Enhancing ADAS with Advanced Radar Technology and Sensor Fusion
Overview
This session delves into the intricacies of automotive radar technology, emphasizing radar sensor modeling, configuration, and integration for Advanced Driver Assistance Systems (ADAS). Participants will explore the generation of synthetic data to simulate real-world driving scenarios, crucial for testing various ADAS functionalities. The session will also cover the construction of a signal processing and sensor fusion pipeline, essential for interpreting radar and sensor data effectively. Additionally, closed-loop validation methods with ADAS systems will be demonstrated. The capabilities of Texas Instruments mmWave hardware support package within the Radar Toolbox will be discussed, highlighting applications in people tracking, parking assistance, and the creation of virtual sensors. This comprehensive exploration aims to enhance vehicle safety and automation through advanced radar and sensor fusion technologies.
Highlights
- Sensor Modeling and Synthetic Data Generation: Simulating real-world driving scenarios for ADAS testing.
- Signal Processing and Sensor Fusion Pipeline: Effective interpretation of radar and sensor data.
- Closed-Loop Validation Methods: Demonstrating validation techniques with ADAS systems.
- Texas Instruments mmWave Hardware Support Package: Applications in people tracking, parking assistance, and virtual sensors creation.
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About the Presenter
Sumit Garg | Principal Application Engineer| MathWorks
Sumit Garg is the principal application engineer at MathWorks India specializing in design analysis and implementation of signal processing and data processing applications. He works closely with customers in areas of radar, phased array, and sensor fusion. He has more than 12 years of industrial experience in the development of hardware and software applications in the radar domain.
Dr. Rishu Gupta | Principal Application Engineer | MathWorks
Rishu Gupta is a principal application engineer at MathWorks India. He primarily focuses on automated driving and artificial intelligence applications. Rishu has over nine years of experience working on applications related to visual contents. He previously worked as a scientist at LG Soft India in the Research and Development unit. Rishu holds a bachelor’s degree in electronics and communication engineering from BIET Jhansi; a master’s in visual contents from Dongseo University, South Korea, working on the application of computer vision; and a Ph.D. in electrical engineering from University Technology Petronas, Malaysia.
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