Development of a Photon-Counting Deadtime Noise Model that Extends Dynamic Range and Resolution in Atmospheric Lidar

TL;DR

This paper introduces a novel photon-counting deadtime noise model for atmospheric lidar that improves dynamic range and resolution, enabling more accurate high-resolution profiling and deadtime correction in lidar measurements.

Contribution

It develops and validates a new noise model that accounts for deadtime effects in photon-counting detectors, enhancing lidar data processing capabilities.

Findings

Outperforms existing models at high resolution and short time-of-flight

Accurately corrects deadtime effects for short integration times

Enables high-resolution atmospheric lidar profiling

Abstract

This work derives and validates a noise model that encapsulates deadtime of non-paralyzable detectors with random photon arrivals to enable advanced processing, like maximum-likelihood estimation, of high resolution atmospheric lidar profiles while accounting for deadtime bias. This estimator was validated across a wide dynamic range at high resolution (4 millimeters in range, 17 milliseconds in time). Experiments demonstrate that the noise model outperforms the current state-of-the-art for very short time-of-flight (2 nanoseconds) and extended targets (1 microsecond). The proposed noise model also produces accurate deadtime correction for very short integration times. This work sets the foundation for further study into accurate retrievals of high flux and dynamic atmospheric features, e.g., clouds and aerosol layers.