Many applications, including military, medical, and security, have a requirement for small, low-power, low-cost pattern recognition systems that are capable of locating and identifying targets or anomalies. Optical correlators can perform twodimensional pattern recognition at greater rates than digital platforms of equivalent size, power and/or weight. The patented Miniature Ruggedized Optical Correlator (MROCTM) has been built to meet the environmental, size, power, and weight requirements of rugged military and commercial applications, and at a cost that will permit wide deployment of the capability. The third generation of the optical correlator (MROC III) includes a ferro-electric liquid crystal (FLC) spatial light modulator (SLM) device in both the input plane and the filter plane, and an improved block design that results in both high light efficiency and very fast operational speed. This new correlator design has a reduced volume of approximately 260 cubic centimeters. The MROC III module, which includes all drive electronics and interfaces developed for the MROC II, is a 6U VME module that now occupies only four VME card slots compared to the 5 slots required for MROC I and MROC II. In this paper we will provide a brief review of the MROC architecture and present sample results for the MROC III. Our initial tests demonstrated very high correlation levels, i.e. excellent discrimination (SNR-'50), at pattern matching rates of 1920 correlations per second (cps).

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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, pre-processor, 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.

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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 recognition 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 (COM) objects (OLE Automation Servers). 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 (from 1 to 32 bits) and even complex (imaginary) images (used in the correlator filter plane). The other supporting server is the Filter Generation Server. This server irains 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 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 consiruction techniques and relies on 128x128 reflective-mode magnetooptic 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 will incorporate Kallman's invariant filters. The output of the correlator is through a 128x128 high speed CCD camera. The correlator system also includes image processing and all electronic drivers. The optical package occupies a volume less than 25 in3 while the whole processor package is less than 1 ft3 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.

The Optical Processor Enhanced Ladar (OPEL) program is designed to evaluate the capabilities of a seeker obtained by integrating two state-of-the-art technologies, laser radar, or ladar, and optical correlation. The program is a thirty-two month effort to build, optimize, and test a breadboard seeker system (the OPEL System) that incorporates these two promising technologies. Laser radars produce both range and intensity image information. Use ofthis information in an optical correlator is described. A correlator with binary phase input and ternary amplitude and phase filter capability is assumed. Laser radar imagery was collected on five targets over 360 degrees ofazimuth from 3 elevation angles. This imagery was then processed to provide training sets in preparation for filter construction. This paper reviews the ladar and optical correlator technologies used, outlines the OPEL program, and describes the OPEL system.

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