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An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles 56367 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 Method(1) Navigation System for Small UAVs • Features – Low cost – Small – Light • Unit 1. Inertial Navigation System (INS) with MEMS inertial sensors 2. Global Positioning System (GPS) Method (2) INS with MEMS inertial sensors MEMS inertial sensors Acceleration Angular ratio Integrate Low cost, small, light, but low accuracy. Position Velocity Attitude INS Method (3) GPS and the Kalman Filter INS Position Velocity The Kalman Filter Position Velocity Attitude Attitude GPS Position Velocity High update ratio. But, high accuracy? Numerical Simulations • Sensor Model (1) • Sensor Model (2) True Value + Not Assumed ! + White Noise Random Drift True Value + + + White Noise Ideal More real Results Horizontal trajectory history 2576 2574 Rotating direction True Value under Sensor Model (1) under Sensor Model (2) Latitude [seconds] 2572 2570 Start and Goal 2568 2566 2738 2740 2742 2744 2746 2748 2750 2752 Longitude [seconds] 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
