Receiver Autonomous Integrity Monitoring Research Articles

Improved protection level for the solution-separation ARAIM based on worst-case fault bias searching

The aviation community is actively pursuing advanced receiver autonomous integrity monitoring (ARAIM) to enhance the safety of aircraft navigation services. Protection level calculation is a crucial task in the solution separation-based ARAIM as it determines the availability of the ARAIM. Accurately determining the worst-case fault bias (WCFB) is beneficial in improving the bounding tightness of protection level on positioning error. Unfortunately, the WCFB determination is a challenging task that requires a time-consuming searching procedure, especially when dealing with the multi-satellite faults. The traditional ARAIM protection level is achieved by constructing a conservative worst-case positioning error bound to avoid the unacceptable time-consumption of the brute-force searching for multi-satellite WCFBs. However, this approach comes at the cost of losing the tightness of the protection level and the availability of the ARAIM. The ARAIM milestone reports have pointed out that the availability of the baseline ARAIM needs to be continuously improved in order to satisfy the worldwide localizer precision vertical 200 (LPV-200) requirements. In response, this paper proposes a novel multi-satellite WCFBs searching method for the ARAIM to improve the tightness of protection level. The method consists of determining the worst-case fault direction and constructing an efficient WCFBs searching procedure. GPS/Galileo dual-constellation simulation result demonstrates that the proposed method not only can improve the availability of ARAIM up to 9.33% when compared with the baseline ARAIM algorithm, but also achieves comparable computation efficiency.

Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval

Accurate integrity risk evaluation is of significance in ensuring that aviation navigation applications satisfy the predefined integrity requirement. The integrity risk evaluation method over a specified exposure interval has been proposed in previous works for the development of advanced receiver autonomous integrity monitoring (ARAIM) (ARAIM technical subgroup reference airborne algorithm description document v4.1, 2022). However, this method typically relies on an underlying optimistic assumption that the satellite geometry remains constant throughout the exposure interval. The variation in satellite geometry due to potential satellite outages undermines the widely-used geometry constant assumption. Thus, we investigate the influence of satellite geometry variations throughout the exposure interval on the integrity performance by introducing a geometry-sensitive risk-evaluation model. The findings demonstrate that, under the nominal situation, the region where the ARAIM fails to meet predefined integrity requirement could expand by a maximum of 2.93% when accounting for satellite geometry variations. Furthermore, in the situation of a single satellite outage, this hazardous region has significantly expanded from 13.12% of the global coverage to 66.82%. Based on these findings, we recommend that the ARAIM should consider satellite outages as a critical factor in real-time integrity risk evaluation.

Mitigation of multiple outliers using consistency checking for GNSS standard point positioning in urban areas

High-precision positioning in urban environments is still a challenging task for global navigation satellite system (GNSS) as the observations are susceptible to outliers. Receiver autonomous integrity monitoring (RAIM) has been widely used in GNSS positioning to resist the outliers. However, conventional RAIM typically assumes only a single outlier, when multiple outliers are present, the method’s robustness can be adversely affected and a time-consuming iterative processing procedure is often required. To process multiple outliers more robustly and efficiently, we propose a consistency-checking approach based on the concept of random sample consensus (RANSAC). Modifications are made to enhance the RANSAC algorithm, including the use of spatial and temporal continuity of positioning geometry to accelerate RANSAC, and adaptive determination of the inlier-outlier threshold based on observation and parameter uncertainty. The effectiveness and efficiency of the proposed method are validated in GNSS single point positioning (SPP) in both a simulation and a real driving test.

RTK ramp faults detection and exclusion by the hybrid control chart

For real-time kinematic (RTK) positioning in intelligent transportation systems (ITS), the slow-growing faults detection and exclusion (FDE) in carrier phase measurements with time-correlated satellite navigation data poses a significant challenge. In response, we propose the short-baseline RTK Receiver Autonomous Integrity Monitoring (RTK-RAIM), which utilizes a hybrid control chart with a colored Kalman filter for detecting small yet persistent faults. The hybrid control chart incorporates the windowed multivariate homogeneously weighted moving average and dual multivariate cumulative sum charts to accelerate fault detection. The fault exclusion is conducted using the solution separation. Experimental validation using static data and dynamic data in suburban and urban areas demonstrates the efficacy of RTK-RAIM in detecting ramp faults with time-correlated noise. Results show that Colored KF can attenuate the detection metrics in the fault-free case when measurements are time-correlated. The hybrid control chart, operating in an open environment, has the ability to detect carrier phase slope faults with a high probability, even when the slope is as small as 0.01cycle/s. It can also detect carrier-phase ramp faults whose gradient are 0.1cycle/s in an urban area. By enhancing the detection ability of FDE in RTK, this hybrid-control-chart-based RAIM promotes safer and more dependable performance in future ITS applications.

An improved detection method of GNSS faults with fractional information divergence

Early detection of faults guarantees the integrity of navigation systems. The standard receiver autonomous integrity monitoring (RAIM) incorporated with the Kullback-Leibler divergence (KLD) has been proposed to improve detection performance. However, the KLD-RAIM cannot ensure a high detection rate in the presence of small or growing faults. This paper broadens the existing KLD-RAIM to further enhance the detection ability for satellite navigation-based aviation applications. The Cumulative residual KL information (CRKL) replaces the KLD to quantify the dissimilarity between the current and normal cumulative distribution functions for the CRKL-RAIM construction. Then CRKL is extended to fractional orders using Riemann–Louville (RL) calculus to form fractional CRKL-RAIM for detection sensitivity enhancement. Simulations using static GNSS station data were conducted to compare four methods: the standard RAIM, existing KLD-RAIM, the proposed CRKL-RAIM, and fractional CRKL-RAIM. When dealing with small step faults, the detection sensitivity increases progressively, with the fractional CRKL-RAIM capable of detecting 10-meter faults. Regarding growing faults, the standard RAIM fails to detect and KLD-RAIM barely detects faults around 600 s with 50% missed detection rate. By contrast, CRKL-RAIM and fractional CRKL-RAIM detect faults around 100 and 200 s in advance, respectively, without any missed detection events.

A computationally efficient Kalman filter-based RAIM algorithm for aircraft navigation with GPS and NavIC

Integrity monitoring with a Kalman filter (KF) has recently attracted significant attention. In this paper, a computationally efficient architecture of a KF-based receiver autonomous integrity monitoring (RAIM) algorithm is discussed for aviation applications to ensure reliable operations of Global Navigation Satellite Systems (GNSS). It is built on the Schmidt KF navigation processor to model time-correlated measurement errors. Reasons for important design choices of the algorithm are clarified. Different strategies are adopted to efficiently include the contributions of past KF measurements in fault detection as well as protection level (PL) calculations. Module-wise most significant numerical complexity is also analyzed in detail. The algorithm performance is studied with simulated Global Positioning System (GPS) and Navigation with Indian Constellation (NavIC) signals for a number of scenarios. They comprise different configurations related to the number of satellites, geometry, total duration, and aircraft dynamics. Fault detection performance of presented KF RAIM is shown to be superior to another innovation-based test with a moving time window. It is demonstrated that KF RAIM running on a single-core virtual machine can complete processing within a small fraction of each time interval. The performance is also analyzed by restricting CPU usage. The processing time of GPS-NavIC KF RAIM at every interval is shown to be consistently less than that of standalone GPS in all scenarios. Therefore, dual constellations not only result in lower PLs, but also require shorter execution times. An explanation for faster execution times with dual GNSS is provided using the numerical complexity of different modules.

Integrity monitoring of NavIC by parsing broadcast ephemeris

Abstract Global navigation satellite systems (GNSS) are used to provide position estimation to the users. These navigation systems must meet the required navigation parameters (RNP) parameters. Among them integrity being the important parameter, defined as a navigation system’s honesty of the information provided to the user by satellites. The extremity of error due to clocks, ephemeris etc., broadcasted in navigation message of NavIC will result in inaccurate information provided by the satellites that tamper the Navigation with Indian constellation (NavIC) system integrity. The information provided by the satellites may be faulty due to various error sources and cannot be used for applications which require very high accuracy. Integrity of the information provided by satellites plays a vital role and the system needs to be notified accordingly. The traditional methods receiver autonomous integrity monitoring (RAIM) algorithms require both navigation and observation data for implementation and involves several computations, hence in this paper an efficient approach considering only navigation message is proposed to monitor the integrity of NavIC. The NavIC Navigation data of 28 days data corresponding to 4 months is collected from IGS website. The integrity check is performed considering the satellite‘s User Range Accuracy Upper Bound (URA UB), fit interval and health parameters from navigation message. It is observed from the results that there are specific instances of integrity failure of NavIC system. However, it is also noticed that 99.5 % of times the integrity provided by NavIC is within specified limits that guarantee the NavIC utility for critical applications.

Worst-Case Integrity Risk Sensitivity for RAIM with Constellation Modernization

The integrity improvement of receiver autonomous integrity monitoring (RAIM) can benefit from a combination of constellations. With the rapid development of constellation modernization, integrity parameters, including the probability of satellite fault (Psat) and user range accuracy (URA), have improved. The integrity loss of RAIM needs to be accurately characterized to control the effect of the improved integrity parameters. To reveal the sensitivity of integrity risk with respect to Psat and URA, a conservative integrity risk estimation method is proposed based on the worst-case protection concept. Acceptable Psat and URA were derived by comparing the estimated worst-case integrity risk with the required integrity risk. The simulation results showed that RAIM can meet the integrity risk requirement of LPV-200 when Psat was 10−4 and URA was smaller than 0.88 m.

An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability

Civil aviation transportation equipment is more convenient and faster than other transportation tools and is an essential part of intelligent transportation. It is significant to study the reliability of positioning information and enhance traffic safety. Advanced receiver autonomous integrity monitoring (ARAIM) can provide vertical guidance during the different navigation stages in civil aviation fields. The traditional multiple hypothesis solution separation (MHSS) algorithm distributes the probability of hazardous misleading information (PHMI) and probability of false alarm (PFA) uniformly over all visible satellites resulting in reduced global availability of ARAIM. Aiming at this problem, we proposed an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm to redistribute integrity and continuity risks and establish a protection level optimization model. Based on the real BeiDou navigation satellite system/global positioning system (BDS/GPS) data, the experimental results show that the optimized algorithm can reduce the vertical protection level (VPL), and the ARAIM global availability of BDS/GPS is improved by 1.73%∼2.73%. The optimized algorithm can improve the availability of integrity monitoring at different stages of the navigation system and provide a basis for ensuring the reliability of the positioning results.

RAIM and Failure Mode Slope: Effects of Increased Number of Measurements and Number of Faults

This article provides a comprehensive analysis of the impact of the increasing number of measurements and the possible increase in the number of faults in multi-constellation Global Navigation Satellite System (GNSS) Receiver Autonomous Integrity Monitoring (RAIM). Residual-based fault detection and integrity monitoring techniques are ubiquitous in linear over-determined sensing systems. An important application is RAIM, as used in multi-constellation GNSS-based positioning. This is a field in which the number of measurements, m, available per epoch is rapidly increasing due to new satellite systems and modernization. Spoofing, multipath, and non-line of sight signals could potentially affect a large number of these signals. This article fully characterizes the impact of measurement faults on the estimation (i.e., position) error, the residual, and their ratio (i.e., the failure mode slope) by analyzing the range space of the measurement matrix and its orthogonal complement. For any fault scenario affecting h measurements, the eigenvalue problem that defines the worst-case fault is expressed and analyzed in terms of these orthogonal subspaces, which enables further analysis. For h>(m−n), where n is the number of estimated variables, it is known that there always exist faults that are undetectable from the residual vector, yielding an infinite value for the failure mode slope. This article uses the range space and its complement to explain: (1) why, for fixed h and n, the failure mode slope decreases with m; (2) why, for a fixed n and m, the failure mode slope increases toward infinity as h increases; (3) why a failure mode slope can become infinite for h≤(m−n). A set of examples demonstrate the results of the paper.

Opportunistic Autonomous Integrity Monitoring for Enhanced UAV Safety

An opportunistic advanced receiver autonomous integrity monitoring (OARAIM) algorithm for unmanned aerial vehicle (UAV) navigation is developed. This algorithm fuses ambient terrestrial signals of opportunity (SOPs) with global navigation satellite system (GNSS) signals to improve the capability of detecting GNSS and SOP measurement faults and provide tight protection level (PL) bounds. A receiver is assumed to make pseudorange measurements on multiple GNSS satellites and terrestrial SOPs. Experimental tests are presented injecting simulated faults into the OARAIM algorithm, which successfully detects the faults in GPS satellites and SOPs. Moreover, the OARAIM algorithm and the inclusion of the SOPs reduces the vertical and horizontal PLs by more than 55% and 70%, respectively, compared to only using GNSS measurements.

Integrity monitoring scheme for single-epoch GNSS PPP-RTK positioning

Integrity monitoring for precise point positioning is critical for safety-related applications. With the increasing demands of high-accuracy autonomous navigation for unmanned ground and aerial vehicles, the integrity monitoring method of high-precision positioning has become an essential requirement. While high precision Global Navigation Satellite Systems (GNSS) positioning is widely used in such applications, there are still many difficulties in the integrity monitoring method for the multi-frequency multi-GNSS undifferenced and uncombined Precise Point Positioning (PPP). The main difficulties are caused by using the measurements of multiple epochs in PPP. Based on the baseline Multiple Hypothesis Solution Separation (MHSS) Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm, this paper discusses the feasibility of the pseudorange-based baseline ARAIM method on the single-epoch PPP based on Real-Time Kinematic (RTK) networks (PPP-RTK) framework to overcome these difficulties. In addition, a new scheme is proposed to transfer the conventional PPP process into the single-epoch PPP-RTK framework. The simulation results using the proposed model are analyzed in this study. The Protection Levels (PLs) estimated by PPP Wide-lane Ambiguity Resolution (PPP-WAR) model with regional corrections can reach the meter level and the PLs estimated by PPP Ambiguity Resolution (PPP-AR) and PPP-RTK models are usually the sub-meter level. Given a horizontal Alert Limit (AL) of 1.5 m, the global coverage of availability above 99.9% for PPP-WAR, PPP-AR, and PPP-RTK can reach 92.6%, 99.4%, and 99.7% respectively. The results using real kinematic data also show that tight PLs can be achieved when the observation conditions are good.

T-RAIM Approaches: Testing with Galileo Measurements.

Several applications rely on time retrieved from Global Navigation Satellite System (GNSS), and this pushes for integrity tailored to timing. Integrity information could be broadcast by GNSS itself, but currently, there are no GNSSs providing such integrity information for a timing application. The integrity provided by GNSS itself could not be timely enough for real time users and does not include local effects due to multipath or other local interferences. In order to fill the gap, integrity can be locally/autonomously computed by the receiver using Timing Receiver Autonomous Integrity Monitoring (T-RAIM) algorithms. Three T-RAIM algorithms have been designed, implemented, and tested; specifically, the algorithms are Forward-Backward (FB), Danish, and Subset. The algorithms are applied to the classical Position Velocity and Timing (PVT) solution and to the time-only case assuming the receiver coordinates are known. Tests using two identical receivers located in different scenarios, open-sky and obstructed, have been carried out to validate the algorithms proposed. The increased redundancy obtained from the knowledge of the receiver coordinates play a fundamental role for the integrity algorithms performance. The benefits of the T-RAIM algorithms activation, in signal degraded conditions, clearly emerged in terms of frequency error and Allan Deviation (ADEV). A small increase of the execution time has been observed when the T-RAIM algorithms are used.

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.

Implementation and analysis of fault grouping for multi-constellation advanced RAIM

The aviation community is pursuing multi-constellation Advanced Receiver Autonomous Integrity Monitoring (ARAIM) to offer safe aircraft navigation services. The computational issue of ARAIM becomes critical when multiple constellations are involved and Fault Exclusion (FE) is enabled. This paper proposes an implementation of fault grouping to improve the efficiency of multi-constellation ARAIM and to benefit navigation performance. To potentially accommodate most ARAIM services, we consider both ARAIM Fault Detection (FD) and ARAIM Fault Detection and Exclusion (FDE) scenarios. In addition, given the difference between Vertical ARAIM (V-ARAIM) and Horizontal ARAIM (H-ARAIM), the implementation steps of fault grouping for V-ARAIM and H-ARAIM are respectively described. More importantly, unlike most of the prior approaches that were limited to dual-constellation scenarios, our implementation can support up to four constellations. The implementation of fault grouping is evaluated using multiple sets of simulations, which are carried out as a function of the number of constellations, prior fault probabilities, error models, and operational services. The results suggest that in most cases, the proposed implementation of fault grouping can effectively reduce the ARAIM computational load while benefiting or maintaining the navigation performance.

Sequential advanced receiver autonomous integrity monitoring method considering the optimal sample size

The integrity monitoring performance of Receiver Autonomous Integrity Monitoring (RAIM) degrades when insufficient satellites are visible, which may cause RAIM to fail to support the approach procedure with vertical guidance service. We propose a sequential advanced receiver autonomous integrity monitoring (S-ARAIM) method to improve the integrity monitoring capability and availability. We first introduce a sample size to a dominant snapshot technique, advanced RAIM (ARAIM), to formulate cumulative test statistics for fault detection. The sample size is then determined to maximize the fault detection capability, including the response speed and sensitivity to minor faults. Meanwhile, the optimal sample size minimizes the undetected fault magnitude bound when no fault is declared. In this manner, S-ARAIM combines the advantage of snapshot RAIM and sequential RAIM in detecting severe pulse and small persistent faults. Additionally, we derive a protection level to envelop the estimate error under the constraints of continuity and integrity requirements. Experiments validate the fault detection performance under single-satellite-fault and dual-satellite-fault scenarios. Compared with least square residual RAIM and ARAIM, S-ARAIM improves the integrity availability by 45.91% and 5.64%, respectively.

Multi-layered Multi-Constellation Global Navigation Satellite System Interference Mitigation

<h3>Abstract</h3> 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 interactions between these layers of interference mitigation and a measurement quality check. Data collected in the presence of increasing levels of jamming were processed using different interference mitigation techniques, including robust interference mitigation (RIM) and the adaptive notch filter (ANF). A software defined radio (SDR) approach was adopted and measurements were generated by considering five interference-mitigation techniques. Position solutions were then computed using a 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 analyzed. The analysis revealed that interference mitigation allows the receiver to track a larger number of signals even in the presence of high levels of jamming power. This increased measurement availability was then effectively exploited by RAIM techniques to provide more reliable solutions. Measurements from several constellations further improved the reliable availability of the position solutions.

A Positioning System in an Urban Vertical Heterogeneous Network (VHetNet)

Global navigation satellite systems (GNSSs) are essential in providing localization and navigation services to most of the world due to their superior coverage. However, due to high pathloss and inevitable atmospheric effect, the positioning performance of any standalone GNSS is still poor in urban areas. To enhance the positioning performance of legacy GNSSs in urban areas, a positioning system, which utilizes high altitude platform station (HAPS) and 5G gNodeBs (gNBs), in a futuristic urban vertical heterogeneous network (VHetNet) is proposed. In this paper, we demonstrate the effectiveness of gNBs in improving the vertical positioning performance for both the GPS-only system and the HAPS-aided GPS system by analyzing the impact of the density of gNBs and the pseudorange error of gNB on the positioning performance of the gNB augmented positioning systems. We also demonstrate the effectiveness of receiver autonomous integrity monitoring (RAIM) algorithms on the HAPS and/or gNB aided GPS systems in urban areas.

A GNSS Instrumentation Covert Directional Spoofing Algorithm for UAV Equipped With Tightly-Coupled GNSS/IMU

Measurement and navigation users cannot operate without the positioning, navigation, and timing (PNT) service provided by the global navigation satellite system (GNSS) instrumentation, but users are also faced with unpredictable and complex interference and even spoofing. In order to effectively control and even counter the unmanned aerial vehicle (UAV) that may pose security threats, using the GNSS spoofing technology to counter UAV is an effective and important technical means. Compared with the existing spoofing algorithms, this article fully considers the navigation system configuration and flight control principle, as well as antispoofing module of UAV equipped, the UAV dynamic model under GNSS spoofing environment is established, and the response law of UAV state to spoofing is analyzed. In order to realize the covert directional spoofing on UAV equipped with tightly-coupled GNSS and inertial measurement unit (IMU), a GNSS covert spoofing algorithm is proposed. The algorithm includes a fixed-point four-step spoofing strategy and pays attention to avoiding the least-squares residual receiver autonomous integrity monitoring (LSR-RAIM) of UAV, so as to ensure the concealment of the deception process. Through the construction of experimental platform and experimental analysis, the effectiveness and concealment of the algorithm are verified. The experiment shows that the spoofing yaw angle error of GNSS covert directional spoofing is −0.03°. In addition, the spoofer has effectively avoided the LSR-RAIM of UAV system in the whole process, and the evasion rate has reached 100% to achieve covert spoofing. For the actual spoofing scenario application, the spoofing yaw angle error can meet the actual needs. Future work will focus on the research and design of more complex covert spoofing algorithms to meet the spoofing needs of UAV equipped with more complex navigation systems and antispoofing techniques.

Preliminary Analysis of BDS-3 Performance for ARAIM

<h3>Abstract</h3> To support the operation of advanced receiver autonomous integrity monitoring (ARAIM), an integrity support message indicating a minimum performance level of satellite constellation is required for aircraft navigation. With BDS-3 providing worldwide service since July 2020, it is desirable to undertake a detailed study on its signal-in-space range error characteristics and prior fault probabilities for ARAIM. The latest accuracy criteria released by the China Satellite Navigation Office in May 2021 is validated by the 27 MEO and IGSO satellites in orbit from July 2020 to June 2021, in which 10 single satellite faults were identified and analyzed in detail with no constellation fault found. Based on this one-year data, the probability of single satellite faults and constellation faults can be initially set as 8 × 10⁻⁵ and 1 × 10⁻³, respectively, for BDS-3 in ARAIM.