Showing papers on "GNSS augmentation published in 2014"

Centimeter Positioning with a Smartphone-Quality GNSS Antenna

Abstract: This paper demonstrates for the first time that centimeteraccurate positioning is possible based on data sampled from a smartphone-quality Global Navigation Satellite System (GNSS) antenna. Centimeter-accurate smartphone positioning will enable a host of new applications such as globally-registered fiduciary-marker-free augmented reality and location-based contextual advertising, both of which have been hampered by the several-meterlevel errors in traditional GNSS positioning. An empirical analysis of data collected from a smartphone-grade GNSS antenna reveals the antenna to be the primary impediment to fast and reliable resolution of the integer ambiguities which arise when solving for a centimeter-accurate carrierphase differential position. The antenna’s poor multipath suppression and irregular gain pattern result in large timecorrelated phase errors which significantly increase the time to integer ambiguity resolution as compared to even a low-quality stand-alone patch antenna. The time to integer resolution—and to a centimeter-accurate fix—is significantly reduced when more GNSS signals are tracked or when the smartphone experiences gentle wavelength-scale random motion.

A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization

Abstract: Integration of inertial navigation system (INS) and global navigation satellite system (GNSS) is usually implemented in engineering applications by way of Kalman-like filtering. This form of INS/GNSS integration is prone to attitude initialization failure, especially when the host vehicle is moving freely. This paper proposes an online constrained-optimization method to simultaneously estimate the attitude and other related parameters including GNSS antenna's lever arm and inertial sensor biases. This new technique benefits from self-initialization in which no prior attitude or sensor measurement noise information is required. Numerical results are reported to validate its effectiveness and prospect in high accurate INS/GNSS applications.

Method and Apparatus for Improved Navigation of a Moving Platform

Abstract: A navigation module and method for providing an INS/GNSS navigation solution for a moving platform, comprising a receiver for receiving absolute navigational information from an external source (e.g., such as a satellite), means for obtaining speed or velocity information and an assembly of self-contained sensors capable of obtaining readings (e.g., such as relative or non-reference based navigational information) about the moving platform, and further comprising at least one processor, coupled to receive the output information from the receiver, sensor assembly and means for obtaining speed or velocity information, and operative to integrate the output information to produce a navigation solution. The at least one processor may operate to provide a navigation solution by using the speed or velocity information to decouple the actual motion of the platform from the readings of the sensor assembly.

An enhanced MEMS-INS/GNSS integrated system with fault detection and exclusion capability for land vehicle navigation in urban areas

Abstract: We describe an enhanced quality control algorithm for the MEMS-INS/GNSS integrated navigation system. It aims to maintain the system's reliability and availability during global navigation satellite system (GNSS) partial and complete data loss and disturbance, and hence to improve the system's performance in urban environments with signal obstructions, tunnels, bridges, and signal reflections. To reduce the inertial navigation system (INS) error during GNSS outages, the stochastic model of the integration Kalman filter (KF) is informed by Allan variance analysis and the application of a non-holonomic constraint. A KF with a fault detection and exclusion capability is applied in the loosely and tightly coupled integration modes to reduce the adverse influence of abnormal GNSS data. In order to evaluate the performance of the proposed navigation system, road tests have been conducted in an urban area and the system's reliability and integrity is discussed. The results demonstrate the effectiveness of different algorithms for reducing the growth of INS error.

The Effect of Different Global Navigation Satellite System Methods on Positioning Accuracy in Elite Alpine Skiing

Abstract: In sport science, Global Navigation Satellite Systems (GNSS) are frequently applied to capture athletes' position, velocity and acceleration Application of GNSS includes a large range of different GNSS technologies and methods To date no study has comprehensively compared the different GNSS methods applied Therefore, the aim of the current study was to investigate the effect of differential and non-differential solutions, different satellite systems and different GNSS signal frequencies on position accuracy Twelve alpine ski racers were equipped with high-end GNSS devices while performing runs on a giant slalom course The skiers' GNSS antenna positions were calculated in three satellite signal obstruction conditions using five different GNSS methods The GNSS antenna positions were compared to a video-based photogrammetric reference system over one turn and against the most valid GNSS method over the entire run Furthermore, the time for acquisitioning differential GNSS solutions was assessed for four differential methods The only GNSS method that consistently yielded sub-decimetre position accuracy in typical alpine skiing conditions was a differential method using American (GPS) and Russian (GLONASS) satellite systems and the satellite signal frequencies L1 and L2 Under conditions of minimal satellite signal obstruction, valid results were also achieved when either the satellite system GLONASS or the frequency L2 was dropped from the best configuration All other methods failed to fulfill the accuracy requirements needed to detect relevant differences in the kinematics of alpine skiers, even in conditions favorable for GNSS measurements The methods with good positioning accuracy had also the shortest times to compute differential solutions This paper highlights the importance to choose appropriate methods to meet the accuracy requirements for sport applications

The four key challenges of advanced multisensor navigation and positioning

Abstract: The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Although many new navigation and positioning methods have been developed in recent years, little has been done to bring them together into a robust, reliable, and cost-effective integrated system. To achieve this, four key challenges must be met: complexity, context, ambiguity, and environmental data handling. This paper addresses each of these challenges. It describes the problems, discusses possible approaches, and proposes a program of research and standardization activities to solve them. The discussion is illustrated with results from research into urban GNSS positioning, GNSS shadow matching, environmental feature matching, and context detection.

Toward accurate localization in guided transport: combining GNSS data and imaging information

Abstract: Global Navigation Satellite Systems (GNSS) are widely spread (with Global Positioning System - GPS) in intelligent transport systems and offer a low cost, continuous and global solution for positioning. Unfortunately, urban users are often the most demanding of accurate localization but receive a degraded service because of signal propagation conditions. Several mitigation solutions can be developed. We propose, within CAPLOC project (2010-2013) to deal with inaccuracy by associating image processing techniques and signal propagation knowledge. In this paper, we focus on the contribution of image processing in more accurate position estimation. Thus, we use a laboratory vehicle, which is equipped with a fisheye camera and two GNSS receivers. The camera is located on the roof and oriented upwards to capture images of the sky. The GNSS receivers are used to obtain raw data, the position of the vehicle and the reference trajectory. The proposed approach consists in determining where satellites are located in the fisheye image, and then excluding those located in non-sky regions when calculating the position. For that, the strategy is based on an image simplification step coupled with a pixels classification. The image-based exclusion procedure is compared with the classical one based on the application of a threshold on carrier-to-noise (CN0) ratio to separate LOS and NLOS signals. Accuracy improvement is satisfying with the CN0-based method and show an improvement from 13m to 4,5m. Image-based detection shows mixed improvements but promising: good in a static area and too harsh in another configuration of the scenario.

Bayesian Localization and Mapping Using GNSS SNR Measurements

Abstract: In urban areas, GNSS localization quality is often degraded due to signal blockage and multi-path reflections. When several GNSS signals are blocked by buildings, the remaining unblocked GNSS satellites are typically in a poor geometry for localization (nearly collinear along the street direction). Multi-path reflections result in pseudo range measurements that can be significantly longer than the line of sight path (true range) resulting in biased geolocation estimates. If a 3D map of the environment is available, one can address these problems by evaluating the likelihood of GNSS signal strength and location measurements given the map. We present two approaches based on this observation. The first is appropriate for cases when network connectivity may be unavailable or undesired and uses a particle filter framework that simultaneously improve both localization and the 3D map. This approach is shown via experiments to improve the map of a section of a university campus while simultaneously improving receiver localization. The second approach which may be more suitable for smartphone applications assumes that network connectivity is available and thus a software service running in the cloud performs the mapping and localization calculations. Early experiments demonstrate the potential of this approach to significantly improve geo-localization accuracy in urban areas.

Selective Integration of GNSS, Vision Sensor, and INS Using Weighted DOP Under GNSS-Challenged Environments

Abstract: Accurate and precise navigation solution can be obtained by integrating multiple sensors such as global navigation satellite system (GNSS), vision sensor, and inertial navigation system (INS). However, accuracy of position solutions under GNSS-challenged environment occasionally degrades due to poor distributions of GNSS satellites and feature points from vision sensors. This paper proposes a selective integration method, which improves positioning accuracy under GNSS-challenged environments when applied to the multiple navigation sensors such as GNSS, a vision sensor, and INS. A performance index is introduced to recognize poor environments where navigation errors increase when measurements are added. The weighted least squares method was applied to derive the performance index, which measures the goodness of geometrical distributions of the satellites and feature points. It was also used to predict the position errors and the effects of the integration, and as a criterion to select the navigation sensors to be integrated. The feasibility of the proposed method was verified through a simulation and an experimental test. The performance index was examined by checking its correlation with the positional error covariance, and the performance of the selective navigation was verified by comparing its solution with the reference position. The results show that the selective integration of multiple sensors improves the positioning accuracy compared with nonselective integration when applied under GNSS-challenged environments. It is especially effective when satellites and feature points are posed in certain directions and have poor geometry.

P-RANSAC: An Integrity Monitoring Approach for GNSS Signal Degraded Scenario

Abstract: Satellite navigation is critical in signal-degraded environments where signals are corrupted and GNSS systems do not guarantee an accurate and continuous positioning. In particular measurements in urban scenario are strongly affected by gross errors, degrading navigation solution; hence a quality check on the measurements, defined as RAIM, is important. Classical RAIM techniques work properly in case of single outlier but have to be modified to take into account the simultaneous presence of multiple outliers. This work is focused on the implementation of random sample consensus (RANSAC) algorithm, developed for computer vision tasks, in the GNSS context. This method is capable of detecting multiple satellite failures; it calculates position solutions based on subsets of four satellites and compares them with the pseudoranges of all the satellites not contributing to the solution. In this work, a modification to the original RANSAC method is proposed and an analysis of its performance is conducted, processing data collected in a static test.

GNSS integration with vision-based navigation for low GNSS visibility conditions

Abstract: In urban canyons, buildings and other structures often block the line of sight of visible Global Navigation Satellite System (GNSS) satellites, which makes it difficult to obtain four or more satellites to provide a three-dimensional navigation solution. Previous studies on this operational environment have been conducted based on the assumption that GNSS is not available. However, a limited number of satellites can be used with other sensor measurements, although the number is insufficient to derive a navigation solution. The limited number of GNSS measurements can be integrated with vision-based navigation to correct navigation errors. We propose an integrated navigation system that improves the performance of vision-based navigation by integrating the limited GNSS measurements. An integrated model was designed to apply the GNSS range and range rate to vision-based navigation. The possibility of improved navigation performance was evaluated during an observability analysis based on available satellites. According to the observability analysis, each additional satellite decreased the number of unobservable states by one, while vision-based navigation always has three unobservable states. A computer simulation was conducted to verify the improvement in the navigation performance by analyzing the estimated position, which depended on the number of available satellites; additionally, an experimental test was conducted. The results showed that limited GNSS measurements can improve the positioning performance. Thus, our proposed method is expected to improve the positioning performance in urban canyons.

A Novel Angle Computation and Calibration Algorithm of Bio-Inspired Sky-Light Polarization Navigation Sensor

Abstract: Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.

An overview of GNSS remote sensing

Abstract: The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters.

Methods of goodness of fit for GNSS interference detection

Abstract: The number of applications based on Global Navigation Satellite System (GNSS) technology is constantly increasing; consequently, the requirements related to signal quality are becoming more and more important. This paper exploits results of the decision theory, aiming at investigating the performance of the goodness of fit test when applied to interference detection in GNSS receivers. It proposes two versions of a signal quality monitoring algorithm: one working exclusively precorrelation, the other providing postcorrelation information as well.

A Comprehensive Method for GNSS Data Quality Determination to Improve Ionospheric Data Analysis

Abstract: Global Navigation Satellite Systems (GNSS) are now recognized as cost-effective tools for ionospheric studies by providing the global coverage through worldwide networks of GNSS stations. While GNSS networks continue to expand to improve the observability of the ionosphere, the amount of poor quality GNSS observation data is also increasing and the use of poor-quality GNSS data degrades the accuracy of ionospheric measurements. This paper develops a comprehensive method to determine the quality of GNSS observations for the purpose of ionospheric studies. The algorithms are designed especially to compute key GNSS data quality parameters which affect the quality of ionospheric product. The quality of data collected from the Continuously Operating Reference Stations (CORS) network in the conterminous United States (CONUS) is analyzed. The resulting quality varies widely, depending on each station and the data quality of individual stations persists for an extended time period. When compared to conventional methods, the quality parameters obtained from the proposed method have a stronger correlation with the quality of ionospheric data. The results suggest that a set of data quality parameters when used in combination can effectively select stations with high-quality GNSS data and improve the performance of ionospheric data analysis.

Adaptive robust ultra-tightly coupled global navigation satellite system/inertial navigation system based on global positioning system/BeiDou vector tracking loops

Abstract: With the development of global navigation satellite system (GNSS), the GNSS/inertial navigation system (INS) integrated system offers the users better positioning or navigation performance. This paper proposes an adaptive robust ultra-tightly coupled GNSS/INS system based on a novel vector tracking strategy for combining both global positioning system (GPS) L1 and BeiDou B1 signals' tracking together. The inherent mechanism of the vector tracking approach has been analysed to describe the relationship between the replica signals and user's dynamic state. Then, an adaptive robust filter is used to gain the accurate estimates of vehicle states when the vehicle is under a weak-signal or large manoeuvring environment. Finally, the experimental platform is set up using a GPS/BeiDou signal simulator and an inertial measurement unit simulator and the test results show that the proposed ultra-tightly coupled system can keep the tracking loops from the high dynamic perturbations, which saves the cost time of signal reacquisition. Moreover, the presented adaptive robust ultra-tightly coupled system can obtain a higher accuracy than Kalman filtering in a simultaneous weak-signal and large manoeuvring environment.

A novel local integrity concept for GNSS receivers in urban vehicular contexts

Abstract: This paper proposes a novel concept of “local integrity” suitable to Global Navigation Satellite System (GNSS) receivers in urban vehicular scenarios. The idea is to take into account not only the system, but also the environment nearby the receiver in its nominal conditions, exploiting the potentialities offered by a Vehicular Ad-hoc Network (VANET) infrastructure. In detail, the potential availability of multiple observations of GNSS signals, taken by different vehicles participating to a VANET, can be shared and combined in order to implement a collaborative spatial/temporal characterization and prediction of the local degradations of the GNSS signals. These concepts are intended to pave the way for the reconsideration/redefinition of the classic GNSS integrity concept, in order to overcome the major problems and limitations to its applicability in urban vehicular scenarios. The analytical development of the proposed methodology and the suitable network architecture for its implementation, as well as some validation results, are presented and discussed in the paper.

Novel ionospheric activity indicator specifically tailored for GNSS users

Abstract: This work introduces a novel ionospheric activity indicator useful for identifying disturbed periods affecting performance for GNSS users, at regional level This indicator is based in the “Along Arc TEC Rate (AATR) and can be easily computed from GNSS data The AATR indicator has been assessed over more than one Solar Cycle (2002-2013) involving 140 receivers distributed world-wide Results show that it is well correlated with the ionospheric activity and, unlike other global indicators linked to the geomagnetic activity (ie DST, Ap), it is sensitive to regional behaviour the ionosphere and identifies specific effects on GNSS users Moreover from a devoted analysis of EGNOS performances in different ionospheric conditions, it follows that the AATR indicator is able to predict SBAS user availability anomalies linked to the ionosphere The AATR indicator has been chosen as the metric to characterise the ionosphere operational conditions in the frame of EGNOS activities This indicator has been also proposed for joint analysis in the International SBAS-Ionosphere Working Group

Software Defined Radio technology for GNSS receivers

Abstract: The Software Defined Radio (SDR) technology, applied to the reception of Global Navigation Satellite Signals (GNSS), allows the implementation of a positioning device with a high flexibility level. The advantage is twofold: not only the GNSS SDR receiver can be easily updated during its operational life, but it becomes an outstanding tool in prototyping innovative algorithms for signal processing and signal quality monitoring. These aspects have been the key-drivers to the implementation of the NGene fully software receiver, developed by the NavSAS group in Torino. This paper exemplifies some of the opportunities opened by SDR in the field of GNSS receivers.

Car navigation system and method in which global navigation satellite system (gnss) and dead reckoning (dr) are merged

Abstract: Disclosed is a car navigation system and method. The present invention includes a sensor unit including a plurality of sensors, each, configured to measure a state of a vehicle using a predetermined scheme and to obtain sensor data; a vehicle to everything (V2X) unit configured to receive the sensor data from the sensor unit, and including a global navigation satellite system (GNSS) module to thereby receive a satellite signal and to generate GNSS data; and a position estimator configured to receive the sensor data and the GNSS data from the V2X unit, to evaluate an accuracy of each of the sensor data and the GNSS data using a predetermined scheme, and to obtain position coordinates of the vehicle by merging GNSS position coordinates obtained from the GNSS data and dead reckoning (DR) position coordinates obtained from the sensor data based on the evaluation result.

GNSS Accuracy Improvement Using Rapid Shadow Transitions

Abstract: Receiver modules in Global Navigation Satellite Systems (GNSS) are capable of providing positioning and velocity estimations that are sufficiently accurate for the purpose of road navigation. However, even in optimal open-sky conditions, GNSS-based positioning carries an average error of 2–4 m. This imposes an effective limitation on GNSS-based vehicle lane detection, a desired functionality for various navigation and safety applications. In this paper, we present a novel framework for lane-level accuracy using GNSS devices and 3-D shadow matching. The suggested framework is based on detection and analysis of rapid changes in navigation satellites' signal strength, which are caused by momentary blockages due to utility and light poles. A method for detecting such momentary changes between line of sight and non line of sight is presented, followed by a geometric algorithm that improves location accuracy of commercial GNSS devices. We have tested the framework's applicability using both simulations and field experiments. We provide the results of these tests and discuss receiver-side sampling rate requirements for high-performance lane-level positioning.

Use of weak GNSS signals in a mission to the moon

Abstract: According to the European Space Agency (ESA) Lunar Exploration program, the use of GNSS weak-signal navigation in future lunar exploration missions has the potential to increase the robustness of the navigation during all mission phases and improve considerably its autonomy The major objectives of the ESA Moon-GNSS project have been to determine the feasibility of using GNSS (GPS/Galileo) weak-signal technology in future lunar missions to improve the navigation performance in terms of accuracy, cost reduction and autonomy The Moon mission scenario is very challenging for the GNSS signals processing: less visibility compared to an Earth-based receiver, low signal strength, poor satellite geometry, Earth and Moon signal occultation, and spacecraft dynamics The identification of the Moon-GNSS navigation receiver requirements for the upcoming lunar exploration missions has been performed The impact of the receiver requirements on the Moon-GNSS receiver module architecture and algorithms has been analyzed (weak signal processing, filtering and navigation), including an overview of the state of the art space-borne GNSS receivers Besides, the synergies between GNSS signal/navigation processing and other navigation sensors (ie accelerometers, optical camera, laser altimeter) have been analyzed, using the state of the art of sensors integration for space missions A demonstrator of the weak-signal Moon-GNSS navigation has been designed and implemented, showing the main functional and performance capabilities of the Moon-GNSS receiver A test campaign representative of a real Moon-GNSS mission has been carried out, covering all the mission phases of the real mission conditions in terms of dynamics and signal disturbances, for different configurations: standard sensors, standard sensors plus GNSS and stand-alone GNSS navigation

Instantaneous GPS/Galileo/QZSS/SBAS Attitude Determination: A Single-Frequency (L1/E1) Robustness Analysis under Constrained Environments

Abstract: The augmentation of new global navigation satellite systems (GNSS) to existing GPS enhances the availability of satellite based positioning, navigation, and timing (PNT) solutions. Among existing systems, the European Galileo system, the Japanese quasi-zenith satellite system (QZSS), and satellite based augmented systems (SBAS) share at least one frequency (L1/E1) with GPS. In this contribution we analyse the robustness of single-frequency instantaneous carrier-phase attitude determination using data from some or all of the four systems GPS/Galileo/QZSS/SBAS. The performance of the constrained (C)-LAMBDA method is studied under various satellite deprived environments and compared to that of the standard LAMBDA method, using L1/E1 data that was observed for ten days at Curtin University, Perth, Australia. The results demonstrate the enhanced robustness that combinations of the four systems bring to single-epoch single-frequency attitude determination. Copyright © 2014 Institute of Navigation.

External gnss receiver module with motion sensor suite for contextual inference of user activity

Abstract: A method for contextual inference of user activity is disclosed In one embodiment, an indication of the motion of a pole mounted sensing device comprising at least one motion sensor and a Global Navigation Satellite System (GNSS) receiver configured to at least generate raw GNSS observables is received from the at least one motion sensor The indication of the motion of the pole mounted sensing device is correlated with an operation defined in a gesture library regarding GNSS data collect by the GNSS receiver at a time when the indication of the motion is detected The indication and the GNSS data are stored

Bayesian GNSS/IMU tight integration for precise railway navigation on track map

Abstract: The localization of a train on a railway network with onboard sensors has been usually tackled by matching an estimated position fix on a track map. In this paper, we face the navigation problem directly in the topological domain of the map without computing an initial global position. We develop a tightly coupled scheme to fuse the raw measurement of Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU) and the information of a digital track map. We model this problem using a Dynamic Bayesian Network (DBN) and we derive a particle filter to handle the discrete and nonlinear nature of the map in the estimation process and to detect the correct path after a train switch. Real measurements are finally used to test the method and analyze the role of raw GNSS measurements and satellite geometry in precision. Results suggest that reliable navigation can be achieved even when less than four satellites are in view.

Performance analysis of duty-cycle power saving techniques in GNSS mass-market receivers

Abstract: The scope of this work is the analysis and assessment of power saving duty cycle techniques for GNSS receivers. One of the key design drivers of mass-market commercial GNSS devices is indeed power consumption. Different techniques are analyzed and a particular method, based on the alternation of active and sleep states, is implemented in a software receiver based on open-loop processing. The main issues related to the parameters re-initialization after the sleep state are described and a solution is proposed. Then, accuracy and performance are evaluated, for different signal power and in three different scenarios, simulating a static, a pedestrian and an automotive user. Results prove the good accuracy of the technique proposed in all conditions, confirming its validity also for applications different from the consumer market.

Avionics-Based GNSS Integrity Augmentation for Unmanned Aerial Systems Sense-and-Avoid

Abstract: This paper investigates the synergies between a GNSS Avionics Based Integrity Augmentation (ABIA) system and a novel Unmanned Aerial System (UAS) Sense-and-Avoid (SAA) architecture for cooperative and non-cooperative scenarios. The integration of ABIA with SAA has the potential to provide an integrity-augmented SAA solution that will allow the safe and unrestricted access of UAS to commercial airspace. The candidate SAA system uses Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) for the cooperative case. In the non-cooperative scenario, the system employs navigation-based image stabilization with image morphology operations and a multi-branch Viterbi filter for obstacle detection, which allows heading estimation. The system utilizes a Track-to-Track (T3) algorithm for data fusion that allows combining data from different tracks obtained with FLS and/or ADS-B depending on the scenario. Successively, it utilizes an Interacting Multiple Model (IMM) algorithm to estimate the state vector allowing a prediction of the intruder trajectory over a specified time horizon. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuver is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole SAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Various simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented SAA (IAS) architecture. The selected host platform was the AEROSONDE Unmanned Aerial Vehicle (UAV) and the simulation cases addressed a variety of cooperative and non-cooperative scenarios in a representative cross-section of the AEROSONDE operational flight envelope. The simulation results show that the proposed IAS architecture is an excellent candidate to perform high-integrity Collision Detection and Resolution (CD&R) utilizing GNSS as the primary source of navigation data, providing solid foundation for future research and developments in this domain.

Accuracy of single receiver static GNSS measurements under conditions of limited satellite availability

Abstract: At least two simultaneously operating receivers are required for differential global navigation satellite system (GNSS) positioning. In this mode, the systematic errors between stations can be estimated or reduced in order to achieve much higher accuracy. Precise point positioning (PPP) is a rather new category. PPP is a combination of the original absolute positioning concept and differential positioning techniques. In PPP we use observation data of a single receiver and additional information on individual GNSS errors derived from a GNSS network, usually from ground based augmentation systems (GBAS). GBAS systems can be divided by the area of operation into global, continental, national or regional ground support systems (e.g. ASG-EUPOS, CORS, SAPOS, SWEPOS). GBAS systems allow users with a single receiver to position in differential mode based on observations from the reference stations. This paper presents an analysis of the position determination accuracy using single receiver GNSS measurements condu...

Performance assessment of pulse blanking mitigation in presence of multiple Distance Measuring Equipment/Tactical Air Navigation interference on Global Navigation Satellite Systems signals

Abstract: It is known that the Aeronautical Radio Navigation Systems sharing the Global Navigation Satellite Systems (GNSS) frequency band represent a threat to the satellite-based navigation services. Distance Measuring Equipment (DME) and Tactical Air Navigation (TACAN) systems broadcast strong pulsed ranging signals within the Global Positioning System L5 and Galileo E5a frequency bands where the aviation positioning aids services are allocated. This study provides an experimental assessment of the DME/TACAN interference effect on the GNSS receivers performance in scenarios where the presence of several transmitters in view generates radio-frequency interference hard to mitigate by means of the classical solutions. In detail, analysis in terms of the receiver performance will be presented by showing the effect of the non-ideal pulse blanking on the GNSS signal quality. The optimal set-up of the mitigation process, investigated by means of a software simulation, is provided.