International Global Navigation Satellite Systems Association
IGNSS Conference 2016
Colombo Theatres, Kensington Campus, UNSW Australia
6 – 8 December 2016
Efficient Processing of Long Duration GNSS Signal
Observations for Space Debris Tracking
Md Sohrab Mahmud
UNSW Canberra Australia
+61 470 218 225 md.mahmud@student.adfa.edu.au
Sana Ullah Qaisar
UNSW Canberra Australia
s.qaisar@adfa.edu.au
Craig Benson
UNSW Canberra Australia
c.benson@adfa.edu.au
ABSTRACT
Space debris poses an increasing threat to space assets, and accurate,
affordable tracking of all space objects is necessary to maintain efficient and
safe space operations. Tracking space objects of very small sizes using
GNSS bistatic radar has been proposed as a potential solution. Previous
research efforts have discussed various aspects of the signal processing
required for debris tracking including signal phase stability, viability of the
signal power budget and the ability to isolate the weak reflected signal in the
presence of the much stronger direct signal. A key difficulty of the tracking
operation is that the object track is accurate to the order of a wavelength over
the entire observation period (ten minutes). The computational cost of
performing a large number of very long correlations has been partially
addressed by previous works that show how the signal sampling rate can be
reduced subject to the Nyquist limit of the largest possible Doppler
uncertainty. This work confirms that the computational cost can be reduced
further by exploiting the non-uniform distribution of the Doppler residual
over time. Over most of the observation time, the phase rate of the residual
frequency is very low whereas the region where it is high is known in
advance. The confirmation first considers the basis for reduction of the
signal sampling rates to near the Nyquist limit set by the maximum possible
Doppler but then exploits the knowledge of the non-constant distribution of
Doppler over the observation time to reduce the number of calculations per
integration by more than an order of magnitude. Results are confirmed by
simulation of a realistic scenario. Finally, the trade between losses and
reduction in sampling rate is examined, including plots of integration loss
versus sample rate reduction, and applications of the same principle to other
GNSS processing challenges are discussed.
KEYWORDS: Space Debris, GNSS, Weak Signal, Long Integration, Audio
Processing.
