The LC29H series can track L1+L5 dual-frequency and multi-GNSS signals, reducing multipath effects in urban canyons and improving positioning accuracy while maintaining low power consumption. With built-in LNA and SAW filter to achieve high sensitivity and strong anti-interference capability. Adopts dual-band positioning and RTK technology to meet the need of centimeter-level high-precision positioning. Ideal for real-time tracking systems and sharing economy applications, helping to develop applications such as drones, smart farm machinery, shared two-wheelers, etc.

• • Standard Raspberry Pi 40PIN GPIO extension header, supports Raspberry Pi series boards, Jetson Nano
  • Supports simultaneous tracking of L1+L5 dual-band satellite signals, reducing multipath effects in urban canyons and improving positioning accuracy
  • Supports concurrent receiving of multi-GNSS systems (GPS, BDS, GLONASS, Galileo and QZSS) while maintaining low power consumption

• • LC29H(AA) GPS HAT with the following features:
    • Supports positioning augmentation systems (WAAS, EGNOS, MSAS and GAGAN) to improve the positioning performance of service areas
    • Supports EASY technology, to realize the positioning using stored information such as ephemeris and almanac data when there is no signal, and improve the positioning and time to first fix

• Built-in low noise amplifier and acoustic surface filter to realize -165dBm high sensitivity and enhance anti-interference performance
• Supports multi-frequency active interference cancellation, effectively suppressing or eliminating narrowband signal (WiFi/2/3/4/5G) interference to ensure navigation accuracy
• A-GNSS (Assisted GNSS) support, reducing the time to first fix (TTFF) with cold start when powered on to 5 seconds
• Support QGNSS software, easy to set various module functions
• Onboard battery holder, supports ML1220 rechargeable cell, for preserving ephemeris information and hot starts
• Onboard 4 LED indicators for module operating status
• Comes with online development resources and manual (Python examples for Raspberry Pi/Jetson Nano)