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EVALUATING INTEGRITY FOR MOBILE ROBOT LOCALIZATION SAFETY
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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ENSURING NAVIGATION INTEGRITY AND CONTINUITY USING MULTI-CONSTELLATION GNSS
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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High-integrity modeling of non-stationary Kalman Filter input error processes and application to aircraft navigation
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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