1 / 9

An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles

An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles. 56367 Masaru Naruoka The University of Tokyo. Introduction and Background Method Numerical Simulations and Results. Introduction and Background. Needs for a new navigation system of small UAVs

olivaj
Download Presentation

An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. An INS/GPS Navigation Systemwith MEMS Inertial Sensorsfor Small Unmanned Aerial Vehicles 56367 Masaru Naruoka The University of Tokyo • Introduction and Background • Method • Numerical Simulations and Results

  2. Introduction and Background • Needs for a new navigation system of small UAVs • Small UAV • About 1 m wingspan • Easy operation • Hope for Autonomy • The existing ones = expensive, big, heavy • What’s new? =Low cost, small, light

  3. Method(1)Navigation System for Small UAVs • Features • Low cost • Small • Light • Unit • Inertial Navigation System (INS) with MEMS inertial sensors • Global Positioning System (GPS)

  4. Method (2)INS with MEMS inertial sensors Low cost, small, light, but low accuracy. MEMS inertial sensors Position Velocity Attitude Acceleration Angular ratio Integrate INS

  5. Method (3)GPS and the Kalman Filter INS Position Velocity Attitude Position Velocity Attitude The Kalman Filter High update ratio. But, high accuracy? GPS Position Velocity

  6. Sensor Model (1) Sensor Model (2) Numerical Simulations Not Assumed! Random Drift + + True Value + True Value + + White Noise White Noise Ideal More real

  7. Results

  8. Conclusion • My new navigation system • Low cost,small,light, fit for small UAVs. • A certain level of precision. • Short term operation … • good estimation. • However, long term operation … • Failed and error accumulation. • Need to improve the algorithm.

  9. Appendix (1)Numerical Simulation Condition • Whole simulation time = 240 sec. • Rotating Radius = 200 meter. • Sensor Model • Accelerometer = ADXL202 (Analog Devices) • Gyro = ADXRS150 (Analog Devices) • Update Ratio • INS = 50 Hz • GPS = 1 Hz

More Related