The Method For Satellite Navigation Signal Collection Based On Compressed Sensing

Currently,satellite navigation has become an indispensable part of daily life.Collection of navigation signal directly determines the quality of the navigation and positioning accuracy.The high bandwidth of navigation signal makes Nyquist sampling theorem has brought great challenges to the cost of hardware and the complexity of hardware.In recent years,a new data collection theory called compressed sensing has been proposed,and it has the ability to break through the restriction of the Nyquist sampling theorem for sparse signal.According to the sparsity of navigation signal,this dissertation presents a hardware implementable compressed sampling method based on compressed sensing.Firstly,this dissertation makes a full introduction about basic principles and implementation of compressed sensing.And the main parameters of the theory are analyzed.In order to effectively measure the navigation signal at low rate,we analyze in detail the sparsity and the measure matrix of the navigation signal.On the basis of analog-to-information converter(AIC),a parallel navigation signal sampling method based on compressed sensing is proposed.Each channel of the proposed structure is composed with a random modular,an integrator and an ADC.The output of each channel is a measurement of input signal.Compared with the collection system using AIC structure,the collection system using the parallel sampling structure requires less number of measurements to achieve equivalent information.The result of this dissertation verifies the advantages and feasibility of navigation signal sampling system using compressed sensing.Digital Simulation and analysis shows the system can collect navigation signal with a lower sampling rate.In the channel whose signal-to-noise ratio is 20dB,we can accurately acquire navigation signal whose frequency is 250MHz with 76.8MHz sampling frequency.