GNSS Multipath Estimation and Mitigation Using a Rotating Antenna

We describe the experimental framework that we have developed to study the use of synthetic aperture in GNSS receivers to estimate and mitigate multipath interference. By combining the signal received by a single moving antenna during different time instants along a known trajectory, it is possible to per-form spatial filtering on the received signal. Our framework is divided in two parts. First, we modified a software GNSS receiver to implement beamforming and direction of arrival (DoA) algorithms, which have been adapted to work with synthetic aperture, instead of with a fixed antenna array. Second, we built a rotating arm supporting an antenna in order to implement circular trajectories of 0.5 to 1 m radius, and adjustable rotating speeds of up to 1.5 rev/s. Finally, we present an analysis of the performance of the algorithms implemented using real data obtained with our rotating antenna

Carrier Tracking using Extended Kalman Filters for GNSS Synthetic Aperture Processing with a Rotating Antenna

A single GNSS antenna moving along a known trajectory can be used to synthesize a virtual array in order to apply spatial diversity techniques, e.g. beamforming. With these techniques, referred as synthetic aperture (SA) techniques, the receiver can mitigate interfering signals, including multipath. The use of a single antenna element, instead of an antenna array, significantly reduces the hardware complexity, and there is no longer need for precise calibration and system synchronization. Before SA techniques can be used to process the GNSS signal, a critical practical issue must be addressed: the carrier Doppler frequency caused by the antenna motion only, that we have called “relative” Doppler, must be isolated from any other carrier frequency contribution. We have called the sum of all these possible contributions “reference” Doppler. In this paper, we propose two new techniques making use of the so-called extended Kalman filter (EKF), in order to compensate the reference Doppler at the correlation output. The first method, named EKF1, tracks the carrier frequency using a conventional FLL, and then uses its output to feed an EKF responsible for the reference Doppler estimation. The second method, named EKF2, is an ultra-tight integration solution in charge of the carrier tracking, while simultaneously estimating the reference Doppler component from the correlators output. A comparison of these new methods with two previously existing techniques, in terms of their impact on direction-of-arrival estimation techniques, is presented. Synthetic and real GPS L1 C/A signals are used in this comparison.Real signal measurements were obtained using a GPS antenna mounted on a mechanical rotating arm –built in-house– to implement an approximately uniform circular movement

Normalized GNSS Interference Pattern Technique

It is well known that water level and snow height can be monitored with the ground reflectometry GNSS-R approach [1, 2]. In this approach the antenna situated on a mast, receives a direct GNSS signal coming from the satellite and a nadir signal reflected by the observed surface. Assuming that the antenna position is known we can compute the position of the surface of reflection. For water level monitoring and snow determination, this approach provides precise localization and dating of the measures that allows to process spatio-temporal comparison of water level and snow cover, respectively. These parameters are very important for flood monitoring, avalanche prevention, as well as for hydroelectic companies. Furthermore the approach is noninvasive and can be easily implemented on a portable instrument and embedded in a vehicle with a mast. The Interference Pattern Technique considers the behavior of the SNR of the received GNSS signal as a function of the satellite elevation [1]. The received signal is indeed the integration by the antenna of the direct and nadir reflected GNSS signals. Due to their different phase variations, the SNR oscillates at a rate proportional to the height between the antenna and the surface of specular reflection. Unfortunately the measurement is typically very long because it needs to process the SNR for high satellite elevation variations. We indeed need to observe a sufficient number of SNR oscillations to estimate the frequency and derive the surface height. In order to reduce the estimation time to a fraction of one period of the SNR variation, we propose to normalize the measures. The normalization consists in varying the antenna height of a value dh in order to read the minimum and maximum value of SNR for a given satellite elevation, and then in processing with these values the SNR measured for different satellite elevations. We show in this paper that the normalization allows to compute the cosine of the phase delay between the direct and reflected signals and to estimate the signal frequency on a fraction of a period. We also derive the minimum antenna variation range dh as a function of the satellite elevation. We deduce from this function the minimum time of observation as a function of the satellite elevation rate. We derive the exact evolution of the SNR as a function of the signals parameters (Doppler frequency, code delay, CN0) of the visible satellites [3]. The proposed method is assessed on real and synthetic signals

Adaptive Tracking Techniques in Non-Stationary Environments

The continuously changing environments have been the main challenge for classical GNSS receiver implementations, as they can have a great impact on signal tracking performance and positioning. For this reason techniques capable of mitigating the impact of time-varying phenomena by adapting to changing conditions, thus improving performance are of great interest. This study reports the benefits of using adaptive techniques for standalone GNSS receivers in three different scenarios. The first scenario compares an adaptive Kalman filter against a classical DLL/PLL architecture in interference environments with user dynamics. The second scenario uses a multipath propagation channel to test alternative carrier tracking architectures which provide better results in terms of robustness. The third scenario uses the same multipath propagation channel to test the adaptive switching technique, 2-Step, in order to evaluate its capacity of guaranteeing and maintaining unambiguous tracking for BOC-type modulations. In order to assess the performance of these techniques a semi-analytical platform has been used. The results presented here show the benefits and trade-offs of different techniques taking into account different propagation channels and scenarios

Parameter Estimation with GNSS-Reflectometry and GNSS Synthetic Aperture Techniques

Aside from intentional interference, multipath is the most significant error source for Global Navigation Satellite Systems (GNSS) receivers in many operational scenarios. In this thesis, we study the multipath estimation from two different perspectives: to retrieve useful information from it using GNSS-Reflectometry (GNSS-R) techniques; and to mitigate its effects or to estimate its direction-of-arrival (DOA) as well as the line-of-sight (LOS) signal¿s using synthetic aperture (SA) processing. The first part of the thesis focuses on precision bounds for GNSS-R techniques for ground-based receivers, in scenarios where a single antenna simultaneously receives the LOS signal and a specular reflection. First, we derive the Cramér-Rao bound (CRB) of the receiver¿s height and the reflection coefficient, with the latter depending on the surface¿s electrical properties. More specifically, we propose a CRB derivation applicable to GNSS-R techniques that make use of the phase information and long observation times, such as the interference pattern technique (IPT). The derivation is based on the parameter transformation of the Fisher information matrix. We study the dependence of the computed CRB on the scenario and the receiver bandwidth. The CRB results for the simulated scenarios are consistent with the precision reported for many GNSS-R techniques used in these scenarios. The proposed CRB is meant to benchmark and compare new and existing techniques. Besides the derived CRB, we propose an algorithm to obtain the maximum-likelihood (ML) estimator of the parameters of interest with the IPT: the segmented ML estimator (SML). The SML transforms a complex multivariate optimization problem into multiple simpler ones by dividing the parameter search space taking advantage of the cost function¿s particular structure. The SML is validated with simulated signal and asymptotically cross-validates the CRB results. The second part of the thesis is devoted to the study of the SA processing of GNSS signals. The goal is to estimate the DOA of the signals received, and mitigate errors in the navigation solution caused by interfering signals, such as multipath. We start by deriving the CRB for the SA context, as a function of the antenna trajectory. This CRB considers the effect of the antenna complex gain, and we show in simulations that it is possible to achieve meaningful DOA estimation only by changing the antenna¿s orientation. We continue by proposing a development framework built upon a signal tracking architecture integrating SA processing. Before any SA processing, it is necessary to estimate and compensate any carrier phase contribution not related to the antenna motion. To do so, we propose two new sequential techniques based on the extended Kalman filter (EKF): EKF1 and EKF2. Also, we develop an open-loop version of the proposed SA tracking architecture, more robust than its closed-loop counterpart. Finally, we validate the proposed architecture and SA-based techniques with synthetic GPS signals at first, and then with real signals, recorded using an antenna mounted on a mechanical rotating arm. The obtained results validate the implemented techniques and show how the proposed SA architecture can ultimately mitigate the position bias error observed in environments with severe multipath interference

Derivation of the Cramér-Rao Bound in the GNSS-Reflectometry Context for Static, Ground-Based Receivers in Scenarios with Coherent Reflection

The use of the reflected Global Navigation Satellite Systems’ (GNSS) signals in Earth observation applications, referred to as GNSS reflectometry (GNSS-R), has been already studied for more than two decades. However, the estimation precision that can be achieved by GNSS-R sensors in some particular scenarios is still not fully understood yet. In an effort to partially fill this gap, in this paper, we compute the Cramér–Rao bound (CRB) for the specific case of static ground-based GNSS-R receivers and scenarios where the coherent component of the reflected signal is dominant. We compute the CRB for GNSS signals with different modulations, GPS L1 C/A and GPS L5 I/Q, which use binary phase-shift keying, and Galileo E1 B/C and E5, using the binary offset carrier. The CRB for these signals is evaluated as a function of the receiver bandwidth and different scenario parameters, such as the height of the receiver or the properties of the reflection surface. The CRB computation presented considers observation times of up to several tens of seconds, in which the satellite elevation angle observed changes significantly. Finally, the results obtained show the theoretical benefit of using modern GNSS signals with GNSS-R techniques using long observation times, such as the interference pattern technique

Estimation Bounds for GNSS Synthetic Aperture Techniques

This paper characterizes the estimation performance of synthetic aperture (SA) techniques in the context of moving GNSS receivers. Under the assumption of a stationary channel, SA techniques transform a single antenna into a virtual array. We first introduce a model for the GNSS signal received by a single moving antenna. Leveraging this model, SA processing enables direction-of-arrival (DOA) and beamforming on a single antenna. The model does not make use of the narrowband assumption, which makes it suitable for relatively large trajectories. In addition, it includes the effects of the polarization mismatch between the received signal and the receiving antenna. Then, the proposed model is used to derive the Cram´er-Rao lower bound (CRB) for the joint estimation of the received signal amplitudes, synchronization and DOA parameters. We compute the CRB for two different antenna motions, with results depending on the antenna trajectory as well as on the scenario geometry. Results highlight how SA processing profits from spatial and polarization diversities, pointing out its potential for DOA estimation and beamforming applications in moving GNSS platforms, such as unmanned air vehicles or smartphones