Gnss Intermediate Frequency Signal Simulation And Weak Signal Receiving Algorithm Research

With the continuous development and improvement of GNSS (Global Navigation Satellite Systems), the requirement of GNSS receiver’s performance continue to increase. In order to develop a high-performance software receiver, we need to constantly optimize the receiver’s receiving algorithm. However, receiving algorithm of software receiver base on GNSS digital IF (Intermediate Frequency) signal. So the digital IF signal simulator is greatly significant for researching the software receiver’s receiving algorithm.This paper first introduces the modular structure of the digital IF signal simulator and the generation algorithms of GNSS digital IF signal. Because of the modular structure, it is convenient to generate the IF signal for the new GNSS signal by adding modules.Second, we elaborate the structure, modulation scheme and the characteristics of the modulation signal of the Galileo L1signal> Galileo E5signal and GPS L1signal.Third, we focus on the research of the weak GNSS signal acquisition algorithm and tracking algorithm. Most commercial receivers are able to capture the signal if its signal-to-noise ratio is high. When the receiver is in the indoor, forest or other mal-environments, the signal-to-noise ratio of the signal falls to a low degree. This makes receivers acquire signals difficultly. So, the research of weak signal reception algorithm has important implications. This article deeply describes the acquisition and tracking algorithms of the weak signal, then compares the ordinary parallel code phase capture algorithms with the modified full bit algorithm.Fourth, we simulate the GPS L1, Galileo L1and Galileo E5signal using Matlab platform on the basis of the structure of the IF digital signal simulator and the generation algorithm.Last, according to the acquisition and tracking algorithm of weak signal, the paper simulates the receiver’s acquisition and tracking algorithm of weak GNSS signal using Matlab, and gets the satisfied simulation result at last.