abstract:

The interference in the received power leads to the problem of the low estimation accuracy of WLAN indoor positioning, so a new method is proposed which constructs the maximum likelihood model and uses the Markov Chain Monte-Carlo sampling method to estimate position coordinates. The method considers taking the interference factor into the model, and uses the random sampling method to solve the estimation problem, which has the advantage of fast convergence and high estimate precision. Furthermore, the Cramer-Rao lower bound (CRLB) of the model is derived. In simulation experiment, the distribution of Cramer-Rao Bound in locating space is given. Finally, simulations show that the MCMC method can estimate the target location accurately. Under the same simulation conditions, the MCMC method achieves greater estimated precision and has a lower computational complexity than the Fletcher-Reeves Method (FR).

Key words: WLAN indoor positioning, likelihood model, Monte-Carlo, Cramer-Rao lower bound

CLC Number:

TN911.72

WANG Yue;BA Bin;CUI Weijia;LU Zhiyu. Indoor positioning algorithm based on Markov Monte Carlo[J].Journal of Xidian University, 2016, 43(2): 145-149.

References

［1］ WANG K. Location-based Services Deployment and Demand: a Roadmap Model［J］. Electronic Commerce Research, 2011, 11(1): 5-29.
［2］苏军峰. 室内无线定位参数估计算法研究［D］. 北京：北京交通大学, 2013.
［3］ WANG T. Novel Sensor Location Scheme Using Time-of-arrival Estimates ［J］. IET Signal Processing, 2012, 6(1): 8-13.
［4］ PARK K H. A Cooperative Clustering Protocol for Energy Saving of Mobile Devices with WLAN and Bluetooth Interfaces［J］. IEEE Transactions on Mobile Computing, 2011, 10(4): 491-504.
［5］王赛伟, 徐玉滨, 邓志安, 等. 基于概率分布的室内定位算法研究［J］. 计算机科学，2009, 36(4A): 45-47.
WANG Saiwei, XU Yubin, DENG Zhian, et al. An Indoor Positioning Algorithm Research Based on Probability Distribution［J］. Computer Science, 2009, 36(4A): 45-47.
［6］ FANG S H, LIN T. Principal Component Localizationin Indoor WLAN Environments［J］. IEEE Transactions on Mobile Computing, 2012, 11(1):100-110.
［7］徐凤燕, 单杭冠, 王宗欣. 一种带参数估计的基于接收信号强度的室内定位算法［J］. 微波学报, 2008(2): 67-72.
XU Fengyan, SHAN Hangguan, WANG Zongxin. An Indoor Location Algorithm Based on Received Signal Strength with Parameter Estimation［J］. Journal of Microwaves, 2008(2): 67-72.
［8］余俊. 基于RSSI的室内无线定位算法研究［D］. 武汉：华中科技大学, 2013.
［9］ NG W, REILLY J P, KIRUBARAJAN T, et al. Wideband Array Signal Processing Using MCMC Methods［J］. IEEE Transactions on Signal Processig, 2005, 53(2): 411-426.
［10］罗亮, 冯象初, 霍雷刚, 等. 非局部MCMC采样和低秩逼近的图像去噪算法［J］. 西安电子科技大学学报, 2013, 40(6): 140-146.
LUO Liang, FENG Xiangchu, HUO Leigang, et al. Image Denoising Method Based on Non-local Markov-chain Monte Carlo Sampling and Low Rank Approximation［J］. Journal of Xidian University, 2013, 40(6): 140-146.
［11］ MASMOUDI A, BELLILI F, AFFES S, et al. A Maximum Likelihood Time Delay Estimator in a Multipath Environment Using Importance Sampling［J］. IEEE Transactions on Signal Processing, 2013, 61(1): 182-193.

[1]	DENG Bing;SUN Zhengbo;YANG Le. Efficient closed-form estimator for TDOA-FDOA-AOA localization [J]. Journal of Xidian University, 2018, 45(2): 171-175+180.
[2]	DENG Bing;SUN Zhengbo;YANG Le;HE Qing. TDOA localization with linear-correction in the presence of sensor position errors [J]. Journal of Xidian University, 2017, 44(4): 106-111.
[3]	LU Hang;CUI Weijia;BA Bin;LU Zhiyu. Visible light localization algorithm based on multi-measurements constraints [J]. Journal of Xidian University, 2017, 44(4): 156-161.
[4]	ZHOU Cheng;HUANG Gaoming;GAO Jun. Optimum sensor array for passive localization from time differences of arrival [J]. Journal of Xidian University, 2016, 43(4): 123-127.
[5]	WANG Nan;MA Juan;ZHANG Yulin. Random computational homogenization for three-dimensional linear elasticity [J]. Journal of Xidian University, 2016, 43(4): 92-99.
[6]	ZHU Guohui;FENG Dazheng;ZHOU Yan. TDOA location algorithm based on multi-reference receivers [J]. J4, 2014, 41(4): 31-35+57.
[7]	YAN Junkun;XIA Shuangzhi;DAI Fengzhou;LIU Hongwei;BAO Zheng. Power allocation strategy for target tracking in asynchronous multistatic radar systems [J]. J4, 2013, 40(6): 32-38+57.
[8]	LIU Xue;JIAO Shuhong;LAN Xiaoyu. Quasi-monte-carlo merging resampling particle filter for passive location [J]. J4, 2012, 39(5): 154-160.
[9]	GUO Hui;JI Hong-bing;WU Bin. Quasi-Monte-Carlo Gaussian particle filter based target tracking for the multiple passive sensor [J]. J4, 2010, 37(6): 1042-1047.
[10]	LI Xiao-jie;XU Lu-ping;ZHOU Xue-song. High accuracy complex sinusoid frequency estimator in low SNR environment [J]. J4, 2009, 36(6): 1010-1014+1020.
[11]	REN Guang-liang;BAI Yun;NI Hao;SUN Chui-qiang. New precise space ranging algorithm for multi-carrier systems [J]. J4, 2009, 36(6): 957-961.
[12]	SHAO Xiao-peng;ZHENG Hong-bin;XU Jun;ZHANG Jian-qi. Statistics model for IR radiance of bare terrain and analysis of texture characteristics [J]. J4, 2007, 34(6): 944-946.
[13]	LI Jin-ping;CHEN Jian-jun;LIU Hai-feng;XU Jian;HUANG Xiao-bian. Analysis of stochastic temperature field by the Neumann expansions [J]. J4, 2007, 34(3): 453-457.

Indoor positioning algorithm based on Markov Monte Carlo

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 13

Metrics

Comments

Recommended 10