Restores high-fidelity physical realism to the C-Shenron radar engine by
aligning the synthesis pipeline with the pure Radar Range Equation.
Core Improvements:
- Physics: Restored 1/R^4 power-delay law (1/R^2 voltage) in Sceneset.py
and heatmap_gen_fast.py. Stripped legacy 1/1000 normalizations and
R^2 area-growth workarounds.
- Geometry: Fixed FFT index asymmetry in radar_processor.py, achieving a
perfectly symmetric 120° FOV sector.
- Metrology: Implemented "Radar Blue" (Viridis) 120° fan-projection for
diagnostic Range-Azimuth heatmaps.
- Automation: Integrated RD/RA/CFAR heatmap persistence into the
automated simulation-to-MCAP pipeline (data_to_mcap.py).
- Docs: Comprehensive update of intel/ directory, including Iterations 17-26
and the Physics/Symmetry Milestone deep-dive.
This milestone ensures that target brightness and spatial positioning
correctly mimic real-world TI AWRL1432 radar hardware.
- Engine: Modified CFAR and Processor to extract raw Range-Doppler and Range-Azimuth energy heatmaps.
- Visuals: Integrated high-fidelity Matplotlib colormapping (Viridis/Magma) for Foxglove image streaming.
- Data: Implemented 32-bit raw .npy persistence and JSONL telemetry for frame-level SNR analysis.
- Tools: Added a dedicated verification utility for end-to-end signal flow validation.
- Docs: Comprehensive documentation for the new 'Radar Lab' architecture in /intel/.
Implemented a major architectural refactor of the C-SHENRON radar engine to achieve physically stable, context-independent detections.
1. Physics Engine Refactor (Iteration 16):
- Sceneset.py: Replaced global 1/N normalization with a fixed Area-Density Integration model. This prevents Energy Starvation where buildings previously suppressed car detections.
- Gaussian Damping: Integrated a 20 deg vertical beamwidth profile to physically suppress tree-top clutter while preserving boresight targets.
- ConfigureRadar.py: Standardized hardware profiles with calibrated 110dB gain and removed Iteration 15 bandages.
2. Repository Reorganization:
- Moved analysis and verification scripts to a new scripts/analysis/ directory.
- Updated path resolution in moved scripts to ensure project-wide stability.
3. Documentation & Metrology:
- Created 3D vertical energy suppression.md detailing the Resolution Independence breakthrough.
- Updated Shenron_debug.md with Iterations 14-16, recording a +234% Target Magnitude recovery.
- Updated Shenron_Debug_Plan.md and possible_issue_resolution.md to reflect resolved technical blockers.
This commit marks the completion of the Iteration 13 'Golden Mix' calibration.
- intel/: Structured documentation into /radar, /scenarios, and /internal subfolders.
- Shenron_debug.md: Comprehensive history of all 13 calibration iterations.
- radar_processor.py: Implemented Blackman-Harris windowing for sidelobe suppression.
- lidar.py: Applied -2.0m parallax shift and ground suppression filtering.
- Sceneset.py: Calibrated specular thresholds and material roughness for stability.
RUSHIL AMBARISH KADU