4 Generations of Tower GS Pixels

Tower Semiconductor posts an article on its global shutter pixels development:

• Gen 1: Our first generation of GS pixels went into production with relatively big (around ~5um) size, about ~20e of noise and a decoupling ratio between PD and MN of around 60dB. Despite being relatively lower performing than the best-in-class CCD pixels at that time, Tower Semiconductor’s GS technology was a huge market success, mainly because of much higher supported speeds at a higher resolution, which is hard to support using CCD technology. This initiated the shift in industrial cameras from CCD to CIS technology.
• Gen 2: Our second-generation pixels were developed during our cooperation with Intel’s first RealSense™ IR camera. Originally intended for commercial applications like gesture control and 3D rendering, we adapted the technology in 2014 for industrial applications by combining 180nm periphery with 110nm metal lines in the pixel. This innovation enabled us to offer a pixel as small as 3.6um with noise of about 3e and rejection ratio of about 65dB (for the smallest pixel).
• Gen 3: Our third generation of GS was developed using the 110nm Cu metallization technology in our TPSCo fab in Japan. In this version we had two embedded micro-lenses, that helped focus the light on the small diode area in this pixel, and also incorporated a tungsten shield (exactly like in best in class CCD), which helped in preventing light from reaching the MN, the pixel size was reduced down to 2.7um as well as a further reduction of the noise to 2e and increase in the rejection ratio to 70dB.
• Gen 4: Our fourth, and the latest, generation of GS pixel was announced earlier this year. It is based on our 300mm wafer 65nm light pipe technology and improved tungsten shield, further enhancing the Gen3 performance. This technology allowed us to introduce the first 2.5um GS pixel with excellent performance (references IEDM, IISW), and are currently in the final development stage on further reduction of the pixel size to 2.2um.
• Next-gen: Looking ahead, we are already developing our next generation GS pixel which will be based on Back-Side Illumination (BSI) technology. This generation would incorporate new innovations in process integration and device design to keep the MN isolated from unwanted light while maximizing light incidence on to the photo diode.

Tower "Looking Ahead" presentation also talks about other prospective markets:

Sigmaintell Puts Galaxycore at #1 in Units Market Share

IFNews quotes Sigmaintell's somewhat optimistic forecast on this year's smartphone camera market. Sigmaintell puts Galaxycore at #1 in terms of unit market share. Almost 1/3 of all mobile phone image sensors are made by Galaxycore:

"GalaxyCore's main product is 2 / 5M, benefiting from the strong demand for 2M sensors from the multi-camera macros and depth of field of terminal manufacturers, Galaxycore Micro performed well in the first quarter. According to data from Sigmaintell, shipments of Galaxycore Micro camera sensors (including feature phones) in the first quarter of 2020 were approximately 400 million units, an increase of approximately 164% year-on-year. After entering the second quarter, the mobile phone brands began to adjust their product strategies in April. The camera upgrade trend of products with RMB 1,000 and below has significantly slowed down. The four-camera upgrade trend has been delayed. Dual-camera and three-camera are still the main market forces. Will affect its market growth rate in the second quarter and this year."

"It is expected that the global smartphone camera sensor shipments will be about 5 billion this year, maintaining a growth rate of about 5% year-on-year.

According to data from Sigmaintell, global mobile phone camera sensor shipments were approximately 1.41 billion units in the first quarter of 2020, of which smartphone camera sensor shipments were approximately 1.29 billion units, a year-on-year increase of approximately 37%. At the same time, before the outbreak, upstream and downstream are very optimistic about the market demand for camera sensors, so many agents have large quantities of stocks at this time (about 1-2 months of inventory). Under the dual pressure of a sharp decline in demand and a large supply chain inventory, the shipment of camera sensors in the second quarter will further decline."

"ToF has gradually become the standard for high-end smartphones, and currently known applications have three main aspects: one is to assist in improving the shooting effect; the other is to realize the face unlocking function; the third is to use space ranging, 3D scanning, 3D modeling and other functions.

As we all know, since the iPhone12 series in the second half of this year has two products with ToF on the market, the four major domestic terminal manufacturers are also accelerating the development of D-ToF. From the perspective of the supply chain, chip manufacturers (including Omnivision Technology and Galaxycore, etc.) are actively increasing the development of ToF hardware and software. According to data from Sigmaintell, global ToF shipments for smartphones will be approximately 90 million units in 2020."

Sony Defines its Starvis Sensor Category

Sony publishes a short presentation explaining what sensors belong to Starvis class:

iPhone 11 Pro Optical Zoom vs Almalence Super-Resolution

Almalence compares its computational super-resolution zoom used in Xiaomi Mi 10 Pro camera with dedicated telephoto camera in Apple iPhone 11 Pro:

"As every high-end smartphone, iPhone 11 Pro uses a dedicated telephoto camera module to achieve the maximum zoom quality. It appears however, that simply utilizing a telephoto module, even of a great design and quality which is undoubtedly the case with an Apple’s product, is not enough to achieve the top zoom performance. According to the DxOMark benchmark, iPhone 11 Pro achieves Zoom Score of 74 while, for example, Xiaomi Mi 10 Pro hits 110, a drastic 1.5x difference!

To go beyond the camera hardware capabilities, top Zoom performers utilize a computational imaging technique, Super Resolution Zoom. As its name suggests, it uses super resolution technique to increase the resolution of the images suffering from the lack of pixels in case the target zoom level exceeds the optical zoom of the telephoto module."

iPhone 11 Pro zoom camera

Almalence super-resolution zoom

iPhone 11 Pro zoom camera

Almalence super-resolution zoom

LiDAR News: Outsight, Hitachi-LG, Velodyne, OS Lab

Sabbir Rangwala, a former Princeton Lightwave LiDAR business leader, writes in Forbes article:

"On the AV front, there is sobering news. The COVID crisis has put tremendous cash flow pressures on automotive OEMs, with subsequent scaling back of investments on AVs. Ford is in a particularly difficult situation with its dismal stock price, difficulty in obtaining financing and suspending their dividend payments. It is likely that they will need substantial help and delay their AV efforts.

GM-Cruise recently announced an 8% reduction in staffing in areas such as business strategy, design, and product development, following on the heels of Ike, Velodyne, and Kodiak. Zoox, the vaunted Silicon Valley unicorn with an ambitious vision of using purpose-built battery driven AVs for ride sharing is finding a difficult time raising more money and could likely get acquired.

And hold your breath – even Waymo had to raise almost $3B recently because they acknowledged that developing AVs is expensive (and presumably because the new Alphabet management is getting what we all routinely go through – the “other bets” syndrome). These events are likely to multiply and trickle down, with a natural impact on the survival of many AV focused LiDAR companies. They all simply cannot survive going forward.

It is likely that less than 10 independent companies will survive as stand-alone AV LiDAR entities over the next couple of years. The remainder will either pivot successfully into other applications or get acquired (by the captives or the stronger independent LiDAR companies). Or, unfortunately, face bankruptcy."

Like some other automotive LiDAR companies, Outsight is looking for the alternative markets for its 3D semantic camera. ZDNet reports that such a new application could be automatic mask wearing or fever monitoring and screening in public places:



Hitachi-LG Data Storage posts a handwashing quality monitoring application for its LiDAR, in addition to a similar video posted a couple of days ago.



Velodyne adopts its LiDAR for human-worn scanning, in partnership with NavVis:

Another recent Velodyne announcement presents a hand-held LiDAR use:

BusinessWire: Meanwhile, SOS LAB LiDAR startup has secured series A+ investment of $8M led by Korea Development Bank (KDB), bringing the company’s total capital raised so far to $14M.

Jiseong Jeong, the CEO of SOS LAB says: “The implementation of Solid-State LiDAR is a must for car LiDAR commercialization. This is because there are advantages in terms of price and durability as it can be mass produced in small sizes and components. However, satisfying the fixed standard (size, amount of power, distance, etc.) is the challenge Solid-State LiDAR must overcome. SOS LAB finds the solution to the challenge through the core technology. Our new product can detect distant objects by delivering high power despite its small size, which is a beam-steering technology that does not have any moving parts."

SOS LAB stated that it has not only entered into an MOU with ON Semiconductor in January but also establishing partnerships with OEMs and electronic component manufacturers at home and abroad for the development of LiDAR. It showed strong confidence about the commercialization of car LiDAR sensor for 2021.

Image Sensors at VLSI Symposia

This year, VLSI Symposia is to be held on-line on June 14-19. Its agenda includes 7 image sensor papers:

• CB2.1 (Invited) - A 2D-SPAD Array and Read-Out AFE for Next-Generation Solid-State LiDAR
  Tuan Thanh Ta, Toshiba Corp., Japan
• CB2.2 - A 36-Channel SPAD-Integrated Scanning LiDAR Sensor with Multi-Event Histogramming TDC and Embedded Interference Filter
  Hyeongseok Seo, Sungkyunkwan University, Republic of Korea
• CB2.3 - A 3.0µW@5fps QQVGA Self-Controlled Wake-Up Imager with On-Chip Motion Detection, Auto-Exposure and Object Recognition
  Arnaud Verdant, CEA-Leti-MINATEC, France
• CB2.4 - A Low Noise Read-Out IC with Gate Driver for Full Front Display Area Optical Fingerprint Sensors
  Yongil Kwon, Samsung Electronics, Republic of Korea
• CB2.5 - An Always-On 4x Compressive VGA CMOS Imager with 51pJ/pixel and >32dB PSNR
  Wenda Zhao, The University of Texas at Austin, USA
• TN1.8 - Ultrahigh Responsivity and Tunable Photogain BEOL Compatible MoS2 Phototransistor Array for Monolithic 3D Image Sensor with Block-Level Ssensing Circuits
  Chih-Chao Yang, Taiwan Semiconductor Research Institute, Taiwan
• FF.7 (Forum) - Smart Vision Sensor
  Hayato Wakabayashi, Sony Semiconductor Solutions, Japan

Samsung CIS Presentation

Samsung has updated its System LSI presentation with 2020 data:

Lumotive Presents Smartphone LiDAR

EETimes: Lumotive, a Seattle-based LiDAR startup, expands its offerings to smartphones:

"With samples available in the fourth quarter of this year, the Lumotive X20 and Lumotive Z20 LiDAR systems target the automotive and industrial automation markets, respectively. Lumotive’s M20, addressing needs of the consumer and mobile markets, will be introduced in 2021.

The X20 targets long-range automotive applications with range over 120 meters in bright sunlight and a 120° x 30° field of view. The Z20 will have a shorter range (~ 50 meters) but an expanded 70° vertical field of view to address industrial and short-range automotive needs."

Looking for alternative applications beyond the slowing automotive market, Lumotive finds inspiration in Apple iPad LiDAR and designs a mobile version of its LiDAR:

5 Days of Free On-Line SPAD Webinars

University of Glasgow, UK, QuantIC group announces a series of 5 Webinars on June 1-5:

Detector Development:
Enhanced detectors underpin many of our demonstrators where increased sensitivity to single- photons at challenging wavelengths and/or higher count rates unlocks pathways to new imaging applications. These sensors will be used across all the sectors covered in these webinar series.

Life Sciences:
The QuantIC programme is delivering paradigm-shifting quantum imaging systems to our innovation partners. Biomedical imaging is an area where QuantIC seeks to expand its contributions. These will primarily be in through body imaging and microscopy. There is strong industry interest in both fluorescence and super-resolution microscopy to improve performance utilising SPAD arrays and other components. This webinar will showcase the progress made in this area to date.

Computational Methods:
The role and impact of computational imaging and machine learning in quantum imaging systems is growing significantly. Our initial focus will be on a Bayesian framework coupled with machine learning methods to develop these methods in partnership with the quantum sensors to make integrated systems where the overall performance is optimised for the limitations and advantages that quantum derived data presents.

Transport:
Imaging through complex media such as fog, rain and snow are some of the most topical challenges in the autonomous vehicles and assisted drivers’ landscape. This webinar will discuss how we are working with end users and technology providers, to deliver system demonstrators combining optimisation of detector technology, image reconstruction for low-photon and low-cost visible and infrared LIDAR.

Security and Sensors:
Quantum phenomena will have impact in broad areas of security and sensors. We are developing quantum LIDAR, radar and covert imaging systems and developing UK capability for near IR SPADs and SPAD arrays for security and defence. Additionally, we continue to develop monitoring systems for secure infrastructure e.g. airports, rail stations, utilising different wavelengths. This session will showcase the latest demonstrator capabilities.

Japan Display Inc. to Enter Image Sensor Business

JapanTimes, Mainichi: Japan Display Inc. (JDI) formed in 2012 through the merger of the display operations of Sony, Hitachi, and Toshiba announces its intention to enter image sensor business. The first product is 15um pixel-based bendable sensor developed with the University of Tokyo that can detect biometric information such as fingerprints and heart rate waves.

"We would like to foster our sensor products as a key pillar of our business that currently relies on the smartphone and the auto market," says JDI President Minoru Kikuoka. The company plans to introduce its image sensor products to the market in a few years, he added.