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检索条件"任意字段=13th Conference on Signal and Data Processing of Small Targets"

共 447 条记录，以下是31-40 订阅

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small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences

Small moving object detection using adaptive subband decompo...

引用

13th conference on signal and data processing of small targets

作者： Bagci, AM Yardimci, Y Çetin, AE Bilkent Univ Dept Elect & Elect Engn Ankara Turkey

ISBN: (纸本)0819441872

In this paper, a small moving object method detection method in video sequences is described. In the first step, the camera motion is eliminated using motion compensation. An adaptive subband decomposition structure is then used to analyze the motion compensated image. In the highband subimages moving objects appear as outliers and they are detected using a statistical detection test based on lower order statistics. It turns out that in general, the distribution of the residual error image pixels is almost Gaussian. On the other hand, the distribution of the pixels in the residual image deviates from Gaussianity in the existence of outliers. By detecting the regions containing outliers the boundaries of the moving objects are estimated. Simulation examples are presented.

关键词： moving object detection adaptive subband decomposition wavelet transform lower order statistics

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Reducing MHT computational requirements through use of Cheap JPDA methods

Reducing MHT computational requirements through use of Cheap...

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13th conference on signal and data processing of small targets

作者： Quevedo, H Blackman, S Nichols, T Dempster, R Wenski, R Raytheon Syst Co El Segundo CA 90245 USA

ISBN: (纸本)0819441872

Hypothesis formation is a major computational burden for any multiple hypotheses tracking (MHT) method. In particular, a track-oriented MHT method defines compatible tracks to be tracks not sharing common observations and then re-forms hypotheses from compatible tracks after each new scan of data is received. the Cheap Joint Probabilistic data Association (CJPDA) method provides an efficient means for computing approximate hypothesis probabilities. this paper presents a method for extending CJPDA calculations in order to eliminate low probability track branches in a track-oriented MHT method. the method is tested using IRST data. this approach reduces the number of tracks in a cluster and the resultant computations required for hypothesis formation. It is also suggested that the use of CJPDA methods can reduce assignment matrix sizes and resultant computations for the hypothesis-oriented (Reid's algorithm) MHT implementation.

关键词： multi target tracking (MTT) multiple hypothesis tracker (MHT) Cheap Joint Probabilistic data Association (CJPDA) infrared search and track (IRST)

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the method of range profile for step frequency MMW radar based on wavelet transform power spectrum estimator

The method of range profile for step frequency MMW radar bas...

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13th conference on signal and data processing of small targets

作者： Li, YH Gao, DT Shen, QH Li, XG Nanjing Univ Dept Elect Sci & Technol Nanjing 210093 Peoples R China

ISBN: (纸本)0819441872

the method of range profile for step frequency MMW radar targets based on wavelet transform power spectrum estimator is studied. We show how the Fourier power spectrum can be detected by using the wavelet function coefficients (WFC) of the DWT. this method can successfully measure the power spectrum in samples for which traditional methods often fail because the sample are finite sized, have a complex geometry, or are varyingly sampled. We demonstrate that the spectrum features, such as the power law index, the magnitude, and the typical scales can be determined by the DWT reconstructed spectrum. We apply this method to the practical step frequency MMW radar target echo signals, and on the condition of the same sampling frequency and sampling data length, it can achieve one dimensional range profile with profile's resolution superior to FFT's, so the one dimensional range profile of targets can be analyzed with high resolution, the detail algorithm of range profiles spectrum estimation based on wavelet transforming multirange cells is proposed. Compare with FFT algorithm, using wavelet spectrum estimator of short data series, we can achieves high resolution, high accuracy, and low SNR threshold. the Experiment results make clear that the DWT estimator is a sensitive tool in range profile of step frequency MMW radar.

关键词： wavelet transform multiresolution analysis spectrum estimator radar signal image processing

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Moving Platform Based Distributed MIMO Radar Detection in Compound-Gaussian Clutter without Training data 13

Moving Platform Based Distributed MIMO Radar Detection in Co...

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13th IEEE International conference on signal processing (ICSP)

作者： Sun, Guohao He, Zishu Zhang, Yile Univ Elect Sci & Technol China Sch Elect Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781509013456

this paper deals with the problem of detection of distributed multi-input multi-output (MIMO) radar on moving platforms. We consider the detection of targets in compound-Gaussian clutter, describing the clutter consisting speckle and texture components. Furthermore, under effects of platform motion and varied scenarios, one major challenge of detector is clutter non-homogeneity. Due to these clutter models, a novel generalized likelihood ratio test (GLRT) based detector is proposed. With the priori knowledge about matrix taper of the clutter covariance matrix, the detector adopts the Bayesian approach without resorting to training data that is non-homogeneity with the samples under test. To handle with the non-homogeneity of the Doppler frequencies of clutters, the detector employs a non-linear processing by iteration and reconstruction of sparse signals to estimate unknown parameters. Some simulations are presented to illustrate the superior performance of the proposed detector in thus complicated scenarios.

关键词： problem detection distributed

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Multi Agents' Multi targets Mission Under Uncertainty Using Probability Navigation Function 13

Multi Agents' Multi Targets Mission Under Uncertainty Using ...

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13th IEEE International conference on Control & Automation (ICCA)

作者： Hacohen, Shlomi Shoval, Shraga Shvalb, Nir Ariel Univ Dept Mecan Engn Ariel Israel Ariel Univ Dept Ind & Management Engn Ariel Israel

ISBN: (纸本)9781538626795

In this paper we consider the problem of cooperative control of a swarm of autonomous heterogeneous mobile agents that are required to intercept a group of moving targets while avoiding contacts with dynamic obstacles. Traditionally these type of problems are solved by decomposing the solution into several sub problems: targets assignments, coordinated interception control, motion planning and motion control. In this paper we present a simultaneous solution to these problems based on the Probabilistic Navigation Function (PNF). the proposed solution considers uncertainties in the targets and obstacles locations. such that the locations and geometries of the targets and obstacles are given by Gaussian probability distributions. these probabilities are convoluted with the agents', obstacles' and targets' geometries to provide a Global Probability Navigation Function - phi. the PNF provides an analytic solution, and guarantees a simultaneous interception of all targets while limiting the risk of the agents to a given value. the complexity of the solution is linear with the number of targets and agents, and therefore is not limited to small problems. Although the solution provided by the PNF is not optimal, it provides simple and efficient solution, making it suitable for a large range of real time applications.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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the evidential reasoning tracker: Further steps towards a unified theory of sensor fusion

The evidential reasoning tracker: Further steps towards a un...

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13th conference on signal and data processing of small targets

作者： Mahalanabis, A Lobbia, RN Nguyen, QB Boeing Co Boeing Phantom Works Div Seattle WA 98124 USA

ISBN: (纸本)0819441872

the discipline of Sensor and data Fusion is increasingly characterized by a set of disparate tools and principles. An initial consideration of these principles belies any theoretical coherence or commonality. Yet secondary inspection may begin to reveal a fundamental basis that ties together these algorithms. this paper represents the second in a multi-part discussion that attempts to explore this common basis. In particular, while our first discussion centered around the use of a traditional state estimation technique (Kalman Filtering) to perform decision-level identity fusion, in the paper we take the opposite approach, using a traditional decision-level ID technique (Dempster-Shafer Calculus) to do state estimation.

关键词： Sensor data fusion

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the target profile identification of step frequency MMW radar based on wavelet neural network

The target profile identification of step frequency MMW rada...

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13th conference on signal and data processing of small targets

作者： Li, YH Gao, DT Shen, QH Li, XG Nanjing Univ Dept Elect Sci & Technol Nanjing 210093 Peoples R China

ISBN: (纸本)0819441872

With the increased availability of coherent wide band radar, there has been a renewed interest in the target recognition of MMW frequency step radar. A large bandwidth gives high resolution in range which means target recognition may be possible. In this paper, by integrating wavelet with neural network, a new adaptive wavelet function neural network is proposed. An artificial neural network with wavelet as weight coefficients is developed for pattern recognition. It is inspired by wavelet transform theory and feed forward neural network. the good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mapping. the wavelet shapes are adaptively computed to minimize an energy function for a specific application of radar targets. the mathematical frame of the neural network is introduced and error back propagation algorithm is used. the procedure of using wavelet neural network for identification is described in detail. Based on the target specific information offered by the range profiles of step frequency MMW radar targets, the wavelet neural network is applied to recognition of three kinds of practical radar targets. We find that we can reliably distinguish for three targets over a range of aspect angle. Experiment results indicate that the new feature vector in low dimension is valuable for target recognition, the wavelet neural network has faster convergence speed and higher correct recognition rate and the noise resistance character is good.

关键词： wavelet neural network multi-resolution analysis target identification radar signal image processing

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On-board Ship targets Detection Method Based on Multi-scale Salience Enhancement for Remote Sensing Image 13

On-board Ship Targets Detection Method Based on Multi-scale ...

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13th IEEE International conference on signal processing (ICSP)

作者： Yu Ji-yang Huang Dan Wang Lu-yuan Liu Xin Li Wen-juan China Acad Space Technol Beijing 100094 Peoples R China China North Ind Grp Corp Sci Res Inst Beijing 100089 Peoples R China

ISBN: (纸本)9781509013456

A on-board ship targets detection method based on multi-scale salience enhancement is proposed. Unlike the traditional wavelet filter enhancement methods, the proposed utilizes the wavelet decomposition to obtain the high-low frequency parts, and estimate the salience feature with both parts, which enhance the ship targets efficiently. First, decompose the remote sensing image by 2-D DWT, and obtain the low-frequency part, high-frequency part of horizontal, vertical and diagonal;then, compute the OSTU threshold, which is subtracted by the low-frequency coefficients to get the low-frequency salience image;and, the high-frequency parts are used to compose the high-frequency salience image;finally, the high-low parts are fused by addition and normalized to obtain the salience map. the original data of multi sets of remote sensing images are experimented, and the results are compared with the method without the proposed salience enhancement. the proposed shows obvious salience enhancement for the low-resolution, high-noise remote sensing images.

关键词： optical remote sensing satellite ship target detection image processing multi-scale

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Detection of small periodic binary signals in image sequences: Moving signal sources

Detection of small periodic binary signals in image sequence...

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13th conference on signal and data processing of small targets

作者： Feldman, G Bar, D Tugendhaft, I Soreq Nucl Res Ctr IL-81800 Yavne Israel

ISBN: (纸本)0819441872

An algorithm developed for detection, localization and tracking of periodic signals, that appear as few-pixel blobs in image sequences and have a characteristic binary pattern in the temporal domain, is described. It is the further development of our original algorithin (1) that extends its capabilities to the detection of moving targets and also improves its performance in some cases. We sketch those stages of the algorithm that were already described and discussed in (1). then we describe in full detail the new features of our algorithm, namely: 1) A search for signal sources that move with a relatively-slowly-varying velocity. this velocity is adaptively estimated and re-estimated in order to maximize the correlation with the time-domain pattern. While the first estimate is performed at pixel level, the re-estimation ( when tracking detected signals) is performed at the blob level. 2) Re-estimation of the spatial domain background around the already-detected blob, yielding a more precise estimate of the blob. the new algorithm was tested by processing simulated, as well as real, image sequences. the results are discussed. the principal conclusion is that all good features of our original algorithm, namely: efficient detection of visible signals, reasonable detection of invisible signals, insensitivity to local motions in a video, to camera motion, to intensity changes and to any weak flickering of background, remain valid. However, we are required to increase slightly the minimal length of the time-domain correlation (thus, the delay in detection) at the same false alarm probability. Finally, we also consider the problem of the most suitable temporal-domain pattern for signals to be detected.

关键词： image sequence signal detection image registration pattern background subtraction correlation

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An Adaptive Solution for the Detection of small and Slowly-Moving targets in Highly Ambiguous Radar Context 13

An Adaptive Solution for the Detection of Small and Slowly-M...

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13th European Radar conference (EuRAD)

作者： Aouchiche, Linda Ferro-Famil, Laurent Adnet, Claude Univ Rennes 1 Rennes France Thales Air Syst Limours France

ISBN: (纸本)9782874870453

this paper deals with the detection problem of small and slowly-moving targets in the context of highly ambiguous pulse Doppler radar using a medium Pulse Repetition Frequency (PRF). A solution for exploiting multiple-burst signals of these radars is proposed. It combines a fast iterative Maximum Likelihood (ML) estimator for target parameter estimation and ambiguities solving and an adaptive detector that uses a multiple-bursts Clutter Correlation Matrix (CCM) estimator to increase the number of Training data (TD). Simulation results show that the proposed approach allows to resolve ambiguities and reveals the presence of small targets buried into strong ground clutter response.

关键词： Maximum likelihood estimation

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