New methodology for reducing sensor and readout electronics circuitry noise in digital domain

Abstract

Upcoming NASA cosmology science missions, such as Joint Dark Energy Mission (JDEM), carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection [2], and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensor and readout electronics. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed, for example, by the James Webb Space Telescope Project (JWST). These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active pixels' signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert-Huang Transform Data Processing System (HHT-DPS) to some component of reference pixel information. The new methodology applies digital signal processing for a 2-D domain. The high-variance components of the thermal noise, carried by both active and reference pixels, facilitate subtraction of a correction matrix from active pixels array in digital domain in addition to subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the statistical parameters in the digital domain (such as statistical averaging of the reference pixels) zero out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast varying noise components using the HHT-DPS and makes the case for re-implementation of HHT-DPS in reconfigurable hardware on-board a spaceflight instrument as a real-time processing system (RT-HHT-DPS) [1].