An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles Masaru Naruoka The University of Tokyo 1.Introduction and Background 2.Method 3.Numerical Simulations and Results

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

Features –Low cost –Small –Light Unit 1.Inertial Navigation System (INS) with MEMS inertial sensors 2.Global Positioning System (GPS) Method(1) Navigation System for Small UAVs

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

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

Numerical Simulations Sensor Model (1)Sensor Model (2) + + True Valu e White Noise + + True Valu e White Noise + Rando m Drift IdealMore real Not Assumed !

Results

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.

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