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Full-Text Articles in Engineering
Target Recognition Using Late-Time Returns From Ultra-Wideband, Short-Pulse Radar, Kenneth J. Pascoe
Target Recognition Using Late-Time Returns From Ultra-Wideband, Short-Pulse Radar, Kenneth J. Pascoe
Theses and Dissertations
The goal of this research is to develop algorithms that recognize targets by exploiting properties in the late-time resonance induced by ultra-wide band radar signals. A new variant of the Matrix Pencil Method algorithm is developed that identifies complex resonant frequencies present in the scattered signal. Kalman filters are developed to represent the dynamics of the signals scattered from several target types. The Multiple Model Adaptive Estimation algorithm uses the Kalman filters to recognize targets. The target recognition algorithm is shown to be successful in the presence of noise. The performance of the new algorithms is compared to that of …
Utilizing Near-Field Measurements To Characterize Far-Field Radar Signatures, John R. Watkins
Utilizing Near-Field Measurements To Characterize Far-Field Radar Signatures, John R. Watkins
Theses and Dissertations
The increased need for stealth aircraft requires an on-site Far-Field (FF) Radar Cross-Section (RCS) measurement process. Conducting these measurements in on-site Near-Field (NF) monostatic facilities results in significant savings for manufacturers and acquisition programs. However, NF measurements are not directly extended to a FF RCS. Therefore, a large target Near-Field to Far-Field Transformation (NFFFT) is needed for RCS measurements. One approach requires an Inverse Synthetic Aperture Radar (ISAR) process to create accurate scattering maps. The focus of this work is the development of accurate NF scattering maps generated by a monostatic ISAR process. As a first look, the process is …
Discovering The Merit Of The Wavelet Transform For Object Classification, Matthew D. Eyster
Discovering The Merit Of The Wavelet Transform For Object Classification, Matthew D. Eyster
Theses and Dissertations
Vision is the primary sense by which most biological systems collect information about their environment. Computer vision is a branch of artificial intelligence concerned with endowing machines with the ability to understand images. Object recognition is a key part of machine vision with far reaching benefits ranging from target recognition, surveillance systems, to automation systems. Extraction of salient features from an image is one of the key steps in object recognition. Typically, geometric primitives are extracted from an image using local analysis. However, the wavelet transform provides a global approach with good locality. Additionally, the directional and multiresolution properties may …
Reconstruction Algorithm Characterization And Performance Monitoring In Limited-Angle Chromotography, Kevin C. Gustke
Reconstruction Algorithm Characterization And Performance Monitoring In Limited-Angle Chromotography, Kevin C. Gustke
Theses and Dissertations
Hyperspectral data collection and analysis is an increasing priority with the growing need to obtain greater classification precision than offered by traditional spatial imagery. In this thesis, trends in hyperspectral chromotomographic reconstruction are explored where reconstruction is performed using a series of spatial-chromatic images. Chromotomography involves capturing a series of two-dimensional images where each image is created by placing a prism in front of the focal plane array; causing spectral dispersion corresponding to a series of prism angles over a single rotation. Before testing reconstruction, synthetic data is produced, approximating what would be produced from prism dispersion on the focal …