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The localization of mobile wireless communication units using time difference of arrival (TDOA) is studied. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented. These techniques are applied to different types of test signals and to a simulated baseband GSM signal. The results of the denoising techniques are compared to the ones employing no denoising in terms of the mean square error. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation.

The localization of mobile wireless communication units is studied. The most important method of localization is the time difference of arrival (TDOA) method. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented in this thesis. These techniques are applied to different types of test signals as well as the GSM signal. The results of the denoising techniques are compared to the ones obtained using no denoising. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation.

The localization of mobile wireless communication units is studied. The most important method of localization is the time difference of arrival (TDOA) method. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented in this thesis. These techniques are applied to different types of test signals as well as the GSM signal. The results of the denoising techniques are compared to the ones obtained using no denoising. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation.

The localization of mobile wireless communication units using time difference of arrival (TDOA) is studied. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented. These techniques are applied to different types of test signals and to a simulated baseband GSM signal. The results of the denoising techniques are compared to the ones employing no denoising in terms of the mean square error. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation.

The localization of mobile wireless communication units is studied. The most important method of localization is the time difference of arrival (TDOA) method. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented in this thesis. These techniques are applied to different types of test signals as well as the GSM signal. The results of the denoising techniques are compared to the ones obtained using no denoising. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation., http://archive.org/details/timedifferenceof1094513574, Turkish Navy author., Approved for public release; distribution is unlimited.

The views expressed in this report are those of the author and do not reflect the official policy or position of the Department of Defense or the United States Government., The localization of mobile wireless communication units using time difference of arrival (TDOA) is studied. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on the wavelet transform are presented. These techniques are applied to different types of test signals and to a simulated baseband GSM signal. The results of the denoising techniques are compared to the ones employing no denoising in terms of the mean square error. The denoising techniques allow a 28 to 81 percent improvement in the TDOA estimation., TENCAP Office, Department of the Navy, N4175698WR87397, Approved for public release; distribution is unlimited.