An ARAIM adaptation for Kalman Filter

This work propose a new Kalman filter-based method for integrity monitoring, following the solution separation approach of the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm. This method evaluates the separation of state correction using different subsets of measurement to detect abnormalities as well as potential faulty satellites for exclusion. This approach differs from existing Kalman filter-based methods, which use innovation vector or residual vector for stochastic evaluation

Integrity Monitoring Using ARAIM Algorithm in Urban Environment

Aviation is one of the earliest application of the Global Navigation Satellite System (GNSS). Since the early days of the Global Positioning System (GPS), satellite navigation has been an essential part of the aviation industry. Being a particular mean of transport, which usually involves a large number of human lives, civil aviation always requires a high level of reliability from the navigation system. Such requirement brings about the concept of integrity, which concerns about the consistency and reliability of a navigation system, is defined as the capability of the system to provide timely warning when it should not be used for navigation. The concept of integrity allows the standardization of guidance systems' performance, with the utmost purpose of keeping safety for every flight. The concept of integrity has gained interests in other GNSS applications as well, especially in those that also require high reliability from the navigation solution, such as Intelligent Transport System (ITS), railways. This leads to the necessity to adapt the integrity monitoring techniques, in particular the Receiver Autonomous Integrity Monitoring (RAIM) algorithms, to use in working conditions other than the typical airport areas, such as urban environment. As a matter of fact, adaptation of RAIM algorithms to urban environment requires a throughout analysis of the environmental difference of the working condition as well as the requirement of the intended applications. This thesis focuses on developing a Kalman filter-based Advanced RAIM (ARAIM) algorithm for urban environment, which is an adaptation of the conventional ARAIM algorithm for civil aviation. ARAIM algorithm is considered the next generation of RAIM, aiming at providing higher integrity performance for more stringent phase of flight. The first step is to survey the necessary changes to adapt ARAIM algorithm to urban scenario. Experimental study highlights the prerequisite of finding a noise model to represents the signal noise level in urban area. After a suitable noise model was found after a comparative study, the KF-based ARAIM algorithm was developed. This method evaluates the separation of state correction using different subsets of measurement to detect abnormalities as well as potential faulty satellites for exclusion. The proposed method was also validated using simulation and real data. Performance analysis results show that the proposed algorithm can effectively follows the changes of signal quality which is expected to occur frequently when moving in urban environment, confirming its suitability for integrity monitoring in urban environment

Evaluation of advanced receiver autonomous integrity monitoring performance on predicted aircraft trajectories

The development of new GNSS constellations, and the modernization of existing ones, has increased the availability and the number of satellites-in-view, paving the way for new navigation algorithms and techniques. These offer the opportunity to improve the navigation performance while at the same time potentially reducing the support which has to be provided by Ground and Satellite Based Augmented Systems (GBAS and SBAS). These enhanced future capabilities can enable GNSS receivers to serve as a primary means of navigation, worldwide, and have provided the motivation for the Federal Aviation Administration (FAA) to form the GNSS Evolution Architecture Study (GEAS). This panel, formed in 2008, investigates the new GNSS-based architectures, with a focus on precision approach down to LPV-200 operations. GEAS identified ARAIM as the most promising system. The literature, produced through a series of studies, has analysed the performance of this new technique and has clearly shown that the potential of ARAIM architectures to provide the Required Navigation Performance for LPV 200. Almost all of the analysis was performed by simply studying a constellation’s configuration with respect to fixed points on a grid on the Earth’s surface, with full view of the sky, evaluating ARAIM performance from a geometrical point of view and using nominal performance in simulated scenarios lasting several days In this paper, we will evaluate the ARAIM performance in simulated operational configurations. Aircraft flights can last for hours and on-board receivers don’t always have a full view of the sky. Attitude changes from manoeuvers, obscuration by the aircraft body and shadowing from the surrounding environment could all affect the incoming signal from the GNSS constellations, leading to configurations that could adversely affect the real performance. For this reason, the main objective of the algorithm developed in this research project is to analyse these shadowing effects and compute the performance of the ARAIM technique when integrated with a predicted flight path using different combinations of three constellations (GPS, GLONASS and Galileo), considered as fully operational

Integrity monitoring scheme for undifferenced and uncombined multi-frequency multi-constellation PPP-RTK

The precise point positioning (PPP)-based real-time-kinematic (RTK) method attracts increasing attention from both academia and industry because of its potential for high accuracy positioning with a shorter convergence time compared to the traditional PPP. Besides high accuracy, integrity monitoring (IM) is indispensable for safety–critical real-time land vehicle and aviation applications. As the traditional advanced receiver autonomous integrity monitoring (ARAIM) method is designed for (smoothed) pseudorange-based positioning, the complexity of multi-frequency multi-constellation PPP-RTK using carrier phase measurements has not been given sufficient consideration. This study proposes an IM scheme for multi-frequency multi-constellation uncombined PPP-RTK applying the ARAIM theory, with a new comprehensive threat model to accommodate not only pseudorange measurements, but also carrier phase measurements, and other fault events arising from the network corrections that support PPP-RTK. Characteristics of different types of faults are analyzed with the aid of numerical experiments. In addition, the impact of ambiguity-fixed solutions on PPP-RTK integrity performance is investigated. The authors have also conducted case studies, including static and real-kinematic positioning experiments. Experiments have demonstrated that fast convergence in accuracy and the position error bounds, or protection levels, with a given integrity risk, in horizontal position components of PPP-RTK could be achieved. For the open sky environments on a highway, the protection levels estimated by PPP-RTK solutions have the potential to meet the alert limit requirement for road transportation using ambiguity-fixed PPP-RTK positioning under the assumption that the risks of wrong ambiguity fixing are very small and can be ignored

Examples of user algorithms implementing ARAIM techniques for integrity performance prediction, procedures development and pre-flight operations

Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is a new Aircraft Based Augmentation System (ABAS) technique, firstly presented in the two reports of the GNSS Evolutionary Architecture Study (GEAS). The ARAIM technique offers the opportunity to enable GNSS receivers to serve as a primary means of navigation, worldwide, for precision approach down to LPV-200 operation, while at the same time potentially reducing the support which has to be provided by Ground and Satellite Based Augmented Systems (GBAS and SBAS)

On the use of a signal quality index applying at tracking stage level to assist the RAIM system of a GNSS receiver

In this work, a novel signal processing method is proposed to assist the Receiver Autonomous Integrity Monitoring (RAIM) module used in a receiver of Global Navigation Satellite Systems (GNSS) to improve the integrity of the estimated position. The proposed technique represents an evolution of the Multipath Distance Detector (MPDD), thanks to the introduction of a Signal Quality Index (SQI), which is both a metric able to evaluate the goodness of the signal, and a parameter used to improve the performance of the RAIM modules. Simulation results show the effectiveness of the proposed method

On Fault Detection and Exclusion in Snapshot and Recursive Positioning Algorithms for Maritime Applications

Resilient provision of Position, Navigation and Timing (PNT) data can be considered as a key element of the e-Navigation strategy developed by the International Maritime Organization (IMO). An indication of reliability has been identified as a high level user need with respect to PNT data to be supplied by electronic navigation means. The paper concentrates on the Fault Detection and Exclusion (FDE) component of the Integrity Monitoring (IM) for navigation systems based both on pure GNSS (Global Navigation Satellite Systems) as well as on hybrid GNSS/inertial measurements. Here a PNT-data processing Unit will be responsible for both the integration of data provided by all available on-board sensors as well as for the IM functionality. The IM mechanism can be seen as an instantaneous decision criterion for using or not using the system and, therefore, constitutes a key component within a process of provision of reliable navigational data in future navigation systems. The performance of the FDE functionality is demonstrated for a pure GNSS-based snapshot weighted iterative least-square (WLS) solution, a GNSS-based Extended Kalman Filter (EKF) as well as for a classical error-state tightly-coupled EKF for the hybrid GNSS/inertial system. Pure GNSS approaches are evaluated by combining true measurement data collected in port operation scenario with artificially induced measurement faults, while for the hybrid navigation system the measurement data in an open sea scenario with native GNSS measurement faults have been employed. The work confirms the general superiority of the recursive Bayesian scheme with FDE over the snapshot algorithms in terms of fault detection performance even for the case of GNSS-only navigation. Finally, the work demonstrates a clear improvement of the FDE schemes over non-FDE approaches when the FDE functionality is implemented within a hybrid integrated navigation system

GNSS Integrity Monitoring assisted by Signal Processing techniques in Harsh Environments

The Global Navigation Satellite Systems (GNSS) applications are growing and more pervasive in the modern society. The presence of multi-constellation GNSS receivers able to use signals coming from different systems like the american Global Positioning System (GPS), the european Galileo, the Chinese Beidou and the russian GLONASS, permits to have more accuracy in position solution. All the receivers provide always more reliable solution but it is important to monitor the possible presence of problems in the position computation. These problems could be caused by the presence of impairments given by unintentional sources like multipath generated by the environment or intentional sources like spoofing attacks. In this thesis we focus on design algorithms at signal processing level used to assist Integrity operations in terms of Fault Detection and Exclusion (FDE). These are standalone algorithms all implemented in a software receiver without using external information. The first step was the creation of a detector for correlation distortion due to the multipath with his limitations. Once the detection is performed a quality index for the signal is computed and a decision about the exclusion of a specific Satellite Vehicle (SV) is taken. The exclusion could be not feasible so an alternative approach could be the inflation of the variance of the error models used in the position computation. The quality signal can be even used for spoofinng applications and a novel mitigation technique is developed and presented. In addition, the mitigation of the multipath can be reached at pseudoranges level by using new method to compute the position solution. The main contributions of this thesis are: the development of a multipath, or more in general, impairments detector at signal processing level; the creation of an index to measure the quality of a signal based on the detector’s output; the description of a novel signal processing method for detection and mitigation of spoofing effects, based on the use of linear regression algorithms; An alternative method to compute the Position Velocity and Time (PVT) solution by using different well known algorithms in order to mitigate the effects of the multipath on the position domain

Performance of Receiver Autonomous Integrity Monitoring (RAIM) for Maritime Operations

The use of GNSS in the context of maritime applications has evolved during the past. The International Maritime Organization (IMO) has defined and published requirements for those applications. Comparing the requirements on the one hand specified by ICAO and on the other hand by IMO, significant differences get obvious. A major focus is on the evaluation of the performance of the integrity algorithms. Also concept drivers are discussed

Reliable Positioning and Journey Planning for Intelligent Transport Systems

Safety and reliability of intelligent transport systems applications require positioning accuracy at the sub-meter level with availability and integrity above 99%. At present, no single positioning sensor can meet these requirements in particular in the urban environment. Possible sensors that can be used for this task are first reviewed. Next, a suggested integrated system of low-cost real-time kinematic (RTK) GNSS, inertial measurement units (IMU) and vehicle odometer is discussed. To ensure positioning integrity, a method for fault detection in GNSS observations and computation of the protection levels (PL) that bound the position errors at a pre-set risk probability of the integrated sensors are presented. A case study is performed for demonstration. Moreover, to save energy, reduce pollution, and to improve the economy of the trip, proper journey planning is required. A new approach is introduced using 3D city models to predict the route with the best positioning integrity, availability and precision for route selection among different possible routes. The practical demonstration shows that effectiveness of this method. Finally, the potential of using the next generation SBAS for ITS applications was tested using kinematic tests carried out in various environments characterized by different levels of sky-visibility that may affect observations from GNSS