feat(radar): Major Update - Shenron Modularity and Physics Refinement (Iteration 18)

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.