William J. Miceli

Photonic computing using the modified signed-digit number representation

Improving the precision of optically performed computations is a critical aspect of photonic computing. One possible method for improving precision is through the use of modified signed-digit (MSD) arithmetic. Optical implementation of MSD arithmetic offers several important advantages over other optical techniques such as the digital multiplication by analog convolution (DMAC) algorithm or the use of residue arithmetic. These advantages include the parallel pipeline flow of digits due to carry-free addition and subtraction, fixed-point as well as floating-point capability, and the potential for performing divisions. We present a brief description of the modified signed-digit number system and suggest one optical architecture for implementing MSD fixed-point addition, subtraction, and multiplication.

Radar Micro-Doppler signatures : processing and applications

* Chapter 1: Micro-Doppler Signatures - Review, Challenges, and Perspectives * Chapter 2: Phenomenology of Radar Micro-Doppler Signatures * Chapter 3: Analysis of Human Signatures using High-Range Resolution Micro-Doppler Radar * Chapter 4: Range and Micro-Doppler Analysis of Human Motion Using High Resolution Experimental HYCAM Radar * Chapter 5: Through-the-Wall Micro-Doppler Signatures * Chapter 6: Identifying Human Movements Using Micro-Doppler Features * Chapter 7: Micro-Doppler Signatures of Helicopter Rotor Blades * Chapter 8: Micro-Doppler Signatures of Small Boats * Chapter 9: Multistatic Micro-Doppler Signature Processing * Chapter 10: Signal Decomposition of Micro-Doppler Signatures * Chapter 11: Sonar Micro-Doppler Signatures: Principles and Applications * Chapter 12: Radar Micro-Doppler Signature of Wind Turbines

Effect of roll, pitch, and yaw motions on ISAR imaging

In this paper, we analyze the effect of roll, pitch and yaw rotations on inverse synthetic aperture radar (ISAR) imaging. An ideal ISAR image of a target with regular motion can be derived from the image projection plane and the radar line-of-sight unit vector. Roll, pitch and yaw rotations induce time-varying Doppler shifts that can be analyzed through the rotation matrix and the effective rotation vector. We simulated the process of ISAR imaging of a rotating target. Thus, the effect of rotational motion on ISAR imaging can be observed, and the effect of individual rotation components can be studied separately. For a target with regular motion, perturbations of roll and pitch motions may make image blurring if conventional motion compensation is used. Advanced motion compensation algorithms that compensate the perturbations may improve the image.

Jump-diffusion processes for the automated understanding of FLIR scenes

We take a pattern theoretic approach to recognizing and tracking ground-based targets in sequences of forward-looking infrared images acquired from an airborne platform. A rich set of transformations on objects represented by 3D faceted models are formulated to accommodate the variability found in FLIR imagery. An hypothesized scene, simulated from the emissive characteristics of the hypothesized scene elements, is compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. A jump-diffusion process empirically generates the posterior distribution. The jumps accommodate the discrete aspects of the estimation problem, such as adding and removing hypothesized targets and changing target types. Between jumps, a diffusion process refines the hypothesis by following the gradient of the posterior. Since the likelihood function may include likelihoods from other sensors and may be defined over past and current times, interframe processing and sensor fusion are natural consequences of the pattern theoretic approach.

Optical implementation of a matching pursuit for image representation

We have developed a technique for image analysis, representation, and decomposition. This technique was motivated by Mallat and Zhangs matching-pursuit algorithm. We have altered and simplified the mechanics of this algorithm to enable an extremely fast implementation via optical processing. Initial computer simulations show that our algorithm is capable of decomposing and representing a 2-D image as a linear combination of basis images with both high speed and high fidelity.

Optoelectronically implemented neural network with a wavelet preprocessor

An optoelectronic neural network based upon the Neocognitron paradigm has been implemented at JPL and successfully demonstrated for automatic target recognition for both focal plane array imageries and range-Doppler radar signatures. A novel feature of this neural network architectural design is the use of a shift-invariant multichannel Fourier optical correlation as a building block for iterative multilayer processing. An innovative bipolar neural weights holographic synthesis technique was utilized to implement both the excitatory and inhibitory neural functions and dramatically increase its discrimination capability. In order to further increase the optoelectronic Neocognitrons self-organization processing ability, a wavelet preprocessor has been developed for feature extraction preprocessing (orientation, size, location, etc.). The addition of this wavelet processor would enable the neocognitron to dynamically focus on the incoming targets based on their known features and result in higher discrimination and lower false alarm rate. The theoretical analysis of an orientation and scale selective wavelet is provided. A multichannel optoelectronic wavelet processor using an e- beam complex-valued wavelet filter is also presented. Experimental demonstrations of wavelet preprocessing for feature extraction are also provided.

One-Dimensional To Two-Dimensional Transformations In Signal Correlation

We explore one-dimensional (1-D) to two-dimensional (2-D) transformations suitable for optical correlation of signals. An intuitive, geometrical development establishes and relates several 2-D formats including variations of the familiar falling raster format. Insight into the folded spectrum is gained by considering a matched spatial filter implementation of correlation between two signals in falling raster formats.

Real-time updatable optical wavelet processor

An all-optical wavelet processor for target detection has been developed and demonstrated at JPL. An innovative 2D Shape-discriminant wavelet filter, encoded with a ternary-valued scheme, was developed and implemented in a Liquid Crystal Television Spatial Light Modulator (LCTV SLM) to enable real-time updatable processing. Applications ranging from flight object discrimination, mine detection, and cancer cell detection have been demonstrated.

Optical Flixed-Point Arithmetic

The DMAC (Digital Multiplication by Analog Convolution) algorithm has been shown to be one technique for performing optical matrix-multiplication with improved precision. Past work in this area has addressed fixed-point arithmetic only. Presented in this paper is an extension of the DMAC algorithm for handling floating-point binary numbers as well. However, the technique employed for handling floating-point numbers is based on fixed-point concepts. For this reason we choose to call the arithmetic as being flixed-point, since it is a hybrid combination of both floating and fixed-point arithmetic. In this paper we also describe an acousto-optical time-integrating architecture using binary flixed-point arithmetic to perform matrix-vector multiplication. By employing an array of full-adders in conjunction with the photodetector array at the back-end of this architecture, it is possible to avoid generating mixed binary outputs that normally result through the use of the DMAC algorithm. Hence, we eliminate the need for analog-to-digital converters needed to convert mixed binary to pure binary. Preliminary experimental results are also presented.

Optical wavelet processor using cascaded liquid crystal television spatial light modulators (LCTV SLMs)

A novel optical wavelet processor is introduced. Generic wavelet functions, consisting of both amplitude and phase information can be optically synthesized using two cascaded Liquid Crystal Television Spatial Light Modulators. An innovative ternary-valued shape discriminant wavelet filter and its optical implementation is also introduced. Experimental demonstrations of multitarget classification using both a 2D Morlet wavelet filter and a ternary wavelet filter are also reported. The experimental results show that the wavelet filters are superior in discrimination than that of the conventional correlation technique.