| Global navigation satellite system(GNSS) is widely applied in military and civilian fields. The development of GNSS technology is of great significance not only for the transportation in navigation but also the development of military technology and national security. China is also actively engaged in the Compass Navigation System. Up to now,GNSS development has actualized the functions of precise positioning and timing. Compared with the general communication systems, the system structure and signals of satellite communication system is special. There still exist some problems to be solved. During signal transmission, the prerequisite of communication is synchronization, whose first task is acquisition. Since the signal is affected by Doppler shift, which is caused by the relative motion of the satellite and the land receiver, its computation increases greatly due to the fact that GNSS acquisition itself is a time-frequency two dimensional search process. In addition, the pseudo-random code sequence of GNSS signal is really long. The number of chips to be searched increases, which makes the acquisition of GNSS signals more difficult. To reduce acquisition algorithm complexity for system implementation is of great significance. Most of the existing acquisition algorithms are based on the correlation of sequences. Some of them make a lower complexity. However, the acquisition algorithm based on correlation has been extensively studied. Though the acquisition algorithm based on correlation has been extensively studied, complexity is limited to certain degree of feasibility.This thesis introduces the development of GNSS and the significance of acquisition technology. Then we do research on the GNSS satellite signal characteristics and relative motion. We analyse the infection of Doppler shift and pseudo-random code length to the complexity of acquisition. Then we do simulation and analysis of existing acquisition algorithms based on sequence correlation and compare the acquisition performance of different algorithm and the method of reducing complexity, which lays the foundation for further study.To probe into the feasibility of reducing the complexity of acquisition, the author has research acquisition algorithms based on compressed sensing theory and phase correlation. The acquisition algorithm based on compressed sensing uses GNSS signal sparse features.It can convert high-dimensional acquisition process into a low-dimensional optimization problem, convex relaxation or through an iterative manner to be addressed. The acquisition algorithm based on phase correlation gives additional phase to signal, and it achieves acquisition by the phase relationship between the local pseudo-code and received signal. To enhance the acquisition performance, we adjust the structure of the algorithm. Through simulation and research complexity of algorithm we can know: In the SNR ideal case, algorithm based on compressed sensing can complete acquisition correctly. Compared to algorithm based on correlation, it reduces computational complexity significantly. But in more severe noise conditions, the acquisition performance deteriorated rapidly. The acquisition algorithm based on phase correlation can use only addition operation to complete acquisition, Compared to algorithm based on correlation, their performance is insignificant. Under certain scenarios, it can effectively reduce the complexity of acquisition. |
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