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.
New White Paper
Physical AI 2.0: Why Physical State Recovery Is the Missing Capability
Explore why vision and language-first world models aren’t enough on their own, and how recovering the actual physical state from incomplete, noisy, or ambiguous observations is the missing layer between world models, reasoning, and action.
Work with Atomathic
Tell us about your project, pilot, or idea — and let’s explore how Physical AI can accelerate it