FR3103047B1 - Procede et dispositif d'apprentissage par reseau de neurones artificiels pour l'aide a l'atterrissage d'aeronef - Google Patents

Procede et dispositif d'apprentissage par reseau de neurones artificiels pour l'aide a l'atterrissage d'aeronef Download PDF

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FR3103047B1
FR3103047B1 FR1912482A FR1912482A FR3103047B1 FR 3103047 B1 FR3103047 B1 FR 3103047B1 FR 1912482 A FR1912482 A FR 1912482A FR 1912482 A FR1912482 A FR 1912482A FR 3103047 B1 FR3103047 B1 FR 3103047B1
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aircraft landing
learning process
network learning
landing
artificial neuron
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FR3103047A1 (fr
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Thierry Ganille
Jean-Emmanuel Haugeard
Andrei Stoian
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Thales SA
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Thales SA
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Priority to US17/084,501 priority patent/US20210158157A1/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G01S13/867—Combination of radar systems with cameras
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
    • G01S13/913—Radar or analogous systems specially adapted for specific applications for traffic control for landing purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/417—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section involving the use of neural networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/096—Transfer learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/13—Satellite images
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/933—Lidar systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/255—Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
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  • General Engineering & Computer Science (AREA)
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  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Astronomy & Astrophysics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Electromagnetism (AREA)
  • Image Analysis (AREA)
  • Traffic Control Systems (AREA)

Abstract

L’invention concerne un procédé d’apprentissage par réseau de neurones pour l’aide à l’atterrissage d’aéronef, le procédé comprenant au moins des étapes de : - recevoir un jeu de données d’apprentissage labélisées comprenant des données capteur associées à une vérité-terrain représentant au moins une piste d’atterrissage et une rampe d’approche ; - exécuter un algorithme d’apprentissage profond par réseau de neurones artificiels sur le jeu de données d’apprentissage, ledit algorithme d’apprentissage profond utilisant une fonction de coût dite trapèze de seuil de piste, paramétrée pour la reconnaissance d’un seuil de piste et de rampes d’approche ; et - générer un modèle d’intelligence artificielle entrainé pour l’aide à l’atterrissage d’aéronef de reconnaissance de piste. Figure pour l’abrégé : Fig. 3
FR1912482A 2019-11-07 2019-11-07 Procede et dispositif d'apprentissage par reseau de neurones artificiels pour l'aide a l'atterrissage d'aeronef Active FR3103047B1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
FR1912482A FR3103047B1 (fr) 2019-11-07 2019-11-07 Procede et dispositif d'apprentissage par reseau de neurones artificiels pour l'aide a l'atterrissage d'aeronef
US17/084,501 US20210158157A1 (en) 2019-11-07 2020-10-29 Artificial neural network learning method and device for aircraft landing assistance

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1912482 2019-11-07
FR1912482A FR3103047B1 (fr) 2019-11-07 2019-11-07 Procede et dispositif d'apprentissage par reseau de neurones artificiels pour l'aide a l'atterrissage d'aeronef

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FR3103047A1 FR3103047A1 (fr) 2021-05-14
FR3103047B1 true FR3103047B1 (fr) 2021-11-26

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FR (1) FR3103047B1 (fr)

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AU2018412712A1 (en) * 2018-03-15 2020-09-24 Nihon Onkyo Engineering Co., Ltd. Training Data Generation Method, Training Data Generation Apparatus, And Training Data Generation Program
US11479365B2 (en) * 2021-01-22 2022-10-25 Honeywell International Inc. Computer vision systems and methods for aiding landing decision
CN113052106B (zh) * 2021-04-01 2022-11-04 重庆大学 一种基于PSPNet网络的飞机起降跑道识别方法
US20240167804A1 (en) * 2021-05-31 2024-05-23 Nidec Corporation Angle detection method and angle detection device
CN113343355B (zh) * 2021-06-08 2022-10-18 四川大学 基于深度学习的飞机蒙皮型面检测路径规划方法
CN114756037B (zh) * 2022-03-18 2023-04-07 广东汇星光电科技有限公司 一种基于神经网络图像识别的无人机***及控制方法
FR3137447B1 (fr) 2022-07-01 2024-05-24 Airbus Helicopters Procédé d’apprentissage d’au moins un modèle d’intelligence artificielle d’estimation en vol de la masse d’un aéronef à partir de données d’utilisation

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AU2001286601A1 (en) * 2000-08-22 2002-03-04 Dimitris K. Agrafiotis Method, system, and computer program product for determining properties of combinatorial library products from features of library building blocks
US7324691B2 (en) * 2003-09-24 2008-01-29 Microsoft Corporation System and method for shape recognition of hand-drawn objects
US20050232512A1 (en) * 2004-04-20 2005-10-20 Max-Viz, Inc. Neural net based processor for synthetic vision fusion
US7925117B2 (en) 2006-06-27 2011-04-12 Honeywell International Inc. Fusion of sensor data and synthetic data to form an integrated image
FR3038047B1 (fr) * 2015-06-24 2019-08-09 Dassault Aviation Systeme d'affichage d'un aeronef, propre a afficher un marquage de localisation d'une zone de presence d'une rampe lumineuse d'approche et procede associe
FR3049744B1 (fr) 2016-04-01 2018-03-30 Thales Procede de representation synthetique d'elements d'interet dans un systeme de visualisation pour aeronef
DE102017205093A1 (de) * 2017-03-27 2018-09-27 Conti Temic Microelectronic Gmbh Verfahren und System zur Vorhersage von Sensorsignalen eines Fahrzeugs
CN108388641B (zh) * 2018-02-27 2022-02-01 广东方纬科技有限公司 一种基于深度学习的交通设施地图生成方法与***

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FR3103047A1 (fr) 2021-05-14

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