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5 Commits (2092c178802819f073fda377f41bc78d8a0d1ba6)

Author	SHA1	Message	Date
RUSHIL AMBARISH KADU	2092c17880	feat(radar): Implement Radar Metrology Suite (Iteration 18) - 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/.	1 month ago
RUSHIL AMBARISH KADU	0f9d3d68b0	feat(radar): iteration 16 - refined physics & resolution independence 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.	1 month ago
RUSHIL AMBARISH KADU	e7ce32aa23	docs(intel): Finalize 3D energy compression benchmark V2 Detailed Gaussian damping math (2.77) and Resolution Trap normalization for Iteration 14.	1 month ago
RUSHIL AMBARISH KADU	b5360b69b8	docs(intel): Finalize document organization and AI navigation roadmap Synchronized internal links, updated iteration history (01-13), and added prioritized AI guidance for radar and scenario tasks.	2 months ago
RUSHIL AMBARISH KADU	0cccf4eba8	feat(intel): Reorganize documentation and stabilize radar physics baseline 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.	2 months ago