2012Journal of Tianjin University Science and TechnologyRequires access

Design and Validation of Direct Digitization Scheme for GNSS Receiver Front-Ends

Qi Wei

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Abstract

Traditional global navigation satellite system(GNSS) receiver front-ends is very complex and inflexible when receiving multi-system signals.To solve such a problem,a digitized radio frequency(RF) front-end design was proposed based on the direct RF sampling.Considering that GNSS signals primarily concentrate on low frequency band and high frequency band,like two integral band-pass signals,the sampling rate of such signals can’t be low due to the wide band.In this paper,firstly,the sampling rate selection algorithm for multiple band-pass signals was discussed.Then the direct RF sampling rate for such two GNSS band-pass bands was determined.For the purpose of lowering the aforementioned high sampling rate,a decimation and filtering network was designed.Finally,based on the fact that analog to digital converter(A/D) specially designed for direct RF sampling is capable of outputting the data at half the sampling rate,the digital down-conversion of the signal of interest as well as its separation from the entire band was realized.Thus multi-frequency signal receiving can be achieved by software implementation of the design and the system flexibility will be greatly improved.Experiments have proved the effectiveness of the design.

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What this paper is about

Traditional global navigation satellite system(GNSS) receiver front-ends is very complex and inflexible when receiving multi-system signals.To solve such a problem,a digitized radio frequency(RF) front-end design was proposed based on the direct RF sampling.Considering that GNSS signals primarily concentrate on low frequency band and high frequency band,like two integral band-pass signals,the sampling rate of such signals can’t be low due to the wide band.In this paper,firstly,the sampling rate selection algorithm for multiple band-pass signals was discussed.Then the direct RF sampling rate for such two GNSS band-pass bands was determined.For the purpose of lowering the aforementioned high sampling rate,a decimation and filtering network was designed.Finally,based on the fact that analog to digital converter(A/D) specially designed for direct RF sampling is capable of outputting the data at half the sampling rate,the digital down-conversion of the signal of interest as well as its separation from the entire band was realized.Thus multi-frequency signal receiving can be achieved by software implementation of the design and the system flexibility will be greatly improved.Experiments have proved the effectiveness of the design.

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Available abstract

Traditional global navigation satellite system(GNSS) receiver front-ends is very complex and inflexible when receiving multi-system signals.To solve such a problem,a digitized radio frequency(RF) front-end design was proposed based on the direct RF sampling.Considering that GNSS signals primarily concentrate on low frequency band and high frequency band,like two integral band-pass signals,the sampling rate of such signals can’t be low due to the wide band.In this paper,firstly,the sampling rate selection algorithm for multiple band-pass signals was discussed.Then the direct RF sampling rate for such two GNSS band-pass bands was determined.For the purpose of lowering the aforementioned high sampling rate,a decimation and filtering network was designed.Finally,based on the fact that analog to digital converter(A/D) specially designed for direct RF sampling is capable of outputting the data at half the sampling rate,the digital down-conversion of the signal of interest as well as its separation from the entire band was realized.Thus multi-frequency signal receiving can be achieved by software implementation of the design and the system flexibility will be greatly improved.Experiments have proved the effectiveness of the design.

Key concepts: GNSS applications, RF front end, Sampling (signal processing), Direct-conversion receiver, Decimation, Software-defined radio, Electronic engineering, Computer science

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