Transitioned the Shenron radar engine from a rigid architecture to a modular,
tunable "Knobs and Dials" framework. This update establishes a physics-first
baseline derived from real-world electromagnetic behavior.
Core Changes:
- Modular Radar Profiles: Pre-configured profiles for TI Cascade, Radarbook,
and AWRL1432 with hardware-specific Bandwidth, Chirp, and nRx parameters.
- Physics Core (Sceneset.py):
- Full implementation of Fresnel and Beckmann-Spizzichino scattering.
- Pure 1/R^4 power law (1/R^2 transmit, 1/R^2 receive) via legacy scaling removal.
- Fixed cos(cos(theta)) bug in CARLA semantic lidar mapping.
- Antenna Gain Integration:
- Implemented separable Azimuth/Elevation gain patterns.
- Added Symmetric Azimuth LUT interpolation and Vertical FOV Hard Cutoff.
- Signal Processing:
- Optimized GPU-accelerated signal synthesis using PyTorch.
- Standardized 110 dB System Calibration Constant for hardware SNR matching.
Architecture & Documentation (intel/radar):
- Reorganized radar intel directory into structured subfolders (core, research,
diagnostics, archive) for better scalability.
- Added SHENRON_MODULAR_ARCHITECTURE.md (System overview).
- Added SHENRON_ANTENNA_GAIN_CALIBRATION.md (Gain physics deep-dive).
- Modernized package README with Windows/Conda specific usage instructions.
- Synchronized all internal and external documentation links.
Calibration: Iteration 18 (Antenna Gain Baseline)
Note: Remaining magic numbers in get_loss_3 are noted for future migration.
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.
RUSHIL AMBARISH KADU