Research On Weak GPS Signal Acquisition Algorithm

With the rapid development of Global Position System (GPS) technology, GPS have been applied in many fields of daily life, and the application area of military will be expended. In order to satisfy the needs of users, it required that the GPS receiver could work correctly in some special environment. Thus whether the signals can be captured has became a key issue to be solved. The thesis mainly focused on the acquisition of weak GPS signal, the main work and results are as follows:1. The GPS signal structure was analyzed, the related properties of spreading codes in the GPS signal and the spreading spectrum modulation were studied in details. The GPS digital intermediate frequency (IF) signal model was built to simulate signals as the experimental source.2. The general principle of GPS signal acquisition was studied, and the key of acquisition is to capture the initial code phase of the pseudo-random spreading codes and Doppler shift of the carrier. The traditional capture strategies were compared, and the theory and specific implementation step of the domain parallel acquisition strategy with code-phase based on FFT were analyzed in detail.3. The parallel acquisition strategy with code-phase based on FFT was applied in the acquisition algorithm of weak GPS signals. The factors of weak GPS signal acquisition were analyzed:pre-detection time length, detection probability and false alarm rate. The three weak signal acquisition algorithms were analyzed and compared: coherent integration, non-coherent integration and differentially coherent integration. And the experiments show that the increasing of cumulative time and the cumulative number could improve the performance of the algorithm. From the relationship between the SNR and the detection probability can we know that, under long cumulative time, the performance of differentially coherent integration was better.4. In order to improve the sensitivity of capturing and the SNR, Wavelet de-noising algorithm combined with differentially coherent integration was proposed. Different wavelets and wavelet decomposition scales could affect wavelet de-noising performance, the optimal wavelet was found by experiments, and it was used in different signal power with the differential coherent cumulative capture. The experiments confirmed that the SNR will be improved3dB by the algorithm.