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Simultaneous Navigation and Attitude Determination of a Reentry Head Using Magnetometer, Sun Sensor, Star Tracker, INS and Unscented Kalman Filter
Sadeghi, Hamed | 2013
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 45394 (08)
- University: Sharif University of Technology
- Department: Mechanical Engineering
- Advisor(s): Salarieh, Hassan
- Abstract:
- Control and guidance of a vehicle is vital for it to do its mission correctly. Guidance system and decisional algorithms used in it need exact information of instantaneous position, velocity, and attitude of the guided vehicle to determine and issue proper guiding commands.
Estimation algorithms and navigation sensors are two necessary tools for navigation. In the first section of present study, the reentry head equations of motion are derived and a 6-DOF simulation is done for it. In the second section, measurements of sensors will be simulated using results of the first section and existing reference models for sun position vector and earth magnetic field. The third section appertains to development of navigation equations, attitude determination using UKF algorithm, and investigation of filter equation parameters.
The designed algorithm is evaluated in different scenarios. Results show that, due to quickness of system dynamics, presence of star tracker is essential for filter convergence in a short time. It is also observed that by omitting the gyroscope, navigation accuracy reduces negligibly. Investigation of the results demonstrates that loosing sun sensor measurements in a period of time during flight, does not disturb algorithm performance. Increasing the initial estimation error, reduces navigation accuracy. The results also show that both magnetic and sun sensors strongly affect navigation accuracy and the effect of magnetic sensor is higher due to its faster update rate - Keywords:
- Six Degree of Freedom Simulation ; Magnetic Sensor ; Navigation ; Unscented Kalman Filter ; Attitude Determination ; Reentry Head ; Sun Sensor ; Star Tracker
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