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Bynav

Inactive

Bynav provides high‑precision GNSS receivers that integrate tightly‑coupled RTK algorithms with inertial and camera sensors to deliver continuous centimeter‑level positioning. Their in‑house GNSS SoC supports multi‑frequency signals from GPS, GLONASS, BDS, Galileo and QZSS, operates with low power, and is designed for automotive autopilot, ADAS, drones, robotics and surveying applications.

长沙市, ChinaFounded 201313300+ followers
Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Product

Problem

Accurate real-time positioning at the centimeter level is difficult to achieve in mobile applications due to signal blockage, interference, and the need to process multiple GNSS constellations while maintaining low power consumption.

Solution

Bynav delivers high-precision GNSS receivers that combine tightly coupled RTK algorithms with integrated inertial measurement and camera sensors. The in‑house GNSS system‑on‑chip supports multi‑frequency signals from GPS, GLONASS, BDS, Galileo and QZSS, including the latest BDS‑3 structure, enabling continuous positioning even in challenging environments. Tight coupling of baseband tracking loops, RTK ambiguity resolution, and INS data provides reliable centimeter‑level accuracy for vehicle autopilot, ADAS and other mobile platforms. The solution is optimized for low power operation, making it suitable for embedded automotive and other mobility applications.

Target Audience

Primary customers are automotive OEMs, autonomous‑driving and ADAS developers, as well as manufacturers of drones, robotics and surveying equipment that require reliable high‑precision positioning.

Features

  • In‑house developed GNSS SoC with multi‑constellation, multi‑frequency support (GPS, GLONASS, BDS, Galileo, QZSS)
  • Tight coupling of RTK baseband tracking, ambiguity resolution, IMU and camera sensors for robust positioning under signal blockage
  • Real-time centimeter‑level accuracy with continuous operation in harsh environments
  • Optimized power consumption for embedded automotive and mobile platforms
  • Integrated navigation algorithms tailored for vehicle autopilot and ADAS systems
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