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COMPRESSIVE SENSING FOR sensor CALIBRATION

COMPRESSIVE SENSING FOR SENSOR CALIBRATION

引用

ieee sensor array and multichannel signal processing workshop

作者： Cevher, Volkan Baraniuk, Richard Rice Univ Dept Elect & Comp Engn Houston TX 77005 USA

ISBN: (纸本)9781424422401

We consider a calibration problem, where we determine an unknown sensor location using the known track of a calibration target and a known reference sensor location. We cast the calibration problem as a sparse approximation problem where the unknown sensor location is determined over a discrete spatial grid with respect to the reference sensor. To achieve the calibration objective, low dimensional random projections of the sensor data are passed to the reference sensor, which significantly reduces the inter-sensor communication bandwidth. The unknown sensor location is then determined by solving an l(1)-norm minimization problem (linear program). Field data results are provided to demonstrate the effectiveness of the approach.

关键词： Direction-of-arrival estimation Microphone arrays sensor networks

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Discriminating between stationary and time-varying autoregressive (TVAR) models in array processing

Discriminating between stationary and time-varying autoregre...

引用

4th ieee sensor array and multichannel signal processing workshop

作者： Abramovich, Y. I. Turley, M. D. E. Spencer, N. K. DSTO Labs 200 ISRD POB 1500 Edinburgh SA 5111 Australia DSTO Labs 200 ISRD Cooperat Res Ctr Sensor Signal & Informat Proc Edinburgh SA 5111 Australia

For a set of T independent N-variate Gaussian training samples (T < N), we derive a test for discriminating between stationary autoregressive models of order m, AR(m), and time-varying autoregressive models of orde... 详细信息

ISBN: (纸本)1424403081

关键词： array processing

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Time Evolution for Dynamic Probabilistic Tensors in Hierarchical Tucker Decomposition Form 10

Time Evolution for Dynamic Probabilistic Tensors in Hierarch...

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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Govaers, Felix Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781538647523

Many real world applications of target tracking and state estimation are non-linear filtering problems and can therefore not be solved by closed-form analytical solutions. In the recent past, tensor based approaches have become increasingly popular due to very effective decomposition algorithms, which allow the representation of discretized, high-dimensional data in compressed form. In this paper, a solution of the prediction step for a Bayesian filter is proposed, where the probability density function (pdf) is approximated by a tensor in Hierarchical Tucker Decomposition. It is shown, that the computation of the predicted pdf is about five times faster than the previously proposed Canonical Polyadic Decomposition format.

关键词： Tensile stress Probability density function Bayes methods array signal processing sensor arrays Conferences"

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ALGORITHMS FOR TRACKING WITH AN array OF MAGNETIC sensorS

ALGORITHMS FOR TRACKING WITH AN ARRAY OF MAGNETIC SENSORS

引用

ieee sensor array and multichannel signal processing workshop

作者： Kozick, Richard J. Sadler, Brian M. Bucknell Univ Lewisburg PA 17837 USA Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9781424422401

We consider the problem of tracking a magnetic target as it travels in a straight-line path in the vicinity of N magnetic sensors. The target is modeled as a magnetic dipole, and we study tracking algorithms when the sensors are total-field (scalar) magnetometers and vector magnetometers. A novel, computationally-efficient vector-field algorithm is presented that jointly processes the data from N sensors, yielding estimates of the track and the target dipole moment vector. Simulation examples are included to illustrate the performance of the total-field and vector algorithms.

关键词： Magnetic sensors

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LOW-COMPLEXITY IMPLEMENTATION FOR WORST-CASE OPTIMIZATION-BASED ROBUST ADAPTIVE BEAMFORMING

LOW-COMPLEXITY IMPLEMENTATION FOR WORST-CASE OPTIMIZATION-BA...

引用

ieee sensor array and multichannel signal processing workshop

作者： Jiang, Biao Hangzhou Appl Acoust Res Inst Underwater Acoust Syst Lab Hangzhou Peoples R China

ISBN: (纸本)9781424422401

In this paper, an efficient low-complexity robust adaptive beamforming method based on worst-case performance optimization is proposed. Lagrangian method was applied to obtain the expression for the robust adaptive weight vector, which is optimized on the boundary of the steering vector uncertainty region, that is to say, in the worst mismatch case. Combining the constraint condition and the eigendecomposition of the array covariance matrix, root-finding method is used to obtain the optimal Lagrange multiplier. Then, the diagonal loading-like robust weight vector is achieved. ne implementation efficiency is greatly improved since the main computational burden is the eigendecomposition operator. Numerical results show that the performance of the proposed method is nearly identical to the robust Capon beamforming.

关键词： Robustness array signal processing Loading signal to noise ratio arrays Interference Algorithm design and analysis

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CRB analysis of the impact of unknown receiver noise on phased array calibration

CRB analysis of the impact of unknown receiver noise on phas...

引用

4th ieee sensor array and multichannel signal processing workshop

作者： van der Tol, Sebastiaan Wijnholds, Stefan J. Delft Univ Technol Dept Elect Engn DIMES Mekelweg 4 NL-2628 CD Delft Netherlands ASTRON R&D Dept NL-7991 PD Dwingeloo Netherlands

ISBN: (纸本)1424403081

In radio astronomy images are made of astronomical objects as they appear at radio frequencies using a technique called aperture synthesis. Signats from several antennas are correlated and integrated over time. The data collected over several hours are further processed to calibrate the instrument and to form an image or intensity map. The calibration and imaging algorithms do not use the autocorrelations because the receiver noise is unstable and hence considered unknown. In literature the Cramer Rao Bound for the calibration problem has been derived assuming that the autocorrelations are part of the available data. If the assumption is correct that the autocorrelations do not contain useful information when the receiver noise is unknown, than the CRB for the case that the autocorrelations are not part of the data will be the same. In this paper we will derive the CRB excluding the autocorrelations and show that it indeed does not matter whether the autocorrelations are included or not.

关键词： Spurious signal noise

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A new model of source dependent noise for robust array signal processing

A new model of source dependent noise for robust array signa...

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Georgiou, PG Kyriakakis, C Univ So Calif Immers Audio Lab Integrated Media Syst Ctr Los Angeles CA 90089 USA

ISBN: (纸本)0780375513

In this work we investigate an alternative model for signals encountered in acoustic environments to the traditional Gaussian process. The sound signals in this case are assumed to be sub-Gaussian of impulsive nature. The noise encountered in these environments predominantly stems from reverberation or multipath effects, which makes it significantly dependent on the source. Hence, the noise is also modeled as jointly sub-Gaussian. The Levy alpha-stable distribution, of characteristic exponent 0.5 and index of symmetry 1, is used together with a multivariate Gaussian density to derive the sub-Gaussian process. Based on this density, the stochastic Maximum Likelihood (ML) estimator is formulated. A separable solution of the estimator is given. Subsequently, simulations demonstrating the performance gains relative to the Gaussian-based ML estimator are provided, as well as a comparison of the two methods on localization of real sounds gathered with a 20- and 41-microphone arrays.

关键词： Stochastic systems

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Computation of Weight Function of 2qth Order Virtual array to Analyse the Estimation Performance 11

Computation of Weight Function of 2qth Order Virtual Array t...

引用

ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Gupta, Payal Agrawal, Monika Indian Inst Technol Ctr Appl Res Elect New Delhi 110016 India

ISBN: (纸本)9781728119465

Increasing the number of sources to be processed from a given array of sensors is an important problem in sensor array signal processing and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of virtual array corresponding to linear array. We have also analytically evaluated the weight function of virtual array and have also studied the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.

关键词： DoA estimation Non-circular signals Sparse array Virtual array Cumulants Underdetermined System Weight function Covariance Matrix

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Antenna array Based Positional Modulation with a Two-Ray Multi-Path Model 10

Antenna Array Based Positional Modulation with a Two-Ray Mul...

引用

10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Zhang, Bo Liu, Wei Univ Sheffield Commun Res Grp Dept Elect & Elect Engn Sheffield S1 4ET S Yorkshire England

ISBN: (纸本)9781538647523

Traditional directional modulation (DM) designs are based on the assumption that there is no multi-path effect between transmitters and receivers. One problem with these designs is that the resultant systems will be vulnerable to eavesdroppers which are aligned with or very close to the desired directions, as the received modulation pattern at these positions is similar to the given one. To solve the problem, a two-ray multi-path model is studied for positional modulation and the coefficients design problem for a given array geometry and a location-optimised antenna array is solved, where the multi-path effect is exploited to generate a given modulation pattern at desired positions, with scrambled values at positions around them.

关键词： Modulation array signal processing Receivers Phased arrays sensor arrays"

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Convex Joint Emitter Localization and Passive sensor Network Synchronization

Convex Joint Emitter Localization and Passive Sensor Network...

引用

ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Jean, Oren Weiss, Anthony J. Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel

ISBN: (纸本)9781467310710

PATENT PENDING. Time-of-arrival (TOA) localization is tightly coupled with sensor time synchronization. Synchronization can be obtained by GPS, atomic clocks or message exchange protocols. All methods affect the energy sources and the synchronization protocols use valuable bandwidth. We present self-synchronized localization algorithms that rely exclusively on TOA measurements performed by the sensor network on passing sources rendering it completely passive. Localization performance is close to that provided by a perfectly synchronized network. Such algorithms can also be used for sensor network synchronization and communication networks in general.

关键词： sensor networks

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