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检索条件"主题词=Detection and tracking algorithms"

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AUTOMATED ADAPTATION FOR ATR algorithms

AUTOMATED ADAPTATION FOR ATR ALGORITHMS

引用

Conference on detection Technologies for Mines and Minelike Targets

作者： SYMOSEK, PF BAZAKOS, ME HONEYWELL TECHNOL CTR MINNEAPOLISMN 55418

ISBN: (纸本)0819418528

For an automatic target recognition (ATR) technology contract, sponsored by the US Marine Corps Systems Command, and by Coastal Systems Station, Honeywell designed, mapped to Khoros, and evaluated state-of-the-art algorithms for target discrimination from an airborne platform. Honeywell's baseline approach to improve traditional algorithm robustness is to use a functional maximization approach for representations of algorithm performance as a function of image metrics and algorithm parameters. Revised ATR parameter values are established by a hillclimbing algorithm that revises the ATR algorithm parameter values in the direction of the largest gradient of the function, thus attaining improved performance for a greater variety of scenarios than those for which the system was trained. The baseline ATR algorithms implemented for this program are designed to effectively exploit spectral features to enhance target cueing reliability. An innovative approach for the mapping of three of the individual waveband images from an array of multispectral images into a feature map which obtains high target versus background contrast is discussed. Experimental results are shown for flight test imagery.

关键词： detection and tracking algorithms Automatic target recognition Land mines Mining Algorithm development Performance modeling Multispectral imaging Image processing Feature extraction Reliability

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NEURAL NETWORK AND CLASSICAL LEAST SQUARES METHODS FOR QUANTITATIVE ANALYSIS IN REMOTE SENSING FTIR SYSTEMS

NEURAL NETWORK AND CLASSICAL LEAST SQUARES METHODS FOR QUANT...

引用

Conference on Optical Instrumentation for Gas Emissions Monitoring and Atmospheric Measurements

作者： WANG, CD WALTER, WT KAGANN, RH AIL SYST INC DEER PKNY 11729

ISBN: (纸本)0819417122

Remote monitoring of molecular species in the atmosphere is accomplished using a Fourier transform infrared (FTIR) spectrometer. Advanced processing algorithms utilized by AIL Systems include the classical least squares (CLS) technique as well as a more recently developed approach which combines digital finite impulse response filtering, adaptive sampling, and artificial neural networks (ANN) to improve detection sensitivity and estimation accuracy. This paper presents a comparison between the CLS and the ANN methods in estimating concentrations of multicomponent mixtures. detection improvement of ANN over CLS has been demonstrated by examining SF₆ in a stack plume and toluene in a laboratory experiment.

关键词： Digital filtering Signal processing Filtering (signal processing) FT-IR spectroscopy Neural networks Optical filters Bandpass filters detection and tracking algorithms Algorithm development Finite impulse response filters

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MINE TARGET detection USING PRINCIPAL COMPONENT AND NEURAL NETWORKS METHOD

MINE TARGET DETECTION USING PRINCIPAL COMPONENT AND NEURAL N...

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Conference on detection Technologies for Mines and Minelike Targets

作者： AZIMISADJADI, MR XI, M COLORADO STATE UNIV DEPT ELECT ENGNFT COLLINSCO 80523

ISBN: (纸本)0819418528

This paper proposes a new system for real-time detection and classification of arbitrarily scattered surface-laid mines. The system consists of six channels which use various neural network structures for feature extraction, detection and classification of targets in six different optical bands ranging from near UV to near IR. A single-layer auto-associative neural network trained by the recursive least square (RLS) learning rule was employed in each channel to perform target feature extraction. The detection/classification based upon the extracted features was accomplished by a three-layer back-propagation neural network with 11-25-10-1 architecture. The outputs of the detector/classifier network in all the channels are fused together in a final decision making system. Simulations were performed on real data for six bands. Forty-eight different images were used in order to account for the variations in size, shape, and contrast of the targets and also the signal-to-clutter ratio. The overall results for the combined system showed a detection rate of approximately 97%, with less than 3% false alarm rate.

关键词： Target detection Neural networks Neurons Feature extraction Sensors Land mines Image fusion Image processing Channel projecting optics detection and tracking algorithms

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FIELD TEST ON SIGNAL PROCESSING METHODS FOR PASSIVE FTIR REMOTE SENSING MEASUREMENTS

FIELD TEST ON SIGNAL PROCESSING METHODS FOR PASSIVE FTIR REM...

引用

Conference on Optical Instrumentation for Gas Emissions Monitoring and Atmospheric Measurements

作者： KAGANN, RH WALTER, WT WANG, CD KOTTER, DK MCMANUS, GJ AIL SYST INC DEER PKNY 11729

Passive FTIR remote sensing measurements were made to test real-time detection of an SF6 seeded stack plume using a probabilistic neural network (PNN) algorithm. The plume concentrations were determined using a classi... 详细信息

ISBN: (纸本)0819417122

Passive FTIR remote sensing measurements were made to test real-time detection of an SF₆ seeded stack plume using a probabilistic neural network (PNN) algorithm. The plume concentrations were determined using a classical least squares (CLS) algorithm and compared well with calculations using measured flow rates for the SF₆ and the waste stream.

关键词： FT-IR spectroscopy Temperature metrology Remote sensing detection and tracking algorithms Absorbance Calibration Neural networks Algorithm development Sensors Signal processing

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Adaptive filtering approach to spectral estimation and SAR imaging 2

Adaptive filtering approach to spectral estimation and SAR i...

引用

Conference on algorithms for Synthetic Aperture Radar Imagery II

作者： LI, J STOICA, P UNIV FLORIDA DEPT ELECT ENGNGAINESVILLEFL 32611

ISBN: (纸本)0819418404

We present an adaptive FIR filtering approach, which is referred to as the APES (amplitude and phase estimation of a sinusoid), for complex spectral estimation. We compare the APES algorithm with other FIR filtering approaches including the Welch and Capon methods. We also describe how to apply the FIR filtering approaches to target range signature estimation and synthetic aperture radar (SAR) imaging. We show via both numerical and experimental examples that the adaptive FIR filtering approaches such as Capon and APES can yield more accurate spectral estimates with much lower sidelobes and narrower spectral peaks than the FFT method, which is also a special case of the FIR filtering approaches. We show that although the APES algorithnm yields somewhat wider spectral peaks than the Capon method, the former gives more accurate overall spectral estimates and SAR images that the latter and the FFT method.

关键词： Optical filters Finite impulse response filters Synthetic aperture radar Digital filtering Fourier transforms Image filtering detection and tracking algorithms Algorithm development Radar imaging Statistical analysis

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Comparison of registration error correction techniques for air surveillance radar network

Comparison of registration error correction techniques for a...

引用

Signal and Data Processing of Small Targets 1995 Conference

作者： LEUNG, H BLANCHETTE, M GAULT, K DEF RES ESTAB OTTAWA SURFACE RADAR SECTOTTAWAONCANADA

ISBN: (纸本)0819419206

This paper considers the effectiveness of different registration algorithms in an air surveillance radar tracking environment. The evaluation is based on real data collected from an operating radar network in Canada. The existing real time quality control (RTQC) routine in the network requires targets to be on both sides of the line between the radars; this type of distribution is usually not available in the area with low air traffic density. The least squares (LS) algorithm which solves for the least squares biases is an alternative to handle this problem. Two algorithms that are considered as being more rigorous in the literature are the maximum likelihood (ML) and generalized least squares (GLS). The ML algorithm is a solution of the registration problem that uses a calculated covariance matrix of the measurement noise. The GLS algorithm is a variation of the ML algorithm where only the variances of the measurement noise are used. Based on the real data analysis, the track separation after registration are identical for the LS and ML algorithm, with the GLS being close most of the time. The result of the RTQC algorithm is close when the radar returns are split evenly between the two sides of the line between the radars. If the data in unevenly distributed, then the RTQC algorithm provides less accurate estimates. Comparing their computational complexities, the RTQC and LS algorithm are very efficient while the ML and GLS algorithm are about hundred times slower in terms of computational speed.

关键词： Radar Image registration Surveillance detection and tracking algorithms Sensors Control systems Data analysis Distance measurement Computing systems Environmental monitoring

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MINE DISCRIMINATION USING MULTISPECTRAL IMAGERY WITH FEEDFORWARD NEURAL NETWORKS

MINE DISCRIMINATION USING MULTISPECTRAL IMAGERY WITH FEEDFOR...

引用

Conference on detection Technologies for Mines and Minelike Targets

作者： DAUD, T DUONG, T LANGENBACHER, H TSU, H THAKOOR, A CALTECH JET PROP LABCTR SPACE MICROELECTR TECHNOLPASADENACA 91109

ISBN: (纸本)0819418528

As a precursor to hardware implementation, we have performed mine detection functions in simulation on a polarimetric hyperspectral imaging (PHI) dataset collected by using a technique of acousto-optic tunable filter (AOTF) camera. In principle, PHI data of an image containing objects of interest in a cluttered background provide significant information about the objects, including their relative sizes, shapes, orientation, and other characteristics such as light reflectance and polarization signatures based on their material properties. The present study was, however, limited only to the direct spectral data for the object of interest. A feedforward artifical neural network (ANN) architecture was programmed to recognize predefined spectral 'templates' by using a well-known, hardware implementable inner-product matching scheme. This scheme is particulartly suited to the problem of spectral discrimination where the spectra to be examined or the objects to be discriminated are uncorrelated, as in the present case. In this paper, we describe the ANN architecture and discuss its hardware implementation issues. In addition, we provide the results of our simulation study performed along with suitable preprocessing steps with various window sizes from 1 X 1 to 50 X 50 pixels, leading to an unambiguous detection of the position of mines in test runs without false alarms.

关键词： Neural networks Land mines Aerospace engineering Curium detection and tracking algorithms Evolutionary algorithms Multispectral imaging Tunable filters Computer simulations Hyperspectral imaging

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IMAGE SCREENING USING SPATIAL FILTERS BASED ON LINEAR TRANSFORMATION FOR IMAGE RECOGNITION

IMAGE SCREENING USING SPATIAL FILTERS BASED ON LINEAR TRANSF...

引用

3rd Annual SPIE Conference on Machine Vision Applications in Industrial Inspection

作者： ARIMURA, K HAGITA, N NIPPON TELEGRAPH & TEL PUBL CORP BASIC RES LABS ATSUGI KANAGAWA 14301 JAPAN

ISBN: (纸本)081941770X

Statistical image recognition methods based on linear transformation require a lot of calculation of correlation between subimages and reference patterns of the specified objects to be detected. Image screening provides an effective preprocessing method for lowering the calculation load and improving recognition accuracy. It selects candidate subimages that are similar to the detecting objects in images and rejects the remainders using spatial filters which are based on linear transformation. We have already investigated the spatial filters that are based on 2D projection pursuit (PP). PP requires more heavy calculation load than the principal components analysis (PCA). We, therefore, compare spatial filters based on two kinds of linear transformation algorithms, the PP and PCA, in terms of recognition accuracy and efficiency. Experiments are made for two object detection tasks: eye- and mouth-area detection in face images and text-area detection in document images. The results show that PCA-based image screening is superior to PP-based one for the eye- and mouth-area detection. PCA also achieves higher recognition rate (75%) than PP for the eye- and mouth-area detection, while PP offers equal performance in text-area detection. The results suggest that PCA is totally superior to PP in image screening.

关键词： Principal component analysis Spatial filters detection and tracking algorithms Tolerancing Image filtering Eye Facial recognition systems Image processing Mouth Error analysis

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APPLICATION OF SYNTHETIC IMAGERY TO TARGET detection ALGORITHM RESEARCH

APPLICATION OF SYNTHETIC IMAGERY TO TARGET DETECTION ALGORIT...

引用

Conference on detection Technologies for Mines and Minelike Targets

作者： BLUME, B WILLIAMS, B NICHOLS RES CORP PANAMA CITY BEACHFL 32417

ISBN: (纸本)0819418528

A multispectral modeling methodology has been developed by Nichols Research Corporation (NRC) in support of the Joint Mine detection Technology Program at Coastal Systems Station, Panama City, FL. The modeling technique is an extension of NRC's Minefield Image Synthesis Tool. Synthetic imagery generated using this methodology has been compared to measured imagery with excellent results. Multispectral images from an intensified multispectral camera being flown over a minefield have been synthetically generated. This sequence of images was processed by NRC's baseline mine detection algorithm. The results were compared to images generated during a flight test. The conclusion is that the model can predict the automatic target recognition (ATR) algorithm's performance. This paper describes the minefield signature modeling methodology, presents a case study of the comparison of a synthetic scene and a measured scene, and indicates the lessons learned about the phenomenological causes of the mine and background signatures and their effects on a particular class of mine detection algorithms.

关键词： detection and tracking algorithms Reflectivity Land mines Sensors Mining Cameras Raster graphics Fractal analysis Image processing Image sensors

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Parallel filter structures for RLS-type blind equalization algorithms

Parallel filter structures for RLS-type blind equalization a...

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Conference on Advanced Signal Processing algorithms

作者： MOONEN, M DEPRETTERE, E KATHOLIEKE UNIV LEUVEN ESATB-3001 HEVERLEEBELGIUM

ISBN: (纸本)0819419222

It is shown that several RLS-type blind equalization algorithms, e.g., decision-directed schemes as well as 'orthogonalized' constant modulus algorithms, possess a common algorithmic structure and are therefore straightforwardly implemented on an earlier developed triangular array (filter structure) for recursive least squares estimation with inverse updating. While the computational complexity for such algorithms is O(N²), where N is the problem size, the throughput rate for the array implementation is O(1), i.e., independent of the problem size. Such a throughput rate cannot be achieved with standard (Gentleman-Kung- type) RLS/QR-updating arrays because of feedback loops in the computational schemes.

关键词： Algorithm development Evolutionary algorithms Digital filtering Chemical elements Feedback loops detection and tracking algorithms Data transmission Receivers Data communications Electrical engineering

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