Recognition of GPS Signal in Low SNR Environment and Its MATLAB Simulation
With the wide application of GPS technology in various fields, the requirements for its reliability and accuracy are getting higher and higher. However, in practical applications, the identification of GPS signals faces certain challenges in some complex environments with weak signal strength and many interferences. In order to solve this problem, the recognition accuracy and stability of GPS signals can be improved through MATLAB simulation.
In this paper, we introduce a MATLAB-based identification method for GPS signals in low SNR environments. The method mainly includes three steps: preprocessing, time-frequency analysis and signal recognition.
First, the original signal received by the GPS receiver is filtered and the DC offset is removed through preprocessing methods. Then, the processed signal is input into a time-frequency analyzer for time-frequency analysis to obtain a spectrogram, and the signal is further processed. Finally, according to the characteristic parameters of the signal, the support vector machine (SVM) classification algorithm is used to classify and identify the signal.
Next, we will give the detailed MATLAB code implementation process of this method.
First, perform preprocessing, including denoising the signal and removing DC offset:
G0 = 1.5; % 初始增益为1.5，可根据实际情况调整
signal = signal - mean(signal)