Global Navigation Satellite Systems Fault Detection and Exclusion: A Parameterized Quadratic Programming Approach

This paper evaluates the potential capacity of Receiver Autonomous Integrity Monitoring (RAIM) algorithms for Global Positioning System (GPS) and GPS Aided GEO Augmented Navigation (GAGAN) to support approach and landing phases of flight with vertical guidance. As the traditional RAIM does not support vertical guidance, Advanced RAIM (ARAIM) with potential to achieve worldwide coverage of vertical guidance, is used. These algorithms have focused on the Horizontal Protection Level (HPL) and Vertical Protection Level (VPL). User position is computed by detecting and excluding faults within the navigation solution and position accuracies are also provided. It is found that using RAIM, Position Dilution of Precision (PDOP) mean was good (1.5674) and Position Error (PE) was estimated to be 9.4042m with Fault Detection and Exclusion (FDE) implementation. While on the other hand, to increase horizontal and vertical accuracies, Advanced RAIM algorithm is implemented using GPS and GAGAN data. In case of GPS, Horizontal Protection Error (HPE) mean is 32.8541m and Vertical Protection Error (VPE) mean is 19.9901m. In case of GAGAN, HPE mean is 2.7190m and VPE mean is 3.3010m, thus achieving 95 percent accuracy requirement.

Currently, global navigation satellite system (GNSS) receivers can provide accurate and reliable positioning service in open-field areas. However, their performance in the downtown areas of cities is still affected by the multipath and none-line-of-sight (NLOS) receptions. This paper proposes a new positioning method using 3D building models and the receiver autonomous integrity monitoring (RAIM) satellite selection method to achieve satisfactory positioning performance in urban area. The 3D building model uses a ray-tracing technique to simulate the line-of-sight (LOS) and NLOS signal travel distance, which is well-known as pseudorange, between the satellite and receiver. The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange. The measurement of the satellite will be excluded if the simulated and raw pseudoranges are inconsistent. Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal. According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

Several layers of defense can be implemented in a Global Navigation Satellite System (GNSS) receiver to improve its performance in the presence of interference. These layers include the use of pre-correlation mitigation techniques, post-correlation quality indicators to screen measurements and Fault Detection and Exclusion (FDE) at the position solution level. This paper provides a characterization of the interaction between these layers of interference mitigation and measurement quality check. Data collected in the presence of increasing power jamming levels have been processed using different interference mitigation techniques, including Robust Interference Mitigation (RIM) and the Adaptive Notch Filter (ANF). A Software Defined Radio (SDR) approach has been adopted and measurements were generated considering five interference mitigation techniques. Position solutions were then computed using the Forward-Backward approach for Receiver Autonomous Integrity Monitoring (RAIM). Signals from GPS, Galileo and Beidou were processed and both single and dual constellation solutions were analysed. The analysis shows that interference mitigation allows the receiver to track a higher number of signals, even in the presence of high jamming levels. This increased measurement availability is then effectively exploited by RAIM techniques that provide reliable solutions. Measurements from several constellation further improve the reliable availability of the position solutions.

Reliability testing, namely receiver autonomous integrity monitoring (RAIM), consists of statistical testing of least-squares residuals of observations, e.g., on an epoch-by-epoch basis aiming towards reliable navigation fault detection and exclusion (FDE). In this paper, classic RAIM and FDE methods are extended with testing of range-rate residuals to find inconsistent velocity solutions in order to contribute to the reliability of the system with special focus on degraded signal environments. Reliability enhancement efforts discussed include a Backward-FDE scheme based on statistical outlier detection and an iteratively reweighted robust estimation technique, a modified Danish method. In addition, measurement weighting assigned to code and Doppler observations is assessed in the paper in order to allow fitting a priori variance models to the estimation processes. The schemes discussed are also suitable in terms of computational convenience for a combined GPS/Galileo system. The objective of this paper is to assess position and velocity reliability testing and enhancement in urban and indoor conditions and to analyze the navigation accuracy conditions with high sensitivity GPS (HSGPS) tests. The results show the necessity of weighted estimation and FDE for reliability enhancement in degraded signal-environment navigation.

Global Navigation Satellite System (GNSS)-based cooperative positioning is highly degraded in dense urban areas due to non-line-of-sight (NLOS) and multipath effects. Multiple simultaneous faulty GNSS measurements can result in traditional fault detection and exclusion (FDE) methods finding a consistent but erroneous group of satellites. This paper describes a novel distributed FDE method based on cooperative reliability message (CRM), which is suitable for cooperative positioning system in connected vehicles. The idea is to take into account not only the consistency check on raw GNSS measurements, but also the prior knowledge about the quality of GNSS measurements offered by nearby cooperators so as to improve the ability to exclude multiple GNSS faults. The line-of-sight (LOS) satellites identified by cooperators are stored in CRMs, which will be shared to the host vehicle to generate the candidates for the set of LOS satellites observed locally. Based on the candidates, a bottom-up searching strategy is designed to find the healthy satellites and isolate the faulty ones precisely. Several experiments involving four moving vehicles were conducted in dense urban areas. Results indicate the superiority of CRM-based method in excluding multiple faults over existing methods.

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.

The satellite transmits carrier signal to Global Positioning System (GPS) receivers suffered signal degradation in varied environmental conditions, from space through atmosphere to ground, especially due to the effects of multipath fading. In order to investigate the error performance of GPS signal transmission over multipath fading situations, a vector delay-locked tracking loop structure is applied to GPS receiver with the support of the Kalman filtering algorithms in this paper. The vector delay-locked tracking loop system is supported with receiver autonomous integrity monitoring (RAIM) and fault detection and exclusion (FDE) algorithm to prevent signal unlocked situation. Simulations of the satellite signal to GPS receiver over the multipath fading noise are investigated under three channel conditions: the additive Gaussian white noise (AWGN), Rayleigh fading noise, and Rician fading noise. The extended Kalman filter (EKF) algorithm is applied to improve the system performance. Analysis for various combinations of the above mentioned algorithms is studied and compared.

GNSS (“Global Navigation Satellite Systems”) applications with high security requirements usually manage integrity with Receiver Autonomous Integrity Monitoring (RAIM). Developed originally for aeronautics, RAIM techniques perform a consistency check on satellite measurements to provide a reliable positioning to the user. Modern versions of RAIM provide high performances for aviation. However, the problematics for terrestrial navigation, especially in urban environments, are quite different and have motivated the development of a new integrity process derived from the RAIM concept. In this paper, we introduce a new detection algorithm based on the a priori coherence between the direct received raw signals and the estimated position provided by the navigator. The use of raw satellite signals allows the detection of more estimation inconsistencies. The major differences between the proposed approach (a priori) and the RAIM approach (a posteriori) are outlined from a theoretical standpoint and illustrated by simulated data. Furthermore, we introduce a new criterion derived from both processes which proves their complementarity. Hence, this paper demonstrates the relevance of such a joint assessment in urban scenarios with degraded signal propagation conditions.

The Advanced Receiver Autonomous Integrity Monitoring (ARAIM) provides an Aircraft‐Based Augmentation System function for aircraft Global Navigation Satellite System equipment. Currently, the consideration of temporal correlations of test statistics is an important update to the ARAIM baseline algorithm. However, due to the tight budgets of integrity and continuity, the updated ARAIM Fault Detection and Exclusion (FDE) is not satisfactory in availability coverage. The baseline algorithm is based on equal allocation of integrity and continuity, which causes ARAIM to be susceptible to faults and satellite outages. An availability optimisation of ARAIM FDE based on dynamic budget allocation is proposed, aiming to make full use of the prior knowledge provided by the Integrity Support Message (ISM). The contribution of each solution separation test in the ARAIM FDE to the total continuity and integrity risks is estimated, and the continuity and integrity allocation constraints are obtained. The impacts of faults and satellite outages on availability are analysed, and a predictive Protection Level (PL) for ARAIM FDE is proposed for use as an objective function for optimising risk allocation. Then, a risk allocation method based on the multiplier penalty function method is proposed. The performances of the baseline algorithm and the proposed method under the maximum Number of Effective Samples are simulated. For dual‐constellation H‐ARAIM, the optimised Horizontal PL (HPL) is 40% lower than that of the baseline algorithm on average, and the average number of critical satellites supporting RNP 0.3 is less than 1 worldwide. For the three‐constellation V‐ARIAM, the optimised HPL is 27% lower than that of the baseline algorithm on average, and the optimised Vertical PL (VPL) is 18% lower. The proposed method has high availability coverage and can better respond to the requirements for high‐performance navigation services.

In the cooperative multi-sensor multi-vehicle (MSMV) localization domain, the data incest problem yields inconsistent data fusion results, thereby reducing the accuracy of vehicle localization. In order to address this problem, we propose the interval split covariance intersection filter (ISCIF). At first, the proposed ISCIF method is applied to the absolute positioning step. Then, we combine the interval constraint propagation (ICP) method and the proposed ISCIF method to realize relative positioning. Additionally, in order to enhance the robustness of the MSMV localization system, a Kullback–Leibler divergence (KLD)-based fault detection and exclusion (FDE) method is implemented in our system. Three simulations were carried out: Simulation scenarios 1 and 2 aimed to assess the accuracy of the proposed ISCIF with various capabilities of absolute vehicle positioning, while simulation scenario 3 was designed to evaluate the localization performance when faults were present. The simulation results of scenarios 1 and 2 demonstrated that our proposed vehicle localization method reduced the root mean square error (RMSE) by 8.9% and 15.5%, respectively, compared to the conventional split covariance intersection filter (SCIF) method. The simulation results of scenario 3 indicated that the implemented FDE method could effectively reduce the RMSE of vehicles (by about 55%) when faults were present in the system.

Integrity Monitoring (IM) for navigation systems is critical to ensure the safety of auto-driving vehicles. It refers to accurately raising alarms to a user when navigation positioning errors exceed the performance limitation. Although Receiver Autonomous Integrity Monitoring (RAIM) methods have been widely applied for Global Navigation Satellite System (GNSS) observations via a consistency checking algorithm, the integrity performance for auto-driving would suffer from a large degradation due to the low satellite visibility with signal occlusions and Non-Line-of-Sight (NLOS) receptions in urban environments. To alleviate this problem, the Fifth-generation (5G) communication signals are used as an auxiliary urban navigation source to increase the number of observations, and then an IM method for the integration of GNSS/5G (G5GIM) is proposed to improve the integrity performance. Specifically, the positioning reference signals of the 5G system in urban canyons are modeled to enrich the observations of the vehicle navigation, followed by the Horizontal Protection Level (HPL) estimation method and the fault detection algorithm for the integration of GNSS and 5G observations. Experimental results on the simulation and UrbanNav datasets show that the proposed G5GIM method significantly outperforms the existing GNSS RAIM method in terms of HPL reduction, fault detection rate and positioning accuracy improvement.

Intelligent transportation systems (ITS) and autonomous vehicles need accurate localization solutions for applications such as lane identification and collision avoidance. Accuracy at the sub-metre level with 100% availability and integrity above 99% are desired. At present, no single positioning sensor can meet these requirements. In this study, continuous positioning is obtained by using GNSS-RTK with MEMS IMU and vehicle odometer. For journey planning, a new approach is presented to choose the route with best positioning performance, where positioning integrity, availability and precision along different possible routes are predicted. Prediction of the satellites in view is performed using 3D city models. A method is presented for computation of the Protection Levels (PL), which bound the position errors along the direction of motion of the vehicle and for the cross-track direction. In the case of actual navigation, the Fault Detection and Exclusion (FDE) process in integrity monitoring (IM) includes applying the Chi-square test for detection of faults and identification is performed using the w-test, both are applied in the observation domain. The exclusion of observations is confirmed using the solution-separation method, performed in the position domain. A new test defined as ‘FIT” is presented, which checks the impact of the remaining measurement and system errors after the FDE on the final position. The proposed methods are demonstrated through a kinematic test run in an urban area, which represents a challenging environment for ITS applications. The predicted positioning metrics were compared with their values computed from the actual test data. Results show that the 3D map-aided method is able to reasonably predict satellite visibility, and accordingly aid prediction of the integrity, availability and precision. However, it was optimistic in some sections of the road. When using RTK, tight PLs were produced and an alert limit of 1.0 m can be implemented with IM availability of 99%. The use of IMU+vehicle odometer computes the time-change in positioning, hence, their biases accumulate with time and their use in bridging RTK positioning should be limited to short periods.

The combination of multiple constellations of the Global Navigation Satellite System (GNSS) provides a great possibility to improve the integrity of the satellite navigation. However, with the increase of the number of satellites, the probability of multiple outliers increases. Although a number of studies analyzed the performance of the combined GNSS Receiver Autonomous Integrity Monitoring (RAIM), the analysis of the case of multiple outliers is still lacking. In this paper, a Maximum Undetectable Position Bias (MUPB) scheme based on Bias Integrity Threat (BIT), is used to analyze the horizontal availability of RAIM with multiple outliers. The theoretical background for BIT and MUPB has been analyzed. Next, detailed simulations and analyses with single or combined GPS/BDS (BeiDou Satellite Navigation System)/GLONASS constellations were conducted to evaluate the performance of RAIM. In the simulated scenarios with 70 satellites (GPS 32+BDS 14+GLONASS 24) and 2 or 3 outliers occurring simultaneously, this paper compared the MUPB and the Horizontal Alert Level (HAL) of different aviation approach phases and analyzed the results.

The field of GNSS integrity comprises a plethora of integrity related algorithms, each featured with different characteristics. These algorithms use a priori information of some parameters in order to provide integrity information to the user. One type of these algorithms, RAIM, is extensively used in the maritime domain in order to provide an indication if the position calculated is likely to be outside of the requirements of maritime performance standards, as it is required by IMO regulation. The term “Classical RAIM” refers to fully autonomous algorithms which can implement only one, a combination or all the following capabilities: Fault Detection, Fault Exclusion and Protection Level computation. In order to provide this indication, a GNSS receiver shall incorporate RAIM using at least Fault Detection (FD) algorithms, or similar means to determine if accuracy is within the performance standards and provide an integrity indication. In order to harmonise and ensure the correct RAIM algorithms implementation, its usage is standardised by the standard IEC 61108, in particular 1 and 3 series for GPS and Galileo constellations. The current RAIM definition in standards does not constrain the specific RAIM algorithm implementation deliberately in order to let the manufactures implement the most suitable one for their applications. In addition, in order to prove that a receiver is compliant with the requirements specified in this standard, two simple tests are proposed. The first one intends to test the performance of the receiver under safe and caution states, and the other one tests the unsafe state. However, as it is recognised by IALA in the last workshop on the future of marine radiobeacons, “current implementations of Receiver Autonomous Integrity Monitoring (RAIM) are considered inadequate due to the current lack of maritime specific RAIM algorithms.” It has been observed some limitation of current RAIM implementations beyond a specific algorithm for maritime. First of all, the relaxed requirements, in terms of high probabilities of false alarms and of not detecting an error condition, might be justified due to the limitations expected from some implementations of RAIM algorithms. In addition, requirements for GPS and Galileo RAIM differs significantly. Secondly, they are based on some hypothesis as single-failure assumption, a priory estimation of error values components (too conservative in order to provide the integrity required for any user under any condition) or the no existence of biases in faultfree measurements that may not ensure the integrity required if these hypothesis are not met in maritime domain. Finally, considering the simplicity of the aforementioned tests, which do not provides a set of parameters for testing or even assess the probabilities of miss-detection or false alarm, there is no assurance that the RAIM algorithm implemented in the receiver correctly provides the integrity required. To ensure this, it would be necessary to improve the test method in order to characterize the value of the introduced error and add new tests to evaluate the complete set of requirements to the implemented integrity algorithm. The GSA (European GNSS Agency), under GSALOT3TRANS framework contract, analysed the implementation of EGNSS in the area of transport applications. In particular, the Specific Contract 7 (SC7) MarTech it is being assessed the potential use of SBAS combined with RAIM in maritime and inland waterways (IWW) domains. The industrial partners of this specific contract are VVA Brussels (prime) and GMV. Although is not contemplated in any of the aforementioned regulations, the use of SBAS on top of other GNSS technologies that use RAIM may imply some important advantages. The first advantage and the most obvious of the SBAS corrections usage on top of RAIM is the increased performances in terms of accuracy, availability and continuity. The use of SBAS integrity information may also overcome the limitation of some RAIM algorithms that are only able to detect one faulty satellite. SBAS integrity messages also contains valuable information about the estimation of error components that may be used by the RAIM algorithm on real time with enough level of integrity to improve the performance. The aim of this paper is to provide a summary of the activities developed so far as part of GSALOT3TRANS SC7 regarding the current RAIM limitations in the maritime domain and the potential use of SBAS in combination with it to overcome some of these limitations.

On the enhanced detectability of GPS anomalous behavior with relative entropy