Research On Method Of Signal Acquisition And Tracking Under New Modulation In GNSS

With the development of the global satellite navigation system, the problem of the frequency band congestion is becoming more and more serious. There is a new modulation method(BOC, Binary Offset Carrier) which can achieve the frequency band sharing and spectrum separation. What’s more, most of the satellite navigation systems have begun to adopt BOC modulation in navigation with the comparison with PSK modulation. The basic thought of the BOC modulation is that the PN code with data is multiplied by a square sub-carrier(sine or cosine phased). However, at the same time, the change of the modulation causes some differences in signal characteristic, especially for the spectrum and auto-correlation function. For the signal acquisition and tracking, there are also some new requirements.The thesis has launched research of the basic principle for the BOC modulation, including MBOC and AltBOC modulation. It also analyzes the characteristics of the BOC signal, including multi-path characteristics, filter bandwidth, discrimination phase curve, power spectral density and auto-correlation function. For BOC signals, their power spectral density has multiple sides peaks and their power spectral density produces frequency shifting.Base on the signal acquisition and tracking, this thesis does some research on the signal acquisition and tracking algorithms, which include bump-jumping method, BPSK-Like method, FFT method and related function method. According to the research and simulation under Matlab on some existing algorithms, each of them has some advantages and disadvantages. The conclusion got from comparison is beneficial for the next improvement.With the characteristics of Beidou signals and the parameters of BOC modulation, the original single side band algorithm is improved. The improved algorithm is the combination of the FFT transform method, the average sampling method and the BPSK-Like algorithm. The FFT transform has the role like the filter, and the average sampling is to solve the problem of too many sampling points. In addition, some comparisons have been made between the original algorithm and the improved one.