Mode-selective read-in integrated circuit with improved input range for infrared scene projectors

Min Ji Cho; Hee Chul Lee

doi:10.1117/12.2518578

14 May 2019 Mode-selective read-in integrated circuit with improved input range for infrared scene projectors

Min Ji Cho, Hee Chul Lee

Proceedings Volume 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX; 1100119 (2019) https://doi.org/10.1117/12.2518578
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

As infrared (IR) imaging systems are being used more often in military fields, the importance of IR sensor evaluation system has emerged. Owing to their non-destructiveness and cost effectiveness, hardware-in-the-loop (HWIL) systems with IR scene projectors (IRSPs) are now being widely used. IRSPs generate virtual IR scenes to evaluate IR imaging systems, which has two performance parameters: thermal range and thermal resolution. Specifically, IR scene quality is determined by the thermal resolution performance and the input digital depth increment can provide a suitable solution to improve resolution. However, the input digital depth increment is limited by system noise and setting a sufficient thermal resolution with wide thermal range is difficult. In this paper, a mode-selective read-in integrated circuit (RIIC) with native transistor is proposed. The native transistor having almost zero threshold voltage, increases the input range, which helps to improve noise margin. A prototype of the RIIC was fabricated using a 0.18-μm 1-poly 6-metal CMOS process and its performance was estimated from measured data. Thermal resolution below 325 K was less than 30 mK and was 185 mK above 325 K in high-current mode; with 14-bit digital resolution, the thermal range varied from 270-325 K to 270-990 K.

Citation Download Citation

Min Ji Cho and Hee Chul Lee "Mode-selective read-in integrated circuit with improved input range for infrared scene projectors", Proc. SPIE 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX, 1100119 (14 May 2019); https://doi.org/10.1117/12.2518578

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