After about 20,000 RF scans of my garage—where there’s no wireless mic to speak of—I’m starting to understand something that never clicked before:

The speed at which you gather data fundamentally changes what you can perceive—especially when that data is averaged, sorted by range, and viewed over time.

Some scans are blurry. Some miss signals entirely because they’re too slow. And some signals? They’re periodic and ephemeral, showing up maybe 1 in every 100 passes. If you blink, you miss them. But if you persist, patterns begin to emerge.

We often hear the phrase, “Insanity is doing the same thing over and over and expecting different results.” But maybe that’s not insanity—maybe it’s data science.

In the world of RF, you can ask the same question again and again—not because you’re stubborn, but because you’re building a statistical profile over time. When I started developing acquisition software for my spectrum analyzer, I noticed something magical: By asking the same question repeatedly, the hardware eventually starts whispering truths it couldn’t tell me the first time.

To help illustrate this, I turn to Jack Barker of Silicon Valley, and his infamous “Conjoined Triangles of Success.” It’s a corporate parody—but surprisingly, it maps perfectly onto RF scanning:

Conjoined Triangles of RF Scanning

• Top (Horizontal Axis): Number of Passes
  (Like multiple scans over time. Persistence reveals the invisible.)

• Right (Vertical Axis): Reliability
  (Accuracy and consistency of signal identification.)

• Bottom (Horizontal Axis): Speed
  (How fast scans are performed. Fast & wide vs. slow & narrow.)

• Left (Vertical Axis): Cross Referencing
  (Matching signals across datasets, locations, and time.)

• Center Diagonal / Hypotenuse: Understanding
  (The balance achieved by compromising between all four.)

Concept Explanation

• Speed vs. Reliability:
  Scanning too quickly may reduce accuracy. Slower scans yield better fidelity—but at the cost of missing transient activity.

• Number of Passes vs. Cross-Referencing:
  Repeating scans over time enables signal pattern recognition, anomaly detection, and correlation with known databases (like government spectrum allocations).

• Understanding as Hypotenuse:
  True insight into the RF environment only happens when all these factors are considered in context. This is the “compromise line”—and it leads to operational awareness, not just raw data.

Success in RF analysis isn’t just a product of better equipment—it’s about maniacal repetition, statistical context, and the persistence to let subtle truths emerge.

And ironically, maybe doing the same thing over and over again is exactly what you need—if you’re listening closely enough.