Signal analysis for multiple target materials through wavelet transforms

Signal identification based on different sensing systems like microwaves, infra-red, x-rays and terahertz waves is one of the classic problems in signal processing. Earlier methods had relied mainly on the amplitude spectrum obtained by these sensing techniques mainly due to non-availability of the phase information for the signals. Most of them are based on techniques like absorbance spectrum that requires a reference material\u27s signal for the test material\u27s identification. They are also sensitive to noise and highly dependent on the peak detection algorithms. Modern equipments with both amplitude and phase information provide an opportunity for time-domain signal based methods that had not been used earlier. In this thesis, the information available through time-domain signals is utilized by the use of different wavelet transform based methods. The methods have been tested for data obtained through the terahertz time-domain spectroscopy (THz-TDS), particularly because of their ability to capture the distinguishing features of the material. The methods presented here are based on the Continuous and the Discrete Wavelet Transforms. The wavelet transforms have been used to calculate time-frequency energy density in the scale-shift domain. These energy densities have then been used to identify the features described as maxima lines and ridges that are used as features for the purpose of material identification. The methods are found to be useful in the presence of noise require no pre-filtering of the signals as required in most conventional material identification techniques. They also provide a scalable method for increasing accuracy based on the computational power available. All the simulations have been done on MATLAB --Abstract, page iii

Sonar image interpretation for sub-sea operations

Mine Counter-Measure (MCM) missions are conducted to neutralise underwater explosives. Automatic Target Recognition (ATR) assists operators by increasing the speed and accuracy of data review. ATR embedded on vehicles enables adaptive missions which increase the speed of data acquisition. This thesis addresses three challenges; the speed of data processing, robustness of ATR to environmental conditions and the large quantities of data required to train an algorithm. The main contribution of this thesis is a novel ATR algorithm. The algorithm uses features derived from the projection of 3D boxes to produce a set of 2D templates. The template responses are independent of grazing angle, range and target orientation. Integer skewed integral images, are derived to accelerate the calculation of the template responses. The algorithm is compared to the Haar cascade algorithm. For a single model of sonar and cylindrical targets the algorithm reduces the Probability of False Alarm (PFA) by 80% at a Probability of Detection (PD) of 85%. The algorithm is trained on target data from another model of sonar. The PD is only 6% lower even though no representative target data was used for training. The second major contribution is an adaptive ATR algorithm that uses local sea-floor characteristics to address the problem of ATR robustness with respect to the local environment. A dual-tree wavelet decomposition of the sea-floor and an Markov Random Field (MRF) based graph-cut algorithm is used to segment the terrain. A Neural Network (NN) is then trained to filter ATR results based on the local sea-floor context. It is shown, for the Haar Cascade algorithm, that the PFA can be reduced by 70% at a PD of 85%. Speed of data processing is addressed using novel pre-processing techniques. The standard three class MRF, for sonar image segmentation, is formulated using graph-cuts. Consequently, a 1.2 million pixel image is segmented in 1.2 seconds. Additionally, local estimation of class models is introduced to remove range dependent segmentation quality. Finally, an A* graph search is developed to remove the surface return, a line of saturated pixels often detected as false alarms by ATR. The A* search identifies the surface return in 199 of 220 images tested with a runtime of 2.1 seconds. The algorithm is robust to the presence of ripples and rocks

Seismic Technology Adapted to Analyzing and Developing Geothermal Systems Below Surface-Exposed High-Velocity Rocks - Final Report

The objective of our research was to develop and demonstrate seismic data acquisition and data processing technologies that allow geothermal prospects below high-velocity rock outcrops to be evaluated. To do this, we acquired a 3-component seismic test line across an area of exposed high-velocity rocks in Brewster County, Texas, where there is high heat flow and surface conditions mimic those found at numerous geothermal prospects. Seismic contractors have not succeeded in creating good-quality seismic data in this area for companies who have acquired data for oil and gas exploitation purposes. Our test profile traversed an area where high-velocity rocks and low-velocity sediment were exposed on the surface in alternating patterns that repeated along the test line. We verified that these surface conditions cause non-ending reverberations of Love waves, Rayleigh waves, and shallow critical refractions to travel across the earth surface between the boundaries of the fast-velocity and slow-velocity material exposed on the surface. These reverberating surface waves form the high level of noise in this area that does not allow reflections from deep interfaces to be seen and utilized. Our data acquisition method of deploying a box array of closely spaced geophones allowed us to recognize and evaluate these surface-wave noise modes regardless of the azimuth direction to the surface anomaly that backscattered the waves and caused them to return to the test-line profile. With this knowledge of the surface-wave noise, we were able to process these test-line data to create P-P and SH-SH images that were superior to those produced by a skilled seismic data processing contractor. Compared to the P-P data acquired along the test line, the SH-SH data provided a better detection of faults and could be used to trace these faults upward to the boundaries of exposed surface rocks. We expanded our comparison of the relative value of S-wave and P-wave seismic data for geothermal applications by inserting into this report a small part of the interpretation we have done with 3C3D data across Wister geothermal field in the Imperial Valley of California. This interpretation shows that P-SV data reveal faults (and by inference, also fractures) that cannot be easily, or confidently, seen with P-P data, and that the combination of P-P and P-SV data allows VP/VS velocity ratios to be estimated across a targeted reservoir interval to show where an interval has more sandstone (the preferred reservoir facies). The conclusion reached from this investigation is that S-wave seismic technology can be invaluable to geothermal operators. Thus we developed a strong interest in understanding the direct-S modes produced by vertical-force sources, particularly vertical vibrators, because if it can be demonstrated that direct-S modes produced by vertical-force sources can be used as effectively as the direct-S modes produced by horizontal-force sources, geothermal operators can acquire direct-S data across many more prospect areas than can be done with horizontal-force sources, which presently are limited to horizontal vibrators. We include some of our preliminary work in evaluating direct-S modes produced by vertical-force sources.Bureau of Economic Geolog

Air Force Institute of Technology Research Report 2006

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

X-Ray Image Processing and Visualization for Remote Assistance of Airport Luggage Screeners

X-ray technology is widely used for airport luggage inspection nowadays. However, the ever-increasing sophistication of threat-concealment measures and types of threats, together with the natural complexity, inherent to the content of each individual luggage make x-ray raw images obtained directly from inspection systems unsuitable to clearly show various luggage and threat items, particularly low-density objects, which poses a great challenge for airport screeners. This thesis presents efforts spent in improving the rate of threat detection using image processing and visualization technologies. The principles of x-ray imaging for airport luggage inspection and the characteristics of single-energy and dual-energy x-ray data are first introduced. The image processing and visualization algorithms, selected and proposed for improving single energy and dual energy x-ray images, are then presented in four categories: (1) gray-level enhancement, (2) image segmentation, (3) pseudo coloring, and (4) image fusion. The major contributions of this research include identification of optimum combinations of common segmentation and enhancement methods, HSI based color-coding approaches and dual-energy image fusion algorithms —spatial information-based and wavelet-based image fusions. Experimental results generated with these image processing and visualization algorithms are shown and compared. Objective image quality measures are also explored in an effort to reduce the overhead of human subjective assessments and to provide more reliable evaluation results. Two application software are developed − an x-ray image processing application (XIP) and a wireless tablet PC-based remote supervision system (RSS). In XIP, we implemented in a user-friendly GUI the preceding image processing and visualization algorithms. In RSS, we ported available image processing and visualization methods to a wireless mobile supervisory station for screener assistance and supervision. Quantitative and on-site qualitative evaluations for various processed and fused x-ray luggage images demonstrate that using the proposed algorithms of image processing and visualization constitutes an effective and feasible means for improving airport luggage inspection

Air Force Institute of Technology Research Report 2017

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Volume II: Mining Innovation

Contemporary exploitation of natural raw materials by borehole, opencast, underground, seabed, and anthropogenic deposits is closely related to, among others, geomechanics, automation, computer science, and numerical methods. More and more often, individual fields of science coexist and complement each other, contributing to lowering exploitation costs, increasing production, and reduction of the time needed to prepare and exploit the deposit. The continuous development of national economies is related to the increasing demand for energy, metal, rock, and chemical resources. Very often, exploitation is carried out in complex geological and mining conditions, which are accompanied by natural hazards such as rock bursts, methane, coal dust explosion, spontaneous combustion, water, gas, and temperature. In order to conduct a safe and economically justified operation, modern construction materials are being used more and more often in mining to support excavations, both under static and dynamic loads. The individual production stages are supported by specialized computer programs for cutting the deposit as well as for modeling the behavior of the rock mass after excavation in it. Currently, the automation and monitoring of the mining works play a very important role, which will significantly contribute to the improvement of safety conditions. In this Special Issue of Energies, we focus on innovative laboratory, numerical, and industrial research that has a positive impact on the development of safety and exploitation in mining

COMBAT SYSTEMS Volume 1. Sensor Elements Part I. Sensor Functional Characteristics

This document includes: CHAPTER 1. SIGNATURES, OBSERVABLES, & PROPAGATORS. CHAPTER 2. PROPAGATION OF ELECTROMAGNETIC RADIATION. I. – FUNDAMENTAL EFFECTS. CHAPTER 3. PROPAGATION OF ELECTROMAGNETIC RADIATION. II. – WEATHER EFFECTS. CHAPTER 4. PROPAGATION OF ELECTROMAGNETIC RADIATION. III. – REFRACTIVE EFFECTS. CHAPTER 5. PROPAGATION OF ELECTROMAGNETIC RADIATION IV. – OTHER ATMOSPHERIC AND UNDERWATER EFFECTS. CHAPTER 6. PROPAGATION OF ACOUSTIC RADIATION. CHAPTER 7. NUCLEAR RADIATION: ITS ORIGIN AND PROPAGATION. CHAPTER 8. RADIOMETRY, PHOTOMETRY, & RADIOMETRIC ANALYSIS. CHAPTER 9. SENSOR FUNCTIONS. CHAPTER 10. SEARCH. CHAPTER 11. DETECTION. CHAPTER 12. ESTIMATION. CHAPTER 13. MODULATION AND DEMODULATION. CHAPTER 14. IMAGING AND IMAGE-BASED PERCEPTION. CHAPTER 15. TRACKING. APPENDIX A. UNITS, PHYSICAL CONSTANTS, AND USEFUL CONVERSION FACTORS. APPENDIX B. FINITE DIFFERENCE AND FINITE ELEMENT TECHNIQUES. APPENDIX C. PROBABILITY AND STATISTICS. INDEX TO VOLUME 1. Note by author: Note: Boldface entries in the table of contents are not yet completed