A Study Of GPS Signal Acquisition Algorithm Based On Compressive Sensing

In recent years, the technology of satellite navigation has been widely used in all areas of modern life with its development. GPS has more widely application and faster development. It is mainly composed of three parts, including space constellation, ground monitoring and user equipment. The design of the user equipment is the key working, generally speaking the design of GPS receiver. In the process of this design, the GPS signal acquisition has directly effect on the subsequent modules in the baseband signal processing. So, the signal acquisition algorithm appears more important. Due to the restriction of the Nyquist specific and the needs of the analog-to-digital conversion, the GPS signals are sampled in high speed in the RF front-end, and then given to the baseband signal processing to capture in the traditional GPS receiver, which leads to the problem of the high sampling and the large data, and which needs strict requirement to the hardware module. It is also the bottleneck of the development of GPS signal acquisition. Compressive sensing theory proposes a new signal processing framework. In this theory, two processing, samping and compression, mesh into one part. It can greatly reduce the signal sampling rate and improve the efficiency of the signal processing by using signal sparse. Therefore, the compressive sensing theory has been paid close attention to in many fields, such as radar detecting, wireless communication and biological sensing. At the same time, it breaks the bottleneck of the aforementioned problem, which makes a new development direction to the acquisition algorithm. Based on the above two aspects of content, this paper researches on the characteristics of the GPS signal, the traditional acquisition algorithms and the compressive sensing theory, and builds the GPS signal acquisition algorithm based on compressive sensing. This framework is on the base of the GPS signal sparse, instead of the signal waveform, which can break the restriction of the Nyquist theorem and samples the signal in lower speed. In terms of observation and reconstruction, two algorithms are present. One makes use of random Gaussian matrix as the observation matrix, and then reconstruct the signal by orthogonal matching pursuit. The other utilizes deterministic matrix as the observation matrix, and then does two stages of measurement to capture the GPS signal, among which Walsh-Hadamard matrix and fast Walsh-Hadamard transform are used. Then the two algorithms based on compressive sensing have been simulated in Matlab platform, which can be drawn that the second algorithm is more stable. After that, the second algorithm is compared with the traditional method of acquisition from the number of the correlator,detection probability and computational complexity. Through the analysis, it can be concluded that the GPS signal acquisition algorithm base on the deterministic compressive matrix has a large advantage. Meanwhile, the proposed direction is improved to achieve the GPS signal acquisition based on compressive sensing theory better.