Sensor Fusion. 21/12-2000 (MJ)Danish GPS Center2 Table of Contents Sensor fusion theory The upgraded testbed Sun sensor Magnetometer Rate gyros Data fusion.

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Presentation transcript:

Sensor Fusion

21/ (MJ)Danish GPS Center2 Table of Contents Sensor fusion theory The upgraded testbed Sun sensor Magnetometer Rate gyros Data fusion State fusion Results Shadowed GPS Conclusion

21/ (MJ)Danish GPS Center3 What is Sensor Fusion? Combination of different types of sensors to reach a better performance than possible with a single sensor Best sensor fusion system: The human brain Why use it? To achieve better performance Extra sensors could work as backup if others fail (redundancy)

21/ (MJ)Danish GPS Center4 Complementary Sensors Example:

21/ (MJ)Danish GPS Center5 Fusion Levels

21/ (MJ)Danish GPS Center6 Applied Techniques

21/ (MJ)Danish GPS Center7 Decentralized Fusion

21/ (MJ)Danish GPS Center8 Extra Sensors Solar Sensor Magnetometer Rate Gyros + GPS

21/ (MJ)Danish GPS Center9 The Upgraded Testbed

21/ (MJ)Danish GPS Center10 Vector Matching Wahba’s Problem: Solution: Use the SVD method 1. Form B matrix of outer products

21/ (MJ)Danish GPS Center11 Vector Matching 2. Split B into three matrices using Singular Value Decomposition 3. The optimal attitude matrix best fitting the vector pairs can be found as:

21/ (MJ)Danish GPS Center12 Solar Cells Model: Working Principle:

21/ (MJ)Danish GPS Center13 Solar Cells Temperature effects

21/ (MJ)Danish GPS Center14 Solar Cells Calibration Sensitivity Mounting Cosine char.

21/ (MJ)Danish GPS Center15 Solar Cells Mounting errors (adjustment of cell-axis)

21/ (MJ)Danish GPS Center16 Solar Cells Cosine corrections

21/ (MJ)Danish GPS Center17 Sun Sensor Performance White Noise?

21/ (MJ)Danish GPS Center18 Magnetometer Calibration Field bias Mounting uncertainties

21/ (MJ)Danish GPS Center19 Magnetometer Calculating internal bias At ‘zero’ attitude (A = I) Each measurement Least Square

21/ (MJ)Danish GPS Center20 Magnetometer Mounting uncertainties calibrated by a small rotation, found using the SVD method Result:

21/ (MJ)Danish GPS Center21 Rate Gyros Working Principle: Measures the state (angular rate) directly

21/ (MJ)Danish GPS Center22 Rate Gyros Error sources: Noise Timevar. bias Scalefactor Accel. sensitivity Off-axis error

21/ (MJ)Danish GPS Center23 Data Fusion Measurement model:

21/ (MJ)Danish GPS Center24 Data Fusion Measurement gradient matrix:

21/ (MJ)Danish GPS Center25 State Fusion Using receiver solution as input measurement Residuals must be redefined:

21/ (MJ)Danish GPS Center26 Results Data fusion

21/ (MJ)Danish GPS Center27 Results State fusion

21/ (MJ)Danish GPS Center28 Shadowed GPS

21/ (MJ)Danish GPS Center29 Conclusion Sensor fusion techniques can be applied to GPS applications mainly on the data and feature level The gain in accuracy was however shown to be only moderate in this project Significant error sources include less than optimal sensors and mechanical alignment problems The accuracy achieved by secondary sensors alone was shown to be sufficient for many space missions