Benjamin C. Flores

Chaotic signals for wideband radar imaging

We explore the characteristics of chaos for wideband radar imaging. Chaos can be generated via non-linear functions that produce statistically independent samples with invariant probability density functions. By feeding this type of chaos to the input of a voltage-controlled oscillator, a stochastic frequency modulated signal with fractal features is generated. The FM signal is an ergodic and stationary process with initial random phase. The power spectral density of such signal is typically broadband. We show that the time autocorrelation associated with the FM signal provides high range resolution for zero Doppler and dies out rapidly for increasing Doppler shifts. Furthermore, we show that a set of realizations of the signal can be processed into a set of ambiguity surfaces that when averaged yield a low self-noise pedestal.

Radar imaging via random FM correlations

Our goal is to study the properties of a random FM process correlator as applied to radar imaging. The driver of the transmitted FM signal is Gaussian, bandlimited random process while the initial phase of the process is uniformly distributed. Thus, the FM process is wide-sense stationary. For wideband modulation, both the autocorrelation and spectrum of the FM process are approximately Gaussian as inferred from Woodwards adiabatic principle. Since the half power bandwidth of the process is linearly proportional to the modulation index (lambda) , the range-delay resolution is inversely proportional to (lambda) . We make use of Monte Carlo simulations to illustrate the stationary nature of the correlator output. Radar imaging of rotating targets is implemented using a microwave tomography algorithm, which requires data collection for a finite number of viewing angles. We demonstrate that the self-noise power in this type of imagery is controlled by the number of samples processed and the number of signal realizations included in calculating the autocorrelations.

Refinement of range-Doppler imagery by feedback control

This paper describes extended work on a comprehensive rotational-motion estimation and compensation technique to improve the quality of range-Doppler imagery. The approach assumes that the target signature is a collection of samples in the frequency space aperture plane. Motion compensation is performed via a polar reformatting scheme that requires knowledge of target kinematics, while motion estimation is accomplished by monitoring an entropy-like function in terms of kinematic parameter estimates. When properly selected, the entropy-like function becomes an accurate measure of image sharpness, and can thus be used to control a down-hill simplex search which yields an optimum set of rotational-motion parameter estimates. Ultimately, this set is needed to produce an optimally focused target image.

SAR sidelobe apodization using the Kaiser window

Traditional synthetic aperture radar (SAR) image processing involves a two-dimensional Fourier transform that may produce significant high intensity sidelobes. These artifacts have the potential of obscuring low intensity scatterers in the image. Spatially variant sidelobe apodization is a technique that reduces sidelobe levels in a Fourier image while maintaining the image resolution that would be obtained using the rectangular window. In this paper, the use of the Kaiser (1974) window for sidelobe apodization is studied. It is shown that the use of this window outperforms the use of the cosine-on-pedestal window. Albeit, the method proposed here is not easily implemented, high resolution and low sidelobe levels are obtained. The method was tested and results are shown when using this new sidelobe apodization technique on an actual SAR image.

Choice of an entropy-like function for range-Doppler processing

Motion compensation of range-Doppler target signatures results in focused target imagery. Recently, an iterative approach based on a logarithmic entropy measure has been proposed for the motion compensation of signatures collected in the frequency domain. The effectiveness of this approach can be significantly improved by using an entropy-like function which is maximally resistant to noise and consistent with statistical boundaries. For purposes of analysis, the entropy-like function is written in terms of an information gain function (Delta) I. Several expressions for (Delta) I are tested to verify the accuracy of radial-motion parameter estimation. The effectiveness of these expressions is determined by the number of iterations required to find the minimum entropy measure, within an acceptable tolerance level for a given signal-to-noise ratio. Results show that the exponential information gain (Delta) I equals exp(1-I) yields an optimally convex entropy measure surface over a prescribed motion- parameter solution space. The surface minimum in this solution space has coordinates which are interpreted as the optimum motion-parameter estimates that can be obtained for the purpose of image focusing.

‘Plus Two’ Peer-Led Team Learning improves student success, retention, and timely graduation

A dasiaplus twopsila strategy has integrated peer-led team learning (PLTL) as a required component of first semester general chemistry at the University of Texas at El Paso (UTEP). Since fall 2000, the C-or-better passing rate has improved from the historic average near 53% to the current rate above 70%, translating into an additional 160 students successfully progressing each year into their science, engineering, and mathematics majors. In 2006, the Plus Two Peer-Led Chemistry Program at UTEP earned the Star Award from the Texas Higher Education Coordinating Board for its innovative active-learning curriculum intervention for improving student success, retention, and timely graduation in the engineering and science disciplines. Plus Two substitutes two hours of Workshop: small-group, active learning guided by an undergraduate STEM student (peer leader) for one hour of large section lecture per week in the three-credit-hour chemistry course. Retention of students for the four semesters subsequent to the plus two innovation improved from 70% to 75% and the number of students receiving undergraduate degrees within nine semesters jumped from approximately 34% to 47%. A National Science Foundation award (DUE - 0653270) entitled ISTAR: integrated student success, teaching, and retention, has now extended the plus two strategy to six other large section lower division courses leading to STEM degrees at UTEP.

Robust method for the motion compensation of ISAR imagery

A technique for improving stepped-frequency inverse synthetic aperture radar (ISAR) imagery via entropy minimization is presented. Image improvement is achieved in the frequency domain where the echo phase can be adjusted to compensate for radial motion. The computational algorithm which determines motion parameters that reduce entropy to an absolute minimum is based on the golden-section-search method and operates in a closed-loop mode. Using this technique one can efficiently focus the image generated by a fully automated high-resolution-radar system that evaluates its own performance in terms of image quality.

Multi-Mode Radar Target Detection and Recognition Using Neural Networks

In typical radar systems, the process of recognizing a target requires human involvement. This human element makes radar systems not fully reliable due to unstable performance that varies between operators. This paper describes an intelligent radar system which addresses this problem in a border surveillance environment. The proposed radar system is capable of automatically detecting and then classifying different targets using an artificial neural network trained with the Levenberg-Marquardt algorithm. The training and test sets presented to the neural network are composed by high-resolution Inverse Synthetic Aperture Radar pictures obtained by the radars detection module. Simulation results show that the intelligent radar system can reliably detect and distinguish the different objectives. Moreover, the radar system can outperform human operators and another radar system that deals with similar objectives. These results indicate that future intelligent systems can potentially replace human radar operators in this critical security setting.

Undergraduate student retention strategies for urban engineering colleges

With the exception of two flagship institutions in Texas, the graduation rate at urban public universities in the state is lower than 40%. New Mexico public universities hold a similar record. A theory for college departure argues that this graduation rate could be increased significantly by reducing the attrition rate during the first years of college. We discuss a multi-component implementation of this theory in a commuter engineering college in west Texas. First, we address the transition between high school and college as an anomic situation that can be corrected by means of a university seminar that incorporates survival skills into the academic content of the course. We explain how academic performance of entering students can be improved via the implementation of learning communities. We also explain how the incorporation of entering students into the college society can be achieved through an academic center for student development. Next, we discuss the advantage of developing a strong undergraduate research program. Finally, we discuss the importance of faculty, and curriculum development in promoting a culture change that focuses on student learning through active participation in the classroom.

Fourier transform receiver processing of hopped frequency sequences for synthetic range profile generation

This article addresses the use of the Fourier transform receiver as a radar system for high-resolution range-profile generation. A significant point of reference is the equivalence of this receiver to the standard matched filter. Henceforth, it is demonstrated that range information can be extracted from beat-frequency measurements by processing a selected set of waveforms. Attention is given to the step and hop-frequency modulation waveforms, which are shown to be easily compressed into an optimum range profile via coherent, narrowband processing. For these waveforms, the effects of velocity are also discussed in the context of profile distortion due to Doppler mismatch.