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Full-Text Articles in Signal Processing
Hyperspectral-Based Adaptive Matched Filter Detector Error As A Function Of Atmospheric Profile Estimation, Allan W. Yarbrough
Hyperspectral-Based Adaptive Matched Filter Detector Error As A Function Of Atmospheric Profile Estimation, Allan W. Yarbrough
Theses and Dissertations
Hyperspectral imagery is collected as radiance data. This data is a function of multiple variables: the radiation profile of the light source, the reflectance of the target, and the absorption and scattering profile of the medium through which the radiation travels as it reflects off the target and reaches the imager. Accurate target detection requires that the collected image matches as closely as possible the known "true" target in the classification database. Therefore, the effect of the radiation source and the atmosphere must be removed before detection is attempted. While the spectrum of solar light is relatively stable, the effect …
Development Of A Cubesat Instrument For Microgravity Particle Damper Performance Analysis, John Trevor Abel
Development Of A Cubesat Instrument For Microgravity Particle Damper Performance Analysis, John Trevor Abel
Master's Theses
Spacecraft pointing accuracy and structural longevity requirements often necessitate auxiliary vibration dissipation mechanisms. However, temperature sensitivity and material degradation limit the effectiveness of traditional damping techniques in space. Robust particle damping technology offers a potential solution, driving the need for microgravity characterization. A 1U cubesat satellite presents a low cost, low risk platform for the acquisition of data needed for this evaluation, but severely restricts available mass, volume, power and bandwidth resources. This paper details the development of an instrument subject to these constraints that is capable of capturing high resolution frequency response measurements of highly nonlinear particle damper dynamics.
Solving The Vehicle Re-Identification Problem By Using Neural Networks, Tanweer Rashid
Solving The Vehicle Re-Identification Problem By Using Neural Networks, Tanweer Rashid
Computational Modeling & Simulation Engineering Theses & Dissertations
Vehicle re-identification is the process by which vehicle attributes measured at one point on a road network are compared to vehicle attributes measured at another point in an effort to match vehicles without using any unique identifiers such as license plate numbers. A match is made if the two measurements are estimated to belong to the same vehicle. Vehicle attributes can be sensor readings such as loop induction signatures, or they can also be actual vehicle characteristics such as length, weight, number of axles, etc. This research makes use of vehicle length, travel time, axle spacing and axle weights for …