Interference Mitigation using a Dual-Polarized Antenna: a deep analysis in Space domain and Polarimetric domain

In this work we aim at providing a comprehensive understanding of the behaviour of a Dual-polarized (DP) array in both space and polarimetric domains. Reference paper: M. Sgammini et al., "Interference Mitigation Using a Dual-Polarized Antenna in a Real Environment, " in Proc. of the 29th Int. Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, OR, September 2016

Standardization of New Airborne Multipath Models

In aeronautical navigation the use of Global Navigation Satellite Systems (GNSS) is becoming ever more important. GNSS are one of the cornerstones of the performance based navigation (PBN) concept. They are currently used for navigation en-route, as well as during arrival procedures and for lateral approach guidance. Together with satellite-based or ground-based augmentation systems (SBAS, GBAS) satellite navigation can provide precision approach guidance down to CAT-I minima. In order to ensure sufficient global availability of these services and enable new services, such as Advanced Receiver Autonomous Integrity Monitoring (ARAIM) for providing services with higher performance levels, including in regions with active ionospheric conditions, existing integrity concepts and augmentation systems are upgraded to incorporate not only GPS but multiple GNSS constellations and also navigation signals on a second frequency. On the side of GNSS, all GPS satellites since the Block IIF generation with currently 12 operational satellites provide signals in the L5 band (in addition to the most commonly used signals in the L1 band), a second frequency band usable for aeronautical applications. The Galileo constellation has currently 22 operational satellites in orbit that all provide signals on the E1 and E5a frequency bands. Other constellations, such as Glonass and BeiDou are also launching further satellites so that a large number of navigation satellites are available to users. The use of dual-frequency and multi constellation techniques will mitigate the impact of most ionosphere-related disturbances, significantly increasing service availability. All GNSS-based navigation methods have in common that they need appropriate integrity concepts safely bounding any residual errors that may prevail in the position solution. With the ionospheric errors largely addressed by dual-frequency and multi-constellation methods, the residual noise and multipath becomes the most significant contributor to the residual errors. In order to bound these errors, standardized error models are used. The existing multipath model was developed based on extensive data analysis, however, using only the legacy GPS signal in the L1 band. Galileo is using a different modulation for the E1 signals which is less susceptible to multipath. The GPS and Galileo signals in the L5/E5a band are using a 10-times higher chipping rate than the L1/E1 signal. Therefore, also for these signals, the multipath envelope is significantly smaller, potentially allowing to have smaller error models for these signals. When using dual-frequency methods to remove the ionospheric delay, the receiver tracking noise and multipath error from the signals on both frequencies are combined. For all these cases the existing model is not well suited for error modelling. Within the frame of the DUFMAN project funded by the European Commission new multipath models for the new signals are developed in order to be able to exploit the potential benefits for aviation users. Previous papers on the project were addressing the methodology, described the results of the studies and the influence of the antenna. This paper explains the standardization activities and discusses choices that were made in setting up the data collection campaign and the subsequent steps to standardized models. Regarding standardization, the International Civil Aviation Organization (ICAO) is producing Standards and Recommended Practices (SARPS) for DFMC SBAS which will make use of the DFMC multipath models. Further requirements on the hardware exist e.g. in form of Minimum Operational Performance Standards (MOPS) that specify performance of certain components, such as the airborne antenna. A variety of antennas differing significantly in performance is available on the market. Furthermore, the airborne receiver hardware may use different correlator spacing and receiver bandwidth settings which may also have an impact on the results. In the effort to characterize the multipath errors, hardware and processing choices had to be made taking into account all those requirements and the impact on the final models. The paper discusses the interdependency between different standards and explains the choices that were made in the project, as well as results in terms of standardization

Initial results for dual constellation dual-frequency multipath models

This paper presents an update of the ongoing work to develop dual frequency dual constellation airborne multipath models for Galileo E1, E5a and GPS L1 and GPS L5 in the frame of the project DUFMAN (Dual Frequency Multipath Models for Aviation) funded by the European Commission. The goal of this activity is to support the development and implementation of airborne GNSS-based navigation solutions, such as Advanced Receiver Autonomous Integrity Monitoring (ARAIM), dual-frequency multiconstellation Satellite Based Augmentation System (SBAS) and dual-frequency multi-constellation Ground based Augmentation System (GBAS). Previous work described the methodology proposed to derive the airborne multipath models and presented preliminary multipath models obtained from an experimental installation. In this paper we present the initial results obtained from flight campaigns conducted within DUFMAN on Airbus commercial aircraft. The measurements are collected from prototypes of dual-frequency multi-constellation avionics receiver and the antenna installed on the aircraft has been selected to meet at best the current dual-frequency dual-constellation antenna requirements. In addition to the initial results obtained from avionics hardware, the impact of the different receiver correlator spacing and bandwidth is investigated and discussed

Final results on airborne multipath models for dualconstellation dual-frequency aviation applications

This paper proposes DFMC airborne multipath models and antenna error models derived from measurement and supported by simulations. Based on the data evaluated, new multipath models (including the contribution from the antenna) for Galileo E1 and GPS L1 and Galileo E5a and GPS L5 are discussed. Furthermore, a model for the Ionosphere-Free combination of the signals is proposed

SVD-based RF interference detection and mitigation for GNSS

SVD-based signal detection is already largely used in cognitive radio networks to detect the presence of wireless signal. Anyway some adjustment and sagacity shall be applied when adopting it as RF interference detector in GNSS. Furthermore a SVD-based eigenfilters has been proposed and its capability to mitigate RF interferences has been evaluated. The computational complexity of the whole system is scalable and can be designed to fit the hardware requirements

Blind Adaptive Beamformer Based on Orthogonal Projections for GNSS

The quality of the ranging data provided by a global navigation satellite systems (GNSS) receiver largely depends on the synchronization error, that is, on the accuracy of the propagation time-delay estimation of the line-of-sight (LOS) signal. In case the LOS signal is corrupted by several superimposed delayed replicas (reflective, diffractive, or refractive multipath) and/or additional radio frequency interference (RFI), the estimation of the propagation time-delay and thus the position can be severely degraded using state-of-the-art GNSS receivers. Multi-antenna GNSS receivers enable application of array processing for effective multipath and interference mitigation. Especially, beamforming (spatial filtering) approaches have been studied intensely for GNSS in the past years due to a balanced trade-off between performance and complexity. Usually these beamforming approaches require knowledge of the spatial signature (spatial reference) of the desired signal and thus require detailed knowledge of the direction-of-arrival (DOA) of the LOS signal and/or non-LOS signals, the antenna response, the array geometry, and other hardware biases. Even if the antenna array response can be approximately determined, either by empirical measurements (array calibration) or by making certain assumptions (e.g. identical sensor elements in known locations), the true antenna array response can be significantly different due to for example changes in antenna location, temperature, calibration inaccuracy and the surrounding environment. Thus, robust beamforming algorithms were developed in order to cope with errors in the array response model to be applied to derive the spatial filter. In this work we propose a blind adaptive beamforming approach based on orthogonal projections for GNSS, for which knowledge about the array response and spatial reference for the LOS signal are not required. The proposed approach is capable of adaptively mitigating RFI and multipath components based on orthogonal projections. In order to derive the needed projectors adaptively two eigendecompositions of the estimate of the spatial covariance matrix before (pre-correlation) and after (post-correlation) despreading are performed. Based on these eigendecompositions appropriate estimations of subspaces are achieved in order to derive projectors onto the interference free and multipath free subspaces, respectively. At pre-correlation stage the covariance matrix estimation can be evaluated over a short time interval in order to realize good performance in case of a jammer with a high time-frequency dynamic (e.g. Chirp-like jammer). For the implementation within a real-time receiver, dedicated building-blocks are used. Computation of the covariance matrix and the projection into the interference free subspace is performed by hardware-macros at sampling-rate. In contrast, the eigendecomposition is executed on a processor achieving projector update-rates in the kHz-range. Implementation issues addressing quantization losses related to wordlength configurations for both hardware building-blocks are discussed. Once interfering signals are removed from the input signals, wordlengths can be reduced in order to minimize implementation costs for the subsequent despreading or correlation. Wordlength reduction is realized using a digital automatic gain control (AGC). At post-correlation stage all available degrees of freedom are used for multipath mitigation, noise reduction and further cancellation of residual interferences. After despreading, projection into the multipath free subspace becomes an individual process for each channel of the receiver. Considering the computational load on a navigation processor, this is a very challenging task since covariance matrices and eigendecompositions have to be computed individually for each channel. A cost-analysis in terms of processing cycles on an embedded processor for the covariance matrix computation and eigendecomposition is provided. In addition, the relation between the covariance observation time and multipath mitigation performance are analyzed for selected scenarios. Simulation results show that the proposed blind adaptive beamforming approach based on orthogonal projections achieves effective interference and multipath mitigation capabilities compared to state-of-the-art non-blind beamforming algorithms. The overall complexity required by the blind beamformer is discussed and a feasible hardware implementation is derived. The accuracy and numerical stability of estimation of the spatial covariance matrix before and after despreading are shown for both block interval and recursive estimation methods. Providing costs in terms of computational requirements and navigation performance related to a specific implementation a trade-off between estimation robustness, time-frequency characterization and mitigation capability is derived. Based on this analysis a complete multi-antenna GNSS receiver architecture is proposed taking into account hardware complexity and navigation performance. A software bit accurate representation of the receiver hardware platform is used for performance evaluation. As the proposed blind approach does not require precise a priori information about the DOAs of the LOS (spatial reference) or non-LOS signals and about the antenna array response, robustness with respect to errors in the antenna array response model and additional hardware biases can be achieved without further increase of complexity

Impact of polarization impurity on compact antenna array receiver for satellite navigation systems

We present a decoupled and matched four-element L1-band antenna array with an inter-element separation of a quarter of the free-space wavelength. We study the impact of polarization impurity in terms of the receiver's equivalent carrier-to-interference-plus-noise ratio when impinged with different numbers of diametrically polarized interferers. We observe that strong polarization impurity of the designed circular compact eigenmode antenna array, particularly for the high-order eigenmodes, reduces the available degrees-of-freedom for nulling by half in the presence of linear-polarized interferers with 40-dB interferer-to-signal power ratio

Four-element compact planar antenna array for robust satellite navigation systems

In this paper, we present a four-element compact planar antenna array for global navigation satellite systems. The array is designed for the 1575.42 MHz (L1 band) frequency having an inter-element separation of d = λ/4. In order to compensate mutual coupling and mismatching, a specifically designed decoupling and matching network has been integrated into the array. We investigate the resulting antenna performance, such as axial-ratio bandwidth, and realized gain, as referred to the decoupling and matching network input ports. Furthermore, we present a receiver model to characterize the equivalent spatial carrier-to-interference plus noise ratio of the antenna array, decoupling and matching network, and low-noise amplifier, using a conventional null-constraint beamformer