A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality
- PDF / 809,180 Bytes
- 23 Pages / 600.03 x 792 pts Page_size
- 10 Downloads / 174 Views
A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality K. W. Cheung,1 H. C. So,1 W.-K. Ma,2 and Y. T. Chan3 1 Department
of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan 3 Department of Electrical & Computer Engineering, Royal Military College of Canada, Kingston, ON, Canada K7K 7B4 2 Department
Received 20 May 2005; Revised 25 November 2005; Accepted 8 December 2005 The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-ofarrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cram´er-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
1.
INTRODUCTION
Accurate positioning of a mobile station (MS) will be one of the essential features that assists third generation (3G) wireless systems in gaining a wide acceptance and triggering a large number of innovative applications. Although the main driver of location services is the requirement of locating Emergency 911 (E-911) callers within a specified accuracy in the United States [1], mobile position information will also be useful in monitoring of the mentally impaired (e.g., the elderly with Alzheimer’s disease), young children and parolees, intelligent transport systems, location billing, interactive map consultation and location-dependent e-commerce [2–6]. Global positioning system (GPS) could be used to provide mobile location, however, it would be expensive to be adopted in the mobile phone network because additional hardware is required in the MS. Alternatively, utilizing the base stations (BSs) in the existing network for mobile location is preferable and is more cost effective for the consumer. The basic principle of this softwarebased solution is to use two or more BSs to intercept the MS signal, and common approaches [6–8] are based on time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and/or angle-of-arrival (AOA) measurements determined from the MS signal received at the BSs.
In the TOA method, the distance between the MS and BS is determined from the measured one-way propagation time of the signal traveling betw
Data Loading...
