AIDAR:
AI Detection and
Ranging
Perception Layer
Atomathic’s proprietary algorithm translates raw I&Q data into sub-beam precision.
By applying convex optimization and signal decomposition techniques, it interprets reflections and micro-motions at the waveform level, providing reliable object detection and tracking even in low-visibility or cluttered environments.
With only half MMICs, Atomathic provides 3X-10X better performance against state-of-art radar solutions
Automotive Performance
(Probability of Correctly Separating Two Pedestrians)
Patented mathematical framework
Based on convex optimization and Atomic Norm principles, it reconstructs sub-beam details from sparse radar data — enabling higher precision without additional hardware.
10x higher detection accuracy
Differentiates objects at twice the distance of conventional radar using fewer sensor channels.
Reduced computational load
Achieves state-of-the-art accuracy using fewer MMICs and less processing power.
Reasoning Layer
10x clarity.
Zero guesswork
Atomathic’s AIDAR delivers hyperresolution point cloud, in real time, while reducing false positives, at a reasonably low computational cost, enabling perception to make better decisions.
Accent Heading
Real-Time
Demonstration
Atomathic’s AIDAR enables reliable detection even in complex environments and adverse weather conditions.
These short demos illustrate how Physical AI interprets motion and distance with a level of clarity comparable to LiDAR, but achieved through radar.
Pedestrian Tracking and Classification
Shows AIDAR’s ability to differentiate fine human motions — kneeling, turning, or walking — in real time and across viewing angles.
Object Identification in Driving Scenarios
Demonstrates accurate detection and separation of multiple objects under typical automotive conditions, ensuring safer decision-making.
Work with Atomathic
Tell us about your project, pilot, or idea — and let’s explore how Physical AI can accelerate it