Low-Power High-Gain Operational Amplifier for Analog Image Pre-Processing in Smart Sensor Systems

Title data

Söll, Christopher ; Mai, Timo ; Shi, Lan ; Röber, Jürgen ; Ußmüller, Thomas ; Weigel, Robert ; Hagelauer, Amelie:
Low-Power High-Gain Operational Amplifier for Analog Image Pre-Processing in Smart Sensor Systems.
In: ANALOG 2016 : Beiträge der 15. ITG/GMM-Fachtagung. - Berlin : VDE Verl. , 2016 . - pp. 28-32
ISBN 978-3-8007-4265-3

Official URL:

Abstract in another language

In this work, a low-power high-gain operational amplifier is presented, which is dedicated to work in an analog image pre-processing stage in a smart sensor system. This stage is able to detect edges and shapes for instance, before the image is passed to the ADC and the digital computation stage, reducing data and precision requirement of both stages. This approach helps to save power, making smart image sensor nodes with energy harvesting reasonable. Since the precision as well as the energy consumption of the edge detection algorithm is highly depended on the amplifier used for the basic summing and multiplier blocks, the design of it plays an important role for the approach. The proposed input/output rail-to-rail operational amplifier is based on a 150 nm CMOS process, has a gain of 77 dB and a unity gain bandwidth of 45.7MHz while consuming only 77 μA statically at a supply voltage of 1.8V.

Further data

Item Type:	Article in a book
Refereed:	Yes
Keywords:	analog pre-processing; operational amplifier; low-power; high-gain; folded-cascode; GRK-1773
Institutions of the University:	Faculties > Faculty of Engineering Science > Former Professors > Chair Communication Electronics - Univ.-Prof. Dr.-Ing. Amélie Marietta Hagelauer Faculties Faculties > Faculty of Engineering Science Faculties > Faculty of Engineering Science > Chair Communication Electronics Faculties > Faculty of Engineering Science > Former Professors
Result of work at the UBT:	No
DDC Subjects:	600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited:	18 Oct 2019 10:51
Last Modified:	18 Oct 2019 10:51
URI:	https://eref.uni-bayreuth.de/id/eprint/52524