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Proceedings of the International conference on Ground Penetrating Radar, GPR

作者： Mehmet Sezgin TÜBITAK UEKAE Gebze Kocaeli Turkey

ISBN: (纸本)9781424446049;9781424446056

In this paper a novel detection warning signal creation method is proposed for pulse Ground Penetrating Radar (GPR) data, especially for small non-metallic targets, in time domain. Background removal is applied to the data through a sliding window scheme and Target Energy Function (TEF) is obtained as correlation summation of consecutive A-scan signals. Then Auxiliary Detection Function (ADF) is defined and a novel automatic Detection Warning signal (DWS) creation is applied. The proposed method has been tested specifically for a set of small sized dielectric targets which are not easily detectable. The results are promising as full detection performance and zero false alarm rate in original dataset. Moreover, it is obtained that the immunity of the proposed method against noise is very satisfactory.

关键词： signal detection Ground penetrating radar Buried object detection Radar detection Object detection signal processing Testing Statistical analysis Clutter Dielectrics

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small target detection in SAR image using the Alpha-stable distribution model

Small target detection in SAR image using the Alpha-stable d...

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International conference on Image Analysis and signal processing, IASP

作者： Jia Xu Wei Han Xiu-feng He Ren-xi Chen Department of Earth Sciences and engineering Hohai University HHU Nanjing China Beijing China

The Constant False Alarm Rate (CFAR) algorithm is most commonly used for small target detection in SAR images. As the goodness-of-fit of distribution model to SAR clutter has great effect on the performance of algorithm, after a comprehensive statistical analysis of background clutters of different SAR data, a modified CFAR algorithm based on the Alpha-stable distribution is proposed for detecting small targets in SAR images, especially under the extremely inhomogeneous background clutter. Considering for the complexity of Alpha-stable distribution model, the parameter estimation and threshold determining steps of the modified algorithm are introduced in detail. Performance of the algorithm is assessed by experiments on ADTS data. Compared with typical two-parameter CFAR (TP-CFAR) algorithm based on Gaussian distribution and K-CFAR algorithm based on K distribution, the proposed method is demonstrated to be most suitable for detecting small target in extremely inhomogeneous regions.

关键词： Object detection Clutter Synthetic aperture radar Layout Gaussian distribution Statistical analysis Parameter estimation Ultraviolet sources Adaptive optics Geoscience

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Multi-radar system database integration using metrized small world technology

Multi-radar system database integration using metrized small...

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International conference on Microwaves, Radar and Wireless Communications

作者： Dmitry Ponomarev Vladimir Krylov Yuri Pankratov Mera Laboratories Nizhny Novgorod Russia

The present article describes the possibility of integrating the data from several radars with shared radiolocation areas in order to acquire precise information about the targets by means of analyzing the events in neighboring spatiotemporal resolution elements. The paper suggests an algorithm for integrating the data based on creating the graph which possesses the characteristics of the “Metrized small World”. A possibility of processing the integrated data in real time is analyzed. The article describes efficient metrics for integrating multi-radar data into a single Metrized small World graph. Examples of such algorithms are given.

关键词： Spatial databases Spatial resolution Bandwidth Costs data analysis Distributed databases Radar scattering signal resolution Information analysis Spatiotemporal phenomena

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Sparsity enhanced fast subsurface imaging for stepped frequency GPRs

Sparsity enhanced fast subsurface imaging for stepped freque...

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IEEE signal processing and Communications Applications (SIU)

作者： Mehmet Ali Çağrı Tuncer Ali Cafer Gürbuz Elektrik ve Elektronik Mühendisliği Bölümü TOBB Ekonomi ve Teknoloji Üniversitesi Turkey

A sparsity enhanced and fast data acquisition and imaging method is presented for stepped-frequency continuous-wave ground penetrating radars (SFCW GPRs). In previous work it is shown that if the target space is sparse like the point like targets, an image of the target space can be constructed with making measurements at only a small number of random frequencies by solving an l 1 minimization problem. This greatly reduces the data acquisition time but the computational complexity for the imaging method is high. In this work, subsurface imaging is done with a suboptimal but fast method, orthogonal matching pursuit. Similar results to l 1 minimization images are obtained within much shorter times. Also the results are sparse and less cluttered compared to standard backprojection images.

关键词： Ground penetrating radar Matching pursuit algorithms Radar imaging data acquisition Compressed sensing

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Sparsity enhanced fast subsurface imaging with GPR

Sparsity enhanced fast subsurface imaging with GPR

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Proceedings of the International conference on Ground Penetrating Radar, GPR

作者： Ali Cafer Gürbüz Department of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Ankara Turkey

ISBN: (纸本)9781424446049;9781424446056

Sparsity of a signal starts to become very important in many applications. In subsurface imaging, generally potential targets covers a small part of the total subsurface volume to be imaged, thus the targets are spatially sparse. Under this assumption it is shown that the subsurface imaging problem can be formulated as a dictionary selection problem which can be solved quickly using basis pursuit type algorithms compared to previously published convex optimization based methods. Spatial sparsity also indicates that the number of measurements (spatial or time/frequency) that GPR collects can be reduced, decreasing the data acquisition time. Orthogonal matching pursuit algorithm is used for reconstructing sparse subsurface images. Results show that the proposed method reduces time both in data acquisition and processing compared to previous methods with similar performance.

关键词： Ground penetrating radar Time measurement data acquisition Matching pursuit algorithms Image reconstruction EMP radiation effects Dictionaries Pursuit algorithms Frequency measurement Radar imaging

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Detection and Localization of Multiple Unresolved Extended targets via Monopulse Radar signal processing

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2009年第2期45卷 455-472页

作者： Zhang, Xin Willett, Peter Bar-Shalom, Yaakov United Technol Res Ctr E Hartford CT 06108 USA Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

When the size of targets is comparable to the range resolution of monopulse radars, these targets should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used to resolve these targets, i.e., estimate the number of targets and their respective angles-of-arrival and ranges. To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and present a maximum likelihood estimator (MLE) to localize the targets. Rissanen's minimum description length (MDL) criterion will be used to decide the number of existing extended objects. We also derive the upper limit on the number of targets and their scattering centers that can be resolved, and we provide necessary conditions for these targets to be uniquely identified. We compare the new extended target monopulse processing scheme with previously developed point-target monopulse techniques in the simulations.

关键词： RADAR ELECTRONIC pulse techniques ELECTRONIC systems signal processing -- Digital techniques MACHINE theory

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A multi-prototype clustering algorithm

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PATTERN RECOGNITION 2009年第5期42卷 689-698页

作者： Liu, Manhua Jiang, Xudong Kot, Alex C. Shanghai Jiao Tong Univ Dept Instrument Sci & Engn Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China Nanyang Technol Univ EEE Singapore 639798 Singapore

Clustering is an important unsupervised learning technique widely used to discover the inherent structure of a given data set. Some existing clustering algorithms uses single prototype to represent each cluster, which may not adequately model the clusters Of arbitrary shape and size and hence limit the clustering performance on complex data structure. This paper proposes a clustering algorithm to represent one cluster by multiple prototypes. The squared-error clustering is used to produce a number of prototypes to locate the regions of high density because of its low computational cost and yet good performance. A separation measure is proposed to evaluate how well two prototypes are separated. Multiple prototypes with small separations are grouped into a given number of clusters in the agglomerative method. New prototypes are iteratively added to improve the poor cluster separations. As a result, the proposed algorithm can discover the clusters of complex structure with robustness to initial settings. Experimental results on both synthetic and real data sets demonstrate the effectiveness of the proposed clustering algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： data clustering Cluster prototype Separation measure Squared-error clustering

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Range-time backprojection for 3D shape estimation of small space debris

Range-time backprojection for 3D shape estimation of small s...

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2009 Asia-Pacific conference on Synthetic Aperture Radar, APSAR 2009

作者： Chen, Shichao Zhang, Lei Xing, Mengdao Qiu, Cheng-Wei Bao, Zheng National Key Lab for Radar Signal Processing Xidian University Xi'an 710071 China Radar and Signal Processing Lab National University of Singapore 117576 Singapore

ISBN: (纸本)9781424427314

A coherent backprojection based approach is presented for 3D shape estimation of small debris in space. The approach utilizes the fact that space debris is in high-speed spinning motion. Making use of the modulated range envelope and Doppler spreading, a backprojection maps the data into a three-dimensional parameter domain, and the spatial coordinates of scatterers can be extracted to reconstruct 3D shape. In most of recent papers on the imaging of space debris or rotating targets, the rotation from the translational motion is assumed to be neglectable, while in our approach the backprojection is combined with a Fourier transform to deal with the rotation of translational motion and full coherent accumulation can be achieved. The approach is robust in the occurrence of serious profile overlapping and strong noise. Simulations confirm its validity and good performance. ©2009 IEEE.

关键词： Space debris

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Infrared small Weak Target Detection via HOSA

Infrared Small Weak Target Detection via HOSA

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International Symposium on Information Assurance and Security (IAS)

作者： Gaoyu Zhang Information Management Institute Shanghai Finance University Shanghai China Computer Science Institute Fudan University Shanghai China

After the characteristics and shortage of some old algorithm about the infrared small weak targets detection being analyzed, a kind of new detection algorithm via high order spectral analysis is proposed for single frame image. Taking the gray level data of the image ground as the noise signal, the gray level data of small weak targets as the harmonic signal mixed in the noise signal, the gray level data of row and arrange pixel in image are processed via power spectral analysis and high order cumulation analysis to restrain noise and detect harmonic. The distinguishability of detection lies on the piece of the rows being spectrum analyzed on the same time. The advantage of the algorithm consists of adopting the same examine theory, easy accomplishment, having the higher accuracy, and needing data limited by the single frame image only. Finally an example applied the detection algorithm is given.

关键词： Infrared detectors Object detection Noise level signal processing Image analysis Detection algorithms Spectral analysis Power system harmonics Infrared imaging Infrared spectra

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Sub-Array processing for parameters estimate of embedded conducting cylinders

Sub-Array Processing for parameters estimate of embedded con...

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European Radar conference (EURAD)

作者： Simone Meschino Lara Pajewski Giuseppe Schettini "Roma Tre" University Italy "Roma Tre" University Rome Italy

A hybrid electromagnetic-statistic approach for the detection and localization of buried perfectly-conducting circular cylinders is presented. The data used for simulating the scenario are produced by using the cylindrical wave approach (CWA) method. The inverse scattering problem is treated by means of a statistical detection technique. In particular, by the use of a SAP (sub-array processing) structure, it is possible to apply several algorithms of direction of arrival (DOA) estimation. By triangulating the DOAs, a set of crossings, condensed around the expected object locations, is obtained. To process the crossing pattern, we develop a statistical model for the crossings distribution, and employ hypothesis testing procedures to identify a collection of small windows containing targets. By defining a suitable threshold from a desired false alarm rate, and dividing the region in small windows it is possible to ascribe each window to the ground or to an object.

关键词： Parameter estimation Direction of arrival estimation Buried object detection Scattering Partitioning algorithms Engine cylinders Inverse problems Testing Landmine detection Array signal processing

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