Extraction of Trap Energy Distribution in Proton-Irradiated Focal Plane Arrays Using a High-Precision Random Telegraph Noise Detection Algorithm

Abstract

Random telegraph noise (RTN) is a type of low-frequency noise that degrades the sensitivity of focal plane arrays (FPAs) and other electronics. Careful analysis of RTN provides information about the material defects generating this noise and ultimately may lead to a solution to eliminate this noise source from the optoelectronic imaging system. The focus of this effort is the definition and demonstration of a simple histogram-based detection algorithm, which evaluates the shape of the pixel output histogram in order to detect RTN pixels and extract the energy levels of the defects. The algorithm sensitivity and precision statistics are benchmarked as a function of the detection threshold. Applying the algorithm to a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1280\times1024$ </tex-math></inline-formula> infrared FPA irradiated with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.2\times 10^{11}$ </tex-math></inline-formula> protons/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (63 MeV) shows a maximum 84% increase in the number of pixels exhibiting RTN from preradiation to post-300 K anneal. The distribution of preradiation trap energies shows clusters at 13 meV above the Fermi level and 14 and 44 meV below the Fermi level. The radiation-induced defects, however, exhibit a different energy distribution with an increased concentration at the Fermi level, suggesting different energy distributions for the traps created during the manufacturing process compared to those created by proton radiation.