What you'll learn:
- Basic Understanding of ADAS and Autonomous Driving (AD)
- Very Good Knowledge of Automotive Radar Sensor and its use in ADAS and AD
- Complete Signal Processing and briefly Data Processing of Automotive Radar with relevant examples
- Exercise problems in form of Quiz to understand mathematics behind the sensor
- Industry oriented Material to help learners to use the course knowledge directly at work
Autonomous Driving is getting its fame very fast across the world and lot of companies are investing huge money to reach the goal. As a result, there is high demand of Skilled people especially Engineers in this field. But as the field itself is quite complex and challenging, it demands multiple skills from one person.
Sensors are very important non-separable part in the Autonomous driving and knowledge of them is very important for everyone working in this field. Depending on the use, either basic knowledge or deep knowledge is necessary. Among the sensors, Camera, Radar, Lidar and Ultrasonic sensors are prominent for environment perception. There are lot of online resources available for Camera and computer vision, Lidar is still in development and even though Radar Technology is very mature in Automotive Sector and also having very wide scope of further research, very limited resources are available for beginners and for experience people at one location. Keeping this in mind, this course is created to provide basic and deep knowledge of Radar Technology with main focus in ADAS (Advanced Driver Assistance Systems) and AD (Autonomous Driving) applications.
This course will help to:
Understand ADAS and AD and the importance of various sensors in the field
How both ADAS and AD are connected to each other
Why Radar Technology is so important and how it works in this field
All about Automotive Radar - including Hardware components, basic and advance Signal processing and data processing
About FFT, Range, Doppler, Angle, RCS Measurements, RD map generation, Radar Detections, etc.
Briefly about Clustering, feature extractions, object formation, Single Object Tracking, Multi Object Tracking, etc.
