Mitigating Baseline Shift in High Event-Rate Systems via Pole-Zero Cancellation and Wiener Filtering

Abstract

Energy reconstruction in high-energy calorimetry systems is strongly affected by signal conditioning, especially under high event-rate conditions. Shaping stages introduce long-duration components in the pulse response, leading to baseline shifts and degraded estimation performance. This work investigates the use of Pole-Zero Cancellation (PZC) as a pre-processing stage combined with Wiener filtering for amplitude estimation. The performance of the Wiener filter alone is compared with the PZC + Wiener approach. The PZC stage compensates for the exponential component introduced by the readout chain, stabilizing the baseline prior to reconstruction. Results show that, while both approaches perform similarly under low-occupancy conditions, the Wiener filter alone degrades significantly in high-occupancy scenarios due to systematic bias. The proposed PZC + Wiener approach reduces reconstruction error and improves robustness in environments with significant signal overlap.