Math Bridge: Wi-Fi sensing Doppler

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Math BridgePrivacy & ComplianceStruggle-friendly runway

When does a Wi-Fi sample rate reveal walking motion?

Turn a reflection into a frequency, then decide what the receiver can reconstruct.

Privacy Priya, the guidePrivacy Priya guides
The one targetCalculate the sampling boundary for motion sensed through Wi-Fi.
The chapter case5 GHz; 1.40 m/s walk; 100 Hz capture; 10 Hz limit.
What it buys youA technical minimisation control with a measurable claim.

A field team faces an unresolved physical question: When does a Wi-Fi sample rate reveal walking motion? They must answer it before changing walk speed on the real device. Predict the direction first.

See the relationship before changing it

The figure reads from left to right. The blue card is walk speed. The middle card applies this page's relationship. The green card is wavelength. Walk the arrows once: set the input, apply the rule, then read the result with its unit.

The retained audit below checks several chapter fixtures. This added model holds every other chapter fixture fixed, so the numeric fixture does not switch without explanation.

Walk speed changes wavelength An input card leads through the page relationship to the wavelength result. SET INPUT ONE CONTROL APPLY RULE predict calculate check units READ RESULT
Walk the arrows. Rate limiting can remove reconstructable gait detail, but aliases can still look like slower motion and must be tested.

Derive the baseline in four named moves

  1. 1

    Name the input. The chapter baseline for walk speed is 1.4.

  2. 2

    Name the relationship. λ = 3.00x10⁸/(5.00x10⁹) = 0.0600 m walking fd = 2(1.40)/0.0600 = 46.7 Hz minimum sample rate = 93.3 Hz breathing fd = 0.628 Hz

  3. 3

    Substitute the chapter fixture. Set walk speed to 1.4. The page ledger gives wavelength as 0.060 m.

  4. 4

    Read the result. Keep m beside the value. Use it only inside the technical boundary on this page.

Predict, then change walk speed

Try Predict the direction of wavelength. Move one control, calculate, then check your prediction.

1.4
Chapter baseline
Wavelength

Observe Rate limiting can remove reconstructable gait detail, but aliases can still look like slower motion and must be tested. Reset the control to 1.4 and compare wavelength.

Explain Only walk speed moves here. The other chapter fixtures remain fixed.

Check yourself

What should you do before trusting a moved-control result?
Answer: Predict its direction, apply the shown relationship, keep the units, and reset to the worked baseline.
What does this small model leave out?
Answer: Only walk speed moves. Field effects named in the page's technical boundary stay fixed.

1. See the body as a changing path

A receiver adds the direct radio path to reflections. When a person moves, one reflected path changes length. Its phase then changes over time, which appears as a Doppler frequency in CSI or RSSI measurements.

Privacy Priya: A radio can sense motion even when nobody sends a motion field.

2. Name every algebra move

1

Find wavelengthλ=c/f.

2

Project velocityMultiply v by cos(θ).

3

Count the return pathfd=2v cos(θ)/λ.

4

Double for Nyquistfsample≥2fd.

3. Reproduce walking and breathing

λ = 3.00×10⁸/(5.00×10⁹) = 0.0600 m
walking fd = 2(1.40)/0.0600 = 46.7 Hz
minimum sample rate = 93.3 Hz
breathing fd = 0.628 Hz

A 100 Hz capture has only a 7.14% margin. Sampling at 10 Hz is 9.33× too slow for that walk and folds that motion to about 3.33 Hz.

4. Try the walking speed

TryMove radial speed and compare the required sample rate with 100 Hz capture and a 10 Hz limit.

Walk speed
Wavelength
Walking Doppler
Nyquist minimum
100 Hz margin
10 Hz shortfall
10 Hz alias
Breathing speed
Breathing Doppler

ObserveFaster radial motion raises Doppler and the honest sampling minimum in direct proportion.

ExplainRate limiting can remove reconstructable gait detail, but aliases can still look like slower motion and must be tested.

Technical boundaries.

The model follows one reflection moving along the link axis.

Geometry
Sideways motion reduces the cos(θ) term
Room
Real multipath produces several Doppler components
Receiver
Noise, quantisation, packets, and algorithms set detection limits

Verify the actual hardware and processing pipeline with consent-safe trials.

5. Turn maths into minimisation

Choose the lowest measurement rate and precision that still support the declared product action. Test whether gait, breathing, presence, or identity clues remain recoverable rather than assuming a lower number is private.

6. Record the privacy boundary

Record carrier, sample rate, resolution, retention, local versus remote processing, outputs, access, consent state, bystander exposure, and tests showing what motion can and cannot be inferred.

7. Check yourself

Why is walking about 46.7 Hz here?
Answer: The reflected path changes twice, so 2×1.40 m/s divided by 0.0600 m gives 46.7 Hz.
Why is 100 Hz only just enough?
Answer: Nyquist requires at least 93.3 Hz for the 46.7 Hz shift.
Does 10 Hz guarantee no motion inference?
Answer: No. It blocks faithful walking reconstruction in this case, but aliases and slower signals may remain.
Honesty boundary.

The chapter names the privacy control; the band, rates, walk, and breathing motion are explicit teaching assumptions.

5 GHz and 1.40 m/s
Worked sensing case
100 Hz and 10 Hz
Compared capture policies
1 cm at 0.300 Hz
Breathing illustration

Correct, not complete: this Doppler ledger does not prove privacy, consent, identity protection, or detector performance.