Deterministic ADAS Simulation

From Random to Repeatable Deterministic Scenarios Bypassing Traffic Manager variance, we utilize direct `set_target_velocity` coordinate control to guarantee exact "Spawn-and-Move" maneuvers—such as cut-ins—execute flawlessly at the same millisecond every run.
Unprecedented Physics-Accurate Radar Simulation Standard bounding boxes fail complex realities. We returned to the laws of electromagnetism, implementing true 1/R⁴ power-decay physics and material-based Fresnel reflections.
Real-Time Multi-Sensor Metrology Synchronously tracking RGB, LiDAR, and phase-preserving Doppler-Slice Radar data perfectly aligned at 30 FPS for visual ground truth comparison.

[ Insert Image: CARLA RGB/Game View ]

CARLA Simulation

[ Insert Image: Radar Heatmap (Foxglove) ]

Shenron Radar

Shenron: Physics-Based Radar Engine

CARLA & Synchronizer

[ Graphic or Logo ]

Shenron Physics Engine

[ CPU/GPU Graphic ]

Radar Signal Processing

[ Heatmap / DSP ]

ADAS-Ready Output

[ Point Cloud / MCAP ]

1/R⁴ Accurate Spatial Decay Physics

Dropped artificial density variables. Reflected energy now strictly attenuates by the inverse square law, forcing massive background structures to cede dominance to near-field targets.

Directional Antenna Pattern Modeling

Resolved the "Isotropic Illumination" limit by implementing true Azimuth & Elevation gain logic. Radar blind-spots act realistically, attenuating 80° side-wall clutter by ~20dB.

Modular Hardware-Matched Pipeline

The "Knobs and Dials" philosophy completely separates base physics from simulation parameters. Easily swap profiles between AWRL1432, Radarbook, and MIMO Cascade hardware.

From Simulation to Validation

Physics-Driven
Metrology Accuracy

Zero-Tilt Symmetry guarantees 120° FOV precision right down the boresight.
Doppler-Slice phase continuity resolves standard blur, delivering sharp "Radar Blue" PointCloud clusters.

Real-World Hardware
Calibration Logic

110dB System Gain tuning aligns exact radar spec hardware profiles.
Modifiable Bandwidth (B), Chirp Repetition, and virtual receiver sets to replicate DSP behavior dynamically.

Automated Core
Testing Platform

GUI Dashboard orchestrating idle-mode GPU utilization for Shenron rendering safely.
Direct pipeline translating serialized JSONL/NPY data into FOXGLOVE MCAP standards.

Deterministic ADAS Simulation

Shenron: Physics-Based Radar Engine

From Simulation to Validation

Physics-DrivenMetrology Accuracy

Real-World HardwareCalibration Logic

Automated CoreTesting Platform

Physics-Driven
Metrology Accuracy

Real-World Hardware
Calibration Logic

Automated Core
Testing Platform