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共 1267 条记录，以下是561-570 订阅

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MMOSPA-based Direction-of-Arrival Estimation for Planar Antenna arrays

MMOSPA-based Direction-of-Arrival Estimation for Planar Ante...

引用

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

作者： Baum, Marcus Willett, Peter Hanebeck, Uwe D. Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA Karlsruhe Inst Technol KIT Intelligent Sensor Actuator Syst Lab ISAS Karlsruhe Germany

ISBN: (纸本)9781479914814

This work is concerned with direction-of-arrival (DOA) estimation of narrowband signals from multiple targets using a planar antenna array. We illustrate the shortcomings of Maximum Likelihood (ML), Maximum a Posteriori (MAP), and Minimum Mean Squared Error (MMSE) estimation, issues that can be attributed to the symmetry in the likelihood function that must exist when there is no information about labeling of targets. We proffer the recently introduced concept of Minimum Mean OSPA (MMOSPA) estimation that is based on the optimal sub-pattern assignment (OSPA) metric for sets and hence inherently incorporates symmetric likelihood functions.

关键词： planar antenna arrays Direction of arrival estimation Likelihood Functions Mean square error Narrowband Antenna arrays Targets SETTING Planar antennas

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Energy Detection for Decision Fusion in Wireless sensor Networks over Ricean-Mixture Fading

Energy Detection for Decision Fusion in Wireless Sensor Netw...

引用

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

作者： Salvo Rossi, Pierluigi Ciuonzo, Domenico Ekman, Torbjoern Kansanen, Kimmo Univ Naples 2 Dept Ind & Informat Engn Naples Italy Norwegian Univ Sci & Technol Dept Elect & Telecommun Trondheim Norway

ISBN: (纸本)9781479914814

In this paper we focus on the energy detector for decision fusion in wireless sensor networks over multiple access channels. More specifically, we derive analytical performance in terms of global probability of false alarm and detection (including asymptotic performance for large number of sensors) when the fading is a Ricean mixture, i.e. channel coefficients are sampled from a Gaussian mixture (GM) distribution. The motivation for the GM is the ability to model real-world scenarios while keeping mathematical tractability. Analytical results are confirmed through numerical simulations.

关键词： Wireless sensor networks energy detector fading color Channel Coefficient probability of false alarm Fusion reactions Fusion, biological FUSION fusion (melting) Multiple Access Channel

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Detection in Analog sensor Networks with a Large Scale Antenna Fusion Center

Detection in Analog Sensor Networks with a Large Scale Anten...

引用

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

作者： Jiang, Feng Chen, Jie Swindlehurst, A. Lee Univ Calif Irvine Ctr Pervas Commun & Comp Irvine CA 92697 USA

ISBN: (纸本)9781479914814

We consider the distributed detection of a zero-mean Gaussian signal in an analog wireless sensor network with a fusion center (FC) configured with a large number of antennas. The transmission gains of the sensor nodes are optimized by minimizing the ratio of the log probability of detection (PD) and log probability of false alarm (PFA). We show that the problem is convex with respect to the squared norm of the transmission gains, and that a closed-form solution can be found using the Karush-Kuhn-Tucker conditions. Our results indicate that a constant PD can be maintained with decreasing sensor transmit gain provided that the number of antennas increases at the same rate. This is contrasted with the case of a single-antenna FC, where PD is monotonically decreasing with transmit gain. On the other hand, we show that when the transmit power is high, the single-and multi-antenna FC both asymptotically achieve the same PD upper bound.

关键词： Distributed detection Analog sensor networks Neyman-Pearson criterion Massive MIMO

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A GNSS Structural Interference Mitigation Technique Using Antenna array processing

A GNSS Structural Interference Mitigation Technique Using An...

引用

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

作者： Daneshmand, Saeed Jafarnia-Jahromi, Ali Broumandan, Ali Lachapelle, Gerard Univ Calgary Schulich Sch Engn Posit Locat & Nav PLAN Grp Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781479914814

Position solutions provided by Global Navigation Satellite Systems (GNSS) can be completely misled by structural interference or spoofing threats. An approach utilizing an antenna array is proposed in order to suppress spoofing attacks. The proposed method is based on the assumption that all spoofing signals are transmitted from a single point source. A spatial domain processing technique is proposed to extract the spoofing signal steering vector and consequently to discard the spoofing signals. This method is implemented before despreading and acquisition stage of a GNSS receiver. Hence, it does not impose a heavy computational load on the receiver operational process since it does not require any extensive search in the code and Doppler domains to separately despread individual authentic and spoofing signals. Moreover, the proposed method does not require any antenna array calibration process. This pre-despreading interference mitigation technique is further extended to maximize signal-to-noise ratio (SNR) of each individual authentic GNSS signal. Simulation results show that the proposed method effectively countermeasures spoofing attacks for a wide range of received spoofing power.

关键词： Spoofing disturbance suppression computer information security Antenna arrays Global Navigation Satellite System array processing signal to noise ratios

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Sparse-signal processing on information-based range grid

Sparse-signal processing on information-based range grid

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

作者： de Jong, Edwin Pribic, Radmila Univ Groningen Dept Appl Phys NL-9700 AB Groningen Netherlands Thales Nederland Delft Sensors Adv Dev Delft Netherlands

ISBN: (纸本)9781479914814

Radar obtains its parameters on an estimation grid whose cell size is related to resolution of underlying radar processing. Existing radar exploits a regular grid (i.e. constant resolution) although the resolution changes with stronger echoes at shorter ranges. We compute radar resolution from the intrinsic geometrical structure of data models that is characterized by the Fisher information. Based on this information-geometry approach, we create an estimation grid whose cells have a constant information distance. In addition, we explore how such an irregular estimation grid can suit radar processing in practice, and propose applying the information-based grid with the sparse-signal processing from compressive sensing. This novel radar processing is applied in an one-dimensional case of range estimation, with emphasis on the grid effects to the sensing incoherence. Results reveal the new flexibility in radar design.

关键词： sparse signals compressive sensing information geometry Fisher information distance radar resolution

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Network Design Via Modular Set Function Optimization in Localization Problems

Network Design Via Modular Set Function Optimization in Loca...

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

作者： Shames, Iman Summers, Tyler Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3052 Australia ETH Automat Control Lab Zurich Switzerland

ISBN: (纸本)9781479914814

We consider the problem of selecting anchors for sensor network localization to optimize a metric of the error covariance of the position estimates. We show that an interesting metric is a modular set function, which allows a globally optimal selection to be obtained using a simple greedy algorithm. We also consider a separate but related problem of choosing a subset of distance measurements between pairs of sensors to optimize a metric of the error covariance. We utilize again modularity properties of an associated set function to construct networks with desirable algebraic rigidity properties. The results are illustrated via numerical examples, which scale to problems beyond the capabilities of current state-of-the-art convex relaxation techniques.

关键词： Network design Modularity greedy algorithm Metric Metronidazole sensor networks Set (Psychology) Covariance Relaxation Techniques

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Statistical Angular Resolution Limit for array Radar with Ultrawideband Stochastic signals

Statistical Angular Resolution Limit for Array Radar with Ul...

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

作者： Zhou, Xiaoli Wang, Hongqiang Cheng, Yongqiang Qin, Yuliang Chen, Haowen Sun, Bin Natl Univ Def Technol Sch Elect Sci & Engn Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781479914814

The 2-D angular resolution limit for array radar with ultrawideband (UWB) stochastic signals based on the statistical resolution theory is presented in this paper. The signal model of monostatic array radar with circular array configuration and UWB stochastic signals is established, while the resolution of two closely spaced targets is modelled as a binary hypothesis test. The statistical angular resolution limit (SARL) for array radar with UWB stochastic signals is derived based on the generalized likelihood ratio test (GLRT) with given probabilities of false alarm and detection. The effects of detection parameters, transmit waveforms, array geometry, signal-to-noise ratio and parameters of target on SARL are analysed. Compared with the conventional resolution defined by ambiguity function, the SARL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.

关键词： array radar Ultra wideband technologies ANGULAR RESOLUTION resolution limit optimal criterion signals Resolving power Stochastic False alarms

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Direction of Arrival Estimation Using Nested Vector-sensor arrays Via Tensor Modeling

Direction of Arrival Estimation Using Nested Vector-Sensor A...

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

作者： Han, Keyong Nehorai, Arye Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781479914814

We propose a new class of nested vector-sensor arrays, via tensor modeling, which is capable of increasing the number of degrees of freedom (DOFs) for direction-of-arrival (DOA) estimation, compared with the uniform linear array (ULA). By using one component's information of the interspectral tensor, the proposed nested vector-sensor array can provide O(N-2) DOFs with only N physical sensors. To utilize the increased DOFs, a novel spatial smoothing approach is proposed, which preserves the data structure and avoids reorganization via tensor modeling. Further, we propose corresponding direction of arrival (DOA) estimation strategies. Based on the analytical results, we consider two main applications: electromagnetic (EM) vector sensors and acoustic vector sensors. We show that the DOA estimation performance is greatly improved due to the combination of the nested-array strategy and tensor modeling. The effectiveness of the proposed methods is verified through numerical examples.

关键词： Direction of arrival estimation nested array electromagnetic vector sensors acoustic vector sensors tensor

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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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A Sparse Regularization Technique for Source Localization with Non-uniform sensor Gain

A Sparse Regularization Technique for Source Localization wi...

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

作者： Weiss, Christian Zoubir, Abdelhak M. Tech Univ Darmstadt Germany Signal Proc Grp D-64283 Darmstadt Germany Grad Sch Computat Engn D-64293 Darmstadt Germany

ISBN: (纸本)9781479914814

A robust sparse regularization technique with applications to source localization in the presence of non-uniform gain distribution is presented. As a key component in sparse optimization, a proper choice of the regularization parameter is crucial. It renders high impact on the localization performance and has to account for any kind of model perturbation. Our proposed technique utilizes a statistical framework to provide a direct relation between the physical system parameters and the regularization parameter of the resulting optimization problem. It addresses the joint effects of sensor gain variations and noise. As a figure of merit, we consider the mean-squared error (MSE) between the perturbed measurements and the assumed underlying model. An upper bound of the MSE is attained in order to estimate the regularization parameter. The presented method shows good performance for moderate gain variances even in low SNR regimes.

关键词： sparse regularization model errors source localization robust model non-uniform sensor gain

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