A Linear Subspace Approach to Burst Communication Signal Processing

This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment

Laser‐driven strong‐field Terahertz sources

A review on the recent development of intense laser‐driven terahertz (THz) sources is provided here. The technologies discussed include various types of sources based on optical rectification (OR), spintronic emitters, and laser‐filament‐induced plasma. The emphasis is on OR using pump pulses with tilted intensity front. Illustrative examples of newly emerging applications are briefly discussed, in particular strong‐field THz control of materials and acceleration and manipulation of charged particles

Spectrum sensing for cognitive radio and radar systems

The use of the radio frequency spectrum is increasing at a rapid rate. Reliable and efficient operation in a crowded radio spectrum requires innovative solutions and techniques. Future wireless communication and radar systems should be aware of their surrounding radio environment in order to have the ability to adapt their operation to the effective situation. Spectrum sensing techniques such as detection, waveform recognition, and specific emitter identification are key sources of information for characterizing the surrounding radio environment and extracting valuable information, and consequently adjusting transceiver parameters for facilitating flexible, efficient, and reliable operation. In this thesis, spectrum sensing algorithms for cognitive radios and radar intercept receivers are proposed. Single-user and collaborative cyclostationarity-based detection algorithms are proposed: Multicycle detectors and robust nonparametric spatial sign cyclic correlation based fixed sample size and sequential detectors are proposed. Asymptotic distributions of the test statistics under the null hypothesis are established. A censoring scheme in which only informative test statistics are transmitted to the fusion center is proposed for collaborative detection. The proposed detectors and methods have the following benefits: employing cyclostationarity enables distinction among different systems, collaboration mitigates the effects of shadowing and multipath fading, using multiple strong cyclic frequencies improves the performance, robust detection provides reliable performance in heavy-tailed non-Gaussian noise, sequential detection reduces the average detection time, and censoring improves energy efficiency. In addition, a radar waveform recognition system for classifying common pulse compression waveforms is developed. The proposed supervised classification system classifies an intercepted radar pulse to one of eight different classes based on the pulse compression waveform: linear frequency modulation, Costas frequency codes, binary codes, as well as Frank, P1, P2, P3, and P4 polyphase codes. A robust M-estimation based method for radar emitter identification is proposed as well. A common modulation profile from a group of intercepted pulses is estimated and used for identifying the radar emitter. The M-estimation based approach provides robustness against preprocessing errors and deviations from the assumed noise model

High-Temperature High-Pressure Carbon Dioxide Removal From Coal Gas.

The noncatalytic gas-solid reaction between CO\sb2(g) and CaO(s) to form CaCO\sb3(s) has been studied at high temperature and high pressure (HTHP) using a thermobalance reactor. This reaction could serve as the basis for a HTHP process for the separation of CO\sb2 from coal-derived gas. The kinetics of the calcination and carbonation reactions were studied as a function of temperature, pressure, CO\sb2 concentration, and background gas composition. Three sorbent precursors which produced CaO having a wide range of structural properties were selected for detailed kinetic studies. They were (i) reagent grade calcium carbonate, (ii) reagent grade calcium acetate, and (iii) commercial grade dolomite containing essentially equimolar quantities of CaCO\sb3 and MgCO\sb3. Multicycle runs were conducted in order to have a better understanding of sorbent durability. Almost complete carbonation was possible using both calcium acetate and dolomite sorbent precursors; carbonation was incomplete when calcium carbonate precursor was used. The following operating conditions were found to be most appropriate: (UNFORMATTED TABLE OR EQUATION FOLLOWS)\vbox{\halign{#\hfil&&\qquad#\hfil\cr &Calcination temperature: &750$\sp\circ$C\cr &Calcination pressure: &1--15 atm\cr &Calcination atmosphere: &any inert gas with low\cr &&CO$\sb2$ partial pressure\cr &Carbonation temperature: &650--750$\sp\circ$C\cr &Carbonation pressure: &15 atm\cr &Carbonation atmosphere: &any sulfur-free or\cr &&low-sulfur coal gas\cr}}. When sulfur-free simulated coal gas was tested, improved sorbent reactivity, capacity, and capacity maintenance were observed. The increase in reactivity was consistent with a higher concentration of CO\sb2, possibly formed by the water-gas shift reaction. The distributed pore size model (Christman and Edgar, 1983) was used to analyze the carbonation results using the reagent grade calcium carbonate precursor. Good agreement between the model and experiment was achieved for runs at 650\sp\circC with varying CO\sb2 mol fraction and reaction pressure. At different carbonation temperatures, however, it was necessary to assign zero activation energies to the intrinsic rate constant and product layer diffusion coefficient in order to match the experimental data. Both of these parameters should have quite large activation energies

Applications of Computational Intelligence to Power Systems

In power system operation and control, the basic goal is to provide users with quality electricity power in an economically rational degree for power systems, and to ensure their stability and reliability. However, the increased interconnection and loading of the power system along with deregulation and environmental concerns has brought new challenges for electric power system operation, control, and automation. In the liberalised electricity market, the operation and control of a power system has become a complex process because of the complexity in modelling and uncertainties. Computational intelligence (CI) is a family of modern tools for solving complex problems that are difficult to solve using conventional techniques, as these methods are based on several requirements that may not be true all of the time. Developing solutions with these “learning-based” tools offers the following two major advantages: the development time is much shorter than when using more traditional approaches, and the systems are very robust, being relatively insensitive to noisy and/or missing data/information, known as uncertainty

JPL Quarterly Technical Review, Volume 2, No. 3

Aerospace engineering including materials, orbits and trajectories, power sources, satellite geodesy, and structural engineerin

Versatile FPGA architecture for skein hashing algorithm

Digital communications and data storage are expanding at fast rates, increasing the need for advanced cryptographic standards to validate and provide privacy for that data. One of the basic components commonly used in information security systems is cryptographic hashing. Cryptographic hashing involves the compression of an arbitrary block of data into a fixed-size string of bits known as the hash value. These functions are designed such that it is computationally infeasible to determine a message that results in a given hash value. It should also be infeasible to find two messages with the same hash value and to change a message without its hash value being changed. Some of the most common uses of these algorithms are digital signatures, message authentication codes, file identification, and data integrity. Due to developments in attacks on the Secure Hash Standard (SHS), which includes SHA-1 and SHA-2 (SHA-224, SHA-256, SHA-384, SHA-512), the National Institute of Standards and Technology (NIST) will be selecting a new hashing algorithm to replace the current standards. In 2008, 64 algorithms were entered into the NIST competition and in December 2010, five finalists were chosen. The final candidates are BLAKE, Keccak, Gr{o}stl, JH, and Skein. In 2012, one of these algorithms will be selected for the Secure Hash Algorithm 3 (SHA-3). This thesis focuses on the development of a versatile hardware architecture for Skein that provides both sequential and tree hashing functions of Skein. The performance optimizations rely heavily on pipelined and unrolled architectures to allow for simultaneous hashing of multiple unique messages and reduced area tree hashing implementations. Additional result of this thesis is a comprehensive overview of the newly developed architectures and an analysis of their performance in comparison with other software and hardware implementations