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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

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Dynamic Transmit Power Allocation for Distributed Mimo Radar Target Detection

Dynamic Transmit Power Allocation for Distributed Mimo Radar...

引用

sensor array and multichannel signal processing workshop

作者： Tuomas Aittomäki Sundeep Prabhakar Chepuri Visa Koivunen Department of Microelectronics TU Delft The Netherlands Department of Signal Processing and Acoustics Aalto University Finland

Distributed multiple-input multiple-output (MIMO) radars can use multiple transmitters and receivers simultaneously to detect targets. In order to maximize the probability of target detection, it is necessary to allocate the available transmit power resources suitably. the optimal allocation requires calculating the probability of detection, which is a computationally complex task, so using the exact distribution is very difficult in a dynamic scenario. In order to alleviate this problem, we propose an approximate distribution that is computationally simpler. this approximation is compared with the exact distribution as well as other cost functions that depend on the distribution of the test statistic, including the Kullback-Leibler divergence. It is demonstrated that the approximate distribution works well in the power allocation problem for MIMO radar target detection.

关键词： signal to noise ratio Covariance matrices Resource management Optimization Object detection Transmitters Receivers

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A new beamformer based on phase dispersion to improve 2D sparse array response

A new beamformer based on phase dispersion to improve 2D spa...

引用

sensor array and multichannel signal processing workshop

作者： Oscar Martinez-Graullera David Romero-Laorden Alberto Ibañez Luis G. Ullate CAEND (UPM-CSIC) Madrid Spain

this work studies a new beamformer for non-periodic sparse bidimensional ultrasonic array transducer. It is based on a weighting factor based on signals phase dispersion to enhance the image points where the phase coherence between the received signals is high. A method to measure the phase dispersion based on Fourier analysis and its integration in the beamformer are presented. Its performance is evaluated using a non-periodic 2D sparse array based on Fermat spiral with 96 elements and a diameter of 60λ. Compared with conventional Delay-And-Sum beamformer the proposed solution reduces the aperture lateral resolution and improves its dynamic range, achieving up to 50dB of contrast in the image and less 1° in lateral resolution.

关键词： arrays Dispersion Apertures Coherence Dynamic range Spirals Image resolution

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Mainlobe Deceptive Jammer Suppression with FDA-MIMO Radar

Mainlobe Deceptive Jammer Suppression with FDA-MIMO Radar

引用

sensor array and multichannel signal processing workshop

作者： Jingwei Xu Jialin Kang Guisheng Liao Hing Cheung So National Lab of Radar Signal Processing Xidian Univesity Xi'an Shaanxi China City University of Hong Kong Hong Kong China

Anti-jamming technique has become an increasing demand in radar systems due to the fast development of electronic countermeasures. To alleviate the extremely difficult deceptive jammer suppression problem, frequency diverse array (FDA) based multiple-input multiple-output (MIMO) radar is devised and a sample selection based deceptive jammer suppression method is developed. the basic principle of the FDA-MIMO radar regarding its superiority in canceling the deceptive jammers is studied in detail. In order to handle the pseudorandom distribution issue of false targets within the secondary training samples, a subspace projection based sample selection method is proposed. When certain a priori knowledge of the true target is available, the time-delayed false targets can be adequately suppressed, even if the latter are in the mainlobe direction. Simulation examples demonstrate the effectiveness of our solution.

关键词： Jamming array signal processing Delay effects Radar countermeasures Doppler radar

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Angular information resolution limit of sensor arrays

Angular information resolution limit of sensor arrays

引用

sensor array and multichannel signal processing workshop

作者： Yongqiang Cheng Xuezhi Wang Bill Moran School of Electronic Science and Engineering National University of Defense Technology China Department of Electrical and Electronic Engineering University of Melbourne Australia Defense Science Institute University of Melbourne Australia

A measure of the ability of a sensor array to resolve two closely spaced point sources in angle is proposed here based on the framework of information geometry. the consideration of the geometric structure of a measurement model leads to the concept of information resolution which serves as a new metric to measure intrinsic similarities and differences between signal distributions that generate the manifold geometry. the statistical divergence between two sources is characterized in terms of the geodesic distance induced by the Fisher information metric. An analytical expression of the angular information resolution limit (AIRL) is derived using the constraints on the probability of error for a binary hypothesis test associated with the resolution of two sources. the influence of the detection error as well as the signal-to-noise ratio (SNR) on resolvability are demonstrated. the proposed AIRL can be used as a performance measure for sensor arrays in localizing remote sources and is applicable to various applications (e.g. radar, sonar, or astronomy).

关键词： sensors

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Localization in sensor networks - A matrix regression approach

Localization in sensor networks - A matrix regression approa...

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sensor array and multichannel signal processing workshop

作者： Paul Honeine Cedric Richard Mehdi Essoloh Hichem Snoussi Institut Charles Delaunay (FRE CNRS 2848)-LM2S Université de technologie de Troyes Troyes France

In this paper, we propose a new approach to sensor localization problems, based on recent developments in machine leaning. the main idea behind it is to consider a matrix regression method between the ranging matrix and the matrix of inner products between positions of sensors, in order to complete the latter. Once we have learnt this regression from information between sensors of known positions (beacons), we apply it to sensors of unknown positions. Retrieving the estimated positions of the latter can be done by solving a linear system. We propose a distributed algorithm, where each sensor positions itself with information available from its nearby beacons. the proposed method is validated by experimentations.

关键词： Distance measurement Kernel Optimization Distributed algorithms Wireless sensor networks Network topology Topology

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Successive Convex Approximation Algorithms for Sparse signal Estimation with Nonconvex Regularizations

Successive Convex Approximation Algorithms for Sparse Signal...

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sensor array and multichannel signal processing workshop

作者： Yang Yang Marius Pesavento Syrneon Chatzinotas Bjōrn Ottersten University of Luxembourg Luxembourg Technische Universitāt Darmstadt Darmstadt Germany

In this paper, we propose a successive convex approximation framework for sparse optimization where the nondifferentiable regularization in the objective function is nonconvex and it can be written as the difference of two convex functions. the proposed framework is based on a nontrivial combination of the majorization-minimization method and successive convex approximation for nonconvex optimization where the regularization function is convex. the proposed framework is flexible and it leads to algorithms that exploit the problem structure and have a low complexity. We demonstrate these advantages by an example application where the nonconvex regularization is the capped l1 -norm function. Customizing the proposed framework, we obtain a best-response type algorithm for which all elements of the unknown parameter are updated in parallel according to closed-form expressions. Finally, the proposed algorithms are numerically tested.

关键词： Approximation algorithms signal processing algorithms Complexity theory Search problems Upper bound Convergence Optimization

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A Method for Simultaneous Creation of an Acoustic Trap and a Quiet Zone

A Method for Simultaneous Creation of an Acoustic Trap and a...

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sensor array and multichannel signal processing workshop

作者： Carl Andersson Jens Ahrens Audio Technology Group Division of Applied Acoustics Chalmers University of Technology Gothenburg Sweden

An acoustical levitation trap can be created by maximizing the Laplacian of the Gor'kov potential and minimizing the pressure at a given location. Marzo et al. have successfully used Broyden-Fletcher-Goldfarb-Shanno minimization to find the phases to be imposed on the elements of an ultrasonic transducer array to create the required pressure field. We extend this method to create a field with one acoustical trap and a quiet zone at a different location. this can be used to, for example, create an independent second trap at the location of the quiet zone. We show through numerical simulations that it is possible to create such sound fields using ultrasonic arrays, and we demonstrate the advantages of the proposed approach over the direct design of a sound field with more than one trap. Our method can create a quiet zone extending almost two wavelengths without affecting the levitation trap.

关键词： Linear programming Acoustics Levitation Transducers array signal processing sensor arrays

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Limited field-of-view multimodal sensor adaptation for data association

Limited field-of-view multimodal sensor adaptation for data ...

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sensor array and multichannel signal processing workshop

作者： Sean M. O'Rourke A. Lee Swindlehurst Center for Pervasive Communications and Computing University of California Irvine Irvine CA USA

We have investigated the utility of field-of-view adaptation for multimodal sensing in cluttered multi-target environments. Measurement data from multiple integrated sensors are collected at a fusion center, which employs a soft association procedure to integrate them into the estimation procedure. A variance penalty model for the limited fields-of-view property is incorporated into the state estimation procedure. this model also forms the basis of an optimization problem that determines the best next-step sensing parameters for the changing target environment. Numerical simulations demonstrate the benefit of the proposed method for both tracking and association metrics compared to a non-adaptive tracker.

关键词： sensors Target tracking Clutter Radio frequency Noise measurement Noise Vectors

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Distributed source processing with linear nested arrays

Distributed source processing with linear nested arrays

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sensor array and multichannel signal processing workshop

作者： Keyong Han Arye Nehorai Preston M. Green Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis MO USA

We consider the problem of using linear nested arrays to estimate the direction of arrival (DOA) of spatially distributed sources and detect the source number, where we have more sources than the actual physical sensors. Angular spread, caused by the multipath nature of distributed sources, makes the commonly used point source assumption ineffective. In this paper, we establish the signal model for distributed sources using a nested array. Due to the characteristics of distributed sources, the regular spatial smoothing technique, which is used to exploit the increased degrees of freedom provided by the co-array, no longer works. We thus propose a novel spatial smoothing approach to circumvent this problem. Based on the analytical results, we construct corresponding DOA estimation and source number detection methods. the effectiveness of the proposed methods is verified through numerical examples.

关键词： arrays Direction-of-arrival estimation Vectors Estimation Smoothing methods Manifolds Multiple signal classification

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Linear-Time Joint Probabilistic Data Association for Multiple Extended Object Tracking

Linear-Time Joint Probabilistic Data Association for Multipl...

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sensor array and multichannel signal processing workshop

作者： Shishan Yang Kolja thormann Marcus Baum Chair for Sensor Technology University of Passau Germany

the Joint Probabilistic Data Association (JPDA) filter for multiple object tracking is based on the assumption that at most one measurement originates from a target object. However, with the development of high-resolution sensors, it is often the case that multiple spatially distributed detections are obtained from a single object. To tackle this emerging data association challenge, this paper presents a JPDA method based on the Poisson spatial measurement model for extended objects. As the constraint that one target gets at most one measurement is relaxed, the marginal association probabilities can be obtained with linear complexity in the number of measurements and targets. the proposed method is compared to a partition-based multiple extended object tracking algorithm.

关键词： Shape Object tracking Clutter Target tracking Probabilistic logic Shape measurement Time measurement

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