A method of high resolution over-the-horizon radars (OTHRs) using time-reversal is described. The method uses timereversal
in the multipath-enriched ionospheric environment in order to achieve the extended virtual aperture. Also, the
double-pass conjugate image scanning scheme allows imaging of non-cooperative targets without requiring apriori
knowledge of environmental conditions. Initial theoretical and experimental results are provided.
The Space Interferometry Mission (SIM) requires the control of the optical path of each interferometer with picometer
accuracy. Laser metrology gauges are used to measure the path lengths to the fiducial corner cubes at the siderostats.
Due to the geometry of SIM a single corner cube does not have sufficient acceptance angle to work with all the gauges.
Therefore SIM employs a double corner cube. Current fabrication methods are in fact not capable of producing such a
double corner cube with vertices having sufficient commonality. The plan for SIM is to measure the non-commonalty of
the vertices and correct for the error in orbit. SIM requires that the non-common vertex error (NCVE) of the double
corner cube to be less than 6 μm. The required accuracy for the knowledge of the NCVE is less than 1 μm. This paper
explains a method of measuring non-common vertices of a brassboard double corner cube with sub-micron accuracy.
The results of such a measurement will be presented.
We propose a method for 2D multiple beam generation without causing extraneous beams in the ASTRO architecture. By simply adding a circular light block (spatial filter) at the center of the polygon mirror on the ASTRO true time delay generator, all the extraneous beams can be removed without requiring additional hardware. Experimental results to prove the concepts will be described with related analyses.
This paper examines the use of composite filters for improving the effectiveness of a Vanderlugt correlator when used for fingerprint identification. A digital simulation, which accounts for noise sources in the optical setup, is used to design and test composite matched spatial filters. Results are presented for a real time video image database containing 10 seconds of video from 200 fingers. Using the composite matched spatial filter the Vanderlugt correlator is getting 70% correct identifications with no false positives.
Two-dimensional multiple beam steering in the Acoustically STeered and ROtated (ASTRO) true time delay generation architecture is described. The architecture is capable of generating 2D multiple beams without causing any extraneous beams. The system can be used as both transmitter and receiver modes simultaneously.
A new 2-D true time delay (TTD) generation system architecture for phased array antennas is described. The method uses fiber chirp gratings and acousto-optic beam deflectors. By combining free-space optics and guided optics, the device complexity in conventional TTD systems has been significantly reduced. A proof-of-concept experimental results are demonstrated.
This paper presents results on direct optical matching of inked and real-time fingerprint images. Direct optical correlations and hybrid optical neural network correlation are used in the matching system for inked fingerprints. Preliminary results on optical matching of real-time fingerprints use optical correlation. The test samples used in the inked image experiments are the fingerprint taken from NIST database SD-9. These images, in both binary and gray level forms, are stored in a VanderLugt correlator. Tests of typical cross correlations and auto correlation sensitivity for both binary and 8 bit gray images are presented. When global correlations are tested on a second inked image results are found to be strongly influenced by plastic distortion of the finger. When the correlations are used to generate features that are localized to parts of each fingerprint and combined using a neural network classification network and separate class-by-class matching networks, 84.3 percent matching accuracy is obtained on a test set of 100,000 image pairs. Initial results with real- time images suggest that the difficulties resulting from finger deformation can be avoided by combining many different distorted images when the hologram is constructed in the correlator. Testing this process will require analysis of 10-20 second sequences of digital video.
Although the concept of using multiplexed holography for data storage has been considered for some time, recent advances in several critical device technologies along with developments in storage materials have greatly enhanced the likelihood of successful implementations. We review several basic architectural concepts along with various multiplexing options and associated techniques for holographic data storage.
Holographic implementations of neural networks using photorefractive crystals and vertical-cavity surface-emitting microlaser arrays are described. This paper concentrates on the nonlinear thresholding elements (optical neurons), an associative memory using time-division multiplexing, and image transmission through a single mode fiber.
This paper reviews the recent progress in the development of holographic neural networks using surface-emitting laser diode arrays (SELDAs). Since the previous work on ultrafast holographic memory readout system and a robust incoherent correlator, progress has been made in several areas: the use of an array of monolithic `neurons' to reconstruct holographic memories; two-dimensional (2-D) wavelength-division multiplexing (WDM) for image transmission through a single-mode fiber; and finally, an associative memory using time- division multiplexing (TDM). Experimental demonstrations on these are presented.
Neural network models for associative memory are derived independently on the basis of an optimization principle without resort to any assumptions related to biological principles. All the features of the Hopfield model, such as the updating rule with nonlinear threshold, the outer product algorithm, the symmetric and zero-diagonal interconnection matrix, and asynchronous timing, are automatically derived from a simple optimization principle for bipolar and binary variables. The derivation is extended to generate higher order models that have higher storage capacity and better convergence. The computational circuits to implement the neural network models are also derived naturally from the same principle. Various optical implementations of the computational circuits are also described.
We demonstrate two optical neuro-processors based on coherent optics: An associative memory for word-break recognition and an on-line learning machine for multicategory classification. Finally, we show how both of the systems can be compacterized using recent devices including surface-emitting micro-laser arrays.