Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

Effect of segmented anodes on the performance and plume of a hall thruster

Development of alternative propellants for Hall thruster operation is an active area of research. Xenon is the current propellant of choice for Hall thrusters, but can be costly in large thrusters and for extended test periods. Condensible propellants may offer an alternative to xenon, as they will not require costly active pumping to remove from a test facility, and may be less expensive to purchase. A method has been developed which uses segmented electrodes in the discharge channel of a Hall thruster to divert discharge current to and from the main anode and thus control the anode temperature. By placing a propellant reservoir in the anode, the evaporation rate, and hence, mass flow of propellant can be controlled. Segmented electrodes for thermal control of a Hall thruster represent a unique strategy of thruster design, and thus the performance of the thruster must be measured to determine the effect the electrodes have on the thruster. Furthermore, the source of any changes in thruster performance due to the adjustment of discharge current between the shims and the main anode must be characterized. A Hall thruster was designed and constructed with segmented electrodes. It was then tested at anode voltages between 300 and 400 V and mass flows between 4 and 6 mg/s, as well as 100%, 75%, 50%, 25%, and <5% of the discharge current on the shim electrodes. The level of current on the shims was adjusted by changing the shim voltage. At each operating point, the thruster performance, plume divergence, ion energy, and multiply charged ion fraction were measured performance exhibited a small change with the level of discharge current on the shim electrodes. Thrust and specific impulse increased by as much as 6% and 7.7%, respectively, as discharge current was shifted from the main anode to the shims at constant anode voltage. Thruster efficiency did not change. Plume divergence was reduced by approximately 4 degrees of half-angle at high levels of current on the shims and at all combinations of mass flow and anode voltage. The fraction of singly charged xenon in the thruster plume varied between approximately 80% and 95% as the anode voltage and mass flow were changed, but did not show a significant change with shim current. Doubly and triply charged xenon made up the remainder of the ions detected. Ion energy exhibited a mixed behavior. The highest voltage present in the thruster largely dictated the most probable energy; either shim or anode voltage, depending on which was higher. The overall change in most probable ion energy was 20-30 eV, the majority of which took place while the shim voltage was higher than the anode voltage. The thrust, specific impulse, plume divergence, and ion energy all indicate that the thruster is capable of a higher performance output at high levels of discharge current on the shims. The lack of a change in efficiency and fraction of multiply charged ions indicate that the thruster can be operated at any level of current on the shims without detrimental effect, and thus a condensible propellant thruster can control the anode temperature without a decrease in efficiency or a change in the multiply charged ion fraction.