rakadu1
/
Simulator
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
CARLA ? C-Shenron based Simualtor for Sensor data generation.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
44 Commits
9 Branches
0 Tags
2.3 MiB
 
 
 
 
 
Tree: a21988ea91
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from 'a21988ea91'
${ noResults }
Simulator/intel/radar/archive/Shenron_Debug_Plan.md

2.5 KiB
Raw Blame History

Shenron Physics-Based Radar: Debug & Troubleshooting Plan (Updated 2026-04-07)

This document tracks the resolution of data-fidelity issues in the C-SHENRON radar integration.

✅ 1. Resolved Blockers (Milestones)

⚡ A. The "Zero Velocity" Bug (Resolved)

  • Status: Fixed in Iteration 04.
  • Solution: Unpacked float32 bitfields using np.view(np.uint32) in src/recorder.py. Radial velocity is now correctly projected onto the LiDAR frame before synthesis.

📐 B. Semantic LiDAR Column Mismatch (Resolved)

  • Status: Fixed in Iteration 09.
  • Solution: Updated lidar.py to support the 7-column CARLA 0.9.16 format. Corrected the map_carla_semantic_lidar_latest table for NPC vehicles (Tag 14).

🔄 C. Coordinate Transformation Logic (Locked)

  • Status: Verified and Locked.
  • Mapping: Side = Index 0, Forward = Index 1. This convention is required for the Sceneset occlusion logic and must not be changed.

🔭 D. 3D Vertical Clumping (Resolved)

  • Status: Fixed in Iteration 14a & 16.
  • Solution: Implemented Gaussian Elevation Damping at the physics layer. Tree-top clutter is now attenuated by >90%.

🛠️ 2. Current Debugging Checklist (The Metrology Phase)

Phase 4: Resolution Independence (Iteration 16)

  • Solve the "Resolution Trap": Replaced dynamic $1/N$ with a fixed DENSITY_REF.
  • Verify Context Independence: Confirmed that buildings no longer "dim" cars (Frame 100 vs 207).
  • Target Power Recovery: Achieved +234% SNR boost for lead vehicles.

Phase 5: Multi-Sensor Synchronization

  • Turn Lag Investigation: Investigate why Shenron points trail ~0.5 frames behind native radar during sharp maneuvers.
  • Timestamp Alignment: Ensure ego-pose T matches the LiDAR capture T in recorder.py.

Phase 6: DSP Calibration

  • CFAR Thresholding: Re-run the False Alarm Rate (FAR) test. With the +234% signal boost, the default threshold: 20 in config.yaml can be tightened to reduce noise.

🛰️ 3. Relevant Documentation

  • 3D Vertical Energy Suppression
  • Main Debug Log (Shenron_debug.md)
  • Deep Metrology Report (Iteration 17)

Last Updated: 2026-04-07 | Status: Target Signal Stable