Non-negative sparse deconvolution method for PMT signals in radiation detectors

Abstract

Electrical signals generated by radiation detectors are often affected by undesired effects that can degrade the detector’s energy resolution. These effects may originate from the measurement system itself or from high event rates. Traditional signal shaping and mitigation methods present limitations, such as the need for explicit prior information about the signals. This paper proposes a deconvolution method based on least squares filtering and non-negative sparsity theory to overcome these limitations. The method is evaluated using simulated data representing a gamma-ray detector composed of a NaI(Tl) crystal and a photomultiplier tube (PMT). In this system, the electrical pulses are preprocessed using a CR coupling circuit followed by an RC integrator. The results show that the traditional method achieves an energy resolution of 6.60%, whereas the proposed method improves it to 5.65%. In addition to increasing accuracy, the proposed approach also reduces implementation complexity.