Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round-Trip-Time Measurements

被引:81
作者
De Angelis, Guido [1 ]
Moschitta, Antonio [2 ]
Carbone, Paolo [2 ]
机构
[1] Reg Govt Umbria, Serv Innovat Enterprise, Umbria, Italy
[2] Univ Perugia, I-06125 Perugia, Italy
关键词
Ultrawideband (UWB); indoor positioning; TOA; tracking; least squares estimator; extended Kalman filter; particle filter; PARTICLE FILTERS; LOCALIZATION; TRACKING; RADIO; MITIGATION; NAVIGATION; VEHICLES;
D O I
10.1109/TITS.2016.2516822
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this paper, a technique for modeling propagation of ultrawideband (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on round-trip-time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an additive white Gaussian noise channel and are detected using a threshold-based receiver, it is shown that RTT measurements may be affected by non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of an RTT-based positioning system are investigated. To this aim, a classical least-squares estimator, an extended Kalman filter, and a particle filter are compared when used to detect a slowly moving target in the presence of the modeled noise. It is shown that, in a realistic indoor environment, the particle filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.
引用
收藏
页码:2272 / 2281
页数:10
相关论文
共 44 条
[1]  
Alavi B, 2006, IEEE COMMUN LETT, V10, P275, DOI 10.1109/LCOMM.2006.04026
[2]   A New Confidence Estimator for Vehicle Tracking Based on a Generalization of Bayes Filtering [J].
Altendorfer, Richard ;
Matzka, Stephan .
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2012, 4 (04) :30-41
[3]  
[Anonymous], 2006, Intelligent robotics and autonomous agents
[4]  
[Anonymous], 2001, Sequential Monte Carlo methods in practice
[5]  
[Anonymous], 1948, Handbook of Mathematical Functions withFormulas, Graphs, and Mathematical Tables, DOI DOI 10.1119/1.15378
[6]  
[Anonymous], 2003, Beyond the Kalman Filter: Particle Filters for Tracking Applications
[7]   A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J].
Arulampalam, MS ;
Maskell, S ;
Gordon, N ;
Clapp, T .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2002, 50 (02) :174-188
[8]  
Aso M, 2001, IEEE VTS VEH TECHNOL, P106, DOI 10.1109/VTC.2001.956565
[9]  
Bar-Shalom Y., 2001, ESTIMATION APPL TRAC
[10]   A Mathematical Model for Wideband Ranging [J].
Bartoletti, Stefania ;
Dai, Wenhan ;
Conti, Andrea ;
Win, Moe Z. .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2015, 9 (02) :216-228