2 resultados para Formation à distance

em Digital Commons - Michigan Tech


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Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

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During the past decades, tremendous research interests have been attracted to investigate nanoparticles due to their promising catalytic, magnetic, and optical properties. In this thesis, two novel methods of nanoparticle fabrication were introduced and the basic formation mechanisms were studied. Metal nanoparticles and polyurethane nanoparticles were separately fabricated by a short-distance sputter deposition technique and a reactive ion etching process. First, a sputter deposition method with a very short target-substrate distance is found to be able to generate metal nanoparticles on the glass substrate inside a RIE chamber. The distribution and morphology of nanoparticles are affected by the distance, the ion concentration and the process time. Densely-distributed nanoparticles of various compositions are deposited on the substrate surface when the target-substrate distance is smaller than 130mm. It is much less than the atoms’ mean free path, which is the threshold in previous research for nanoparticles’ formation. Island structures are formed when the distance is increased to 510mm, indicating the tendency to form continuous thin film. The trend is different from previously-reported sputtering method for nanoparticle fabrication, where longer distance between the target and the substrate facilitates the formation of nanoparticle. A mechanism based on the seeding effect of the substrate is proposed to interpret the experimental results. Secondly, in polyurethane nanoparticles’ fabrication, a mechanism is put forward based on the microphase separation phenomenon in block copolymer thin film. The synthesized polymers have formed dispersed and continuous phases because of the different properties between segments. With harder mechanical property, the dispersed phase is remained after RIE process while the continuous phase is etched away, leading to the formation of nanoparticles on the substrate. The nanoparticles distribution is found to be affected by the heating effect, the process time and the plasma power. Superhydrophilic property is found on samples with these two types of nanoparticles. The relationship between the nanostructure and the hydrophilicity is studied for further potential applications.