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Author	SHA1	Message	Date
RUSHIL AMBARISH KADU	269aecdd35	docs: upgrade Memory Update Protocol to v1.1 and expand v1.1 "Ares" Chronicles - Overhauled intel/memory_update.md with v1.1 protocol: - Implemented "Trigger Identification" thresholds (Structural, Physical, Behavioral). - Added "AI Search Optimization" requirements (Keyword Density, Structural Consistency). - Mandated "Doc-Code Parity" verification checklist. - Standardized absolute file:/// URIs for instant cross-document navigation. - Established "Rule of Thumb" for Chronicles executive summary length (10-12%). - Expanded CHRONICLES.md Executive Summary: - Added high-density briefings for Architecture (Stage-based), Radar (Shenron Iterations), Data Export (MCAP Metrology), Dashboard (SSE), and the new Physics Layer. - Synchronized gemini.md, Shenron_debug.md, and dashboard.md with v1.1 "Ares" architecture: - Documented VideoStage, centralized physics.py, and new telemetry tags. - Resolved legacy "Pending Issues" in calibration logs.	4 weeks ago
RUSHIL AMBARISH KADU	23ccf9a9bf	Intel update. V1.1	4 weeks ago
RUSHIL AMBARISH KADU	fef711edbf	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.	1 month ago

Author

SHA1

Message

Date

RUSHIL AMBARISH KADU

269aecdd35

docs: upgrade Memory Update Protocol to v1.1 and expand v1.1 "Ares" Chronicles

- Overhauled intel/memory_update.md with v1.1 protocol:
    - Implemented "Trigger Identification" thresholds (Structural, Physical, Behavioral).
    - Added "AI Search Optimization" requirements (Keyword Density, Structural Consistency).
    - Mandated "Doc-Code Parity" verification checklist.
    - Standardized absolute file:/// URIs for instant cross-document navigation.
    - Established "Rule of Thumb" for Chronicles executive summary length (10-12%).

- Expanded CHRONICLES.md Executive Summary:
    - Added high-density briefings for Architecture (Stage-based), Radar (Shenron Iterations), Data Export (MCAP Metrology), Dashboard (SSE), and the new Physics Layer.

- Synchronized gemini.md, Shenron_debug.md, and dashboard.md with v1.1 "Ares" architecture:
    - Documented VideoStage, centralized physics.py, and new telemetry tags.
    - Resolved legacy "Pending Issues" in calibration logs.

4 weeks ago

RUSHIL AMBARISH KADU

23ccf9a9bf

Intel update. V1.1

4 weeks ago

RUSHIL AMBARISH KADU

fef711edbf

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.

1 month ago

3 Commits (70aa058e4d5a407f04bc1232fb1b192cc0de3042)