Two base station location techniques with adjusted measurements in circular scattering environments

• Published in: International journal of communication systems Vol. 29; no. 6; pp. 1073 - 1083
• Main Authors: Wu, Shixun, Xu, Dengyuan, Tan, Jin, Xu, Kai, Wang, Honggang
• Format: Journal Article
• Language: English
• Published: Chichester Blackwell Publishing Ltd 01-04-2016; Wiley Subscription Services, Inc
• Subjects: Adjustment; Algorithms; angle; Angles (geometry); circular scattering model; Computer simulation; line-of-sight (LOS); Mathematical models; non-line-of-sight (NLOS); Nonlinearity; Optimization; range; Scattering
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.3073

Summary
In circular scattering environments, novel location techniques with only two base stations (BSs) are proposed in this paper. The proposed techniques estimate the true or line‐of‐sight ranges and angle based on non‐line‐of‐sight range and angle measurements. Three new variables are introduced when range measurements and angle measurement are available from two BSs and the serving BS, respectively. Bounds and relationships between the three variables are extracted from the geometry of the cell layout with the unknown and known scattering radius conditions, respectively. Our aim is to obtain the estimation of three new variables and then the hybrid line of position technique with the adjusted ranges, and angle is utilized to obtain the position estimation of a mobile station. In order to obtain the estimation of three new variables, a new nonlinear objective function is built to form the constrained nonlinear optimization and solved by the existing optimization algorithms. However, because of the nonconvex objective function, the optimization algorithm may converge to the local optimum and lead to bad performance. Thus, a heuristic search algorithm is proposed by averaging all the potential point. Simulation results show that the proposed techniques outperform conventional hybrid techniques. Copyright © 2015 John Wiley & Sons, Ltd.
In this paper, three new variables are introduced to form the constrained nonlinear optimization with only two base stations. The adjusted measurements are obtained with the solution of the nonlinear optimization; then a new hybrid line of position algorithm is presented. Due to the nonconvex objective function, a heuristic search algorithm is proposed by averaging all the potential point. Simulation results show that the proposed algorithms outperform the existing algorithm.