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检索条件"任意字段=2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016"

共 1002 条记录，以下是161-170 订阅

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sensor Network Distributed Computation for Direct Position Determination

Sensor Network Distributed Computation for Direct Position D...

引用

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

作者： Pourhomayoun, Mohammad Fowler, Mark L. SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)9781467310710

Classical localization systems based on TDOA/FDOA use a two-stage estimation approach. In the first stage, pairs of sensors share data to estimate TDOA/FDOA. Then, the extracted TDOA/FDOA measurements are used to estimate the emitter location. In some recently published methods, an optimal single-stage approach named Direct Position Determination (DPD) has been proposed to improve the position estimation accuracy. However, unlike the classical two-stage method where the TDOA/FDOA estimation can be distributed across all sensors, DPD processes all the received signals together at a single sensor node. However, when sensors have limited computational capabilities it is desirable to distribute the computation across all sensors. Furthermore, concentrating all the processing into a single node makes the location system less robust to the loss of sensors. In this paper, we develop a distributed localization method with the goal of reducing the computational load on each sensor and increasing the reliability of the system.

关键词： Time difference of arrival

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Target Detection Based on Canonical Correlation Technique for Large array MIMO Radar in Spatially Correlated Noise 11

Target Detection Based on Canonical Correlation Technique fo...

引用

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

作者： Zhou, Meihan Jiang, Hong Dong, Siyan Jilin Univ Coll Commun Engn Changchun 130012 Peoples R China

ISBN: (纸本)9781728119465

A novel target detection algorithm for large array multi-input multi-output (MIMO) radar in spatially correlated noise is proposed in this paper using canonical correlation technique (CCT). In the signal model, two separate sub-arrays are employed as the receive array of a transmit diversity MIMO radar system. Assume that the elementary noise in each sub-array has spatial correlation, and the number of receive elements is large and grows as the same rate with the snapshots. The detection statistics is constructed based on the generalized likelihood ratio test (GLRT) criterion and the sample canonical correlation coefficient between the two sub-arrays. The expression of decision threshold is derived via the Tracy-Widom distribution of order 2 in random matrix theory. The simulation results show that the detection performance of the proposed algorithm is better than that of the conventional condition number (CN)-based algorithm in the presence of spatially correlated noise and large array.

关键词： MIMO radar target detection canonical correlation spatially correlated noise random matrix theory

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Frequency-Switching Sparse arrays 13

Frequency-Switching Sparse Arrays

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13rd ieee sensor array and multichannel signal processing workshop (sam)

作者： Zhang, Yimin D. Chowdhury, Md Waqeeb T. S. Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA

ISBN: (纸本)9798350344820;9798350344813

In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low-complexity manner. Unlike multi-frequency sparse arrays which require processing of wideband signals comprising multiple frequency components, the proposed frequency-switching sparse arrays only need to process a single-frequency component at any time instant, thereby eliminating such hurdles and significantly reducing the system complexity. A frequency-switching sparse array achieves the same number of degrees-of-freedom as a multi-frequency counterpart with comparable DOA estimation performance. Numerical results on the DOA estimation performance and Cramer-Rao bounds are provided to illustrate the effectiveness of the proposed frequency-switching sparse arrays.

关键词： Sparse array direction-of-arrival estimation frequency diversity frequency-switching group sparsity

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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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Fast rank-adaptive beamforming

Fast rank-adaptive beamforming

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1st ieee sensor array and multichannel signal processing workshop (sam 2000)

作者： McWhorter, T Mission Res Corp Monterey CA 93940 USA

ISBN: (纸本)0780363396

This paper is concerned with the construction of an adaptive beamformer, which uses the dominant subspace information of a sample covariance matrix. We assume that the sample covariance matrix and its eigenvalue decomposition (EVD) are to be updated as data arrive. We present a unified structure for updating the EVD and introduce a robust method for adapting the rank of the dominant subspace. We use the EVD of the sample covariance matrix to build a fast rank- and weight-adaptive beamformer. A useful component of the beamforming routine is a fast algorithm for updating the estimates of the direction of arrival of the dominant sources.

关键词： Algorithm design and analysis array signal processing Bibliographies Covariance matrix Eigenvalues and eigenfunctions Joining processes Matrix decomposition Performance evaluation Robustness Stochastic processes

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Decentralized Online Direction-of-Arrival Estimation and Tracking 12

Decentralized Online Direction-of-Arrival Estimation and Tra...

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ieee 12th sensor array and multichannel signal processing workshop (sam)

作者： Fan, Yufan Ardic, Cemil Emre Minh Trinh-Hoang Pesavento, Marius Tech Univ Darmstadt Commun Syst Grp Darmstadt Germany

ISBN: (纸本)9781665406338

The problem of the decentralized Direction-ofArrival (DoA) estimation and tracking is addressed, where the sample covariance matrix is represented as a recursive update of rank-one components. Due to the fact that the conventional decentralized power method is a batch approach and involves high communication costs, we propose a distributed DoA estimation method combining the decentralized online eigenvalue decomposition and the ESPRIT algorithm. The Push-Sum protocol is applied to realize the local interactions among neighboring subarrays. The simulation results show that the Root Mean Square Error (RMSE) performance of our distributed algorithm surpasses that of the power method based d-ESPRIT algorithm in the DoA estimation with lower total communication cost, and that of the decentralized Normalized Oja (d-NOja) method in DoA tracking applications with faster convergence speed.

关键词： Direction-of-arrival estimation Costs Protocols Simulation signal processing algorithms Estimation Eigenvalues and eigenfunctions

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An Anti-jamming Method Against Frequency Diverse array for ISAR by Spatial Location Feature Recognition 11

An Anti-jamming Method Against Frequency Diverse Array for I...

引用

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

作者： Liu, Zhidong Li, Kaiming Luo, Ying Zhang, Qun Huang, Qingzhu Air Force Enginnering Univ Inst Informat & Nav Xian Peoples R China Unit 94608 PLA Nanjing Peoples R China

ISBN: (纸本)9781728119465

By means of frequency-shifting jamming processing of target echo signal and pulse compression in imaging processing, group of false targets will appear in different spatial locations around the true target. The feature extraction of false targets is complex and limited in existing countering methods. In this paper, an anti-jamming method against frequency diverse array (FDA) is proposed to identify the spatial location characteristics of the deception false targets. By adjusting the parameters of the radar transmitting signal, the method simultaneously transmits the anti-jamming signal and carries out the false target identification and elimination in the range dimension. Eventually, the optimal signal parameter design of anti-jamming signal is given by comparing with the range resolution. The validity of the proposed method is proved by deducing the mathematical model between the spatial distribution characteristics of the false targets and the radar transmitting signal parameters and demonstrated by simulations.

关键词： frequency diverse array inverse synthetic aperture radar anti-jamming spatial location feature Recognition

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Angular Information Resolution Limit of sensor arrays

Angular Information Resolution Limit of Sensor Arrays

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8th ieee sensor array and multichannel signal processing workshop (sam)

作者： Cheng, Yongqiang Wang, Xuezhi Moran, Bill Natl Univ Def Technol Sch Elect Sci & Engn Beijing Peoples R China Univ Melbourne Melbourne Sch Engn Dept Elect & Elect Engn Melbourne Vic 3010 Australia Univ Melbourne Melbourne Sch Engn Def Sci Inst Melbourne Vic 3010 Australia

ISBN: (纸本)9781479914814

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： Geometry

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Spectrum estimation from quantum-limited interferograms

Spectrum estimation from quantum-limited interferograms

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1st ieee sensor array and multichannel signal processing workshop (sam 2000)

作者： Fuhrmann, DR O'Sullivan, JA Snyder, DL Smith, WH Washington Univ Dept Elect Engn St Louis MO 63130 USA

ISBN: (纸本)0780363396

A quantitative model for interferogram data collected in a quantum-limited hyperspectral imaging system is derived. This model accounts for the geometry of the interferometer the Poisson noise, and the parameterization of the mean of the noise in terms of the autocorrelation function of the incident optical signal. An estimation-theoretic approach to recovering the image spectrum is derived, based on the likelihood function for the received data. The computations proposed constitute an alternating minimization algorithm.

关键词： Autocorrelation Hyperspectral imaging Hyperspectral sensors Optical imaging Optical interferometry Optical noise Optical sensors Optical signal processing Spectral analysis Spectroscopy

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Calibration of Polarimetric Antenna arrays Using Neural Networks 13

Calibration of Polarimetric Antenna Arrays Using Neural Netw...

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13rd ieee sensor array and multichannel signal processing workshop (sam)

作者： Springer, Jannik Mikus, Philipp Oispuu, Marc Koch, Wolfgang Knott, Peter Fraunhofer Inst Commun Informat Proc & Ergon FKIE Fraunhoferstr 20 D-53343 Wachtberg Germany Fraunhofer Inst High Frequency Phys & Radar Tech Fraunhoferstr 20 D-53343 Wachtberg Germany

ISBN: (纸本)9798350344820;9798350344813

This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based array signal processing techniques require an accurate model of the complex array response and model errors can, for example, cause significant systematic direction finding errors. Modeling the response of polarimetric antenna arrays can be particularly challenging due to cross-polarization and mutual coupling effects in the multi-port antenna elements. This work proposes a new calibration technique for polarimetric antenna arrays using neural networks that learn any mismatches between the modeled and the actual array response. The technique is evaluated based on the measured response of a five-element dual-polarized antenna array and outperforms conventional calibration techniques like mutual coupling calibration or local polynomial approximation. Its performance is studied exemplarily for the direction finding problem.

关键词： antenna array polarization calibration machine learning neural network direction finding

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