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lecture_15 - 16.333: Lecture #15 Inertial Sensors...

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Unformatted text preview: 16.333: Lecture #15 Inertial Sensors Complementary filtering Simple Kalman filtering 1 Fall 2004 16.333 152 Fall 2004 16.333 153 Image removed due to copyright considerations. Fall 2004 16.333 154 Image removed due to copyright considerations. Fall 2004 16.333 155 Image removed due to copyright considerations. Image removed due to copyright considerations. Fall 2004 16.333 156 Fall 2004 16.333 157 Fibre Coil Lens Spatial Filter Laser Source Splitters Sagnac 0 Phase Shift Lens Fringe Pattern Detector Polariser Beam Optical Intensity Phase Shift Proportional to Fall 2004 16.333 1511 Fall 2004 16.333 158 Fall 2004 16.333 159 Examples of Estimation Filters from Recent Aircraft Projects at MIT November 2004 Sanghyuk Park and Jonathan How Complementary Filter (CF) Often, there are cases where you have two different measurement sources for estimating one variable and the noise properties of the two measurements are such that one source gives good information only in low frequency region while the other is good only in high frequency region. You can use a complementary filter ! accelerometer rate gyro g output accel. sin 1 - not good in long term due to integration- only good in long term- not proper during fast motion Low Pass Filter High Pass Filter dt rate) (angular est Example : Tilt angle estimation using accelerometer and rate gyro + = 1 1 s + = example for , 1 s s Complementary Filter(CF) Examples CF1. Roll Angle Estimation CF2. Pitch Angle Estimation CF3. Altitude Estimation CF4. Altitude Rate Estimation CF1. CF1....
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This note was uploaded on 11/07/2011 for the course AERO 16.333 taught by Professor Alexandremegretski during the Fall '04 term at MIT.

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lecture_15 - 16.333: Lecture #15 Inertial Sensors...

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