Conventional Global Navigation Satellite System Research Articles

Integrated study of water levels and water storage variations using GNSS-MR and remote Sensing: A case study of Sarez Lake, the world's Highest-Altitude dammed lake

Sarez Lake, recognized as the world's highest-altitude dammed lake, necessitates meticulous monitoring of dam deformation, lake water levels, and water storage fluctuations to ensure its safety. In pursuit of this critical objective, a Global Navigation Satellite System (GNSS) monitoring network has been established around the lake to compute real-time station coordinates for deformation monitoring. GNSS Multipath Reflectometry (GNSS-MR) technology has been introduced as an innovative approach, enabling water level retrieval through conventional GNSS geodetic receivers. However, the complex and rugged terrain surrounding Sarez Lake poses challenges to the application of GNSS-MR in this region. This research is dedicated to addressing the challenges posed by the limited available elevation range selection and the retrieval of inter-site water level combinations in such demanding terrain. It proposes a novel method for effectively discerning valid Signal-to-Noise Ratio (SNR) arcs and an inter-site inter-signal water level combination retrieval approach, resulting in a continuous sequence of water level retrievals for this region. The incorporation of remote sensing techniques further facilitates the estimation of water storage fluctuations in the area. The outcomes of this study demonstrate the efficacy of GNSS-MR in capturing the lake's seasonal water-level variations, with retrieval uncertainties ranging from centimeters to low decimeters. The fusion of GNSS-MR with remote sensing data offers a comprehensive approach for monitoring the water levels and water storage fluctuations of Sarez Lake within its challenging environmental conditions. This research provides a valuable methodology applicable to the study and monitoring of other dammed lakes.

Enabling the Galileo high accuracy service with open-source software: integration of HASlib and RTKLIB

The Galileo high accuracy service (HAS) is a free-of-charge service designed to deliver decimeter-level accuracy in real-time precise point positioning (PPP) applications using global navigation satellite systems (GNSS). With the intention of facilitating the use of HAS corrections with open access tools, we present the open-source library named HASlib and its integration with another open-source library named RTKLIB. HASlib decodes the Reed–Solomon encoded Galileo E6 navigation data pages and outputs the corrections in commonly used formats. This enables the utilization of HAS with conventional GNSS receivers and PPP engines that lack native support for HAS formats. For instance, the outputs from HASlib enable the use of HAS corrections in RTKLIB. In order to validate this integration, we demonstrate that HAS can allow decimeter-level accuracy using only free-of-charge services and tools. We have obtained a 3D root mean square error below 20 cm (1 sigma) after a convergence time of 10–90 min in Finland. This accuracy has overcome classical real-time solutions with broadcast and satellite-based augmentation system (SBAS) data by one order of magnitude. Compared to post-processed multi-GNSS PPP, HAS corrections required longer convergence times, given the real-time nature. Furthermore, our assessment revealed that the longer convergence time, compared to prior literature, was attributed to RTKLIB filtering procedure and geometry deficiencies in high latitudes. Nevertheless, once convergence was attained, a sub-decimeter level of accuracy was observed in both horizontal and vertical components. These findings highlight the effectiveness of Galileo HAS, HASlib, and RTKLIB as powerful tools for providing open-access to real-time PPP solutions.

Assessment of Multi-GNSS RT-PPP Services for the Antarctic Region

The international service that ensures access to data and products of global navigation satellite systems (GNSSs), known as the IGS, runs a real-time service (RTS) project to support users who need real-time access to precise products. Thanks to the RTS project, it is now possible to obtain real-time precise point positioning (RT-PPP) solutions. RT-PPP can be used in many real-time positioning applications that require a high level of accuracy, efficiency, and flexibility, including earth sciences, atmosphere sciences, marine sciences, natural hazards, and many more. In this study, we tested the impact of different worldwide RTS products and satellite configurations on the performance of RT-PPP accuracy, as well as convergence time, in the Antarctic’s challenging environment and extreme atmospheric conditions. We applied RT-PPP solutions using real-time precise products (satellite orbit/clock corrections, and biases to conduct the real-time PPP) provided by the IGS and NAVCAST (a real-time PPP positioning service) based on different GNSS constellations: GPS-only, Galileo-only, and a combination of GPS and Galileo. In this way, the performance of two different real-time (RT) services was compared with each other. At the same time, the effectiveness of the Galileo global navigation satellite system for RT-PPP was also tested, and the Galileo system’s contribution to the GPS-only RT-PPP solution was investigated. The PPP-WIZARD software was used to process the corrections and GNSS data from a reference station in the Antarctic region. Although GPS-only, Galileo-only, and multi-GNSS solutions obtained from both RT services were found to have very close accuracy to each other, the combination of the GPS and Galileo systems produced better accuracy than when using the GPS system alone. According to the numerical results of this study, it was concluded that the real-time PPP technique gave promising results in such a challenging environment of the Antarctic region. However, we also observe that the RT-PPP technique requires a stable and robust internet connection, which might limit its usefulness in remote regions. Overall, we found the RT-PPP technique to be a viable alternative to conventional relative GNSS positioning techniques, especially in areas where continuously operating reference networks or similar networks are lacking.

On the low-cost asynchronous one-way range measurement method and the device for micro to nano deep space probes

Recent startups and university space activities extend to cis-lunar and near-Earth interplanetary field. One of the biggest hurdles in those missions is in the orbit determination based on the range measurements, while the radio transmission and reception capability becomes within those small organizations' facilities. Also, about the navigation in cis-lunar space, conventional GNSS (Global Navigation Satellite System) real time positioning is hardly available and some alternative methods have been sought. The most straight forward approach is to be supported by the space agencies' facilities for the range measurement with the transponders onboard the probes. However, it depends on the facilities availability and also on the relatively expensive, old and analogue transponders. This paper presents a new method deriving from the GNSS based devices. It does not require the transponders but inexpensive radio circuits easily built. And both the probes and the ground stations have only to be equipped with the common and simple inexpensive devices. The method enables the small organizations to perform autonomous operation of the probes in a distance beyond the moon's orbit. The paper first presents the latest test data obtained during the development using the Software Defined Radio (SDR) boards.

GNSS‐stereo‐inertial SLAM for arable farming

AbstractThe accelerating pace in the automation of agricultural tasks demands highly accurate and robust localization systems for field robots. Simultaneous Localization and Mapping (SLAM) methods inevitably accumulate drift on exploratory trajectories and primarily rely on place revisiting and loop closing to keep a bounded global localization error. Loop closure techniques are significantly challenging in agricultural fields, as the local visual appearance of different views is very similar and might change easily due to weather effects. A suitable alternative in practice is to employ global sensor positioning systems jointly with the rest of the robot sensors. In this paper we propose and implement the fusion of global navigation satellite system (GNSS), stereo views, and inertial measurements for localization purposes. Specifically, we incorporate, in a tightly coupled manner, GNSS measurements into the stereo‐inertial ORB‐SLAM3 pipeline. We thoroughly evaluate our implementation in the sequences of the Rosario data set, recorded by an autonomous robot in soybean fields, and our own in‐house data. Our data includes measurements from a conventional GNSS, rarely included in evaluations of state‐of‐the‐art approaches. We characterize the performance of GNSS‐stereo‐inertial SLAM in this application case, reporting pose error reductions between 10% and 30% compared to visual–inertial and loosely coupled GNSS‐stereo‐inertial baselines. In addition to such analysis, we also release the code of our implementation as open source.

Accuracy of Structure-from-Motion/Multiview Stereo Terrain Models: A Practical Assessment for Applications in Field Geology

We assess the accuracy of Structure-from-Motion/Multiview stereo (SM) terrain models acquired ad hoc or without high-resolution ground control to analyze their usage as a base for inexpensive 3D bedrock geologic mapping. Our focus is on techniques that can be utilized in field projects without the use of heavy and/or expensive equipment or the placement of ground control in logistically challenging sites (e.g., steep cliff faces or remote settings). We use a Terrestrial Light Detection and Ranging (LiDAR) survey as a basis for the comparison of two types of SM models: (1) models developed from images acquired in a chartered airplane flight with ground control referenced by natural objects located on Google Earth scenes; and (2) drone flights with a georeference established solely from camera positions located by conventional, differentially corrected Global Navigation Satellite systems (GNSS). We find that all our SM models are indistinguishable in scale from the LiDAR reference model. The SM models do, however, show rigid body translations and rotations, with translations generally within the 1–5 m size of the natural objects used for ground control, the resolution of the GNSS receivers, or both. The rigid body rotations can be attributed to a poor imaging plan, which can be avoided with survey planning. Analyses of point densities in various models show a limitation of Terrestrial LiDAR point clouds as a mapping base due to the rapid falloff of resolution with distance. In contrast, SM models are characterized by relatively uniform point densities controlled by camera optics, the numbers of images, and the distance from the target. This uniform density is the product of the Multiview stereo step in SM processing that fills areas between key points and is important for bedrock geologic mapping because it affords direct interpretation on a point cloud at a relatively uniform scale throughout a model. Our results indicate that these simple methods allow SM model construction to be accurate to the range of conventional GNSS with resolutions to the submeter, even cm, scale depending on data acquisition parameters. Thus, SM models can, and should, serve as a base for high-resolution geologic mapping, particularly in a steep terrain where conventional techniques fail. Our SM models appear to provide accurate visualizations of geologic features over km scales that allow detailed geologic mapping in 3D with a relative accuracy to the decimeter or centimeter level and absolute positioning in the 2–5 m precision of GNSS; a geometric precision that will allow unprecedented new studies of any geologic system where geometry is the fundamental data.

Stepped-Frequency Binary Offset Carrier Modulation for Global Navigation Satellite Systems

In this paper, we propose Stepped-Frequency Binary Offset Carrier (SFBOC) modulation for Global Navigation Satellite Systems (GNSS) that use spread spectrum signals. SFBOC modulation generates a Binary Offset Carrier (BOC) signal of which the subcarrier frequency varies stepwise within each period of the pseudorandom-noise (PRN) code. The generated SFBOC signal can have a sharp autocorrelation function (ACF) output and an almost flat spectrum over a wide frequency band. These characteristics result in correlation properties, multipath mitigation, and anti-interference that are superior to those of conventional GNSS modulations. To testify, we compare the performance of SFBOC in various aspects to conventional GNSS modulations and other time-varying subcarrier frequency (TVSF) modulations. From numerical simulations, we show that the proposed SFBOC has higher ranging accuracy, lower tracking ambiguity, and more robustness to noise, interference, and multipath than the conventional GNSS modulations. In addition, we demonstrate that the proposed SFBOC moulation has two advantages while other modulations with TVSF cannot have both; that SFBOC is robust to code-Doppler and that, when filterbank is employed, SFBOC improves the signal-to-noise ratio (SNR) significantly without any loss of weak early arrival path in the Non-line of sight (NLOS) multipath environments.

Low-Cost Satellite-Based Correction Service for Precise Point Positioning in Latin America

Global Navigation Satellite Systems (GNSS) applications have been continuously expanding during the last years. When centimeter-level accuracy is required, the use of a single conventional GNSS receiver is not suitable because of the presence of different error sources that degrade the quality of its measurements. Precise Point Positioning (PPP) methods depend on applying corrections to significantly improve the accuracy of a single receiver allowing to obtain centimeter-level performance. This paper focuses on the design of a satellite-based service that broadcast the open access corrections for PPP generated by the International GNSS Service (IGS) being appropriate for real-time applications. The proposed system is based on the Argentinian geostationary satellite ARSAT 2 capable of providing service to Latin America. The system requirements and specifications are defined in order to deliver a good quality of service reducing the complexity and the cost of the users receivers. Thoroughly analyzes and calculations carried out demonstrate that, adopting practical design criteria, a low-cost implementation is possible. We present the main characteristics of the uplink ground station and downlink user receivers. Moreover, different user receiver architectures as well as the design of a simple antenna are proposed. Simulation results using real data show that our solution is able to provide up to centimeter-level accuracy achieving a performance similar to other costly commercial correction services.

GDDS: Python software for GNSS data download

With the rapid development of global navigation satellite system (GNSS), GNSS data products have been widely used for high-precision positioning and navigation applications. They are typically downloaded from the international GNSS service (IGS) analysis centers and continuously operating reference stations (CORS). However, the conventional GNSS data download method is cumbersome, repetitive, and time-consuming, and it is challenging to meet the demands for rapid acquisition of multi-source data products. Therefore, we have developed a GNSS data download software with Python, which provides an interactive interface for the Windows or Linux operating system to realize the efficient and stable download for a large amount of GNSS data. The software includes five main function modules: Global IGS Data, Post-Processing Product, Regional CORS Data, Custom Download, and Data Decompression. It has the characteristics of diverse data products, map interaction support, and station information retrieval, which can meet the needs of different users.

SPWVD-PSD 겹침 이미지를 이용한 전이학습기반 GNSS 재밍식별기법

In this paper, a transfer learning-based global navigation satellite system (GNSS) jamming classification scheme using overlapped images of the smoothed pseudo-Wigner-Ville distribution (SPWVD) and power spectral density (PSD) is proposed. Five types of jamming are considered: amplitude modulation jamming (continuous wave interference), linear chirp jamming, frequency modulation jamming, narrow-band noise jamming, and distance measurement equipment jamming (pulse jamming). The performance of the proposed scheme is shown to be the F1 score and the confusion matrix for pre-mentioned 5 jamming types with no jamming case. A representative conventional transfer learning-based GNSS jamming classification scheme uses a concatenated image comprising a spectrogram, in-phase and quadrature constellation, PSD, and histogram. However, in conventional schemes, the spectrogram

Sensitivity study of fiducial-aided navigation of Unmanned Aerial Vehicles

The possible applications and benefits of autonomous Unmanned Aerial Vehicle (UAV) use in urban areas are gaining considerable attention. Before these possibilities can be realized, it is essential that UAVs be able to navigate reliably and precisely in urban environments. The most common means of determining the location of a UAV is to utilize position measurements from Global Navigation Satellite Systems (GNSS). In urban environments, however, GNSS measurements are significantly degraded due to occlusions and multipath. This research analyzes the use of camera Line-of-Sight (LOS) measurements to self-describing fiducials as a replacement for conventional GNSS measurements. An extended Kalman filter (EKF) is developed and validated for the purpose of combining continuous measurements from an Inertial Measurement Unit (IMU) with the discrete LOS measurements to accurately estimate the states of a UAV. The sensitivity of the estimation error covariance to various system parameters is assessed, including IMU grade, fiducial placement, vehicle altitude, and image processing frequency.

Spatial and Temporal Distributions of Ionospheric Irregularities Derived from Regional and Global ROTI Maps

Major advancements in the monitoring of both the occurrence and impacts of space weather can be made by evaluating the occurrence and distribution of ionospheric disturbances. Previous studies have shown that the fluctuations in total electron content (TEC) values estimated from Global Navigation Satellite System (GNSS) observations clearly exhibit the intensity levels of ionospheric irregularities, which vary continuously in both time and space. The duration and intensity of perturbations depend on the geographic location. They are also dependent on the physical activities of the Sun, the Earth’s magnetic activities, as well as the process of transferring energy from the Sun to the Earth. The aim of this study is to establish ionospheric irregularity maps using ROTI (rate of TEC index) values derived from conventional dual-frequency GNSS measurements (30-s interval). The research areas are located in Southeast Asia (15°S–25°N latitude and 95°E–115°E longitude), which is heavily affected by ionospheric scintillations, as well as in other regions around the globe. The regional ROTI map of Southeast Asia clearly indicates that ionospheric disturbances in this region are dominantly concentrated around the two equatorial ionization anomaly (EIA) crests, occurring mainly during the evening hours. Meanwhile, the global ROTI maps reveal the spatial and temporal distributions of ionospheric scintillations. Within the equatorial region, South America is the most vulnerable area (22.6% of total irregularities), followed by West Africa (8.2%), Southeast Asia (4.7%), East Africa (4.1%), the Pacific (3.8%), and South Asia (2.3%). The generated maps show that the scintillation occurrence is low in the mid-latitude areas during the last solar cycle. In the polar regions, ionospheric irregularities occur at any time of the day. To compare ionospheric disturbances between regions, the Earth is divided into ten sectors and their irregularity coefficients are calculated accordingly. The quantification of the degrees of disturbance reveals that about 58 times more ionospheric irregularities are observed in South America than in the southern mid-latitudes (least affected region). The irregularity coefficients in order from largest to smallest are as follows: South America, 3.49; the Arctic, 1.94; West Africa, 1.77; Southeast Asia, 1.27; South Asia, 1.24; the Antarctic, 1.10; East Africa, 0.89; the Pacific, 0.32; northern mid-latitudes, 0.15; southern mid-latitudes, 0.06.

Area-Efficient Universal Code Generator for Multi-GNSS Receivers

Although conventional global navigation satellite systems (GNSS) receivers were originally designed for single signals, studies on multi-signal receiver design have recently been actively conducted to achieve high accuracy, precision, and reliability. However, in order for a multi-signal receiver to support various codes, the receiver should support the generation of individual codes. Therefore, the resulting problem of increased complexity must be solved. This paper proposes a hardware structure for an area-efficient linear feedback shift register (LFSR)-based multi-frequency universal code generator. Whereas the existing universal code generators were configured so that feedback polynomials, output registers, and initial values can be selected by placing read-only memories (ROMs), multiplexers (MUXs), and exclusive ORs (XORs) by register bit, in the case of the proposed universal code generator; the circuit was implemented by applying the hardwiring technique to those register bits that have fixed values. According to the results of field programmable gate array (FPGA) implementation, the proposed LFSR-based universal code generator can improve look up table (LUT) by up to 37% and register by up to 78% when compared to conventional code generators, and LUT by up to 36% when compared to the previous universal code generator. Therefore, the proposed universal code generator is a good candidate for implementing multi-frequency receivers to achieve high precision and high reliability.

NOANET: A Continuously Operating GNSS Network for Solid-Earth Sciences in Greece

Abstract The NOANET network is a continuously operating high-rate Global Navigation Satellite System (GNSS) network in Greece whose primary role is to enhance and support geophysical research employing GNSS data. This network is operated by the Institute of Geodynamics of the National Observatory of Athens and currently (September 2020) consists of 26 stations, most of which are located close to major seismogenic structures of Greece to optimally measure tectonic and seismically induced motions. All NOANET receivers are configured to record and collect data with a sampling rate of 1 Hz, although some of them also collect data every 5 Hz on their ring buffer. The network is committed to free and open data sharing within the scientific community, and the collected data are made available via the NOANET data repository and distribution point for all interested parties with no limitations. Integrity, validity, and quality checks of the acquired data are performed using a variety of software tools along with in-house developed programs to supervise the network performance and detect ill-formed data and/or awkward station behavior. In addition, the conventional low-rate GNSS observation data of all NOANET stations are routinely processed on a daily basis to supervise their performance through their position time series. Since the beginning of its establishment, the NOANET network has recorded a variety of deformation signals, and a large number of published papers have used GNSS data from stations that are part of NOANET to constrain, model, and interpret the nature of the associated geophysical phenomena.

Navigator Notes

Navigator Notes

The Flexible Microwave Payload-2: A SDR-Based GNSS-Reflectometer and L-Band Radiometer for CubeSats

This article presents the FMPL-2 on board the FSSCat mission, the 2017 ESA Small Sentinel Satellite Challenge and overall Copernicus Masters Competition winner. FMPL-2 is a passive microwave instrument based on a software-defined radio that implements a conventional global navigation satellite system—Reflectometer and an L -band radiometer, occupying 1 U of a 6 U CubeSat. The article describes the FSSC at mission context, the payload design and implementation phases, the tests results in a controlled environment, and finally the calibration algorithms applied to the downloaded data in order to extract the appropriate geophysical parameters: sea-ice coverage, sea-ice thickness (SIT), and low-resolution soil moisture. This article covers the overall payload design, from a high-level block diagram down to single-component specifications from both hardware and software points of view. The main block of the instrument is based on the combination of an FPGA, which virtualizes a dual-core ARM processor, where most of the calculus are performed, and a software-defined radio module, in charge of I/Q data demodulation. The article also explains the design and implementation of a signal conditioning board required for the correct operation and calibration of both instruments.

Single point positioning using full and fractional pseudorange measurements from GPS and BDS

In conventional global navigation satellite system (GNSS) receivers, full pseudorange measurements are usually required to complete a single point position fix, which takes longer time than obtaining fractional pseudorange measurements. In order to shorten the time to first fix and improve the position accuracy during cold or warm start of a dual-constellation GNSS receiver, we propose a positioning algorithm using at least four full pseudorange measurements from one constellation and fractional measurements from either or both constellations. Theoretical rapid position results can be obtained with an identical accuracy to that of the conventional method using full measurements. Tests with simulated and real Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) data validate the performance of the proposed approach.

Augmenting Vehicle Localization by Cooperative Sensing of the Driving Environment: Insight on Data Association in Urban Traffic Scenarios

Precise vehicle positioning is a key element for the development of Cooperative Intelligent Transport Systems (C-ITS). In this context, we present a distributed processing technique to augment the performance of conventional Global Navigation Satellite Systems (GNSS) exploiting Vehicle-to-anything (V2X) communication systems. We propose a method, referred to as Implicit Cooperative Positioning with Data Association (ICP-DA), where the connected vehicles detect a set of passive features in the driving environment, solve the association task by pairing them with on-board sensor measurements and cooperatively localize the features to enhance the GNSS accuracy. We adopt a belief propagation algorithm to distribute the processing over the network, and solve both the data association and localization problems locally at vehicles. Numerical results on realistic traffic networks show that the ICP-DA method is able to significantly outperform the conventional GNSS. In particular, the analysis on a real urban road infrastructure highlights the robustness of the proposed method in real-life cases where the interactions among vehicles evolve over space and time according to traffic regulation mechanisms. Performances are investigated both in conventional traffic-light regulated scenarios and self-regulated environments (as representative of future automated driving scenarios) where vehicles autonomously cross the intersections taking gap-availability decisions for avoiding collisions. The analysis shows how the mutual coordination in platoons of vehicles eases the cooperation process and increases the positioning performance.

Measuring phase scintillation at different frequencies with conventional GNSS receivers operating at 1\xa0Hz

Ionospheric scintillation causes rapid fluctuations of measurements from Global Navigation Satellite Systems (GNSSs), thus threatening space-based communication and geolocation services. The phenomenon is most intense in equatorial regions, around the equinoxes and in maximum solar cycle conditions. Currently, ionospheric scintillation monitoring receivers (ISMRs) measure scintillation with high-pass filter algorithms involving high sampling rates, e.g. 50 Hz, and highly stable clocks, e.g. an ultra-low-noise Oven-Controlled Crystal Oscillator. The present paper evolves phase scintillation indices implemented in conventional geodetic receivers with sampling rates of 1 Hz and rapidly fluctuating clocks. The method is capable to mitigate ISMR artefacts that contaminate the readings of the state-of-the-art phase scintillation index. Our results agree in more than 99.9% within ± 0.05 rad (2 mm) of the ISMRs, with a data set of 8 days which include periods of moderate and strong scintillation. The discrepancies are clearly identified, being associated with data gaps and to cycle-slips in the carrier-phase tracking of ISMR that occur simultaneously with ionospheric scintillation. The technique opens the door to use huge databases available from the International GNSS Service and other centres for scintillation studies. This involves GNSS measurements from hundreds of worldwide-distributed geodetic receivers over more than one Solar Cycle. This overcomes the current limitations of scintillation studies using ISMRs, as only a few tens of ISMRs are available and their data are provided just for short periods of time.

Bayesian fusion of GNSS, ITS-G5 and IR–UWB data for robust cooperative vehicular localization

Abstract In the automotive domain, Cooperative Localization (CLoc) is a new promising paradigm that aims at outperforming conventional Global Navigation Satellite Systems (GNSS) in terms of positioning accuracy, robustness, and service continuity, by relying on Vehicle-to-Vehicle (V2V) communications and hybrid data fusion. However, the growing number and the variety of the sensors aboard vehicles raise unprecedented challenges, especially in the context of distributed fusion approaches. This paper thus compares parametric and nonparametric Bayesian data fusion engines (e.g., based on cooperative variants of the Extended Kalman Filter (EKF) and Particle Filter (PF), respectively), while validating a CLoc scheme suitable to Vehicular Ad Hoc Networks (VANETs). More particularly, absolute position information from both onboard GNSS receiver and ITS-G5 V2V messages, as well as relative distance measurements based on the Impulse Radio–Ultra-Wideband (IR–UWB) technology, are combined into a single location solution that is hopefully more robust and more accurate than that of standalone GNSS. First, we investigate V2V ranging accuracy on a highway under real mobility conditions. In the same environment, we then provide offline validations of CLoc positioning, confirming significant performance gains through cooperation over conventional GNSS, even in case of poor initialization. In this specific context, the PF solution is thus shown to yield even better accuracy in comparison with EKF, thanks to its fine robustness against faced non-linear dynamics and non-Gaussian noise processes. Finally, we illustrate the resilience of the proposed solution under temporary GNSS denial.