Abstract
In this study, a hybrid TOA/RSSI wireless localization is proposed for accurate positioning in indoor UWB systems. The major problem in indoor localization is the effect of Non-Line of Sight (NLOS) propagation. To mitigate the NLOS effects, an unconstrained nonlinear optimization approach is utilized to process Time-of-Arrival (TOA) and Received Signal Strength (RSS) in the location system.TOA range measurements and path loss model are used to discriminate LOS and NLOS conditions. The weighting factors assigned by hypothesis testing, is used for solving the objective function in the proposed approach. This approach is used for describing the credibility of the TOA range measurement. Performance of the proposed technique is done based on MATLAB simulation. The result shows that the proposed technique performs well and achieves improved positioning under severe NLOS conditions.
Highlights
The usage of cell phones has risen exponentially in the recent past compelling wireless service providers to scrounge everyday for new technology to accommodate the enormous populations and to provide superior wireless location-based services
Considering the fact that the ensemble of MS is mainly located in an indoor condition, in this study, we propose for UWB radio link, a hybrid TOA/RSSI using unconstrained nonlinear optimization technique
For accurate calculation of position of MS, a hybrid TOA/RSSI indoor wireless location for UWB application has been proposed. This location algorithm uses base stations (BSs) without the knowledge of LOS/Non-Line of Sight (NLOS) conditions, assesses range measurements based on TOA using GCC
Summary
The usage of cell phones has risen exponentially in the recent past compelling wireless service providers to scrounge everyday for new technology to accommodate the enormous populations and to provide superior wireless location-based services. The forthcoming sections discusses Hybrid TOA/RSSI wireless location algorithm, Nonlinear objective function, path loss model, LOS/NLOS BS identification, simulation results and conclusion. Selected path loss model: The relationship between RSSI and distance is utilized to determine the values of weight factors and the corresponding distances from the Mobile Station to all Base Stations for a given RSSI, can be determined by the path loss model in a wireless transmission network These parameters i.e. the path loss model RSSI are utilized for estimating the transmitter-receiver separations, which are further used in LOS/NLOS identification.
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