A Software-Based Receiver Sampling Frequency
Calibration Technique and its Application in
GPS Signal Quality Monitoring
Yanhong Kou, Xingyun Zhou, Beihang University, China
Yu Morton, Miami University
Dennis M. Akos, University of Colorado- Boulder
BIOGRAPHY
Yanhong Kou is an associate professor in the School of
Electronic and Information Engineering at Beihang
University, China. She received a Ph.D. in Electrical
Engineering from Beihang University. Her research
interests are in GNSS simulators, high performance
receivers, digital signal processing, and wireless
communication.
Xingyun Zhou is a master degree candidate in the School
of Electronic and Information Engineering at Beihang
University, China. He received a B.S. from Dalian
University of Technology, China in July 2008. His
research interests are in GNSS software receivers.
Dr. Yu (Jade) Morton is a Professor in the Department of
Electrical and Computer Engineering at Miami University.
She holds a PhD in Electrical Engineering from Penn
State. Her current research areas are in software radio
techniques, high performance GPS receiver design, radar
remote sensing and modeling of the ionosphere, and
navigation applications.
Dennis M. Akos completed the Ph.D. degree in Electrical
Engineering at Ohio University within the Avionics
Engineering Center. He has since served as a faculty
member with Luleå Technical University, Sweden, and
then as a researcher with the GPS Laboratory at Stanford
University. Currently he is a faculty member with the
Aerospace Engineering Science Department at the
University of Colorado, Boulder.
ABSTRACT
Due to manufacturing and environmental reasons, a GPS
receiver's actual and manufacturer specified sampling
frequency may differ significantly. Accurate knowledge
of the sampling frequency is fundamental for high
sensitivity and high accuracy receiver signal processing.
Additionally, applications such as pre-correlation signal
quality monitoring employing periodic averaging and
dithered sampling techniques to enhance the signal-to-
noise ratio (SNR) and sampling resolution depend on the
accuracy of the sampling frequency. A refined
mathematical model of software-correlator based receiver
processing in the presence of clock error is established in
the paper, and a novel inline method is presented to
estimate the accurate sampling frequency. The method is
a solely software-based technique requiring no additional
hardware other than the GPS receiver RF front end output
samples. Neither a priori knowledge of the specific
frequency plan of the RF front end circuit nor complex
receiver output data fitting are needed. The impact of the
sampling frequency error on the performance of receiver
signal processing and pre-correlation periodic averaging,
and the performance of the frequency calibration method
are evaluated using simulated signals as well as live GPS
signals collected by GPS data acquisition equipments
manufactured by different vendors. Several experimental
measurements are presented to support the evaluation
including the receiver observables and navigation
solutions, as well as the pre-correlation time domain
waveforms and eye patterns, Power Spectrum Density
(PSD) envelopes, amplitude probability density
histograms, correlation function and S-curve bias after
periodic averaging. Our simulation results show that the
method can calibrate the sampling frequency with an
accuracy resolution down to 10
-9
of the true sampling
frequency online, and the pre-correlation SNR can be
potentially improved by 39dB using periodic averaging.
INTRODUCTION
A digital GPS receiver extracts measurements from the
processing of digitized GPS signals in step with its own
local oscillator [1]. Due to manufacturing and
environmental effects (such as aging, temperature/power
supply fluctuation, platform acceleration, Ionizing
radiation, etc.), the oscillator’s true output frequency often
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