An INS_GPS Navigation System with Consumer Level MEMS Inertial

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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


				
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