Course 064 LiDAR Sensors from System to Transistor/Device Level and Miniaturization through ASIC and (Co-)Packaging

Dr. Farzad Parsaie, founder of SAND Microsystems GmbH, Switzerland is teaching this 5-day course on LiDAR Sensors. LiDAR, that stands for Light Detection and Ranging or simply Light Radar, has already been known for decades and used in different areas as meteorology and space. Recently more attention and interest has been devoted to LiDAR to detect objects for plenty of new applications as autonomous driving (AD), advanced driver assistance systems (ADAS), drones, robots, 3D Imaging and scanning, etc. However, the conventional LiDAR instruments in use have been quite bulky and very expensive. This has strongly limited the usage of this sensor so far. Over 100 companies are working on the development of new LiDAR solutions that can be used for many product applications mentioned above. This course enables Engineers and Managers to become familiar with different concepts that a LiDAR sensor can be realized from the top system level down to the transistor and device level. It is planned to raise the awareness of the participants about the challenges and the development issues of LiDAR by proposing several solutions that can help to minimize the development risks and time. After introduction and comparison of architectures details of Electronic and Optoelectronic components and subsystems will be covered. Advanced techniques and technologies will be introduced that enable us to minimize the size and cost of LiDAR tremendously.

Available course dates

This course has no planned course dates.

If you are interested in this course, contact us at cei@cei.se

TECHNOLOGY FOCUS

LiDAR is a sensor that measures distance with light and can be used to detect obstacles for vehicles and robots or to scan buildings.

Over 100 companies are working to develop LiDAR solutions that can bring the required high performance and are more economic in terms of costs and much smaller for better integration in vehicles, robots, and drones so that they can be easily portable.

Instructor

Dr. Farzad Parsaie

COURSE CONTENT

This course provides an overview of different LiDAR architectures in their use cases. Examples are Time of Flight (ToF) and FMCW techniques, where light can be scanned over the scene or illuminate the whole field of view with a flash.

The advantages and challenges of each case will be discussed in detail. The course will focus from System level to Transistor and Device level on all Electronic and Optoelectronic components and subsystems. Advanced discrete and integrated techniques and technologies like Analog/RF-Frontend topologies, Discriminator, ADC, ASIC process technology (CMOS, BiCMOS), (Co-) Packaging, different devices like Photodetectors and Laser Diodes as well as switches, switch drivers and power management techniques will be addressed extensively.

Solutions for miniaturization of novel LiDAR products through ASIC integration and (Co-) packaging will be shown with the goal how to reduce costs and improve performance.

WHO SHOULD ATTEND

This is a course about the development of LiDAR as a multi-disciplinary product, hence of interest for technical staff of different disciplines. They need to understand details and consider optimization on the higher product level and not only locally on a single discipline level. In general, it will be of interest to:

– Engineers, Physicists, Scientists, technical staff, and Students
– System Architects, Project Managers and Technical Managers
– Business Development Managers, Marketing Managers, who plan to be involved in specification and development of such a multi-disciplinary optoelectronic product and want to do business with it with fast Time to Market.

Day 1

Overview LiDAR and Architectures

  • Introduction LiDAR
  • Time of Flight (ToF) LiDAR, Flash and scanning LiDAR
  • AMCW, FMCW, FM Comb LiDAR
  • What is a solid-state LiDAR?
  • Light wavelength and Power, Eye Safety

Day 2

The Optical Receive Channel

Part1: Photodetectors

  • Introduction of discrete and integrated Photodetectors
  • Physical Principles and Technologies
  • Light power and wavelength sensitivity, materials
  • Noise sources, sensitivity, and speed

Day 3

The Optical Receive Channel

Part2: Electronic Interface and Signal Conditioning

  • Low noise and high-speed electronic Interfacing of Photodetectors
  • Discrimination topologies
  • Topologies for Analog to Digital Converters (ADC) and Time to Digital Converters (TDC)
  • Discrete (with off-the-shelf components) and integrated (ASIC) Realization
  • ASIC Integration Technologies and Challenges

Day 4

The Transmit Channel

  • Introduction of Light Sources
  • Laser Diode Control Electronics
  • Introduction and principles of Switch Components
  • Switch Driver Electronics and the parasitics to be minimized
  • EMC issues, Integration and Miniaturization

Day 5

Light Steering Methods, Power Management and Packaging

  • MEMS Mirrors for Light Steering (technology, challenges, sensing and control electronics, ASIC)
  • Optical Phased Arrays (OPA) and the role of Silicon Photonics
  • Power Management Topologies for LiDAR (discrete and integrated)
  • Electronic and Optoelectronic (Co-)Packaging and Hybrid Assembly

ALL COURSE DATES FOR THE CATEGORY: , ,

E-Learning Courses, Sensors and Digital Imaging

E-Course Bundle 601-603 Advanced course in image sensors and digital cameras

Location: E-Course 12 months access

Instructor: Professor Albert J.P Theuwissen

The course includes:
  • 284 minutes on-demand video
  • 80 modules
  • 12 months access
Part 1 – Introduction to Correlated and Uncorrelated Noise in Imagers In the introduction of the course, the difference between Correlated and Uncorrelated Noise will be explained.  In a first instance, one can put all fixed-pattern noise sources or noise in the spatial domain under the header of Correlated Noise, and one can put all temporal noise sources or noise in the time domain under the header of Uncorrelated Noise. Part 2 – Characterization of Noise in Dark It may sound strange that an image sensor, which is made to capture light, will be characterized first in dark conditions.  But actually this should not really be surprising because noise will first become visible in the darkest parts of an image.  For that reason the dark performance of an image sensor plays crucial role.  It also sets the lower end of the dynamic range. Part 3 – Characterization of Noise with Light In the third and last part of the course, the image sensor will be characterized with light input. First the fixed-pattern noise (= correlated noise) will be measured, and next the temporal noise (= uncorrelated noise) will be characterized. All measurements will be based on an existing camera and with uniform light input. For both noise types, correlated and uncorrelated, some extra statistical operations will allow to split the overall noise characterized into a contribution on row level, on column level and on pixel level. This gives very useful information on where to find the root cause of the noise sources. Read full course description including course schedule.

Early Bird
450,00 493,00 

E-Learning Courses, Sensors and Digital Imaging

E-Course 601 Introduction to Correlated and Uncorrelated Noise in Imagers

Location: E-Course 3 months access

Instructor: Professor Albert J.P Theuwissen

Introduction to Correlated and Uncorrelated Noise in Imagers In the introduction of the course, the difference between Correlated and Uncorrelated Noise will be explained.  In a first instance, one can put all fixed-pattern noise sources or noise in the spatial domain under the header of Correlated Noise, and one can put all temporal noise sources or noise in the time domain under the header of Uncorrelated Noise. The course includes:
  • 42 minutes on-demand video
  • 9 modules
  • 3 months access
This introductory course is the first part of a series of three e-Learning courses about Image Sensors. For effective training benefit, we recommend also attending course 602 Characterization of Noise in Dark and course 603 Characterization of Noise with Light. Get a better price when ordering all three courses: Bundle 601-603 Advanced Course in Image Sensors and Digital Cameras Read full course description including course schedule.

95,00 
 

E-Learning Courses, Sensors and Digital Imaging

E-Course 603 Characterization of Noise with Light

Location: E-Course 3 months access

Instructor: Professor Albert J.P Theuwissen 

Characterization of Noise with Light In the third and last part of the course, the image sensor will be characterized with light input. First the fixed-pattern noise (= correlated noise) will be measured, and next the temporal noise (= uncorrelated noise) will be characterized. All measurements will be based on an existing camera and with uniform light input. For both noise types, correlated and uncorrelated, some extra statistical operations will allow to split the overall noise characterized into a contribution on row level, on column level and on pixel level. This gives very useful information on where to find the root cause of the noise sources. The course includes:
  • 126 minutes on-demand video
  • 34 modules
  • 3 months access
This course is the third part of a series of three e-Learning courses about Image Sensors. For effective training benefit, we recommend also attending course 601 Introduction to Correlated and Uncorrelated Noise in Imagers and course 602 Characterization of Noise in Dark. Get a better price when ordering all three courses: Bundle 601-603 Advanced Course in Image Sensors and Digital Cameras Read full course description including course schedule.

199,00 
 

E-Learning Courses, Sensors and Digital Imaging

E-Course 602 Characterization of Noise in Dark

Location: E-Course 3 months access

Instructor: Professor Albert J.P Theuwissen

Characterization of Noise in Dark It may sound strange that an image sensor, which is made to capture light, will be characterized first in dark conditions.  But actually this should not really be surprising because noise will first become visible in the darkest parts of an image.  For that reason the dark performance of an image sensor plays crucial role.  It also sets the lower end of the dynamic range…… The course includes:
  • 116 minutes on-demand video
  • 37 modules
  • 3 months access
This course is the second part of a series of three e-Learning courses about Image Sensors. For effective training benefit, we recommend also attending course 601 Introduction to Correlated and Uncorrelated Noise in Imagers and course 603 Characterization of Noise with Light. Get a better price when ordering all three courses: Bundle 601-603 Advanced Course in Image Sensors and Digital Cameras

199,00 
 

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