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At least 127 records · Page 7

Algorithms For Detection Of Correlation Spots

Three algorithms provide for improved postprocessing of outputs of optical correlators based on binary phase-only filters. Detect correlation spots. Function in presence of noise and executed rapidly. First algorithm starts processing correlation-image data while data fed out of video camera and digitized for subsequent analysis. Second involves convolution of correlation image with small-window two-dimensional impulse-response function followed by threshold operation in which negative values of convolution integral set to zero. Third affects generation as well as postprocessing of correlation image.

Scholl, Marija S.↗

Pipelined digital SAR azimuth correlator using hybrid FFT-transversal filter

A synthetic aperture radar system (SAR) having a range correlator is provided with a hybrid azimuth correlator which utilizes a block-pipe-lined fast Fourier transform (FFT). The correlator has a predetermined FFT transform size with delay elements for delaying SAR range correlated data so as to embed in the Fourier transform operation a corner-turning function as the range correlated SAR data is converted from the time domain to a frequency domain. The azimuth correlator is comprised of a transversal filter to receive the SAR data in the frequency domain, a generator for range migration compensation and azimuth reference functions, and an azimuth reference multiplier for correlation of the SAR data. Following the transversal filter is a block-pipelined inverse FFT used to restore azimuth correlated data in the frequency domain to the time domain for imaging.

Wu, C.↗

Optimization of Adaboost Algorithm for Sonar Target Detection in a Multi-Stage ATR System

JPL has developed a multi-stage Automated Target Recognition (ATR) system to locate objects in images. First, input images are preprocessed and sent to a Grayscale Optical Correlator (GOC) filter to identify possible regions-of-interest (ROIs). Second, feature extraction operations are performed using Texton filters and Principal Component Analysis (PCA). Finally, the features are fed to a classifier, to identify ROIs that contain the targets. Previous work used the Feed-forward Back-propagation Neural Network for classification. In this project we investigate a version of Adaboost as a classifier for comparison. The version we used is known as GentleBoost. We used the boosted decision tree as the weak classifier. We have tested our ATR system against real-world sonar images using the Adaboost approach. Results indicate an improvement in performance over a single Neural Network design.

Adaboost↗

Optimal filtering in the presence of unmodeled time correlated driving disturbances.

In many realistic data filtering problems, the cross correlation of the state estimation error and the state forcing function is unknown due to the poor knowledge of the time history of the forcing function. In this paper, the conservative and minimal approximation to the cross correlation terms is presented. It requires only the knowledge of the estimation error covariance and the forcing function covariance, with the choice of an associated free parameter left to the user. If the estimation error covariance and/or the forcing function covariance are bounded from above but not known exactly, the cross correlation approximation using those upper bounds remains conservative. This cross correlation approximation leads to a conservative approximation to the estimation error covariance matrix differential equation between measurement times. The free parameter is determined as the analytic solution to an associated optimal control problem. The procedure is expanded to include discrete linear measurement incorporation.

Fraser, D. C.↗

Real-time optical correlator using computer-generated holographic filter on a liquid crystal light valve

Limitations associated with the binary phase-only filter often used in optical correlators are presently circumvented in the writing of complex-valued data on a gray-scale spatial light modulator through the use of a computer-generated hologram (CGH) algorithm. The CGH encodes complex-valued data into nonnegative real CGH data in such a way that it may be encoded in any of the available gray-scale spatial light modulators. A CdS liquid-crystal light valve is used for the complex-valued CGH encoding; computer simulations and experimental results are compared, and the use of such a CGH filter as the synapse hologram in a holographic optical neural net is discussed.

Chao, Tien-Hsin↗

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM for digital-to-optical correlation-filter data conversion, and a charge-coupled device (CCD) for detection of correlation peaks. In operation, the input scene grabbed by a video sensor is streamed into the input SLM. Precomputed correlation-filter data files representative of known targets are then downloaded and sequenced into the filter SLM at a rate of 1,000 Hz. When there occurs a match between the input target data and one of the known-target data files, the CCD detects a correlation peak at the location of the target. Distortion- invariant correlation filters from a bank of such filters are then sequenced through the optical correlator for each input frame. The net result is the rapid preliminary recognition of one or a few targets.

Moynihan, Philip↗

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Downie, John D.↗

Extension of synthetic estimation filters for relative position measurements

The construction of synthetic estimation filters (SEF) for out-of-plane rotation is reported. When images corresponding to rotations between the angles which were used to construct the estimator were input to the simulator, the yaw measurement accuracy was a little better than one-half of a degree over the five degree range. If individual phase-only filters were used and the only criteria for yaw angle was 'best correlation', 11 filter would be required for the same range and accuracy. The technique proposed here is invariant to translation.

Monroe, Stanley E., Jr.↗

Joint transform correlation with the synthetic estimation filter

The synthetic estimation filter (SEF) combines a set of input images into a much smaller set of filters. Those input images correspond to views of a known object taken with a variety of values of the pose parameter to be estimated. The response of the filter to variations in the pose parameter is tailored so that estimation can be done to a precision considerably finer than the intervals between filters in the pose space. The technique is extended to the joint transform correlator; as a reference, the composite image from which the SEF is conventionally calculated is used. Precautions are necessary for practical reasons. For example, the SEF algorithm may call for negative values in the image, an unrealizable condition with amplitude encoding, whereas with phase-mostly filtering in the SEF, negative image values are easily accommodated.

Monroe, Stanley E., Jr.↗

Time-correlated gust loads using matched filter theory and random process theory - A new way of looking at things

This paper describes and illustrates two ways of performing time-correlated gust-load calculations. The first is based on Matched Filter Theory; the second on Random Process Theory. Both approaches yield theoretically identical results and represent novel applications of the theories, are computationally fast, and may be applied to other dynamic-response problems. A theoretical development and example calculations using both Matched Filter Theory and Random Process Theory approaches are presented.

Pototzky, Anthony S.↗

Digital Signal Processing of Radar Pulse Echoes

Modern high-performance radar systems are employing ever-more Digital Signal Processing (DSP), replacing ever-more formerly analog components. Precisely predicting the performance of digital filters and correlators requires an awareness of some of the finer points and characteristics of digital filters. We examine a representative radar receiver DSP chain that is processing a Linear Frequency Modulated (LFM) chirp.

47 OTHER INSTRUMENTATION↗

Signal sequence detection given noisy, common background image sets.

The optimum processing (likelihood functional) is found for a set of M images, each the sum of a member of a signal sequence due to an object to be detected and its parameters estimated, a sample function of a noise field, and a sample function of a common background field. The noise fields are independent, zero mean, white Gaussian fields, all independent of the background field. The latter is assumed to be either (1) completely unknown or of known mean and covariance functions with (2) a certain fluctuation property or (3) Gaussian. Three equivalent forms of the optimum processing are found: (1) a summation of generalized matched filterings of the images, (2) a summation of matched filtering of certain generalized differences of the images, and (3) a summation of 'estimator-correlator' type filterings. The detection performance and optimum signal/image selection under the Neyman-Pearson criterion is given, and is shown that optimum processor and signal design can completely eliminate any effect of the background on detectability.

Harger, R. O.↗

Review of image correlation systems - Hybrid and optical

The operating principles, design, and development histories of three image correlation systems, the Portable Correlator Unit (PCU), the Miniature Correlator Unit (MCU), and the Coherence Interferometer (CI) are reviewed. The PCU and MCU are compact versions of the classical Vander Lught filter optical correlator, essentially parallel optical processors by light valve; the CI is a white-light correlator which functions entirely by interfering light waves, with electronic detection only at the final output, and thus represents a parallel optical processor by rotational-shear interferometer. Details of the design and construction are discussed and illustrated with drawings and photographs. Also considered are applications of the MCU to NASA tasks such as rendezvous and docking on the Mars Rover and Sample Return mission, autonomous robotic exploration of planetary surfaces, and compression and pattern-recognition of remote-sensing data.

Breckinridge, James B.↗

Miniaturized optical correlator

A robust optical correlator that is a miniaturized version of the classic Vander-Lugt correlator is developed. The correlator consists of a simple diode laser for illumination and a CMOS photodetector to detect the correlation peak. A set of roof prisms is configured to fold the light path into a compact design. A holographic plate is used for storing the matched filter. This correlator is particularly applicable to docking autonomous vehicles near a predesignated landing mark. This miniature optical correlator is described in terms of its functional performance.

Scholl, M. S.↗

Remote sensing of the atmosphere of Mars using infrared pressure modulation and filter radiometry

The study of the atmosphere and climate of Mars will soon be advanced considerably by the Mars Observer mission. This paper describes the atmospheric sounder for this mission and how it will measure key Martian atmospheric parameters using IR gas correlation and filter radiometry. The instrument now under development will provide high-resolution vertical profiles of atmospheric temperature, pressure, water vapor, dust, and clouds using limb sounding techniques as well as nadir observations of surface thermal properties and polar radiative balance.

Mccleese, D. J.↗

Program Computes SLM Inputs To Implement Optimal Filters

Minimum Euclidean Distance Optimal Filter (MEDOF) program generates filters for use in optical correlators. Analytically optimizes filters on arbitrary spatial light modulators (SLMs) of such types as coupled, binary, fully complex, and fractional-2pi-phase. Written in C language.

Barton, R. Shane↗

Image processing via VLSI: A concept paper

Implementing specific image processing algorithms via very large scale integrated systems offers a potent solution to the problem of handling high data rates. Two algorithms stand out as being particularly critical -- geometric map transformation and filtering or correlation. These two functions form the basis for data calibration, registration and mosaicking. VLSI presents itself as an inexpensive ancillary function to be added to almost any general purpose computer and if the geometry and filter algorithms are implemented in VLSI, the processing rate bottleneck would be significantly relieved. A set of image processing functions that limit present systems to deal with future throughput needs, translates these functions to algorithms, implements via VLSI technology and interfaces the hardware to a general purpose digital computer is developed.

Nathan, R.↗

Optimal realizable filters and the minimum Euclidean distance principle

Minimizing a Euclidean distance in the complex plane optimizes a wide class of correlation metrics for filters implemented on realistic devices. The algorithm searches over no more than two real scalars (gain and phase). It unifies a variety of previous solutions for special cases (e.g., a maximum signal-to-noise ratio with colored noise and a real filter and a maximum correlation intensity with no noise and a coupled filter). It extends optimal partial information filter theory to arbitrary spatial light modulators (fully complex, coupled, discrete, finite contrast ratio, and so forth), additive input noise (white or colored), spatially nonuniform filter modulators, and additive correlation detection noise (including signal dependent noise).

Juday, Richard D.↗