Intelligent AI Tracking Technology
Technical Principle
The radar integrates MIMO (Multiple-Input Multiple-Output) architecture with FMCW modulation to achieve high angular resolution via virtual aperture. After generating high‑density point clouds, an AI engine takes over: deep learning networks perform clutter suppression and target detection, distinguishing vehicles, pedestrians, and noise; reinforcement learning or neural‑enhanced Kalman filters enable intelligent trajectory prediction and smoothing, significantly improving tracking continuity and ID consistency in occlusion, crossing, and dense traffic. The entire pipeline – from point cloud to trajectory – is AI‑driven, transforming raw data into actionable intelligence.
Key Features
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AI‑enhanced perception & adaptive interference rejection – Deep learning for clutter suppression and target classification; AI analyzes environment in real time, dynamically adjusting filters and thresholds to counter ground echoes, multipath, and weather – delivering superior accuracy and robustness.
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All‑weather reliable operation – Unaffected by rain, snow, fog, or night; AI adapts parameters dynamically for consistent performance in harsh conditions.
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High‑precision multi‑dimensional measurement – Decimeter range, 0.1m/s speed, with AI‑assisted angular super‑resolution for improved azimuth and elevation – full‑dimension accurate positioning.
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Intelligent multi‑target tracking – Tracks hundreds of objects simultaneously; AI‑based prediction and association minimize dropouts and ID swaps, ensuring trajectory continuity in occlusion and crossing scenarios.
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Low‑latency real‑time response – Edge AI acceleration, refresh ≤50ms, output up to 20Hz – meeting the stringent timing requirements of real‑time control and early warning.