Engineering topics
Publications and source records attributed to Perez, R. M..
Participants at the 13th Airborne Earth Science Workshop reported science research and applications results with spectral images measured by the NASA Airborne Invisible/Infrared Imaging Spectrometer (AVIRIS).
The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.
A method is presented for the measurement of the harmonic output power of high power klystron amplifiers, involving coherent hemispherical radiation pattern measurements of the radiated klystron output. Results are discussed for the operation in saturated and unsaturated conditions, and with a waveguide harmonic filter included.
This article describes the techniques used and experimental results obtained in improving transmitter stability by control of the klystron body temperature. Related work in the measurement of klystron phase control parameters (pushing factors) is also discussed. The contribution of waveguide temperature excursions to uplink phase stability is presented. Suggestions are made as to the direction of future work in this area.
Thermal measurements of microwave transmitter feedhorn windows were performed using an imaging infrared radiometer. The measurement technique is described and results are presented for windows made of 0.001-in. Kapton (trademark of Dupont Chemical Co.) and 0.1-in. HTP-6 (Space Shuttle tile material). Measured and calculated temperatures agree well.