28 June 2021 to 2 July 2021
Europe/Vienna timezone

Distributed detection and fusion of multi-signature explosion-sourced waveforms: predictive capability, quantitative performance, and experimental demonstration

1 Jul 2021, 09:00


e-Poster T3.5 - Data Analysis Algorithms T3.5 e-poster session


Mr Joshua Carmichael (Los Alamos National Laboratory (LANL), Los Alamos, NM, USA)


Quantitative methods that enable multi-physics waveform fusion support explosion monitoring and general research in geophysical processes that comprises background emissions for explosion monitoring. We offer a constructive method to fuse statistics that we derive from multi-physics waveforms and improve our capability to detect small, above-ground explosions over methods that consume single waveforms. Our method advances Fisher’s Method to operate under both hypotheses of a binary test on noisy data and provides density functions required to forecast our ability to screen fused explosion signatures from noise. We apply this method against 12-day, multi-signature chemical explosion and noise records to illustrate three primary results. We show that: (1) a fused multi-physics statistic that combines radio, acoustic, and seismic waveforms can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability; (2) we can quantitively predict how this fused, multi-physics statistic performs with Fisher’s Method; and (3) that this data stream method competes well with lower fidelity, decentralized detection approaches. We additionally present our preliminary, but more general work that addresses multi-signature association of data streams to a common source.

Promotional text

This work supports the objective of improving nuclear test monitoring and verification by using chemical explosion test data to develop better methods of signal detection.

Primary authors

Mr Joshua Carmichael (Los Alamos National Laboratory (LANL), Los Alamos, NM, USA) Mr Neill Symons (Los Alamos National Laboratory (LANL), Los Alamos, NM, USA) Mr Brian Williams (Los Alamos National Laboratory (LANL), Los Alamos, NM, USA) Mr Dale Anderson (Los Alamos National Laboratory (LANL), Los Alamos, NM, USA)

Presentation materials