Abstract
With the popularity of smart devices, applications based on location services have been widely used, and wireless positioning technology can provide accurate positioning information. However, due to the effect of non-line-of-sight (NLOS) errors, the performance of the system can drop significantly. Accordingly, this paper introduces the theory of quadratic programming optimization based on the research of the time difference of arrival (TDOA) theory and proposes an optimization algorithm that can effectively suppress the influence of NLOS error. Simulation results show that compared with other common wireless location algorithms, the proposed algorithm has more reliable positioning accuracy under different environment models and has better system stability.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Li H. Study of wireless sensor network applications in network optimization. Sens Transducers. 2013;157(10):180–9.
Vaghefi RM, Amuru SD, Buehrer RM. Improving mobile node tracking performance in NLOS environments using cooperation. In: IEEE international conference on communications; 2015. p. 6595–600.
Xu W, Quitin F, Leng M, et al. Distributed localization of a RF target in NLOS environments. IEEE J Sel Areas Commun. 2015;33(7):1317–30.
Kireev A, Fokin G, Al-odhari AHA. TOA measurement processing analysis for positioning in NLOS conditions. In: Systems of signals generating and processing in the field of on board communications; 2018. p. 1–4.
Wang Y, Ho KC. An asymptotically efficient estimator in closed-form for 3-D AOA localization using a sensor network. IEEE Trans Signal Process. 2015;14(12):6524–35.
Kim R, Ha T, Lim H, et al. TDOA localization for wireless networks with imperfect clock synchronization. In: International conference on information networking; 2014. p. 417–21.
Gholami MR, Vaghefi RM, Ström EG. RSS-based sensor localization in the presence of unknown channel parameters. IEEE Trans Signal Process. 2013;61(15):3752–9.
Feng Y, Fritsche C, Gustafsson F, et al. TOA-based robust wireless geolocation and Cramér-Rao lower bound analysis in harsh LOS/NLOS environments. IEEE Trans Signal Process. 2013;61(9):2243–55.
Long C, Wang Y, et al. A mobile localization strategy for wireless sensor network in NLOS conditions. China Commun. 2016;13(10):69–78.
Fascista A, Ciccarese G, Coluccia A, Ricci G. A change-detection approach to mobile node localization in bounded domains. In: Conference on information sciences and system; 2015. p. 1–6.
Martin RK, Yan C, Fan HH, et al. Algorithms and bounds for distributed TDOA-based positioning using OFDM signals. IEEE Trans Signal Process. 2011;59(3):1255–68.
Qi Y, Kobayashi H, Suda H. Analysis of wireless geolocation in a non-line-of-sight environment. IEEE Trans Wirel Commun. 2006;5(3):672–81.
Caffery JJ, Stuber GL. Subscriber location in CDMA cellular networks. IEEE Trans Veh Technol. 1998;47(2):406–16.
Venkatraman S, Caffery JJ, You HR. A novel TOA location algorithm using LOS range estimation for NLOS environments. IEEE Trans Veh Technol. 2004;53(5):1515–24.
Cheung KW, So HC, Ma WK, et al. A constrained least squares approach to mobile positioning: algorithms and optimality. EURASIP J Adv Signal Process. 2006. https://doi.org/10.1155/asp/2006/20858.
Zheng X, Hua J, Zheng Z, et al. LLOP localization algorithm with optimal scaling in NLOS wireless propagations. In: Proceedings of IEEE international conference on electronics information and emergency communication; 2014. p. 45–8.
Chan YT, Ho KC. A simple and efficient estimator for hyperbolic location. IEEE Trans Signal Process. 2002;42(8):1905–15.
Acknowledgements
This paper was sponsored by the National Natural Science Foundation of China under grant No. 61471322.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Liu, G., Hua, J., Li, F., Lu, W., Xu, Z. (2020). A Quadratic Programming Localization Based on TDOA Measurement. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_148
Download citation
DOI: https://doi.org/10.1007/978-981-13-6504-1_148
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6503-4
Online ISBN: 978-981-13-6504-1
eBook Packages: EngineeringEngineering (R0)