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Title: UNMANNED AIRCRAFT SYSTEM SENSE AND AVOID INTEGRITY AND CONTINUITY
Creator: Jamoom, Michael B.
Date: 2016, 2016-05
Description: This thesis describes new methods to guarantee safety of sense and avoid (SAA) functions for Unmanned Aircraft Systems (UAS) by evaluating...
Show moreThis thesis describes new methods to guarantee safety of sense and avoid (SAA) functions for Unmanned Aircraft Systems (UAS) by evaluating integrity and continuity risks. Previous SAA e↵orts focused on relative safety metrics, such as risk ratios, comparing the risk of using an SAA system versus not using it. The methods in this thesis evaluate integrity and continuity risks as absolute measures of safety, as is the established practice in commercial aircraft terminal area navigation applications. The main contribution of this thesis is a derivation of a new method, based on a standard intruder relative constant velocity assumption, that uses hazard state estimates and estimate error covariances to establish (1) the integrity risk of the SAA system not detecting imminent loss of “well clear,” which is the time and distance required to maintain safe separation from intruder aircraft, and (2) the probability of false alert, the continuity risk. Another contribution is applying these integrity and continuity risk evaluation methods to set quantifiable and certifiable safety requirements on sensors. A sensitivity analysis uses this methodology to evaluate the impact of sensor errors on integrity and continuity risks. The penultimate contribution is an integrity and continuity risk evaluation where the estimation model is refined to address realistic intruder relative linear accelerations, which goes beyond the current constant velocity standard. The final contribution is an integrity and continuity risk evaluation addressing multiple intruders. This evaluation is a new innovation-based method to determine the risk of mis-associating intruder measurements. A mis-association occurs when the SAA system incorrectly associates a measurement to the wrong intruder, causing large errors in the estimated intruder trajectories. The new methods described in this thesis can help ensure safe encounters between aircraft and enable SAA sensor certification for UAS integration into the National Airspace System.
Ph.D. in Mechanical and Aerospace Engineering, May 2016
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Title: EVALUATING INTEGRITY FOR MOBILE ROBOT LOCALIZATION SAFETY
Creator: Duenas Arana, Guillermo
Date: 2019
Description: Precise localization is paramount for autonomous navigation. Localization errors are not only dangerous by themselves, but can also mislead...
Show morePrecise localization is paramount for autonomous navigation. Localization errors are not only dangerous by themselves, but can also mislead other dependent systems into moving to a hazardous location. Unfortunately, the problem of quantifying robot localization safety is only sparsely addressed in the robotics literature, and most robotics algorithms still quantify pose estimation performance using a covariance matrix or particle spread, which only accounts for nominal sensor errors. This is insufficient for life- and mission-critical applications, such as autonomous vehicles and other co-robots, where ignoring sensor or sensor or processing faults can lead to catastrophic localization errors. Thus, other methods must be employed to ensure safety.In response, this research leverages prior work in aviation integrity monitoring to tackle the more challenging case of evaluating localization safety in mobile robots. In contrast to aviation applications, that heavily rely on the Global Navigation Satellite System (GNSS) for localization, robots often operate in complex, GNSS-denied environments that require a more sophisticated sensor suite to ensure localization safety. Localization integrity risk is the probability that a robot's pose estimate lies outside pre-defined acceptable limits while no alarm is triggered. In this work, the integrity risk is rigorously upper bounded by accounting for both nominal noise and other non-nominal sensor faults, resulting in a safe upper bound on the localization integrity risk.The main contribution of this dissertation is the design and evaluation of a sequential integrity monitoring methodology applicable to mobile robot localization algorithms that use feature extraction and data association. First, faults introduced during the feature extraction and data association processes are distinguished, and the probability of the latter is rigorously upper bounded using analytical methods. The impact of faults in the estimate error's and fault detector's distributions is then determined to quantify integrity risk, which is evaluated under the worst-possible fault combination. To determine the impact of previous faults without a boundlessly growing number of fault hypotheses, this dissertation presents a novel method that uses a preceding time window to build a limited set of hypotheses and a prior estimate bias to account for faults occurring before the start of the time window. The proposed methodology is applicable to Kalman Filter and fixed-lag smoothing localization. Simulated and experimental results are presented to validate the methodology.
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Title: ENSURING NAVIGATION INTEGRITY AND CONTINUITY USING MULTI-CONSTELLATION GNSS
Creator: Zhai, Yawei
Date: 2018, 2018-05
Description: Global navigation satellite system (GNSS) measurements are vulnerable to faults including satellite and constellation failures, which can...
Show moreGlobal navigation satellite system (GNSS) measurements are vulnerable to faults including satellite and constellation failures, which can potentially lead to catastrophic consequences in safety-critical applications. To mitigate their impact, receiver autonomous integrity monitoring (RAIM) fault detection has been designed and used in aviation as a backup navigation tool. Future GNSS has been foreseen to provide dramatically increased measurement redundancy and reduced measurement error. These revolutionary developments, together with important advancements in the RAIM concept itself, will open the possibility to independently support aircraft navigation using GNSS, from takeoff, through en-route flight and final approach to landing, with minimal investment in ground infrastructure. Therefore, this research focuses on developing new dual-frequency, multi-constellation advanced RAIM (ARAIM) fault detection and exclusion methods to ensure high navigation integrity and continuity. In this thesis, the theoretical basis is established to quantify the contributions of fault events and unscheduled satellite outages on continuity risk. Accordingly, the need for airborne fault exclusion is assessed, and the requirements for the exclusion function itself are speci fied. To improve continuity, a new fault exclusion scheme is developed, for which the real-time implementation of the algorithm is described and the associated integrity risk bound is derived. With the theoretical methods being fully characterized, this thesis comprehensively quanti es the achievable ARAIM navigation performance over various numbers and qualities of constellations. The results show high service availability can be achieved using multi-constellation GNSS, while meeting both integrity and continuity requirements. Furthermore, this work investigates the impact of test statistic time correlation on integrity and continuity risk, and rigorously derives the new methods to evaluate the actual risk over the exposure time. The results show that the false alarm probability is two orders of magnitude higher than previously thought. A feasible solution to resolve this issue at the user receiver is provided, and the performance is analyzed. The most signifi cant new feature of ARAIM is the integrity support message (ISM), which provides assertions on the GNSS signal-in-space performance. This dissertation describes the design, analysis, and evaluation of the offline ground monitor, which aims at validating the ISM broadcast to the users. The proposed architecture utilizes a worldwide network of sparsely distributed reference stations, and paramet- ric satellite orbital models to estimate the satellite position and clock. Two separate analyses, covariance analysis and model delity evaluation, are carried out to respec- tively quantify the impact of measurement errors and of residual model errors on the estimation. The results indicate this ground monitor design is adequate for ARAIM ISM validation.
Ph.D. in Mechanical and Aerospace Engineering
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Title: Integrity based landmark generation: A method to generate landmark configurations that guarantee mobile robot localization safety
Creator: Chen, Yihe
Date: 2020
Description: From the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar...
Show moreFrom the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar to how the wide-spreading of automobile had modified the modern cities in early 20th century, we are now standing on the eve of yet another traffic revolution. With the vast spreading of autonomous/semi- autonomous robotics application, it is important for the urban designers to design or retrofit urban environment that is safe and friendly to the autonomous robots; As more robots are deployed in life-critical situations, such as autonomous passenger vehicles, it is imperative to consider their safety, and in particular, their localization safety. While it would be ideal to guarantee safety in any environment without having to physically modify said environment, this is not always possible and one may have add landmarks or active beacons to reach an acceptable level of safety for landmark-based localization. Localization safety is assessed using integrity, the primary safety metric used in open-sky aviation applications that has been recently applied to mobile robots and can ac- count for the impact of rarely occurring, undetected faults. Conventional integrity monitor- ing method has high dependency on GPS system, while the traditional Global Navigation Satellite System - Inertia Measurement Unit (GNSS-IMU) based localization does not ap- plied in the metropolitan areas due to the signal blocking and multi-pathing problem caused by high-rise structures. Thus, this dissertation concentrates on the feature based integrity monitoring method. This dissertation formulates environmental localization safety problem as a system- atic optimization problem: given the robot’s trajectory and the current landmark map, add the minimal number of new landmarks at certain location such that the integrity risk along the trajectory is below a given safety threshold. This dissertation proposes two algorithms to solve the problem: Integrity-based Landmark Generator (I-LaG) and Fast I-LaG. I-LaG adds fewer landmarks but it is relatively computationally expensive; Fast I-LaG is less com- putationally intensive at the expense of more landmarks. Both simulation and experimental results are presented.
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Title: High-integrity modeling of non-stationary Kalman Filter input error processes and application to aircraft navigation
Creator: Gallon, Elisa
Date: 2023
Description: Most navigation applications nowadays rely heavily on Global Navigation Satellite Systems (GNSSs) and inertial sensors. Both of these systems...
Show moreMost navigation applications nowadays rely heavily on Global Navigation Satellite Systems (GNSSs) and inertial sensors. Both of these systems are known to be complementary, and as such, their outputs are very often combined in an extended Kalman Filter (KF) to provide a continuous navigation solution, resistant to poor satellite geometry, as well as radio frequency interference. Additionally, recent development in safety critical applications (such as aviation) revealed the performance limitations of current algorithms (Advance Receiver Autonomous Integrity Monitoring - ARAIM) to vertical guidance down to 200 feet above the runway (LPV-200). When nominal constellations are depleted, LPV-200 can only sparsely be achieved. Exploiting satellite motion in ARAIM (for instance using a KF) could help alleviate those limitations, but would require adequate modeling of the errors, including the error's time correlation.Power Spectral Density (PSD) bounding is a methodology that provides high integrity, time correlated error models, but this approach is currently limited to stationary errors (which is rarely the case with real data), and has never been applied to navigation errors. More generally, no high integrity, time correlated error models have ever been derived for navigation errors.As a result, in the first part of this thesis, a methodology for high integrity modeling of time correlated errors is introduced. The PSD bounding methodology is extended to both stationary and non-stationary errors. In the second part of this thesis, these methodologies are applied to the 3 main error sources impacting iono-free GNSS measurements (orbit and clock errors, tropospheric errors and multipath), as well as to inertial errors.The methodology introduced in this dissertation provides high integrity time correlated error models and is applicable to any type of applications where high integrity is required (e.g. Differential GNSS - DGNSS, Aircaft Based Augmentation System - ABAS, Ground Based Augmentation System - GBAS, Space Based Augmentation System - SBAS, etc...). Additionally, the error models derived here are not only limited to high integrity applications, but could also be used in applications were the correlation over time of the errors plays an important role (such as any KF integration).In the last part of this dissertation, we focus on a specific safety critical application: aviation, and in particular ARAIM. The dissertation is concluded with an assessment of the performance improvements provided by recursive ARAIM, using those bounding dynamic error models, with respect to those models, used for baseline snapshot ARAIM. Additionally, a sensitivity analysis is performed on each of the error model parameters to assess which of them impacts the KF performance (i.e. covariance) the most.
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