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Inexpensive Sensing For Full State Estimation of Spacecraft

Inexpensive Sensing For Full State Estimation of Spacecraft. Benoit Pigneur and Kartik Ariyur School of Mechanical Engineering Purdue University June 2013. O utline. Background & Motivation Methodology Test Cases Conclusion & Future Work. Background & Motivation.

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Inexpensive Sensing For Full State Estimation of Spacecraft

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  1. Inexpensive Sensing For Full State Estimation of Spacecraft Benoit Pigneurand KartikAriyur School of Mechanical Engineering Purdue University June 2013

  2. Outline • Background & Motivation • Methodology • Test Cases • Conclusion & Future Work Benoit Pigneur - Purdue University

  3. Background & Motivation • Next generation/future missions • Increase landing mass (ex: human mission) Benoit Pigneur - Purdue University

  4. Background & Motivation • Next generation/future missions • Increase precision landing Benoit Pigneur - Purdue University

  5. Background & Motivation • Next generation/future missions • Reduce operational costs • Improve autonomous GNC Benoit Pigneur - Purdue University

  6. Background & Motivation • State of the art of GNC algorithms for EDLS Numerical Predictor-Corrector Analytical Predictor-Corrector Gravity Turn MSL: Convex optimization of power-descent Profile Tracking Terminal point controller (Apollo) 1960 2010 2000 Benoit Pigneur - Purdue University

  7. Background & Motivation • Current 2 main directions in development in sensing and state estimation • Development of better sensor accuracy • Ex: Hubble’s Fine Guidance Sensors • Improvement in processing inertial measurement unit data • Ex: Mars Odyssey aerobraking maneuver Benoit Pigneur - Purdue University

  8. Background & Motivation • Improve sensing andstate estimation • Develop next generation of autonomous GNC algorithms • Answer some of the challenges for future missions • Reduce costs • Reduce operational cost during spacecraft operational life by increasing the autonomy • Reduce cost by using low SWAP (size weight and power) sensors Benoit Pigneur - Purdue University

  9. Outline • Background & Motivation • Methodology • Test Cases • Conclusion & Future Work Benoit Pigneur - Purdue University

  10. Methodology • Multiple distributed sensors: Geometric configuration • Low SWAP sensors • Large distribution • Exclude outlier measurement • Combine measurements with geometric configuration Center of mass z’ y’ r’ r R z y x’ x MEMS accelerometers Benoit Pigneur - Purdue University

  11. Methodology • Mathematical model: rigid body with constant mass • Acceleration equation with inertial to non-inertial frame conversion formula • R is the distance in the inertial frame • r’ is the distance in the non-inertial frame (rotating frame) • ω is the angular velocity • is the angular acceleration Benoit Pigneur - Purdue University

  12. Methodology • Mathematical model: change of inertia • Inertia -> angular acceleration • Angular velocity -> attitude (Euler angles) 1.Euler equations of motion 2.Kinematic equations Benoit Pigneur - Purdue University

  13. Methodology • Mathematical model: • Assuming r’ is constant for a rigid body (accelerometers are fixed in the body frame) • The subscript represents the index of the measurement units • a : linear acceleration of the body in the inertial frame • is the accelerometer position • ω is the angular velocity • is the angular acceleration • is the accelerometer measurement Benoit Pigneur - PurdueUniversity

  14. Outline • Background & Motivation • Methodology • Test Cases • Conclusion & Future Work Benoit Pigneur - Purdue University

  15. Test Cases • 3 different cases: • Circular 2D orbit • Entry, descent and landing • Change of inertia during descent phase • Comparison between nominal trajectory, standard IMU simulation and distributed multi-accelerometers simulation • Uncertainty in measurement of acceleration • Error ratio of 1/5 between the standard IMU and the distributed multi-accelerometers Benoit Pigneur - Purdue University

  16. Test Cases • Circular 2D orbit: • Simulation conditions: • circular orbit at 95 km altitude around the Moon • no external force Benoit Pigneur - Purdue University

  17. Test Cases • Entry, descent and landing: • Simulation conditions: • Moon • Starting altitude at 95 km • Velocity: 1670 m/s • Flight path angle: -10° Benoit Pigneur - Purdue University

  18. Test Cases • Entry, descent and landing: change of inertia • Simulation conditions: • Thrusters time: ON at 200s, OFF at 270s • single-axis stabilization along thrust direction Benoit Pigneur - Purdue University

  19. Outline • Background & Motivation • Methodology • Test Cases • Conclusion & Future Work Benoit Pigneur - Purdue University

  20. Conclusion & Future Work • Advantages of the proposed method • Low SWAP sensors reduce the cost • Optimal geometric configuration and algorithm improve the state estimation • Distributed sensors (accelerometers) give useful information about flexible and moving parts • The methodology is applicable to different sensors: MEMS accelerometers, CMOS imagers… Benoit Pigneur - Purdue University

  21. Conclusion & Future Work • Future Work • Improve estimation algorithm by development of optimal geometric configuration • Develop the technique for more challenging environment (atmospheric disturbances, gravity gradient, magnetic field, solar pressure, ionic winds…) • Develop autonomous GNC based on the improvement of the state estimation • Develop this method for other sensors • Improve the attitude estimation for 3-axis stabilized spacecraft Benoit Pigneur - Purdue University

  22. Thanks! Questions ? Authors: Benoit Pigneur (speaker): bpigneur@purdue.edu KartikAriyur Benoit Pigneur - Purdue University

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