28 lines
1.1 KiB
Markdown
28 lines
1.1 KiB
Markdown
# MDS-MAP localization simulation
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This project simulates localization in an ad-hoc/sensor network using MDS-MAP
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and two anchor-only baselines: circular lateration (nonlinear least squares)
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and square lateration (min-max bounds).
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## Install and run
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Use Python 3.10 or newer:
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```powershell
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python -m pip install -r requirements.txt
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python scripts/run_single.py
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python scripts/run_remote_carlo.py
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pytest
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```
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The default experiment places 4 anchors and 16 unknown nodes in a 100 m
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square, uses a 55 m radio range, Gaussian ranging noise, and 30 repetitions.
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Outputs are written to `results/figures` and `results/tables`. Edit
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`config/default.yaml` to change the experiment. A connected graph is required
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for shortest-path completion; increase `radio_range` if a random run is
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disconnected.
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The position figure compares actual unknown positions with all estimates and
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anchors. The error-distribution figure is a histogram over all unknown nodes
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and repetitions. The metrics CSV contains RMSE, MAE, mean, standard deviation,
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median, maximum, and 95th percentile errors for every repetition and method. |