Research on A/D driver circuit level nonuniformity correction technology based on machine learning

Abstract

A non-uniformity correction method based on machine learning for A/D driver circuit level. Firstly, different types of infrared detectors are placed in a temperature uniform radiation field. When they are working normally, the analog output signal waveform of each detector in multiple scenarios is collected multiple times to obtain the approximate average voltage value of each line in a frame, and saved as a document; Secondly, using GPU for machine learning of the above documents and accurately driving the D/A chip for digital to analog conversion, simulating the waveform voltage value of the analog output signal mentioned above to generate waveform voltage with similar nonuniformity; Thirdly, the voltage waveform generated by the multi-channel voltage output digital to analog converter is followed by an operational amplifier, filtered, and then output to the A/D chip as the reference voltage for sampling; Finally, the analog video signal output by the infrared detector is sampled and quantized by an A/D chip to obtain a more uniform image digital signal.