This thesis investigates the suitability of global navigation satellite system (GNSS) signals for cellular phone location. The requirement is to determine and report the location of a phone during an emergency call.<p> The thesis analyzes acquisition and tracking techniques suitable for very weak signals as received by a cellular phone indoors. The L1 and L5 signals from GPS satellites and the L1 signal from Galileo satellites are considered. It is shown that long integration times and coherent integration are required for the weakest expected signals. Long coherent integration times require a precise knowledge of the Doppler shift due to the range rate of the satellite. The tolerance to Doppler shift can be increased by using FFTs in the analysis of the data. Non-coherent averaging techniques improve the Doppler tolerance but compared to coherent averaging, the loss of signal to noise ratio is too large for the weakest signals.<p> Coherent averaging of the GPS L1 signal requires data removal that can be accomplished with assistance from the cellular network. The GPS L5 and Galileo L1 signals include a data-less or pilot channel. The GPS L5 pilot channel includes a 20 bit Neuman Hoffman code with a bit period of 1 ms. This code has to be acquired or removed before coherent averaging. Similarly the Galileo pilot channel includes a 25 bit short code.<p> Once code acquisition has been accomplished, it is necessary to track the signals from at least four satellites for long enough to compute a position estimate. A discussion of tracking techniques is included to show the signal to noise ratio limitations for adequate tracking accuracy.<p> The results show that GNSS signals are suitable for cellular phone location in a large number of situations. Increased receiver sensitivity would permit location in additional situations. In rural situations GNSS may be the only available option.

This thesis investigates the suitability of global navigation satellite system (GNSS) signals for cellular phone location. The requirement is to determine and report the location of a phone during an emergency call.<p> The thesis analyzes acquisition and tracking techniques suitable for very weak signals as received by a cellular phone indoors. The L1 and L5 signals from GPS satellites and the L1 signal from Galileo satellites are considered. It is shown that long integration times and coherent integration are required for the weakest expected signals. Long coherent integration times require a precise knowledge of the Doppler shift due to the range rate of the satellite. The tolerance to Doppler shift can be increased by using FFTs in the analysis of the data. Non-coherent averaging techniques improve the Doppler tolerance but compared to coherent averaging, the loss of signal to noise ratio is too large for the weakest signals.<p> Coherent averaging of the GPS L1 signal requires data removal that can be accomplished with assistance from the cellular network. The GPS L5 and Galileo L1 signals include a data-less or pilot channel. The GPS L5 pilot channel includes a 20 bit Neuman Hoffman code with a bit period of 1 ms. This code has to be acquired or removed before coherent averaging. Similarly the Galileo pilot channel includes a 25 bit short code.<p> Once code acquisition has been accomplished, it is necessary to track the signals from at least four satellites for long enough to compute a position estimate. A discussion of tracking techniques is included to show the signal to noise ratio limitations for adequate tracking accuracy.<p> The results show that GNSS signals are suitable for cellular phone location in a large number of situations. Increased receiver sensitivity would permit location in additional situations. In rural situations GNSS may be the only available option.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.