Integrity determination for a vision based precision relative navigation system

Calhoun, Sean; Raquet, John

doi:10.1109/plans.2016.7479713

Cited by 4 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the importance of the topic has drawn more attention from the research community, a few pioneered and innovative methods addressing various aspects of the visual positioning integrity monitoring have been developed more recently. Calhoun and Raquet (2016) and Calhoun et al (2015) proposed a relative positioning method by matching rendered images with measurement images. An important innovative point of the work is that the image correspondence error was quantified and a protection level could be calculated for the relative position.…”

Section: Recent Developments In Visual Positioning Integritymentioning

confidence: 99%

“…x x The nominal error propagation should be monitored in a conservative way (e.g., by using overbounded error model) so that the obtained error distribution of the estimates is not overoptimistic. The studies by Calhoun and Raquet (2016), Calhoun et al (2015), and Zhu et al (2019aZhu et al ( , 2019b are the result of development for nominal error integrity, which are capable of calculating PL in nominal operation for particular problems. Nevertheless, one challenge remaining in nominal error monitoring is that conservative measurement noise models are needed for different types of features.…”

Section: An Integrity Description Framework For Visual Positioningmentioning

confidence: 99%

See 1 more Smart Citation

Integrity of Visual Navigation—Developments, Challenges, and Prospects

Zhu

Meurer

Günther

2022

navi

View full text Add to dashboard Cite

Global navigation satellite systems (GNSSs) are widely used in applications nowadays. From maritime transportation to civil aviation, from route guidance to location-based services on smartphones, GNSS is a core technique for positioning. However, significant challenges with new applications in specific environments persist. Autonomous driving, unmanned aerial vehicles (UAV), and urban air mobility (UAM) require reliable navigation in deep urban areas. In these environments, the performance of GNSS is degenerated due to shadowing by tall buildings and strong multipath signals. It is difficult to solve these problems using GNSS technologies only. Multiple sensor fusion is necessary to deliver sufficient navigation performance required by such applications.Visual navigation using cameras as part of a multi-sensor solution offers a number of advantages in such applications. Firstly, the number of visual cues for camera-based localization algorithms is large in dense urban environments where GNSS faces its greatest challenges. The associated detailed visual information leads to precise estimates of the camera's pose (position and orientation). Secondly, the

show abstract

Section: Recent Developments In Visual Positioning Integritymentioning

confidence: 99%

Section: An Integrity Description Framework For Visual Positioningmentioning

confidence: 99%

Integrity of Visual Navigation—Developments, Challenges, and Prospects

Zhu

Meurer

Günther

2022

navi

View full text Add to dashboard Cite

show abstract

“…Integrity monitors can contribute to exceptionally safe autonomous system operation and this quantification can result in overcoming the trust burden from humans and achieve better compliance with local regulations. At the same time, they can promote a better understanding of the trade-off between safety and system availability [2,3] and eventually motivate the development of more efficient navigation solutions.…”

Section: Introductionmentioning

confidence: 99%

Navigation Algorithm-Agnostic Integrity Monitoring based on Solution Separation with Constrained Computation Time and Sensor Noise Overbounding

Bosdelekidis

Bryne

Sokolova

et al. 2022

J Intell Robot Syst

View full text Add to dashboard Cite

Integrity monitoring (IM) in autonomous navigation has been extensively researched, but currently available solutions are mainly applicable to specific algorithms and sensors, or limited by linearity or 'Gaussianity' assumptions. This study investigates a Solution Separation (SS) based framework for universal IM, scalable to multi-sensor fusion as each hypothesis assumes a whole sensor measurement set as faulty. Architecturally we consider that: 1) multi sensor systems must account for various sensor noise models which lead to inconsistent estimates of uncertainties, 2) a module must be able to detect sensor failure or sensor noise mismodeling and suggest better bounds for the error, without being constantly conservative, 3) some algorithms are computationally heavy to monitor in the SS setting or the provided covariances cannot be interpreted in IM. A hybrid SS architecture can be practical, where some solutions are evaluated with a navigation algorithm with known characteristics, although the all-sensor-in solution is evaluated with the monitored algorithm. Experiments are run on filter and smoothing-based navigation algorithms. In addition, we experiment with hybrid SS monitoring and time-correlated noise to evaluate the appropriability of our framework in the context of the above-mentioned requirements. This is a novel framework in the IM domain, directly integrable in existing navigation solutions and, in our opinion, it will facilitate the quantification of the effect of different sensors in navigation safety.

show abstract

Autonomous Integrity Monitoring for Relative Navigation of Multiple Unmanned Aerial Vehicles

Sun

2021

Remote Sensing

View full text Add to dashboard Cite

Accurate and reliable relative navigation is the prerequisite to guarantee the effectiveness and safety of various multiple Unmanned Aerial Vehicles (UAVs) cooperation tasks, when absolute position information is unavailable or inaccurate. Among the UAV navigation techniques, Global Navigation Satellite System (GNSS) is widely used due to its worldwide coverage and simplicity in relative navigation. However, the observations of GNSS are vulnerable to different kinds of faults arising from transmission degradation, ionospheric scintillations, multipath, spoofing, and many other factors. In an effort to improve the reliability of multi-UAV relative navigation, an autonomous integrity monitoring method is proposed with a fusion of double differenced GNSS pseudoranges and Ultra Wide Band (UWB) ranging units. Specifically, the proposed method is designed to detect and exclude the fault observations effectively through a consistency check algorithm in the relative positioning system of the UAVs. Additionally, the protection level for multi-UAV relative navigation is estimated to evaluate whether the performance meets the formation flight and collision avoidance requirements. Simulated experiments derived from the real data are designed to verify the effectiveness of the proposed method in autonomous integrity monitoring for multi-UAV relative navigation.

show abstract

Integrity determination for a vision based precision relative navigation system

Cited by 4 publications

References 6 publications

Integrity of Visual Navigation—Developments, Challenges, and Prospects

Integrity of Visual Navigation—Developments, Challenges, and Prospects

Navigation Algorithm-Agnostic Integrity Monitoring based on Solution Separation with Constrained Computation Time and Sensor Noise Overbounding

Autonomous Integrity Monitoring for Relative Navigation of Multiple Unmanned Aerial Vehicles

Contact Info

Product

Resources

About