Abstract
In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.
Highlights
The purpose of a wireless location identification algorithm is to estimate the position of a mobile station (MS) in a wireless communication network
This paper presents a novel positioning algorithm based on neural network to determine MS
We develop algorithm which make use of the feasible intersections of three time of arrival (TOA) circles to provide improved MS location accuracy in the presence of NLOS errors
Summary
The purpose of a wireless location identification algorithm is to estimate the position of a mobile station (MS) in a wireless communication network. A variety of wireless location techniques are known, including signal strength [1], angle of arrival (AOA) [2], time of arrival (TOA) [3], and time. The mobile positioning technique plays an important role in providing location-based services in wireless communication networks. With this new feature, it can be applied to several valuable location-based services. Applications of wireless location services include the E-911 wireless emergency services, location-based billing, fleet management and intelligent transportation system (ITS) [5]. For E-911 services, an important issue is that the public safety officer know the caller’s phone number and accurate location. Many fleet operators have already applied the location technology to track their vehicles, which can operate their fleets more efficiently, but improve their field service [5]
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