A Novel GNSS Weak Signal Acquisition Using Wavelet Denoising Method
Jin Tian, Yang Liu · 2008
With the increasing demands of precise positioning in weak signal environment, high sensitive GNSS receiver research and development has been pushed badly in need. Conventional GNSS signal acquisition techniques are considered inadequate when the incoming signal is too weak. In this paper we have mainly consider wavelet denoising algorithm applying in weak GNSS signal acquisition. Conventional wavelet de-noising algorithms include regional scale transformation method and threshold method. The first method requires less limitation about the noise type, but the latter one is applied only in Gauss noise conditions. Besides wavelet de-noising process is done when the signal is independent in time sequence, therefore our work has done based on the traditional correlation acquisition. When the noncorrelation or differential correlation has done, the noise distribution and property has been also changed. If the noise pre-processed is Gauss distributed, the postprocessed noise is no longer Gauss white noise. Under this circumstance we conduct statistics analysis to estimate the derivation of noise, and assume a new Gauss noise. Then the wavelet de-noising process is done. Our algorithm contains three key steps. Firstly, correlation and differential correlation method are used to acquire the very weak signal; secondly, noise derivation is estimated and noise model is established; then the wavelet denoising process is applied. The result turns out fine for the signal lower than other acquisition method.