Framing the Discussion

Past experience · Sonar pipeline relevance · Working system

The Sonar Context

Sonar systems operate under persistent physical uncertainty: multipath, thermoclines, variable noise floors.

Data is expensive to collect, often ambiguous at first pass, and frequently understood after the fact.

That makes long-term storage, replay, and re-interpretation operational necessities.

Relevant Experience I Bring

I’ve spent ~20 years building long-lived, high-throughput systems where data must remain usable years after capture.

This includes large-scale digital asset management, continuous ingest pipelines, data capture, tagging, analysis and systems where assumptions and processing logic evolve.

My focus has consistently been keeping systems defensible, testable, and replayable over time.

Where This Fits in Your Pipeline

In sonar, raw acoustic data is evidence, not just input to a model.

If capture, preprocessing, and configuration aren’t versioned and replayable, confidence degrades quickly.

The system I’ll walk through shows how my experience maps directly onto capture, DSP, detection, and regression testing.

I’ll follow a real signal through a working pipeline, and at each stage explain where my past experience directly applies to the problems you’re solving.