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Accelerated Hyperspectral Unmixing With Endmember Variability Via The Sum-Product Algorithm, Charan Puladas
Accelerated Hyperspectral Unmixing With Endmember Variability Via The Sum-Product Algorithm, Charan Puladas
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The rich spectral information captured by hyperspectral sensors has given rise to a number of remote sensing applications, ranging from vegetative assessment and crop health monitoring, to military surveillance and combatant identification. However, due to limited spatial resolution, multiple ground materials generally contribute, i.e. mix, to form the spectrum recorded for a single pixel. The unmixing problem considers the inverse problem of determining the underlying material spectra, called endmembers, from sensor measurements. While classical unmixing approaches were deterministic in nature and did not attempt to identify in-scene materials, recent methods use labeled training data to generate statistical models of endmember …
Performance Prediction Of Constrained Waveform Design For Adaptive Radar, Aaron M. Jones
Performance Prediction Of Constrained Waveform Design For Adaptive Radar, Aaron M. Jones
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Today's radars face an ever increasingly complex operational environment, intensified by the numerous types of mission/modes, number and type of targets, non-homogenous clutter and active interferers in the scene. Thus, the ability to adapt ones transmit waveform, to optimally suit the needs for a particular radar tasking and environment, becomes mandatory. This requirement brings with it a host of challenges to implement including the basic decision of what to transmit. In this dissertation, we discuss six original contributions, including the development of performance prediction models for constrained radar waveforms, that aid in the decision making process of an adaptive radar …