🪐 Walkthrough: Radar Metrology Suite (Iteration 18)

This walkthrough documents the full implementation and verification of the Radar Metrology Suite, a major architectural upgrade that exposes the internal signal processing states of the C-SHENRON radar engine for high-fidelity ADAS debugging.

🚀 1. Overview of Achievements

The Metrology Suite has successfully transitioned the simulation from generating "Points" to generating a complete Signal Spectrum.

Phase 1 (Engine Extraction): Modified the CA-CFAR and RadarProcessor to capture raw energy matrices.
Phase 2 (Visual Pipeline): Implemented real-time image colormapping (Viridis/Magma/Plasma) and MCAP streaming.
Phase 3 (Persistence): Established a structured hierarchy for raw .npy and .jsonl telemetry.
Phase 4 (Verification): Completed a 250-frame simulation sweep (Iteration 18) proving system stability.

📡 2. Visual Diagnostic Capabilities

We have introduced three new specialized heatmaps, now available as live topics in Foxglove:

Topic	Channel	Colormap	Purpose
`/radar/heatmaps/range_doppler`	RD Heatmap	Viridis	High-contrast view of targets in Velocity vs. Range space.
`/radar/heatmaps/range_azimuth`	RA Heatmap	Magma	Top-down spatial energy distribution (Bird's Eye View).
`/radar/heatmaps/cfar_mask`	Detection Gate	Plasma	Visualizes the "Detection Wall" (Noise $\times$ Threshold).

📊 3. Deep Telemetry & Data Structure

For every frame processed, the system now persists bit-perfect data for offline engineering analysis.

Raw Signal Dumps (`metrology/`)

Saved in Shenron_debug/iterations/<iter_name>/<radar_type>/metrology/:

rd/*.npy: 256x64 Raw Power floating-point matrices.
ra/*.npy: 256x256 Angular energy polar-coordinates.
cfar/*.npy: The adaptive threshold baseline for that specific frame.

Global Metrics (`metrics.jsonl`)

A frame-by-frame log of signal health, including:

peak_snr_db: Signal-to-Noise ratio of the strongest target.
avg_noise_floor: Estimated environment noise level.
active_bins: Number of cells currently "breaking through" the CFAR gate.

🏁 4. Verification Results (Iteration 18)

The initial full-scale run of the suite confirmed Optimal Signal Integrity:

Peak SNR: ~15.3 dB in peak frames (Confirmed by metrics.jsonl).
Processing Performance: 16.63 Frames/Sec (Streaming images + PCD logic).
GPU Acceleration: Confirmed active on cuda:0:0.

🛠️ 5. How to Use & Debug

Launching the Metrology Suite

To run a new iteration with full metrology extraction:

cmd /c "C:\ProgramData\miniconda3\Scripts\activate.bat carla312 && python scripts/test_shenron.py --iter <your_name>"

Signal Verification Utility

Use the specialized verification tool to check a single frame's signal chain:

cmd /c "C:\ProgramData\miniconda3\Scripts\activate.bat carla312 && python scripts/analysis/verify_metrology_logic.py"

[!IMPORTANT] Engineering Note: The RA Heatmap uses a 1D Angle-FFT reduction across all Doppler bins. This provides a spatial "snapshot" that ignores velocity, making it ideal for checking multipath and ghosting against the ground-truth LiDAR map.

Verified by Antigravity | Date: 2026-04-08

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