FIELD ENGINEERING UWB LOCALIZATION / 01

See the position.
Understand the uncertainty.

A virtual greenhouse. A mobile tag. An observable experiment.

Explore how anchor geometry and biased ranges change the position you trust—then compare estimators on the same measurements.

Known-height 2D localization3D slant rangesReproducible simulation
01

Localization observatory

SIMULATION
Current position error—Horizontal distance · m
Trajectory RMSE—Root mean square error · m
95th percentile error—95% of valid errors are below · m
Solver availability—Valid estimates / observations · %
Through selected timeSelected estimator
Greenhouse observatoryPreparing the experiment
18.0 × 10.8 m · prescribed tag motion
Reference positionNLS estimateHuber estimateNLS nominal 95% ellipse
SITE LOCATORm
Drag to orbit · Scroll to zoom · Right-drag to pan
Preparing the observatoryBuilding geometry and reproducible measurements
SHOW
OBSERVATION TIME00:00 / 00:00
02

ASK A BETTER ENGINEERING QUESTION

Configure the experiment

Change one factor. Apply it. Observe what changes.

Measurement model

10 Hz

Independent Gaussian range noise plus a constant positive bias on one selected anchor. These are controlled assumptions.

Surveyed anchor positions

METRES
AnchorXYZUse

Coordinates are assumed exact. The solver uses 3D anchor-to-tag distance while estimating X and Y.

Prescribed inspection route

18 × 10.8 m

Prescribed tag path; no robot dynamics or crop-avoidance model.

The rover visualizes the experiment. It does not navigate from the UWB estimate.

Current configuration applied.

03

FROM MEASUREMENT TO POSITION

Inspect the evidence

Residuals describe fit. Position error describes accuracy.

Current range observations

SELECTED SAMPLE
AnchorMeasured
m
NLS residual
m
Huber residual
m
Huber
weight

A small residual does not prove that a range—or a position—is unbiased.

Position error along the route

METRES / SECONDS

Both fits use identical range observations. The reference position is used for scoring only.

04 / REPRODUCIBLE COMPARISON

One route is an illustration.
Twenty seeds reveal the pattern.

Compare ordinary and robust fitting across twenty paired full-route simulations, using the applied anchor survey and range model.

Same scenario. Same observations. Two estimators.
Is robust fitting helping in this scenario?

Use error statistics, availability, and nominal ellipse coverage together. Robust fitting is not guaranteed to improve every error metric.

Pooled error statistics use each estimator’s valid solves; compare availability as well. NLS ellipse coverage is a nominal LOS diagnostic, not calibrated under bias. Coverage is not a 95% calibration test when σ = 0.

TAKE THE EVIDENCE WITH YOU

Ready for a technical discussion.

Export the measurements, assumptions and figures behind the demonstration.

FIGURE CAPTION

Simulated known-height planar UWB localization with surveyed three-dimensional anchor positions. All reported performance is generated by the specified measurement model and is not a field measurement.

Model, interpretation & provenanceWhat the experiment represents—and where its evidence ends.

OBSERVATION MODEL

3D ranges. A known-height position.

The tag height is known and fixed. The estimator recovers only horizontal X and Y from anchor-to-tag slant ranges:

ri = √[(x − aix)² + (y − aiy)² + (h − aiz)²] + εi + bi

Range noise is independent Gaussian noise with standard deviation σ. A user-selected anchor can have an additional constant positive range bias. Anchor coordinates are treated as exactly surveyed.

Both estimators receive only anchor coordinates, ranges, σ, and the known tag height. They do not receive the reference trajectory or true position.

ESTIMATION & GEOMETRY

Fit is not the same as confidence.

Nonlinear least squares minimizes squared range residuals. The robust fit uses a Huber loss with a transition at 1.5σ (and a small numerical floor when σ = 0). Both methods use the same measurement-derived candidate starting points; neither is temporally filtered.

Σ = σ² (JᵀJ)−1   ·   χ²2, 0.95 = 5.991

The ellipse is centered at the NLS estimate and is a local, nominal unbiased-Gaussian LOS approximation. Selecting Huber does not turn it into a Huber confidence region. It is not calibrated uncertainty in the presence of bias.

Near-collinear anchors can produce mirror ambiguity. A local ellipse cannot reveal every alternative position solution.

EXPERIMENTAL SCOPE

An inspectable simulation.

The reference trajectory is prescribed and used only to generate observations and score estimated positions. Heading follows the route; UWB does not estimate the displayed robot heading.

The model does not simulate RF propagation, multipath, clock offsets, packet loss, antenna offsets, survey errors, sensor calibration, vehicle dynamics, or obstacle avoidance. The greenhouse and rover are explanatory 3D geometry, not measured perception. The diagonal and custom paths use an empty test floor so the prescribed path can be examined without crossing the illustrated benches. Range links show ideal geometric connections, not noisy range radii. The geometry map shows nominal horizontal RMS from the local covariance, saturating at 0.50 m; invalid cells are gray.

Use the experiment to examine sensitivity and design a test. Deployment performance requires measurements from the intended hardware and site.

Technical reading

These sources provide context for UWB ranging and localization geometry. The demonstration is an independent illustrative model, not a reproduction of published field results.

Software acknowledgements
ADAPTIVE AGROTECH — UWB LOCALIZATION STUDIO 3D
Third-party notices

Three.js r128 and OrbitControls
Source: https://github.com/mrdoob/three.js
License: MIT

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All field and robot geometry is procedural. No remote dependencies are used.
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