This project developed a CMOS Image Sensor (CIS) for the 2nd generation remote sensing satellite,its main achievement is to improve the ground resolution (also known as the Ground Sampling Distance, GSD) from 2 meters to sub-meter. The 12-cm large size chip of CMOS image sensor is implemented using Back-Side Illumination (BSI) CIS technology with mask stitching technologyutilizing the CMOS Time Delay Integration (CMOS TDI) technology in this design.

A CMOS image sensor is developed for the national space organization (NSPO) 3rd generation high-resolution remote sensing satellite,the main achievement is its capability to satisfy the demanded ground resolution of 0.5 m. This CMOS image sensor with a new time delay integration circuit is implemented using Back-Side Illumination CIS 0.13 μm technology. The anti-radiation capability of the chip is also boosted to extend the lifetime of the chip. Measurement systemdata analysis programs are developed to provide performance parameters of the proposed CMOS image sensor.

1.Low-Power Processing-in-sensor CMOS Image Sensor 2.Implementation of Low-PowerLow-Latency Deep Learning Chip based on Neuromorphic Intelligence (collaborated with MOST 108-2622-8-007-009) 3.Development of Neuromorphic Chip based on The Fruit Fly VisualSpatial Sensory Systems 4.Hardware-Software Co-Design for Neuromorphic AI Chips

Dynamic vision sensors have been investigated to report motion-only images for moving object recognition. Less but essential information helps post-process recognition algorithm reduces computationimproves accuracy. Implement low powerlow latency deep Learning chip based on neuromorphic Intelligence. The neuromorphic obstacle detection algorithm integrates visualproprioceptive signals. The algorithm is characterized by its efficiencylow power consumption. We possess the next-generation in-memory computing AI chipsnext-generation UAV key softwarehardware technology