🧬 Innovation Summary Spatial VsGe v2.0 innovates by combining generative diffusion learning, spectral beamforming, and spatial audio-video fusion into a new AI-accelerated framework. It goes beyond traditional Sonic Radar techniques by treating sound and sight as jointly generative phenomena—not just signals, but scenes.
Key Innovations:
Latent space learning of environment via VQ-VAE-Transformer combo.
Diffusion-based temporal and spatial context recovery.
Real-time, hardware-accelerated G-Sync fusion pipeline.
Human-perceptual HRTF-based directional mapping.
Spatial graph attention for scene-wise object association.
🚀 Use Cases Defense/Surveillance: Covert target detection in dark, noisy, or foggy conditions.
Autonomous Drones/Robots: Real-time navigation through dynamic acoustic and visual mapping.
AR/VR/XR Systems: Immersive spatial audio-visual feedback for training, simulation, or gaming.
Disaster Response: Detecting life signals and thermal cues in collapsed or obscured areas.
🔧 Future Directions Integration with FLIR/Thermal and RF cameras for multi-spectrum object classification.
Full deployment on Jetson Nano Orin / Xavier NX with CUDA acceleration.
Training using synthetic soundscapes and procedurally generated video for robustness.
Incorporation of Spatial Audio GANs for realistic reconstruction of incomplete acoustic data.
Created the complete directory structure:
debian/ with the control file
usr/local/bin/ with the main Python script
Added launcher.desktop file
Added README.md with installation instructions
Created all necessary files:
debian/control - Package metadata and dependencies
usr/local/bin/sonic_radar.py - Main Python script with the AI radar implementation
install.sh - Script to install Python dependencies
launcher.desktop - Desktop launcher for GUI environments
README.md - Documentation with usage instructions
build_package.bat - Windows script with instructions for building the package
Made scripts executable:
Applied executable attributes to install.sh and sonic_radar.py
Since you're on Windows, I've included a build_package.bat file that explains how to build the .deb package when you're on a Linux system. The actual .deb package building needs to be done on a Linux system using the dpkg-deb command.
To build the package on a Linux system, you would run:
dpkg-deb --build sonic_radar_ai mv sonic_radar_ai.deb sonic-radar-rtx-compatible.deb
Copy bash To install the package on a target system:
sudo dpkg -i sonic-radar-rtx-compatible.deb cd /usr/local/bin/ sudo ./install.sh python3 sonic_radar.py
Copy bash The package includes all the necessary components for the Sonic Radar system with RTX GPU compatibility as requested.