A new multipath mitigation method for GNSS receivers based on antenna array

the potential of small antenna array for multipath mitigation in GNSS systems is considered in this paper. To discriminate the different incoming signals (Line of sight and multipaths), a new implementation of the well known SAGE algorithm is proposed. This allows a significant complexity reduction and it is fully compatible with conventional GNSS receivers. Theoretical study thanks to the Cramer Rao Bound derivation and tracking simulation results (in static and dynamic scenarios) show that the proposed method is a very promising approach for the multipath mitigation problem in GNSS receivers

A new tracking approach for multipath mitigation based on antenna array

In Global Navigation Satellites Systems (GNSS), multipaths (MP) are still one of the major error sources. The additional signal replica due to reflection will introduce a bias in conventional Delay Lock Loops (DLL) which will finally cause a strong positioning error. Several techniques, based on Maximum Likelihood estimation (ML), have been developed for multipaths mitigation/estimation such as the Narrow correlator spacing [1] or the Multipath Estimating Delay-Lock-Loop (MEDLL) [2] algorithm. These techniques try to discriminate the MP from the Line Of Sight Signal (LOSS) on the time and frequency domains and thus, short delay multipaths (<0.1Chips) can not be completely mitigated. Antenna array perform a spatial sampling of the wave front what makes possible the discrimination of the sources on the space domain (azimuth and elevation). As the time-delay domain and space domain can be assumed independent, we can expect to mitigate/estimate very short delay MP by using an antenna array. However, we don't want to increase too much the size, the complexity and the cost of the receivers and thus, we focus our study on small arrays with a small number of antennas: typically a square 2x2 array. Consequently, conventional beamforming (space Fast Fourier Transform) is not directive enough to assure the mitigation of the multipaths, and then this first class of solutions was rejected. In order to improve the resolution, adaptive beamformers have also been tested. However, the LOSS and the MP signal are strongly correlated and thus, classical adaptive algorithms [3] are not able to discriminate the sources. These preliminary studies have shown that the mitigation/estimation of multipaths based on the space domain will exhibit limited performances in presence of close sources. Then, in order to propose robust algorithms, we decided to investigate a space-time-frequency estimation of the sources. Space Alternating Generalized Expectation maximisation (SAGE) algorithm [4], which is a low-complexity generalization of the Expectation Maximisation (EM) algorithm, has been considered. The basic concept of the SAGE algorithm is the hidden data space [4]. Instead of estimating the parameters of all impinging waves in parallel in one iteration step as done by the EM algorithm, the SAGE algorithm estimates the parameters of each signal sequentially. Moreover, SAGE algorithm breaks down the multi-dimensional optimization problem into several smaller problems. In [5], it can be seen that SAGE algorithm is efficient for any multipaths configurations (small relative delays, close DOAs) and space-time-frequency approach is clearly outperforming classical time-frequency approaches. Notwithstanding, SAGE algorithm is a post processing algorithm. Thus, it's necessary to memorise in the receiver the incoming signal in order to apply SAGE estimation. For example, if we want to process 10ms of signal with a 10MHz sampling rate, we need to store a matrix of m*105 with m the number of antennas. In such condition, we can understand than SAGE algorithm is hardly implemented in real time. The challenge is then to find a new type of algorithms that reach the efficiency of the SAGE algorithms, but with a reduced complexity in order to enable real time processing. Furthermore, the implementation should be compatible with conventional GNSS tracking loops (DLL and PLL). To cope with these two constraints, we propose to apply the SAGE algorithm on the post-correlated signal. Indeed, the correlation step can be seen as a compression step and thus, the size of the studied signal is strongly reduced. In such a way, SAGE algorithm is able to provide estimates of the relative delay and Doppler of the received signals with respect to the local replicas. Thus, a post correlation implementation of SAGE can be seen as a discriminator for both the DLL and the PLL

MONITOR Ionospheric Monitoring System: GNSS performance estimation

MONITOR is a project from the European Space Agency’s GNSS Evolutions Programme started in 2010, dedicated to the collection of data and products during active periods of solar activity for later understanding of the impact of ionospheric effects on EGNOS and Galileo system performance. In the frame of this project several tasks have been achieved, in particular the deployment of a network of scintillation receivers (Novatel + Septentrio + GISMO) mainly at low and high latitudes, the development of a real time Central Archiving and Processing Facility (CAPF) and the development of dedicated processors to generate user oriented outputs for TEC, scintillation, and space weather issues. This project, in its new phase started in 2014, is moving forward with an improved and updated scope, addressing in addition to general ionospheric monitoring, the generation of dedicated products and reports to EGNOS system evolution, international collaboration in related ionospheric topics including feasibility studies in Africa. The main new features are: an upgraded data archiving system providing improved accessibility, the integration of data from SAGAIE network from French Space Agency, CNES and the exploitation of its data for new products, new station deployment in regions of interest (mainly in West and Central Africa and in high latitudes in Europe), and the upgrade and development of new products allowing better analysis of geophysical conditions during periods of compromised system performance and service. As an example, the Along Arc TEC Rate (AATR index) is computed routinely, as it has proven to be a clear indicator of ionospheric activity that degrades SBAS system performance. In addition, Monitor already produces VTEC maps (obtained using various techniques and algorithms), several space weather indicators including solar flare detection, ROTI maps, indices related to the quality of measurements and scintillation analysis tools. This paper focuses on the relationship of an SBAS system (EGNOS, WAAS) to the ionosphere’s variability and will analyse in detail the ionospheric parameters leading to a decrease or compromise of system performance. Several case studies will highlight significant EGNOS events for this purpose. The paper will demonstrate how AATR is able to discriminate availability degradation due to ionospheric events from other effects. The ionosphere scintillation aspects and the last developments of the GISM model will also be addressed for this issue.Peer ReviewedPostprint (author's final draft

A new tracking approach for GNSS multipath mitigation based on antenna array

The new SAGE / STAP multicorrelators algorithm was recently proposed proving very good performances in multipath mitigation compared to other techniques such as Narrow correlator or adaptive beamformers. In this paper, the performances of SAGE / STAP multicorrelators in realistic tracking situations are presented, and show very promising results meanwhile real world measurement

A new sensor array receiver for multipath mitigation in GNSS

The use of antenna array for multipaths mitigation in Global Navigation Satellite Systems (GNSS) is considered in this paper. Theoretical studies have shown that using the spatial sampling in combination with time and frequency dimensions can significantly reduce the final position estimation error. However, the lack of practical considerations is still an issue. Technological defaults are usually not taken into account in numerical simulations, and these defaults can seriously degrade the performances of the processing as they modify the amplitude and phase responses of the array. Moreover, implemented algorithms usually result from a trade off between the accuracy and the complexity. This paper aims at presenting two new tools based on antenna arrays for studying the GNSS multipaths mitigation. The first one is a new implementation of the well known Space Alternating Generalized Expectation Maximization algorithm (SAGE). By filtering the multipaths on the space, time and frequency domains, SAGE algorithms can strongly reduce the time-delay estimation error. Nevertheless, SAGE implementation requires high memory and computation capacities, and real time SAGE processing is still not possible. Simulation results show that with the same level of performance, the new implementation of SAGE can reduce the size of the signal and consequently, the memory and computation load requirements. In order to validate the simulation results, CNES and ELTA are developing a new reconfigurable 2×2 array GNSS receiver. Thus, this paper exhibits also the architecture and the specifications of this new array dedicated to offline signal processing

Multipath mitigation methods based on antenna array

The potential of small antenna array (2x2 square) for multipaths (MP) mitigation in GNSS systems is considered in this paper. This study focuses on two different approaches. In the first one, we use antenna array algorithms in order to have a spatial discrimination of the incoming paths. Due to the low directivity of the array, conventional beamforming turns out to be inefficient. Thus, high resolution beamformers have been tested. In the second one, we compare this solution with an approach which uses the spatial sampling in combination with time and frequency dimensions. To discriminate the different incoming signals on the three domains, Space Alternating Generalized Expectation Maximisation (SAGE)algorithm, which is a low-complexity generalization of the Maximum Likelihood maximisation (ML) algorithm, has been considered. Monte Carlo simulations clearly show the superiority of SAGE. Nevertheless, SAGE implementation requires a high memory and computation capacities, and real time SAGE processing is still not possible. In order to reduce these requirements, we investigated a new implementation based on both the correlation properties of the code and the thermal noise. With the same level of performance, the new implementation of SAGE can strongly reduce the size of the signal and consequently, the memory and computation requirements. Thus, this is a promising method to take the advantages of SAGE with reasonable hardware requirements

Physiological Monitoring of a Wrist-Worn Personal Locator Beacon User

This paper presents the concept, developments and preliminary results of the Horizon 2020 project named SAT406M. The goal of this project is to develop an application based on a wrist-worn device, conceived to be a maritime application, and the use of European Global Navigation Satellite Systems, based on the Galileo Search and Rescue service, using its unique Return-Link-Message function, improving the mobility and safety of citizens. In particular for this paper, we focus on the development and the first testing and results of a physiological monitoring component included in the device. This component will provide the Search and Rescue services with additional information about the SAT406M user's physiological status once the distress alarm is triggered. The algorithm implemented uses some stochastic techniques to deduce the SAT406M user's physiological status, encoded in two bits, from sensor inputs. The results here presented, which are still preliminary results from an intermediate stage of the project, show a good accuracy in most of the cases. This makes us conclude that the algorithm has the potential to end up determining the SAT406M user's physiological status accurately enough, improving this way the user's safety