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A fast algorithm for direction of arrival estimation in multi-path environments

A fast algorithm for direction of arrival estimation in mult...

引用

Conference on Wireless Sensing and Processing II

作者： Tayem, Nizar Naraghi-Pour, Mort Louisiana State Univ Dept Elect & Comp Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9780819466990

A new spectral direction of arrival (DOA) estimation algorithm is proposed that can rapidly estimate the DOA of non-coherent as well as coherent incident signals. As such the algorithm is effective for DOA estimation in multi-path environments. The proposed method constructs a data model based on a Hermitian Toeplitz matrix whose rank is related to the DOA of incoming signals and is not affected if the incoming sources are highly correlated. The data is rearranged in such a way that extends the dimensionality of the noise space. Consequently, the signal and noise spaces can be estimated more accurately. The proposed method has several advantages over the well-known classical subspace algorithms such as MUSIC and ESPRIT, as well as the Matrix Pencil (MP) method. In particular, the proposed method is suitable for real-time applications since it does not require multiple snapshots in order to estimate the DOA's. Moreover, no forward/backward spatial smoothing of the covariance matrix is needed, resulting in reduced computational complexity. Finally, the proposed method can estimate the DOA of coherent sources. The simulation results verify that the proposed method outperforms the MUSIC, ESPRIT and Matrix Pencil algorithms.

关键词： Signal to noise ratio Radon Smoothing Antennas Computer simulations detection and tracking algorithms Error analysis Matrices Data modeling Interference (communication)

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A Bayesian framework for ATR decision-level fusion experiments

A Bayesian framework for ATR decision-level fusion experimen...

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Conference on Multisensor, Multisource Information Fusion

作者： Morgan, Douglas R. Ross, Timothy D. Consultant BAE Mountain View CA USA AFRL SNAR Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9780819466938

The US Air Force Research Laboratory (AFRL) Fusion for Identifying Targets Experiment (FITE) program aims to determine the benefits of decision-level fusion (DLF) of Automatic Target Recognition (ATR) products. This paper describes the Bayesian framework used to characterize the trade-space for DLF approaches and applications. The overall fusion context is represented as a Bayesian network and the fusion algorithms use Bayesian probability computations. Bayesian networks conveniently organize the large sets of random variables and distributions appearing in fusion system models, including models of operating conditions, prior knowledge, ATR performance, and fusion algorithms. The relationship between fuser performance and these models may be analytically stated (the FITE equation), but must be solved via stochastic system modeling and Monte Carlo simulation. A key element of the DLF trade-space is the degree to which the various models depend on ATR operating conditions, since these will determine the fuser's complexity and performance and will suggest new requirements on source ATRs.

关键词： Automatic target recognition Sensors Monte Carlo methods Performance modeling Data fusion detection and tracking algorithms Systems modeling Autoregressive models Data modeling Environmental sensing

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Sparse and redundant representations and motion-estimation-free algorithm for video denoising

Sparse and redundant representations and motion-estimation-f...

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Conference on Wavelets XII

作者： Protter, Matan Elad, Michael Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

ISBN: (纸本)9780819468499

The quality of video sequences (e.g. old movies, webcam, TV broadcast) is often reduced by noise, usually assumed white and Gaussian, being superimposed on the sequence. When denoising image sequences, rather than a single image, the temporal dimension can be used for gaining in better denoising performance, as well as in the algorithms' speed. This paper extends single image denoising method reported in(1,2) to sequences. This algorithm relies on sparse and redundant representations of small patches in the images. Three different extensions are offered. and all are tested and found to lead to substantial benefits both in denoising quality and algorithm complexity compared to running the single image algorithm sequentially. After these modifications, the proposed algorithm displays state-of-the-art denoising performance, while not relying on motion estimation.

关键词： Associative arrays Denoising Chemical species Video Motion estimation 3D image processing Image denoising detection and tracking algorithms Image quality Image processing

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Tomographic image reconstruction using the Cell Broadband Engine (CBE) general purpose hardware

Tomographic image reconstruction using the Cell Broadband En...

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Conference on Computational Imaging V

作者： Knaup, Michael Steckmann, Sven Bockenbach, Olivier Kachelriess, Marc Univ Erlangen Nurnberg IMP Henkestr 91 D-91052 Erlangen Germany Mercury Comp Syst D-12163 Berlin Germany

ISBN: (纸本)9780819466112

Tomographic image reconstruction, such as the reconstruction of CT projection values, of tomosynthesis data, PET or SPECT events, is computational very demanding. In filtered backprojection as well as in iterative reconstruction schemes, the most time-consuming steps are forward- and backprojection which are often limited by the memory bandwidth. Recently, a novel general purpose architecture optimized for distributed computing became available: the Cell Broadband Engine (CBE). Its eight synergistic processing elements (SPEs) currently allow for a theoretical performance of 192 GFlops (3 GHz, 8 units, 4 floats per vector, 2 instructions, multiply and add, per clock). To maximize image reconstruction speed we modified our parallel-beam and perspective backprojection algorithms which are highly optimized for standard PCs, and optimized the code for the CBE processor.(1-3) In addition, we implemented an optimized perspective forward projection on the CBE which allows us to perform statistical image reconstructions like the ordered subset convex (OSC) algorithm.(4) Performance was measured using simulated data with 512 projections per rotation and 512(2) detector elements. The data were backprojected into an image of 512(3) voxels using our PC-based approaches and the new CBE-based algorithms. Both the PC and the CBE timings were scaled to a 3 GHz clock frequency. On the CBE, we obtain total reconstruction times of 4.04 s for the parallel backprojection, 13.6 s for the perspective backprojection and 192 s for a complete OSC reconstruction, consisting of one initial Feldkamp reconstruction, followed by 4 OSC iterations.

关键词： Sensors Image restoration Clocks Reconstruction algorithms detection and tracking algorithms Tomography Computing systems Image processing Computed tomography CT reconstruction

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Two different approaches for attacking BOWS

Two different approaches for attacking BOWS

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9th Conference on Security, Steganigraphy, and Watermarking of Multimedia Contents

作者： Comesana, Pedro Perez-Gonzalez, Fernando Univ Vigo Dept Teoria Senal & Comun ETSI Telecom E-36310 Vigo Spain

ISBN: (纸本)9780819466181

From December 15, 2005 to June 15, 2006 the watermarking community was challenged to remove the watermark from 3 different 512 x 512 watermarked images while maximizing the Peak Signal to Noise Ratio (PSNR) measured by comparing the watermarked signals with their attacked counterparts. This challenge, which bore the inviting name of Break Our Watermarking System (BOWS),(1) and was part of the activities of the European Network of Excellence ECRYPT, had as its main objective to enlarge the current knowledge on attacks to watermarking systems;in this sense, BOWS was not aimed at checking the vulnerability of the specific chosen watermarking scheme against attacks, but to inquire in the different strategies the attackers would follow to achieve their target. In this paper the main results obtained by the authors when attacking the BOWS system are introduced. Mainly, the strategies followed can be divided into two different approaches: blind sensitivity attacks and exhaustive search of the secret key.

关键词： Digital watermarking Sensors Distortion Signal detection Binary data detection and tracking algorithms Signal to noise ratio Algorithm development Information security Signal processing

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Field test results of standoff chemical detection using the FIRST

Field test results of standoff chemical detection using the ...

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Conference on Chemical and Biological Sensing VIII

作者： Spisz, Thomas S. Murphy, Patricia K. Carter, Christopher C. Carr, Alison K. Vallieres, Alexander Chamberland, Martin Johns Hopkins Univ Appl Phys Lab Johns Hopkins Rd Laurel MD 20723 USA Telops Inc Quebec City PQ Canada

ISBN: (纸本)9780819466761

The FIRST, a commercial hyperspectral imager developed by Telops, features high sensitivity in a compact and robust package. This sensor provides hypercubes of spectral radiance of up to 320x256 pixels at 0.35mrad spatial resolution over the 8 - 12 mu m spectral range at user selectable spectral resolutions of up to 0.25 cm(-1). The measurements are converted into "chemical maps" by the use of powerful algorithms using both spatial and spectral information. The FIRST has been used at several field tests for the standoff detection and identification of chemicals. During these tests, the sensor is usually operated at 4 cm(-1) of spectral resolution and the image size is tailored according to the dissemination. algorithms based on a combination of clutter-matched filters and spectral angle mapper have been developed and used to process the measured data. The algorithms combine sub-band selection to minimize the correlation between the spectral signatures in the library and careful selection of the thresholds to reduce the level of false alarms. The output of the algorithms is the image of the clouds superimposed on the broadband thermal image. JHU/APL has developed a processing approach that adapts to different backgrounds, yields low probability of false alarm, and performs well in the presence of "hot" pixels. The algorithm combines background/noise suppression techniques, spectral detection techniques, such as the spectral angle mapper and the matched filter, and automatic adaptive threshold techniques. This paper will present the successful standoff detection and identification of various chemical compounds using a variety of field measurements. Images of chemical disseminations will be presented, with some of them including mixtures of 2 different chemicals.

关键词： Clouds Sensors Long wavelength infrared Spectral resolution Standoff detection Absorption detection and tracking algorithms Terbium Infrared imaging Optical filters

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A high resolution terahertz spectrometer for chemical detection

A high resolution terahertz spectrometer for chemical detect...

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Conference on Terahertz for Military and Security Applications V

作者： Majewski, Alexander Abreu, Rene Wraback, Michael Goodrich Corp ISR Syst Div 100 Wooster Heights Danbury CT USA US Army Res Lab Sensors & Elect Devices Directorate Adelphi MD USA

ISBN: (纸本)9780819466716

Goodrich has been developing a high resolution, broad band spectrometer that operates in the Terahertz (THz) region of the spectrum with the intent of performing chemical detection. THz spectroscopy exploits rotational resonances for detection of gas phase compounds. High resolution THz spectroscopy can improve detection and identification through increased probability of detection and reduced false alarms. The Goodrich THz spectrometer is based upon CW photomixer technology in a heterodyne configuration. The current Goodrich design offers continuous tunability across a 0.1 THz to 1.2 THz frequency range. One of the unique aspects of the Goodrich spectrometer is laser system control that has demonstrated difference frequency line widths on the order of 1.5 MHz with stability measured over long time scales. Absolute frequency accuracy is of the order of 4 MHz. The spectrometer design enables high THz energy densities with narrow line widths tunable over a broad spectrum. The system has demonstrated SNR better than a cryogenically cooled hot electron bolometer. This capability allows the Goodrich system to accurately determine absorption signatures of multiple chemicals with exceptional performance. Goodrich has completed initial system testing and verified performance. Initial tests were completed to determine SNR of the heterodyne photomixer transceiver. System performance was also verfied for laser line width, stability, and repeatability. The spectrometer was tested against various toxic industrial chemicals. Preliminary data for HCN, HCl, NH3, and SO2 is presented.

关键词： Spectroscopy Terahertz radiation Absorption Control systems Laser stabilization Signal to noise ratio Chemical detection Toxic industrial chemicals Heterodyning detection and tracking algorithms

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A survey of PHD filter and CPHD filter implementations

A survey of PHD filter and CPHD filter implementations

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Conference on Signal Processing, Sensor Fusion, and Target Recognition XVI

作者： Maher, Ronald Lockheed Martin MS2 Tact Syst Eagan MN USA

ISBN: (纸本)9780819466891

The probability hypothesis density (PHD) filter has attracted increasing interest since the author first introduced it in 2000. Potentially practical computational implementations of this filter have been devised, based on sequential Monte Carlo or on Gaussian mixture techniques. Research groups in at least a dozen different nations are investigating the PHD filter and its generalization, the CPHD filter, for use in various applications. Some of this work suggests that these filters may, under certain circumstances, outperform conventional multitarget filters such as MHT and JPDA. This paper summarizes these research efforts and their findings.

关键词： Filtering (signal processing) Electronic filtering Monte Carlo methods Target detection detection and tracking algorithms Motion models Sensors Computer simulations Expectation maximization algorithms Nonlinear filtering

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Real-time vehicle detection in infrared and visible images

Real-time vehicle detection in infrared and visible images

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Conference on Signal Processing, Sensor Fusion, and Target Recognition XVI

作者： Yu, Changhua Dong, Anlei Yue, Zhanfeng Topiwala, Pankaj FastVDO LLC Columbia MD 20740 USA

ISBN: (纸本)9780819466891

Real time object detection is still a challenging computer vision problem in uncontrolled environments. Unlike traditional classification problems, where the training data can properly describe the statistical models, it is much harder to discriminate certain object class from rest of the world with limited negative training samples. Due to the large variation of negatives, sometimes the intra-object class difference may be even larger than the difference between objects and non-objects. Besides this, there are many other problems that obstruct object detection, such as pose variation, illumination variation and occlusion. Previous studies also demonstrated that infrared (IR) imagery provides a promising alternative to visible imagery. Detectors using IR imagery are robust to illumination variations and able to detect object under all lighting conditions including total darkness, where detectors based on visible imagery generally fail. However, IR imagery has several drawbacks, while visible imagery is more robust to the situations where IR fails. This suggests a better detection system by fusing the information from both visible and IR imagery. Moreover, the object detector needs exhaustive search in both spatial and scale domain, which inevitably lead to high computation load. In this paper, we propose to use boosting based vehicle detection in both infrared and visible imagery. Final decision will be a combination of detection results from both the IR and visible images. Experiments are carried out using ATR helmet device with both EO and IR sensors.

关键词： Infrared imaging Visible radiation Feature extraction Infrared detectors Sensors detection and tracking algorithms Infrared sensors Infrared radiation Information visualization Visualization

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Video surveillance of pedestrians and vehicles

Video surveillance of pedestrians and vehicles

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Conference on Acquisition, tracking, Pointing and Laser Systems Technologies XXI

作者： Gutchess, Daniel Ablavsky, Vitaly Thangali, Ashwin Sclaroff, Stan Snorrason, Magnus Charles River Analyt Cambridge MA 02138 USA Boston Univ Dept Comp Sci Boston MA 02215 USA

ISBN: (纸本)9780819466914

In this paper, we focus on the problem of automated surveillance in a parking lot scenario. We call our research system VANESSA, for Video Analysis for Nighttime Surveillance and Situational Awareness. VANESSA is capable of. 1) detecting moving objects via background modeling and false motion suppression, 2) tracking and classifying pedestrians and vehicles, and 3) detecting events such as person entering or exiting a vehicle. Moving object detection utilizes a multi-stage cascading approach to identify pixels that belong to the true objects and reject any spurious motion, (e.g., due to vehicle headlights or moving foliage). Pedestrians and vehicles are tracked using a multiple hypothesis tracker coupled with a particle filter for state estimation and prediction. The space-time trajectory of each tracked object is stored in an SQL database along with sample imagery to support video forensics applications. The detection of pedestrians entering/exiting vehicles is accomplished by first estimating the three-dimensional pose and the corresponding entry and exit points of each tracked vehicle in the scene. A pedestrian activity model is then used to probabilistically assign pedestrian tracks that appear or disappear in the vicinity of these entry/exit points. We evaluate the performance of tracking and pedestrian-vehicle association on an extensive data set collected in a challenging real-world scenario.

关键词： Video surveillance 3D modeling Video Motion models detection and tracking algorithms Particle filters Particles Databases Image segmentation Surveillance

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