A Recursive Method for Real-Time Waveform Fitting with Background Noise Rejection
Abstract
We present here a technique for developing a high-throughput algorithm to fit a combination of template pulse shapes while simultaneously subtracting parameterized background noise. By convolving the psuedoinverse of the least-squares fit design matrix along a regularly sampled waveform trace, the time evolution of the fit parameters for each basis function can be determined in real-time. We approximate these sliding linear fit response functions using piecewise polynomials, and develop an FPGA-friendly algorithm to be implemented in high sample-rate data acquisition systems. This is a robust universal filter that compares well to common filters optimized for energy calibration/resolution, as well as filters optimized for timing performance, even when significant noise components are present.
Cite
@article{arxiv.2012.05937,
title = {A Recursive Method for Real-Time Waveform Fitting with Background Noise Rejection},
author = {A. P. Jezghani and L. J. Broussard and C. B. Crawford},
journal= {arXiv preprint arXiv:2012.05937},
year = {2020}
}
Comments
This work has been submitted to IEEE TNS for publication