EVALUATION OF MAGNESIUM AS A HALL THRUSTER PROPELLANT

In this study, the use of magnesium as a Hall thruster propellant was evaluated. A xenon Hall thruster was modified such that magnesium propellant could be loaded into the anode and use waste heat from the thruster discharge to drive the propellant vaporization. A control scheme was developed, which allowed for precise control of the mass flow rate while still using plasma heating as the main mechanism for evaporation. The thruster anode, which also served as the propellant reservoir, was designed such that the open area was too low for sufficient vapor flow at normal operating temperatures (i.e. plasma heating alone). The remaining heat needed to achieve enough vapor flow to sustain thruster discharge came from a counter-wound resistive heater located behind the anode. The control system has the ability to arrest thermal runaway in a direct evaporation feed system and stabilize the discharge current during voltage-limited operation. A proportional-integral-derivative control algorithm was implemented to enable automated operation of the mass flow control system using the discharge current as the measured variable and the anode heater current as the controlled parameter. Steady-state operation at constant voltage with discharge current excursions less than 0.35 A was demonstrated for 70 min. Using this long-duration method, stable operation was achieved with heater powers as low as 6% of the total discharge power. Using the thermal mass flow control system the thruster operated stably enough and long enough that performance measurements could be obtained and compared to the performance of the thruster using xenon propellant. It was found that when operated with magnesium, the thruster has thrust ranging from 34 mN at 200 V to 39 mN at 300 V with 1.7 mg/s of propellant. It was found to have 27 mN of thrust at 300 V using 1.0 mg/s of propellant. The thrust-to-power ratio ranged from 24 mN/kW at 200 V to 18 mN/kW at 300 volts. The specific impulse was 2000 s at 200 V and upwards of 2700 s at 300 V. The anode efficiency was found to be ~23% using magnesium, which is substantially lower than the 40% anode efficiency of xenon at approximately equivalent molar flow rates. Measurements in the plasma plume of the thruster—operated using magnesium and xenon propellants—were obtained using a Faraday probe to measure off-axis current distribution, a retarding potential analyzer to measure ion energy, and a double Langmuir probe to measure plasma density, electron temperature, and plasma potential. Additionally, the off axis current distributions and ion energy distributions were compared to measurements made in krypton and bismuth plasmas obtained in previous studies of the same thruster. Comparisons showed that magnesium had the largest beam divergence of the four propellants while the others had similar divergence. The comparisons also showed that magnesium and krypton both had very low voltage utilization compared to xenon and bismuth. It is likely that the differences in plume structure are due to the atomic differences between the propellants; the ionization mean free path goes down with increasing atomic mass. Magnesium and krypton have long ionization mean free paths and therefore require physically larger thruster dimensions for efficient thruster operation and would benefit from magnetic shielding.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.