A new detection system has been designed and constructed that enables remote sensing, recording and archiving of
Electrical Over-Stress (EOS) and Electro Static Discharge (ESD) events, a major cause of electronic device failure in
ruggedized military applications. Advances have been made in the design and manufacture of magneto-optic static event
detection devices and in the ability to perform automatic detection of polarization states of the devices. The combined
automatic reader and next-generation device are providing viable prototypes for insertion into legacy circuit boards for
EOS and ESD monitoring.
This paper describes algorithmic development toward an automated process that generates a same patient sequence of fundic images that are normalized in position and intensity and have noise artifacts removed. Normalization of these fundic images is a key first step to further automatic analysis for the presence or progress of ophthalmic diseases. The Litton PRC team, inclusive of LItton Data Systems and Tomey Inc., evaluated the potential use of a hybrid optical/digital processor in the normalization of ophthalmic imagery. PRC provided the funding, initial architecture and approach for disease analysis using the optical processor. Tomey Inc. provided the fundus imagery and clinical advice on 'normalization' or images prior to undertaking the disease analysis. Litton Data Systems prototyped the algorithms and test using a rapid application prototyping tool for object recognition. The team approach was to do a coarse vessel alignment to bring the images within a to-be-determined level of alignment, and the repeat the algorithms at a threshold and alignment for fine vessels. The success of the coarse work encouraged the investigation of algorithms for processing higher resolution images with greater accuracy. The combined results completed the IRAD investigation and are shown as successfully aligning two images.
Many image processing applications require small, low-power, low-cost pattern recognition systems that are capable of
locating and identifying objects. Space applications require additional features such as environmental ruggedness, stability,
and maintenance-free operation. Miniature optical correlators can perform two-dimensional pattern recognition at greater
rates than digital platforms of equivalent size, power and/or weight. The patented Miniature Ruggedized Optical Correlator
(MROC) module is built to meet the environmental, size, power, maintenance-free operation and weight requirements of
military and commercial space applications, and at a cost that permits wide deployment of the capability. The second version
of the MROC module consists of a ferroelectric liquid crystal (PLC) device in the input plane for high light efficiency and
incorporates a reflective magneto optic spatial light modulator (RMOSLMTM) device in the filter plane for very high speed
operation. MROC II breadboard tests demonstrated excellent correlation peaks, i.e. excellent discrimination (SNR>25), at
pattern matching rates of 1920 per second on images of military vehicles.
The recognition system rapid application prototyping tool (RSRAPT) was developed to evaluate various potential configurations of miniature ruggedized optical correlator (MROC) modules and to rapidly assess the feasibility of their use within systems such as missile seekers. RSRAPT is a simulation environment for rapidly prototyping, developing, and evaluating recognition systems that incorporate MROC technology. It is designed to interface to OLE compliant Windows applications using standard OLE interfaces. The system consists of nine key functional elements: sensor, detection, segmentation, pre-processor, filter selection, correlator, post-processor, identifier, and controller. The RSRAPT is a collection of object oriented server components, a client user interface and a recognitions system image and image sensor database. The server components are implemented to encapsulate processes that are typical to any optical-correlator based pattern recognition system. All the servers are implemented as Microsoft component object model objects. In addition to the system servers there are two key 'helper servers.' The first is the image server, which encapsulates all 'images'. This includes gray scale images and even complex images. The other supporting server is the filter generation server. This server trains the system on user data by calculating filters for user selected image types. The system hosts a library of standard image processing routines such as convolution, edge operators, clustering algorithms, median filtering, morphological operators such as erosion and dilation, connected components, region growing, and adaptive thresholding. In this paper we describe the simulator and show sample results from diverse applications.
The military has a requirement for small, low-power, low- cost pattern recognition systems that are capable of locating and identifying high value hostile targets. Miniature optical correlators can perform 2D pattern recognition at greater rates than digital platforms of equivalent size, power and/or weight. The patented miniature ruggedized optical correlator (MROC) can be built to meet the environmental, size, power, and weight requirements of military and rugged commercial applications, and at a cost that will permit wide deployment of the capability. The second version of the MROC correlator consists of a ferroelectric liquid crystal device in the input plane for high light efficiency and incorporates a reflective magneto optic spatial light modulator device in the filter pane for very high speed operation. The correlator has a volume of approximately 20 cubic inches. The MROC module, which includes all drive electronics and interfaces, is a 6U VME module that occupies 5 VME card slots. In this paper we will provide a brief review of the MROC construction and present sample results obtained from the MROC II breadboard. Initial tests demonstrated very high correlation levels, i.e. excellent discrimination, at pattern matching rates of 1920 per second on visible and simulated LADAR images of military vehicles and digital images of fingerprints.
Automatic fingerprint classification, automatic fingerprint identification, and latent or partial fingerprint matching each continue to present significant computational challenges despite the rapid improvements in the speed of digital computers. The new emerging technology of optical processing promises to alleviate this computational roadblock and bring fingerprint classification and identification to the everyday user. Several areas of research utilizing optical processors for fingerprints are currently being conducted. In this paper we will discuss the se of optical correlation for whole and partial fingerprint matching with known fingerprints from a preselected set of candidates. Initial optical correlator simulations and breadboard tests indicate that the hybrid processor provides significant capability increases in speed and throughput over a pure digital system. Results showing good correlation of matches and good discrimination from non-matches are presented. Additionally, correlation of partial prints is demonstrated with a strong degree of discrimination.
The reflective magneto-optic spatial light modulator (R-MOSLM) device was developed over the past few years by a group of Litton divisions and Carnegie Mellon University. The device has been fabricated into 128 X 128 arrays on 24 micron pitch. The performance of individual devices has been reported in previous years. This paper describes the use of the device in an optical correlator. Litton has been developing the miniature ruggedized optical correlator (MROC) for use in a variety of pattern recognition applications. This paper discusses the packaging of the device, the drive electronics, and the interfacing of the device to the MROC unit.
This paper is a report on the characteristics of a new high resolution, high frame rate, reflected R-MOSLM. This effort is aimed at the production of Miniature Ruggedized Optical Correlators for Optical Pattern Recognition. Pixel size is under one mil center to center, one-third the dimension of present transmission mode devices, thereby reducing the optical path length by an order of magnitude. This development includes optimization of the optical and functional characteristics of the MOSLM for Mil Spec Systems.
The reflected mode magneto-optic spatial light modulator (R-MOSLM) has been developed over the past couple of years. This development has led to a device that has state-of-the-art performance and is producible. This SLM device is truly compatible with semiconductor manufacturing techniques and is now being fabricated in a production environment. Performance details of individual devices is presented elsewhere. However, in this paper we discuss the measured parameters of multiple devices for statistics, discuss yield and packaging, and describe the impact of its manufacturability on cost. The system description of the correlator system using these devices is reported in a companion paper.
An electro-optic processor (EOP) incorporating a miniature ruggedized optical correlator (MROC) has been fabricated for use on a remotely piloted vehicle (RPV). The EOP consists of a single-board computer for system control, a MaxVideo 20 card for interfacing to the sensor and performing image processing functions, and an MROC module. The MROC and associated electronics (SLM drive electronics, CCD readout electronics, laser controller, preprocessor, and controller) are configured in a chassis that is placed into an RPV with a visible camera for signal input and a telemetry system for output of the optical processor to the ground.
This paper is a report on the advanced development and characteristics of a new high resolution, high frame rate, reflected R-MOSLM. This effort is aimed at the production of miniature ruggedized optical correlators (MROC) for optical pattern recognition. Pixel size is under one mil center to center, one third the dimension of present transmission mode devices, thereby reducing the optical path length by an order of magnitude. This development includes optimization of the optical and functional characteristics of the MOSLM for Mil Spec Systems. The device research and process development has been performed at Carnegie Mellon University NSF Data Storage System Center under contract from Litton Data Systems. The Litton Electron Device Division is transitioning the device to production. The MROC system description is described in companion paper (1959-09).
The development of an optical correlator system and flight tests to be conducted from a remotely piloted vehicle (RPV) are described. The optical processor is based on laser gyroscope construction techniques and relies on 128 X 128 reflective-mode magneto-optic spatial light modulators for both the input image and spatial filter insertion. The input image is obtained from a visible camera in the nose of the RPV. The processing system incorporates Kalman's invariant filters. The output of the correlator is through a 128 X 128 high speed CCD camera. The correlator system also includes image processing and all electronic drivers. The optical package occupies a volume less than 25 in<SUP>3</SUP> while the whole processor package is less than 1 ft<SUP>3</SUP> and weighs less than 40 lbs, and is ruggedized for temperature, shock, and vibration. The RPV, Eglin Air Force Base test range facilities, tower tests, telemetry, and training set acquisition are discussed.
In this paper we discuss the development of a new computer tool, InfraRed Design Optimization Code (IRDOC), for the design of infrared sensors. IRDOC consists of a robust model for IR sensors and a powerful optimizing algorithm. The model predicts the signal-to- noise (including clutter) ratio (SNR) with filtering. The model combines important features of spatial-frequency-domain analysis and time-domain analysis. The program inputs a number of system parameters, several constraints, and the allowed ranges for the sensor variables from the user. IRDOC determines the set of variables within their allowed ranges and subject to the constraints, that maximizes the signal-to-noise ratio. A generic example of a point detection sensor and an example of an imaging sensor using scanning sensors are optimized for a variety of background conditions.
Focal plane applications demand a high degree of linearity in the detector response function (voltage out vs. photon flux in). For calibrating radiometric data and for correcting channel-to- channel nonuniformities in nonradiometric data, the response function of the focal plane must be correctable to within 0.1%. This specification requires either significant improvement in focal plane technologies or in methods to correct for it. Two-point calibration is often used to correct for nonuniformities across a focal plane array (FPA), as well as for calibration. Because the input-output curves of FPA channels are nonlinear, two-point calibration produces a systematic calibration error as a function of flux, and the channel-to-channel variations of this calibration error leave a significant post-correction nonuniformity. A simple physical model of the detector nonlinearity is used to illustrate these points. The sensor degradation due to nonlinearities is predicted from the pixel-to-pixel variations in nonlinearity after two-point correction. Variations of only 0.2% can result in significant degradations of the array D<SUP>*</SUP>.
A critical component of IR sensors is the infrared detector. In order to predict sensor performance, a step-function optical response is typically assumed. This model is then used to predict overall sensor performance and to optimize signal processing algorithms. However, pixels rarely exhibit this ideal behavior. Two deviations in ideal response are described: a pixel center region degradation and an exponentially decaying region on the outside of the pixel corresponding to carrier diffusion. The corresponding MTFs are calculated and the effect on matched filters and sensor performance is modeled.
Infrared sensors are being incorporated in more systems and are often placed close to radar systems. The IR sensor is thus subjected to various microwave levels from the sidelobes or reflections of the radar pulses. In this paper we address the effect of microwaves on the performance of mercury-cadmium-telluride longwave photodiodes. We examine the effects of microwaves entering directly through the optical window (front-door mechanism) and entering along wires connected to the dewar (back-door mechanism). The diode noise voltage was measured before, during, and after the microwaves pulses by transimpedance amplification. The diode noise characteristics were shown to respond very rapidly to the microwave pulse. A linear relationship between detector noise and microwave power was observed. A strong dependence of noise on microwave frequency was observed and attributed to the resonances of the dewar design.
Two-point calibration is often used to correct for nonuniformities across focal plane arrays (FPAs), as well as for calibration. Because the input-output curves of FPA channels are nonlinear, two-point calibration produces a systematic calibration error as a function of flux, and the channel-to-channel variations of this calibration error leave a significant post-correction nonuniformity. A physical model of detector nonlinearity is used to illustrate these points. A simple formula is proposed, which fits the input-output curves much better than the straight line used by two-point calibration, and is almost as easy to use. When the new formula is used, the system's performance is no longer sensitive to the choice of calibration temperatures, and no longer degrades rapidly outside the calibration interval.