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GNSS augmentation

About: GNSS augmentation is a research topic. Over the lifetime, 2478 publications have been published within this topic receiving 28513 citations. The topic is also known as: SBAS & Satellite Based Augmentation System.


Papers
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Journal ArticleDOI
TL;DR: In this article, extreme spatial gradients in ionospheric total electron content (TEC) were observed on 8 April 2008 at Ishigaki (24.3°N, 124.2°E, +19.6° magnetic latitude), Japan.
Abstract: Associated with plasma bubbles, extreme spatial gradients in ionospheric total electron content (TEC) were observed on 8 April 2008 at Ishigaki (24.3°N, 124.2°E, +19.6° magnetic latitude), Japan. The largest gradient was 3.38 TECU km −1 (total electron content unit, 1 TECU = 10 16 el m −2 ), which is equivalent to an ionospheric delay gradient of 540 mm km −1 at the GPS L1 frequency (1.57542 GHz). This value is confirmed by using multiple estimating methods. The observed value exceeds the maximum ionospheric gradient that has ever been observed (412 mm km −1 or 2.59 TECU km −1 ) to be associated with a severe magnetic storm. It also exceeds the assumed maximum value (500 mm km −1 or 3.08 TECU km −1 ) which was used to validate the draft international standard for Global Navigation Satellite System (GNSS) Ground-Based Augmentation Systems (GBAS) to support Category II/III approaches and landings. The steepest part of this extreme gradient had a scale size of 5.3 km, and the front-normal velocities were estimated to be 71 m s −1 with a wavefront-normal direction of east-northeastward. The total width of the transition region from outside to inside the plasma bubble was estimated to be 35.3 km. The gradient of relatively small spatial scale size may fall between an aircraft and a GBAS ground subsystem and may be undetectable by both aircraft and ground.

17 citations

Journal ArticleDOI
TL;DR: In this paper, a carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs is presented, where recursive optimal estimation algorithms are developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations).
Abstract: This paper presents the second part of the research activity performed by Cranfield University to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicles (UAVs). This part focuses on carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro-Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD) sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

17 citations

Journal ArticleDOI
TL;DR: This paper describes a new approach to achieve observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas.
Abstract: There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).

17 citations

Journal Article
TL;DR: This novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).
Abstract: This paper presents a novel Global Navigation Satellite System (GNSS) Avionics Based Integrity Augmentation (ABIA) system architecture suitable for civil and military air platforms, including Unmanned Aircraft Systems (UAS). Taking the move from previous research on high-accuracy Differential GNSS (DGNSS) systems design, integration and experimental flight test activities conducted at the Italian Air Force Flight Test Centre (CSVRSV), our research focused on the development of a novel approach to the problem of GNSS ABIA for mission- and safety-critical air vehicle applications and for multi-sensor avionics architectures based on GNSS. Detailed mathematical models were developed to describe the main causes of GNSS signal outages and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system is able to generate integrity cautions (predictive flags) and warnings (reactive flags), as well as providing steering information to the pilot and electronic commands to the aircraft/UAS flight control systems. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In other words, this novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).

17 citations

Patent
Jeyhan Karaoguz1, Charles Abraham1, Mark Buer1, David Garrett1, David Lundgren1, David Murray1 
26 Mar 2010
TL;DR: In this article, a GNSS enabled mobile device moves from a first area where GNSS signal quality and/or level is above a threshold to a second area where the signal quality or level is below a threshold.
Abstract: A GNSS enabled mobile device moves from a first area where GNSS signal quality and/or level is above a threshold to a second area where GNSS signal quality and/or level is below the threshold. The GNSS enabled mobile device in the second area determines its own location utilizing previous GNSS measurements in the first area. GNSS signals are received to calculate GNSS measurements whenever the GNSS enabled mobile device is in the first area. The calculated GNSS measurements are utilized to determine a location of the GNSS enabled mobile device within the first area. The GNSS enabled mobile device in the second area utilizes the most current GNSS measurements in the first area to determine its own location. Sensors such as an image sensor, a light sensor, an audio sensor and/or a location sensor are used to refine the location of the GNSS enabled mobile device in the second area.

17 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023122
2022266
202144
202062
201956
201851