High-Precision Automotive Radar Target Simulation


Book Description

Radar target simulators (RTSs) deceive a radar under test (RuT) by creating an artificial environment consisting of virtual radar targets. In this work, new techniques are presented that overcome the rasterization deficiency of current RTS systems and enable the generation of virtual targets at arbitrary high-precision positions. This allows for continuous movement of the targets and thus a more credible simulation environment.




Modeling Backscattering Behavior of Vulnerable Road Users Based on High-Resolution Radar Measurements


Book Description

During the evolvement of autonomous driving technology, obtaining reliable 3-D environmental information is an indispensable task in approaching safe driving. The operational behavior of automotive radars can be precisely evaluated in a virtual test environment by modeling its surrounding, specifically vulnerable road users (VRUs). Such a realistic model can be generated based on the radar cross section (RCS) and Doppler signatures of a VRU. Therefore, this work proposes a high-resolution RCS measurement technique to determine the relevant scattering points of different VRUs.




Intelligent Reflecting Surfaces in Wireless Communication Systems


Book Description

Accompanied with the development of the wireless communication technologies, the high data traffic is more necessary for civil and industrial applications than ever The concept of an intelligent reflective surface (IRS) has attracted considerable attention recently as a low-cost solution. As the main contribution, the dissertation creates new state-of-the-art and formulates a solid milestone for the IRS research field.




Radar Signal Processing for Autonomous Driving


Book Description

The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.







Simulation of Automotive Radar Point Clouds in Standardized Frameworks


Book Description

The simulation of the vehicle’s environmental sensors, the so-called sensor simulation, is crucial for testing and validating autonomous driving. Automobile manufacturers are increasingly focusing on a standardized architecture with a high level of abstraction. In order to simulate the sensors, such as radar sensors, most realistically on a point cloud level, data-based methods are used in many cases. In general, and specifically in case of radar sensors, there are still challenges to be faced. Therefore, four research questions are addressed: Is it possible to generate synthetic training data for data-based models? Which statistical approaches are suitable to simulate radar point clouds and how shall their learning capacities be evaluated? Is there a modeling approach to circumvent the disadvantages of statistical modeling? How to tackle the statistical nature of radar sensors during validation? Die Simulation der Umfeldsensoren des Fahrzeugs, die sogenannte Sensorsimulation, ist für Test und Absicherung des autonomen Fahrens entscheidend. Die Automobilhersteller setzen dabei zunehmend auf eine standardisierte Architektur mit hohem Abstraktionsgrad. Um die Sensoren, wie z.B. Radarsensoren, möglichst realitätsnah auf Punktwolkenebene zu simulieren, werden in vielen Fällen datenbasierte Methoden eingesetzt. Im Allgemeinen und speziell im Fall von Radarsensoren gilt es noch immer zahlreiche Herausforderungen zu meistern. Daher werden in dieser Arbeit vier Forschungsfragen behandelt: Können synthetische Trainingsdaten für datenbasierte Modelle generiert werden? Welche statistischen Ansätze sind geeignet, um Radar-Punktwolken zu simulieren und wie können die Ansätze bewertet werden? Gibt es einen Modellierungsansatz, um Nachteile der statistischen Modellierung zu umgehen? Wie kann die statistische Natur bei der Validierung berücksichtigt werden?




Large Aperture Array Radar Systems for Automotive Applications


Book Description

The radar, besides camera and Lidar systems, is a core sensor to enable autonomous driving. The relatively limited angular resolution is the major drawback of the radar. This thesis shows the development of a conceptual future radar system for automotive applications. The focus is on providing a large antenna aperture to achieve the required high angular resolution. Two genetic algorithms are developed to optimize the antenna array for a good side lobe level while providing high angular resolution. Two demonstrators are built to implement certain aspects of the proposed radar system and prove the general concept viable. The first demonstrator features a large aperture with a limited side lobe level and is using a modular approach. The modules are synchronized with a radio over fiber system. The second demonstrator uses the previously proposed antenna array, which is implemented with a synthetic aperture radar approach. The system’s capabilities in a real scenario are demonstrated, and the reconstruction of a high-resolution three-dimensional image from the captured data is shown. Das Radar stellt, neben Kamera- und Lidar-Systemen, einen zentralen Sensor für das autonome Fahren dar. Dabei ist die relativ geringe Winelauflösung der primäre Nachteil des Radars. Diese Arbeit zeigt die Entwicklung eines konzeptionellen zukünftigen Radarsystems für automobile Anwendungen. Der Schwerpunkt liegt auf der Umsetzung einer großen Antennenapertur, um die erforderliche hohe Winkelauflösung zu erreichen. Zwei evolutionäre Algorithmen werden vorgestellt, um das Antennen-Array auf einen guten Nebenkeulen-Pegel zu optimieren und gleichzeitig eine hohe Winkelauflösung zu erreichen. Zwei Demonstratoren werden gebaut, um bestimmte Aspekte des vorgeschlagenen Radarsystems zu implementieren und die Durchführbarkeit des allgemeinen Konzepts zu zeigen. Der erste Demonstrator weist eine große Apertur mit einem begrenzten Nebenkeulen-Niveau auf und verwendet einen modularen Ansatz. Die Module sind mit einem Radio-over-Fiber-System synchronisiert. Der zweite Demonstrator verwendet die zuvor entworfene Antennenanordnung, die mit einem Radar mit synthetischer Apertur realisiert wird. Die Fähigkeiten des Systems werden in einem realen Szenario demonstriert und die Rekonstruktion eines hochauflösenden dreidimensionalen Bildes aus den erfassten Daten gezeigt.




Radar Target Detection


Book Description




Communications, Signal Processing, and Systems


Book Description

This book brings together papers presented at the 2022 International Conference on Communications, Signal Processing, and Systems, online, July 23-24, 2022, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications, signal processing and systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).




Radar Target Backscattering Simulation


Book Description

Collection of programs for the simulation of various properties of aerial targets.