| Both in civilian and military applications, navigation and positioning performan--ce of GNSS receivers are very important. GNSS signals in the process of transmissi--on will be affected by a variety of continuous wave interference, so that it is difficult to offer accurate navigation and position based on GNSS receiver signal. Therefore, eliminating the interference signal of the GNSS signals is very important, which requires the GNSS receiver has the capability of strong interference detection and filtering.GNSS receiver’s signal is non-stationary, its statistic is a time-varying function. Only to understand global characteristics of signal in time or frequency domain is not enough, it need to know the signal spectrum changes over time. In this paper, a novel CWT based TF analysis algorithm has been proposed in the interference detection for GNSS receivers. The CW kernel function is introduced to the Cohen’s class in order to attenuate the cross terms of the traditional TF approaches. The proposed method is tested by simulations on Galileo El signals in radio frequency interference scenarios compared to the state of the art TF analysis interference detection techniques such as spectrogram and WVD, unproved TF localization properties and interference detecti--on sensitivity have been achieved with the developed technique, providing its effecti--veness and validity for interference detection for GNSS receivers. In terms of GNSS receiver filter, in order to reduce the damage to useful GNSS signal filtering process, the paper designs the adaptive trap to eliminate interference signals, and is verified by simulation experiment adaptive trap can effectively eliminate interference signals, and the useful signal has almost no damage.In this dissertation, the time-frequency analysis and adaptive trap can greatly improve the GNSS receiver interference detection and filtering ability, thus greatly improve the performance of the navigation and positioning receiver. |
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