Project Overview
As artificial intelligence is embodied into daily, real-world applications, the need for low-cost and low-compute methods of determining the kinematics of moving objects in the application environment becomes more prevalent to ensure correct operation and safety. Mmwave Radar, offering a small form factor and high range resolution could be a suitable alternative to a more mainstream approach like computer vision, which is computationally intensive in comparison.
Additionally, research has demonstrated that measurements from multiple mmWave radar nodes may be fused to accurately determine the relative pose of nodes and resolve the absolute trajectories of objects passing through the overlapping field of views of the nodes with higher accuracy.
Spatial Calibration
Accurately determine the relative poses of multiple radars (up to 4) by moving a single object through their FOVs
Trajectory Stitching
Once spatially synchronized, stitch together trajectories of objects moving through the FOVs
Real-Time Fusion
Perform fusion in a real-time field environment with millisecond-level time synchronization
How It Works
Time Synchronization
Each Jetson communicates with a base station for time synchronization over Wi-Fi
Radar Data Acquisition
Base station commands each Jetson to start frame collection. The AWR board transmits chirps and receives reflections via CSI2 to DCA1000, then to Jetson over Ethernet
Signal Processing Pipeline
ADC samples undergo sequential processing:
- Range FFT: ADC samples → range profile
- Doppler FFT: Chirps per frame → velocity profile
- Static Clutter Removal: Filter out stationary objects
- 2D OSCFAR: Detect likely target coordinates
- Angle FFT: Generate range-doppler-angle point clouds
Data Fusion
Point clouds sent to base station for DBSCAN clustering. Extended Kalman Filter estimates relative radar positions and fuses trajectories across FOVs
System Architecture
Hardware Layer
Processing Layer
Fusion Layer
Technical Highlights
Team
Oviya Seeniraj
NTP & Time Synchronization
Andrey Otvagin
Jetson/Node Development
Vihan Jayaraman
Wireless Infrastructure
William Ni
Visualization Development
Jason Wang
Auto-Calibration Algorithms