Please use this identifier to cite or link to this item: https://elibrary.tucl.edu.np/handle/123456789/7050
Title: GSM Mobile Positioning Based on Path Loss Using Hyperbolic Positioning and Different Interpolation Techniques
Authors: Joshi, Manju
Keywords: Hyperbolic Localization;Interpolation;Weighted Least Square (WLS);Root Mean Square Error (RMSE)
Issue Date: Nov-2019
Publisher: Pulchowk Campus
Institute Name: Institute of Engineering
Level: Masters
Abstract: Location estimation is an essential feature for many location-based services. Different location-based services may have different performance and operation requirements such as accuracy in localization and frequency of location tracking. Time Difference Of Arrival (TDOA), Angle of Arrival (AOA), Time Of Arrival (TOA), Received signal Strength (RSS), Received Signal Strength Indicator (RSSI), Stationary Signal Strength Difference (SSSD) are some methods used for estimating location of MS. Location estimation using RSS is a promising technique since it does not require any modification in the network side and time synchronization information are also not required. In this thesis, RSS received from serving and neighbor Base Station Transceiver (BTS) and known transmitter power are main parameter for estimating distance to Mobile Station (MS) from BTS using Walfisch-Ikegami pathloss model. Distance difference of MS from two BTS is used to draw hyperbola and intersection of two such hyperbola is the location of MS. Estimated distance contains error because of various reason such as error in signal measuring device, error in network parameter and error introduced by pathloss model itself which leads to error in location estimation. Cubic spline interpolation along with weighted least square method is used to minimize such error. With this consideration 69 percentile of estimated location are within 90m whereas only 36 percentile of location estimated using polynomial interpolation are within 90 m. Hence, from result it is found that hyperbolic localization along with spline interpolation and WLS method gives better location estimation than that of polynomial interpolation.
Description: Location estimation is an essential feature for many location-based services. Different location-based services may have different performance and operation requirements such as accuracy in localization and frequency of location tracking.
URI: https://elibrary.tucl.edu.np/handle/123456789/7050
Appears in Collections:Electronics and Computer Engineering

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