Abstract
The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (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 Cramer-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.
Highlights
A Constrained Least Squares Approach to Mobile PositioningThe problem of locating a mobile terminal has received significant attention in the field of wireless communications
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
This paper considers a unified constrained weighted least squares (CWLS)/weighted least squares (WLS) mobile location approach for time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) measurements
Summary
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. 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 Cramer-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is confirmed by simulation results
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
