Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods

Conformance monitoring supports UTM safety by observing if unmanned aircraft (UA) are adhering to declared operational intent. As a supporting system, robust cooperative tracking is critical. Nevertheless, tracking systems for UAS traffic management (UTM) are in an early stage and under-standardized...

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Main Authors: Dai, Wei, Quek, Zhi Hao, Pang, Bizhao, Feroskhan, Mir
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/172653
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1726532023-12-19T15:31:10Z Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods Dai, Wei Quek, Zhi Hao Pang, Bizhao Feroskhan, Mir School of Mechanical and Aerospace Engineering Air Traffic Management Research Institute Engineering::Aeronautical engineering::Accidents and air safety Monte Carlo UAS Traffic Management Conformance monitoring supports UTM safety by observing if unmanned aircraft (UA) are adhering to declared operational intent. As a supporting system, robust cooperative tracking is critical. Nevertheless, tracking systems for UAS traffic management (UTM) are in an early stage and under-standardized, and existing literature hardly addresses the problem. To bridge this gap, this study aims to probabilistically evaluate the impact of the change in tracking performances on the effectiveness of conformance monitoring. We propose a Monte Carlo simulation-based method. To ensure a realistic simulation environment, we use a hybrid software-in-the-loop (SITL) scheme. The major uncertainties contributing to the stochastic evaluation are measured separately and are integrated into the final Monte Carlo simulation. Latency tests were conducted to assess the performance of different communication technologies for cooperative tracking. Flight technical error generation via SITL simulations and navigational system error generation based on flight experiments were employed to model UA trajectory uncertainty. Based on these tests, further Monte Carlo simulations were used to study the overall impacts of various tracking key performance indicators in UTM conformance monitoring. Results suggest that the extrapolation of UA position enables quicker non-conformance detection, but introduces greater variability in detection delay, and exacerbates the incidence of nuisance alerts and missed detections, particularly when latencies are high and velocity errors are severe. Recommendations for UA position update rates of ≥1 Hz remain consistent with previous studies, as investments in increasing the update rate do not lead to corresponding improvements in conformance monitoring performance according to simulation results. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Published version This research and the APC were funded by the National Research Foundation (NRF), Singapore, and the Civil Aviation Authority of Singapore (CAAS), under the Aviation Transformation Programme. 2023-12-19T02:37:20Z 2023-12-19T02:37:20Z 2023 Journal Article Dai, W., Quek, Z. H., Pang, B. & Feroskhan, M. (2023). Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods. Drones, 7(10), 597-. https://dx.doi.org/10.3390/drones7100597 2504-446X https://hdl.handle.net/10356/172653 10.3390/drones7100597 2-s2.0-85175416864 10 7 597 en Drones © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Aeronautical engineering::Accidents and air safety
Monte Carlo
UAS Traffic Management
spellingShingle Engineering::Aeronautical engineering::Accidents and air safety
Monte Carlo
UAS Traffic Management
Dai, Wei
Quek, Zhi Hao
Pang, Bizhao
Feroskhan, Mir
Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
description Conformance monitoring supports UTM safety by observing if unmanned aircraft (UA) are adhering to declared operational intent. As a supporting system, robust cooperative tracking is critical. Nevertheless, tracking systems for UAS traffic management (UTM) are in an early stage and under-standardized, and existing literature hardly addresses the problem. To bridge this gap, this study aims to probabilistically evaluate the impact of the change in tracking performances on the effectiveness of conformance monitoring. We propose a Monte Carlo simulation-based method. To ensure a realistic simulation environment, we use a hybrid software-in-the-loop (SITL) scheme. The major uncertainties contributing to the stochastic evaluation are measured separately and are integrated into the final Monte Carlo simulation. Latency tests were conducted to assess the performance of different communication technologies for cooperative tracking. Flight technical error generation via SITL simulations and navigational system error generation based on flight experiments were employed to model UA trajectory uncertainty. Based on these tests, further Monte Carlo simulations were used to study the overall impacts of various tracking key performance indicators in UTM conformance monitoring. Results suggest that the extrapolation of UA position enables quicker non-conformance detection, but introduces greater variability in detection delay, and exacerbates the incidence of nuisance alerts and missed detections, particularly when latencies are high and velocity errors are severe. Recommendations for UA position update rates of ≥1 Hz remain consistent with previous studies, as investments in increasing the update rate do not lead to corresponding improvements in conformance monitoring performance according to simulation results.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Dai, Wei
Quek, Zhi Hao
Pang, Bizhao
Feroskhan, Mir
format Article
author Dai, Wei
Quek, Zhi Hao
Pang, Bizhao
Feroskhan, Mir
author_sort Dai, Wei
title Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
title_short Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
title_full Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
title_fullStr Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
title_full_unstemmed Analysis of UTM tracking performance for conformance monitoring via hybrid SITL Monte Carlo methods
title_sort analysis of utm tracking performance for conformance monitoring via hybrid sitl monte carlo methods
publishDate 2023
url https://hdl.handle.net/10356/172653
_version_ 1787136455301136384