Simulation of Automotive Radar Point Clouds in Standardized Frameworks

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Eder, Thomas
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Göttingen : Cuvillier Verlag, 2021.
Temas:
Cloud computing > Law and legislation.
Cloud computing > Law and legislation
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Chapter 1 Autonomous driving andsimulational challenges
  • 1.1 Safety validation and simulative test drives
  • 1.2 Principles of automotive radar sensors
  • 1.3 Modeling and standardized simulationframeworks
  • Chapter 2 State of research in automotiveradar modeling
  • 2.1 Differentiation of various modeling levels
  • 2.2 Ray-tracing in environments of high-fidelity
  • 2.3 Models executable in standardized environments
  • 2.4 Validation and verification of sensor models
  • Chapter 3 Derivation of research questions,hypotheses and objectives
  • 3.2 Stochastic radar models based on deepgenerative networks
  • 3.3 Hybrid multipurpose approaches for radar sensormodels
  • 3.4 Deficiencies of current validation criteria
  • Chapter 4 Modeling challenges related to raycone tracing
  • 4.1 The caustic distance and the angular beamexpansion
  • 4.2 Estimating current errors in case of multiplereflections
  • 4.3 Consequences and lower bounds for the numberof rays
  • Chapter 5 Approaches to statistical radar pointcloud simulation
  • 5.1 Statistical formulation of radar sensor modeling
  • 5.2 Kernel density estimation and radar point clouds
  • 5.3 Deep generative networks as sensor models
  • 5.4 Comparison of learning capacities and itsconsequences
  • Chapter 6 A hybrid modeling approach forradar point clouds
  • 6.1 Tracing and catching rays as the baseline
  • 6.2 Improvements to the ray casting approach
  • 6.3 Capabilities for data-based optimization
  • 6.4 Bottom line on the hybrid modeling approach
  • Chapter 7 Validation based on statisticalhypothesis testing
  • 7.1 Consistency of validation criterion
  • 7.2 On the Kolmogorov-Smirnov test
  • 7.3 Applications to radar sensor models
  • 7.4 Retrospective and future validation challenges
  • Chapter 8 Conclusion and prospectivechallenges
  • 8.1 Recap of the radar point cloud simulation
  • 8.2 Lessons learned and future recommendations
  • Nomenclatur
  • References
  • Index

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