Michael Niestroj, Marius Brachvogel, Soeren Schoenbrod, RWTH Aachen University, Chair of Navigation, Germany; Michael Meurer, RWTH Aachen University, Chair of Navigation, and German Aerospace Center (DLR), Institute of Communications and Navigation, Germany

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Abstract:

In the field of positioning and timing for safety critical applications using Global Navigation Satellite System (GNSS), multi antenna systems provide a very effective technique for suppressing interferences, spoofers and multipath signals[1, 2]. However, for many of the used algorithms, the performance is degraded, if the gain and phase characteristics of the individual antenna channels of the multi-antenna radio frequency (RF) system of the receiver differ. This especially holds for all deterministic beamforming and null-steering techniques for spatial or spatial-temporal signal processing which are widely used to counteract interference and multipath. In order to compensate for these differences, a calibration of the transfer characteristics is required. This applies even more, if the modern wideband signals like Galileo E5 Open Service (OS) [3] and E6 [4] or even the protected ones like Global Positioning System (GPS) M-Code or Galileo Public Regulated Service (PRS) are considered. For those, complete transfer functions have to be calibrated due to the large relative bandwidth of the signals compared to the carrier frequency. An in-system calibration hereby allows for a continuous tracking of the transfer characteristics and thus is also applicable in case of frontend parameters, which might vary in time. Such variations may for example result from changes of system temperature, mechanical vibrations or other factors of influence, which may not be completely controlled. In our paper, we present an approach for a blind in-system wideband calibration of the multichannel RF frontend of multi antenna GNSS receivers. This novel calibration scheme uses the available GNSS observations and thus does not require any specific hardware solution for antennas or frontends reducing costs, weight and size.