4 citations · 6 across the 5 of their papers we have counts for
5 papers
Development of a Photon-Counting Deadtime Noise Model that Extends Dynamic Range and Resolution in Atmospheric Lidar
Grant J. Kirchhoff, Matthew Hayman, Willem J. Marais +2
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-likeli…
Global Estimation of Range Resolved Thermodynamic Profiles from MicroPulse Differential Absorption Lidar
Matthew Hayman, Robert A. Stillwell, Adam Karboski +2
We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface…
2D Signal Estimation for Sparse Distributed Target Photon Counting Data
Matthew Hayman, Robert A. Stillwell, Josh Carnes +3
In this study, we explore the utilization of maximum likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifica…
Mimicking non-ideal instrument behavior for hologram processing using neural style translation
John S. Schreck, Matthew Hayman, Gabrielle Gantos +2
Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can…
Neural network processing of holographic images
John S. Schreck, Gabrielle Gantos, Matthew Hayman +2
HOLODEC, an airborne cloud particle imager, captures holographic images of a fixed volume of cloud to characterize the types and sizes of cloud particles, such as water droplets an…