Acoustic weapons identification is the forensic analysis of audio recordings to characterise firearm events and, where evidence permits, attribute them to specific weapon classes. The discipline draws on two distinct physical signatures: the muzzle blast, a low-frequency pressure wave from propellant gases, and the ballistic crack, a supersonic shockwave from the projectile. Their relative timing constrains the shooter's azimuth and, combined with cyclic-rate measurement, weapon type. Spectrogram analysis of the blast's frequency envelope permits calibre inference against reference recordings from anechoic databases.
The method applies when a recording contains audio of sufficient quality to distinguish impulsive acoustic events: identifying weapon types responsible for casualties, estimating firing position distance and direction, distinguishing outgoing from incoming fire, corroborating or refuting official accounts, and verifying the authenticity of claimed combat footage. Each measurement, taken alone, is ambiguous. The pattern, corroborated across independent recordings and reference sources, is not.
ACU-001 sets out the methodology for securing, extracting, analysing, and grading audio evidence from conflict recordings to evidentiary standard.
Eight workflow steps, six tooling sources, five false-positive checks, five chain-of-custody requirements.
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01
Required Tools
Six platforms covering audio extraction, spectrogram analysis, and reference comparison.
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02
OPSEC
Local-only analysis, hashing requirements, and peer review before publication.
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03
Workflow
Eight-step sequence from source acquisition to graded, archived findings.
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04
False Positives
Reverberation, codec artefacts, shared cyclic rates, and non-gunshot impulsive sources.
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05
Chain of Custody
Five requirements covering hashing, extraction logging, and intermediate file retention.
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06
Key Queries
Six operator paths across Audacity, FFmpeg, Google Scholar, and MSU Database.
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A PDF version of ACU-001 is available below for Signal subscribers.
