Quadrature BandPass Sampling Front-end for Global Navigation Satellite Systems

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Copyright: Mookiah, Vaidhya
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Abstract
Multi-frequency multi-GNSS is the next generation of satellite navigation receiver that will provide higher accuracy with flexibility. Software Defined Radio (SDR) is a great platform to build these receivers due to its reconfigurability, but there is a question of obtaining flexibility of the Radio Frequency (RF) front-end. A traditional analogue front-end is hardware-based, so they are complex and inflexible. Bandpass Sampling (BPS) is a subsampling architecture which downconverts and samples the signal in a single step. In BPS architecture, the Analogue-to-Digital Converter (ADC) is closer to the antenna, which supports the SDR receiver. Even though BPS has more advantages than fully analogue front-end, it has its drawbacks. An improvement to BPS is made by implementing it with two ADCs with one having a quadrature time delay from the other. This improvement produces direct in-phase (I) and quadrature phase (Q) output and hence is called Quadrature Bandpass Sampling (QBPS). QBPS can have the advantage of using half the sampling frequency of BPS as the signal is sampled using two ADCs. In this thesis, QBPS is analysed for degradation due to noise aliasing and is compared with BPS. Analysis shows that the noise contribution by BPS sampling and QBPS remains the same even with lower sampling frequencies. Unlike an analogue front-end, the IQ samples of QBPS aren’t sampled at the same instant, so effects due to the delay are studied. The delay between the I and Q samples is found to cause degradation in Pseudo Random Noise (PRN) correlation peak, which will cause error in position calculation. As the delay is known, the degradation is quantified and a correction is proposed. Once the degradation due to delay is corrected, a novel QBPS design with variable delay is proposed. Simulation and analysis show that variable delay would help relax the narrow quadrature delay requirement for high frequency GNSS signals. It also offers a new way of handling multi-frequency signals by changing the signal and image strength.
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Author(s)
Mookiah, Vaidhya
Supervisor(s)
Dempster, Andrew
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Publication Year
2015
Resource Type
Thesis
Degree Type
Masters Thesis
UNSW Faculty
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