Nonlinear programming-based ranging optimization for three-dimensional indoor time of arrival localization

The distribution of ranging errors of time of arrival techniques fails to satisfy zero means and equal variances. It is one of the major causations of position error of least square–based localization algorithm. The optimization of time of arrival ranging is defined as a nonlinear programming problem. Then, time of arrival ranging error model and geometric constraints are used to define the initial values, objective functions, and constraints of nonlinear programming, as well as to detect line of sight and nonline of sight. A three-dimensional localization algorithm of an indoor time of arrival–based positioning is proposed based on least square and the optimization algorithm. The performance of the ranging and localization accuracies is evaluated by simulation and field testing. Results show that the optimized ranging error successfully satisfies zero mean value and equal variances. Furthermore, the ranging and localization accuracies are significantly improved.

[1]  Xenofon D. Koutsoukos,et al.  A Survey on Localization for Mobile Wireless Sensor Networks , 2009, MELT.

[2]  Yuechun Chu,et al.  A UWB-based 3D location system for indoor environments , 2005, 2nd International Conference on Broadband Networks, 2005..

[3]  Yue Wang,et al.  Reference Selection for Hybrid TOA/RSS Linear Least Squares Localization , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[4]  Kaveh Pahlavan,et al.  UDP identification and error mitigation in toa-based indoor localization systems using neural network architecture , 2009, IEEE Transactions on Wireless Communications.

[5]  Paul T. Boggs,et al.  Sequential Quadratic Programming , 1995, Acta Numerica.

[6]  Álvaro Marco,et al.  Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization , 2006, EURASIP J. Adv. Signal Process..

[7]  Xiaodai Dong,et al.  Localization algorithms for asynchronous time difference of arrival positioning systems , 2017, EURASIP Journal on Wireless Communications and Networking.

[8]  Brian D. O. Anderson,et al.  Sensor network localization with imprecise distances , 2006, Syst. Control. Lett..

[9]  Chin-Der Wann,et al.  Hybrid TOA/RSSI Wireless Location with Unconstrained Nonlinear Optimization for Indoor UWB Channels , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[10]  Jie He,et al.  Modelling ranging error of indoor TOA-based position system based on receive signal strength , 2013, Int. J. Sens. Networks.

[11]  Kaveh Pahlavan,et al.  Toward Accurate Human Tracking: Modeling Time-of-Arrival for Wireless Wearable Sensors in Multipath Environment , 2014, IEEE Sensors Journal.

[12]  Aamir Saeed Malik,et al.  Survey of NLOS identification and error mitigation problems in UWB-based positioning algorithms for dense environments , 2010, Ann. des Télécommunications.

[13]  Joon-Hyuk Chang,et al.  Robust time-of-arrival source localization employing error covariance of sample mean and sample median in line-of-sight/non-line-of-sight mixture environments , 2016, EURASIP Journal on Advances in Signal Processing.

[14]  Saeed S. Ghassemzadeh,et al.  The Ultra-wideband Indoor Path Loss Model , 2002 .

[15]  Umberto Mengali,et al.  A Maximum Likelihood UWB Localization Algorithm Exploiting Knowledge of the Service Area Layout , 2013, Wirel. Pers. Commun..

[16]  Kaveh Pahlavan,et al.  Modeling of the TOA-based distance measurement error using UWB indoor radio measurements , 2006, IEEE Communications Letters.

[17]  Sartaj Sahni,et al.  A computational geometry method for DTOA triangulation , 2007, 2007 10th International Conference on Information Fusion.

[18]  Shyi-Ching Liang,et al.  Localization Algorithm based on Improved Weighted Centroid in Wireless Sensor Networks , 2014, J. Networks.

[19]  Kaveh Pahlavan,et al.  Identification of the Absence of Direct Path in Indoor Localization Systems , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[20]  Alexander V. Ivanov.  Asymptotic Expansions Related to the Least Squares Estimator , 1997 .

[21]  Ali H. Sayed,et al.  Network-based wireless location , 2005 .

[22]  Chee-Hyun Park,et al.  Time-of-arrival source localization based on weighted least squares estimator in line-of-sight/non-line-of-sight mixture environments , 2016, Int. J. Distributed Sens. Networks.

[23]  Moe Z. Win,et al.  NLOS identification and mitigation for localization based on UWB experimental data , 2010, IEEE Journal on Selected Areas in Communications.

[24]  Fei Liu,et al.  CC-KF: Enhanced TOA Performance in Multipath and NLOS Indoor Extreme Environment , 2014, IEEE Sensors Journal.