Archives for December 2019

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Japanese Applied Physics Express Journal publishes a paper "High-exposure-durability, high-quantum-efficiency (>90%) backside-illuminated soft-X-ray CMOS sensor" by Tetsuo Harada, Nobukazu Teranishi, Takeo Watanabe, Quan Zhou, Jan Bogaerts, and Xinyang Wang from University of Hyogo, Shizuoka University, and Gpixel.

"We develop a high-quantum-efficiency, high-exposure-durability backside-illuminated CMOS image sensor for soft-X-ray detection. The backside fabrication process is optimized to reduce the dead-layer thickness, and the Si-layer thickness is increased to 9.5 μm to reduce radiation damage. Our sensor demonstrates a high quantum efficiency of greater than 90% in the photon-energy range of 80–1000 eV. Further, its EUV-regime efficiency is ~100% because the dead-layer thickness is only 5 nm. The readout noise is as low as 2.5 e− rms and the frame rate as high as 48 fps, which makes the device practical for general soft X-ray experiments.

...we developed a new CMOS sensor with further improvements to the backside process to afford a thicker Si layer of 9.5 μm; we called this sensor the SP3 sensor. This soft-X-ray/EUV-regime SP3 image sensor is also based on the Gpixel BSI CMOS image sensor, GSENSE400SQBSI. ...We made two changes to the backside fabrication process for the SP3 relative to the SBSA: the silicon thickness was changed from 3.5 to 9.5 μm to suppress radiation damage, and that the implantation energy was decreased by one digit to reduce the non-sensitive-layer thickness. Our CMOS sensor adopts a rolling shutter and a high dynamic range (HDR) scheme using the double-conversion gain method, and has 2048 (H) × 2048 (V) 11 μm pixels. "


Thanks to NT for the link!

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Sony IEDM 2019 paper "Three-layer Stacked Color Image Sensor With 2.0-μm Pixel Size Using Organic Photoconductive Film" by H. Togashi, T. Watanabe, M. Joei, T. Hayashi, S. Hirata, S. Fukuoka, Y. Ando, Y. Sato, J. Yamamoto, I. Yagi, M. Murata, M. Kuribayashi, F. Koga, T. Yamaguchi, Y. Oike, T. Ezaki, and T. Hirayama combines 3T organic PD pixel with 4T Si-based pixel ideas:

"A three-layer stacked color image sensor was formed using an organic film. The sensor decreases the false color problem as it does not require demosaicing. Furthermore, with the 2.0-μm pixel image sensor, improved spectral characteristics owing to green adsorption by the organic film above the red/blue photodiode, were successfully demonstrated."

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Digitimes: Two major Taiwan-based CMOS sensor packaging companies Tong Hsing and Kingpark have agreed to merge to turn them into one of the world's largest CIS packaging houses.

Taipei Times: Tong Hsing plans to acquire all of the shares in Kingpak after its board of directors approved a share-swap deal. The companies hope to complete the deal by June 30, 2020 and expect to pursue emerging opportunities in the smartphone, ADAS, IoT, the Internet of Vehicles, VR, and AR markets, the filing said.

“The two companies have little overlap in customers and products, but they are highly complementary,” Tong Hsing president Heinz Ru said at a press conference at the Taiwan Stock Exchange. Kingpak is to become a wholly owned unit of Tong Hsing and be delisted from the Taipei Exchange when the merger is completed.

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Sony paper at IEDM 2019 presents "A 1/2inch 48M All PDAF CMOS Image Sensor Using 0.8µm Quad Bayer Coding 2×2OCL with 1.0lux Minimum AF Illuminance Level" by T. Okawa, S. Ooki, H. Yamajo, M. Kawada, M. Tachi, K. Goi, T. Yamasaki, H. Iwashita, M. Nakamizo, T. Ogasahara, Y. Kitano, and K. Tatani.

"Currently, there are two coding trends in mobile image sensors: Quad Bayer coding (QBC) and dual photodiode (DPD). QBC realizes high resolution and high dynamic range (HDR), whereas DPD achieves high phase detection auto focus (PDAF) performance. We propose a QBC with 2×2 on-chip lens (2×2OCL) architecture as a potential next-generation high-performance CMOS image sensor. This combines high resolution, HDR, and high PDAF performance in one sensor. The critical issues of 2×2OCL are degradation of the resolution due to the sensitivity difference between 4 pixels under the same color filter and increasing the crosstalk among different colors. To overcome these issues, the OCL and pixel isolation shapes were optimized respectively. The world`s first image sensor using 2×2OCL architecture we prepared in this paper, has 1/2 inch 48M pixels with 0.8µm QBC for high resolution, and all pixel PDAF achieved a minimum AF illuminance level of 1 lux."

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OSA Optics Express publishes an open access paper "Joint electromagnetic and ray-tracing simulations for quad-pixel sensor and computational imaging" by Guillaume Chataignier, Benoit Vandame, and Jérôme Vaillant from InterDigital and University Grenoble Alpes, France.

"Since Canon released the first dual-pixel autofocus in 2013, this technique has been used in many cameras and smartphones. Quad-pixel sensors, where a microlens covers 2x2 sub-pixels, will be the next development. In this paper we describe the design for such sensors; related wave optics simulations; and results, especially in terms of angular response. Then we propose a new method for mixing wave optics simulations with ray tracing simulations in order to generate physically accurate synthetic images. Those images are useful in a co-design approach by linking the pixel architecture, the main lens design and the computer vision algorithms."

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Instructables publish a Sean Hodgins' project on DIY 32 x 32 image sensor and a camera based on it:

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BusinessKorea quotes TSR report on image sensor market:

"According to market research firm TSR, the global image sensor market is expected to have grown from US$13,116 million to US$15,883.9 million this year. At present, the market shares of Sony, Samsung Electronics and SK Hynix are 48.3 percent, 21 percent and 2.1 percent, respectively. The current market size is about 25 percent of the size of the NAND flash market and the former is predicted to catch up with the latter in the near future.

In the third quarter of this year, Sony was the world’s eighth-largest semiconductor company in terms of sales despite the fact that image sensors are almost the only semiconductor product it produces."

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Toshiba Teli publishes a presentation on trends in machine vision cameras:

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Omnivision's IEDM 2019 paper "A 2.2µm stacked back side illuminated voltage domain global shutter CMOS image sensor" by Geunsook Park, Alan Chih-Wei Hsuing, Keiji Mabuchi, Jingming Yao, Zhiqiang Lin, Vincent C. Venezia, Tongtong Yu, Yu-Shen Yang, Tiejun Dai, and Lindsay A. Grant presents the world's smallest GS pixel that appears to be optimized for 940nm structured light 3D vision applications:

"This paper presents a 2.2µm pixel pitch back side illuminated (BSI) Voltage Domain Global Shutter (VDGS) image sensor with Stacked Pixel Level Connection (SPLC) and full backside Deep Trench Isolation (DTI). With these cutting edge technologies, Full Well Capacity (FWC) more than 12,000 electrons and parasitic light sensitivity (PLS) larger than 100 dB are reached. A 38% Quantum Efficiency (QE) and 60% of Modulation Transfer Function (MTF) at 940nm, half Nyquist frequency (Ny/2) is demonstrated."

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Samsung IEDM 2019 paper "A 0.8 µm Smart Dual Conversion Gain Pixel for 64 Megapixels CMOS Image Sensor with 12k e- Full-Well Capacitance and Low Dark Noise" by Donghyuk Park, Seung-Wook Lee, Jinhwa Han, Dongyoung Jang, Heesang Kwon, Seungwon Cha, Mihye Kim, Haewon Lee, Sungho Suh, Woong Joo, Yunki Lee, Seungjoo Nah, Heegeun Jeong, Bumsuk Kim, Sangil Jung, Jesuk Lee, Yitae Kim, Chang-Rok Moon, and Yongin Park presents the company's latest generation sensor:

"A 0.8 μm-pitch 64 megapixels ultra high resolution CMOS image sensor has been demonstrated for mobile applications for the first time. Full-well capacity (FWC) of 6k e- was achieved in 0.8 μm pixels as the best in the world, and the advanced color filter (CF) isolation technology was introduced to overcome sensitivity degradation. Dual conversion gain (CG) technology was also first applied to mobile applications to improve the FWC performance of Tetracell up to 12k e-. In addition, highly refined deep trench isolation (DTI) and photodiode design significantly improved dark noise characteristics."

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Livox announces long range 260m Horizon and 500m Tele-15 LiDARs:


Velodyne publishes a white paper "LiDAR-based Security Solutions" saying that one of the key LiDAR advantages over camera is privacy:

"With increased concerns that facial-recognition technology will be used for general surveillance,1 a system that utilizes lidar as the initial source of object detection data enables a security solution that preserves trust and anonymity. This is especially important in applications involving the general public, such as retail monitoring and queue management."


MicrocontrollerTips publishes a 4-part review "LIDAR and Time of Flight" by Bill Schweber. Few quotes:

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Renato Turchetta, CEO of IMASENIC, Barcelona, Spain presents "CMOS image sensors for scientific, bio-medical and space applications: more than pretty pictures!" at CERN seminar. Few slides from the document:

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Digitimes: Goodix is to become the largest TSMC customer for its 8-inch fabs, thanks to its burgeoning business of under-display optical fingerprint sensors.

Sony opens Osaka-area design center for CMOS image sensors on April 1, 2020. "With the opening of the Osaka office, Sony has strengthened its CMOS image sensor design and development capabilities for mobile devices and the IoT market, which are expected to expand in the future, by acquiring talented analog and logic design engineers in Kansai. We aim to expand our product lineup."


Bloomberg reports that Sony has hard time manufacturing enough image sensors to keep up with high demand.

"For the second straight year, the Japanese company will run its chip factories constantly through the holidays to try and keep up with demand for sensors used in mobile phone cameras, according to Terushi Shimizu, the head of Sony’s semiconductor unit.

“Judging by the way things are going, even after all that investment in expanding capacity, it might still not be enough,” Shimizu said in an interview at the Tokyo headquarters. “We are having to apologize to customers because we just can’t make enough.”

Sony in May said it controls 51% of the image sensor market as measured by revenue and is targeting a 60% share by fiscal 2025. Shimizu estimates Sony’s portion of the pie grew by a few percentage points this year alone.

Sony is now looking to a new generation of sensors that can see the world in three dimensions. “This was the year zero for time of flight,” Shimizu said. “Once you start seeing interesting applications of this technology, it will motivate people to buy new phones.”

Sony’s ToF camera module.Photographer: Kiyoshi Ota/Bloomberg

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MDPI paper "A Time-of-Flight Range Sensor Using Four-Tap Lock-In Pixels with High near Infrared Sensitivity for LiDAR Applications" by Sanggwon Lee, Keita Yasutomi, Masato Morita, Hodaka Kawanishi, and Shoji Kawahito from Shizuoka University, Japan promises enhanced range and ambient light tolerance:

"In this paper, a back-illuminated (BSI) time-of-flight (TOF) sensor using 0.2 µm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) technology is developed for long-range laser imaging detection and ranging (LiDAR) application. A 200 µm-thick bulk silicon in the SOI substrate is fully depleted by applying high negative voltage at the backside for higher quantum efficiency (QE) in a near-infrared (NIR) region. The proposed SOI-based four-tap charge modulator achieves a high-speed charge modulation and high modulation contrast of 71% in a NIR region. In addition, in-pixel drain function is used for short-pulse TOF measurements. A distance measurement up to 27 m is carried out with +1.8~−3.0% linearity error and range resolution of 4.5 cm in outdoor conditions. The measured QE of 55% is attained at 940 nm which is suitable for outdoor use due to the reduced spectral components of solar radiation."

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International Journal of Engineering Research & Technology (IJERT) publishes a paper "CMOS Image Sensors: Recent Innovations in Imaging Technology" by Gagan Khanduri, Dev Bhoomi Institute of Technology, Dehradun, India. Most of the "recent innovations" in the paper are a deep history by now:

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GPixel publishes a fairly detailed datasheet explaining 4MP, 6.5um pixel GSENSE2020BSI sCMOS sensor operation and performance (link to datasheet file has been removed on GPixel request):

"Same as other sCMOS sensors in the GSENSE series, GSENSE2020BSI outputs the image signal from both the top readout chain and the bottom readout chain simultaneously. These two images have exact the same exposure time, but different analog gains, where the low gain (LG) image is optimized for high full well capacity, and the high gain (HG) image is optimized for low readout noise. User may combine both high gain (HG) and low gain (LG) images from the sensor to generate one HDR image off-chip. Figure 1 shows the sensor operation for high dynamic range (HDR) image combination."

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Sony presentation at IEDM 2019 "Nanophotonics contributions to state-of-the-art CMOS Image Sensors" by Sozo Yokogawa discusses the recent features that Sony has added to its BSI pixel lineup:

"Recent progress of Back-illuminated CMOS image sensor (BI-CIS), focusing on their pixel improvements with design of optical properties using subwavelength sizescale structures and photonics technologies, are reviewed. These technologies contribute not only improving BI-CIS basic performances but also adding new functions for versatile sensing applications."

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BusinessWire: ams releases the NanoVision and NanoBerry evaluation kits, which provide a ready-made platform for the development of innovative solutions based on the NanEyeC miniature image sensor. The NanEyeC camera is a full-featured image sensor supplied as a tiny 1mm x 1mm surface-mount module. This small form factor can produce an amazing 100kpixel resolution up to 58fps.

The new NanoVision demo kit for the NanEyeC is based on an Arduino development platform. The NanoBerry evaluation kit uses a NanEyeC image sensor add-on board to the Raspberry Pi board. Ams considers a multitude of new markets spanning from low frame-rate applications like presence detection to more demanding operations like eye tracking or stereo vision systems.

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Pioneer announces the mass production readiness of its MEMS LiDAR: Pioneer has "developed a mass-production model of 3D LiDAR sensor, which is a much compact size, an extended measurement distance and improved performance. The sensor is expected to be equipped in advanced autonomous driving vehicles (supporting level-three and above autonomous vehicles) and will be released in first half of FY2020, and started a full-scale production from autumn 2020.

The 3D-LiDAR sensor, which is to be mass-produced in autumn 2020 (“2020 model”, hereafter) has adopted Micro Electric Memory Systems (MEMS) mirror-based scanning method. In addition to offering high resolution, it has been downsized to less than 20% of previous model (“2018 model”, hereafter) while achieving 1.5 to 2 times the measurement distance. There are three types of sensors with different angles of view and measurement distances, and an angle type, making it possible to accommodate customer needs by combining the different types."


BusinessWire: ON Semi to demo its SPAD-based silicon photomultiplier (SiPM) LiDAR sensor inside Robosense RS-LiDAR-M1 scanning LiDAR:

“SiPMs are quickly displacing APDs in solid-state LiDAR systems at the near-infrared (NIR), 905nm wavelength,” said Wade Appelman, VP of the SensL Division, Intelligent Sensing Group at ON Semiconductor. “We are excited to be highlighting our LiDAR partners who have designed in our latest AEC-Q101 qualified R-Series detectors because of their market leading 15% photon detection efficiency (PDE), a critical performance parameter to achieve long distance ranging.”

Low density versions of the technology have been used in consumer applications, but these devices do not work beyond 2 meters and are not reliable enough in bright lighting conditions. The new devices are said to be far more flexible and can be used with a variety of scene illumination architectures for ToF including scanning and flash.


VentureBeat: Russian Yandex announces its LiDAR plans too in its Medium post:

"Two lidar sensors will hit the streets in the coming months — one with a 120-degree view that’s solid-state (meaning the entire system is built on a silicon chip) and a second that provides a 360-degree view of its surroundings.”

“Third-party lidars analyze and filter data as soon as it’s collected. Using our lidars, we receive more information about the vehicle’s surroundings since we can access the sensors’ raw data,” says Dmitry Polishchuk, Head of Self-Driving Cars at Yandex. “With our lidars, we can analyze the raw data and synchronize it with information from other sensors, so that the car can better identify objects. In addition, our current prototypes are already half the cost of existing devices. With the transition to mass production, the cost of our lidars will be even lower, and we will ultimately save up to 75% on the cost of sensors.”


IDTechEx forecasts that LiDAR will become quite a sizable market, but only after 2028:

"By 2030, the autonomous driving system (including lidars, radars, cameras, computers, software and maps) market will reach $57 billion; the market value will more than triple by 2040, reaching $173 billion."


Yu Huang publishes a large 223-page presentation on LiDAR technology. Among other things, the presentation discusses the LiDAR calibration complexities:

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MDPI paper "An Optical Filter-Less CMOS Image Sensor with Differential Spectral Response Pixels for Simultaneous UV-Selective and Visible Imaging" by Yhang Ricardo Sipauba Carvalho da Silva, Rihito Kuroda, and Shigetoshi Sugawa from Tohoku University, Japan, belongs to the Special Issue Special issue on the 2019 International Image Sensor Workshop (IISW2019).

"This paper presents a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) capable of capturing UV-selective and visible light images simultaneously by a single exposure and without employing optical filters, suitable for applications that require simultaneous UV and visible light imaging, or UV imaging in variable light environment. The developed CIS is composed by high and low UV sensitivity pixel types, arranged alternately in a checker pattern. Both pixel types were designed to have matching sensitivities for non-UV light. The UV-selective image is captured by extracting the differential spectral response between adjacent pixels, while the visible light image is captured simultaneously by the low UV sensitivity pixels. Also, to achieve high conversion gain and wide dynamic range simultaneously, the lateral overflow integration capacitor (LOFIC) technology was introduced in both pixel types. The developed CIS has a pixel pitch of 5.6 µm and exhibits 172 µV/e− conversion gain, 131 ke− full well capacity (FWC), and 92.3 dB dynamic range. The spectral sensitivity ranges of the high and low UV sensitivity pixels are of 200–750 nm and 390–750 nm, respectively. The resulting sensitivity range after the differential spectral response extraction is of 200–480 nm. This paper presents details regarding the CIS pixels structures, doping profiles, device simulations, and the measurement results for photoelectric response and spectral sensitivity for both pixel types. Also, sample images of UV-selective and visible spectral imaging using the developed CIS are presented."

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EPFL publishes PhD Thesis "Challenges and Solutions to Next-Generation Single-Photon Imagers" by Samuel Burri.

"In this thesis, we look at the challenges of massively parallel photon-counting cameras from all performance angles. The thesis deals with a number of performance issues that emerge when the number of pixels exceeds about 1/4 of megapixels, proposing characterization techniques and solutions to mitigate performance degradation and non-uniformity. Two cameras were created to validate the proposed techniques. The first camera, SwissSPAD, comprises an array of 512 x 128 SPAD pixels, each with a one-bit memory and a gating mechanism to achieve 5ns high precision time windows with high uniformity across the array. With a massively parallel readout of over 10 Gigabit/s and positioning of the integration time window accurate to the pico-second range, fluorescence lifetime imaging and fluorescence correlation spectroscopy imaging achieve a speedup of several orders of magnitude while ensuring high precision in the measurements. Other possible applications include wide-field time-of-flight imaging and the generation of quantum random numbers at highest bit-rates. Lately super-resolution microscopy techniques have also used SwissSPAD. The second camera, LinoSPAD, takes the concepts of SwissSPAD one step further by moving even more 'intelligence' to the FPGA and reducing the sensor complexity to the bare minimum. This allows focusing the optimization of the sensor on the most important metrics of photon efficiency and fill factor. As such, the sensor consists of one line of SPADs that have a direct connection each to the FPGA where complex photon processing algorithms can be implemented. As a demonstration of the capabilities of current lowcost FPGAs we implemented an array of time-to-digital converters that can handle up to 8.5 billion photons per second, measuring each one of them and accounting them in high precision histograms. Using simple laser diodes and a circuit to generate light pulses in the picosecond range, we demonstrate a ubiquitous 3D time-of-flight sensor. The thesis intends to be a first step towards achieving the world's first megapixel SPAD camera, which, we believe, is in grasp thanks to the architectural and circuital techniques proposed in this thesis. In addition, we believe that the applications proposed in this thesis offer a wide variety of uses of the sensors presented in this thesis and in future ones to come."

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