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Maximum Privacy under Perfect Utility in sensor Networks 11

Maximum Privacy under Perfect Utility in Sensor Networks

引用

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

作者： Wang, Chong Xiao Tay, Wee Peng Song, Yang Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781728119465

Each node or sensor in a network makes a local observation that is linearly related to a set of public and private parameters. The nodes send their observations to a fusion center to allow it to estimate a set of public parameters. However, the fusion center may also abuse this information to estimate other private parameters. To prevent leakage of the private parameters, each node first sanitizes its local observation using a local privacy mechanism before transmitting it to the fusion center. We consider the maximum privacy achievable under perfect utility in terms of the Cramer-Rao lower bounds. We propose a method to maximize the estimation error for inferring the private parameters while ensuring the estimation error for inferring the public parameters remains unchanged after sanitizing the sensors' measurements.

关键词： estimation privacy sensor networks decentralized system Cramer-Rao lower bound

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sensor scheduling using a 0-1 mixed integer programming framework

Sensor scheduling using a 0-1 mixed integer programming fram...

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4th ieee sensor array and multichannel signal processing workshop

作者： Chhetri, Amit S. Morrell, Darryl Papandreou-Suppappola, Antonia Arizona State Univ Dept Elect Engn Tempe AZ 85281 USA Arizona State Univ Dept Engn Tempe AZ 85281 USA

ISBN: (纸本)1424403081

In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 01 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

关键词： sensor networks

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Listener-Position Adaptive Crosstalk Cancelation Using A Parameterized Superdirective Beamformer 10

Listener-Position Adaptive Crosstalk Cancelation Using A Par...

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

作者： Ma, Xiaohui Hohnerlein, Christoph Ahrens, Jens Dynaudio AS DK-8660 Skanderborg Denmark Berlin Inst Technol Ernst Reuter Pl 7 D-10587 Berlin Germany Chalmers Univ Technol S-41296 Gothenburg Sweden Aarhus Univ Dept Engn Finlandsgade 22 DK-8200 Aarhus N Denmark

ISBN: (纸本)9781538647523

We present a method for cancelation of the acoustic crosstalk between the ears of a listener using a linear loudspeaker array. This allows for controlling the signals that arise at listener's ear independently of each other so that binaural cues can be imposed. We employ superdirective near-field beamforming (SDB) over the vast part of the frequency range. Allowing the listener to move in front of the array requires the computation of a new SDB solution for each possible position of the listener, which is a computationally expensive procedure. We show that the beamformer weights exhibit a very smooth evolution for listening positions along a line parallel to the array. This makes it straightforward to parameterize pre-computed beamformer weights with a few parameters for each frequency. Upon realtime execution, the beamformer weights can be determined efficiently for any arbitrary position along the listener contour from the parameters with negligible error. Simulation results show that the proposed beamformer provides a higher channel separation than previously published solutions while maintaining robustness.

关键词： Loudspeakers Ear Crosstalk array signal processing Robustness sensor arrays"

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Integrated waveform design for an Integrated Radar and Communication System with a Uniform Linear array 11

Integrated waveform design for an Integrated Radar and Commu...

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

作者： Jiang, Mengchao Liao, Guisheng Yang, Zhiwei Liu, Yongjun Chen, Yufeng Li, Haichuan Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China

ISBN: (纸本)9781728119465

To reduce the consumption of spectrum and hardware resource, two methods are proposed to design the integrated waveform that can satisfy the requirements for both radar and communication. First, a linear superposition (LS) method is proposed to design the transmit waveforms of a uniform linear array (ULA). In the far field of the ULA, the designed transmit waveforms can simultaneously synthesize the desired radar and communication waveforms in different directions. However, the designed waveforms usually have high peak-to-average power ratio (PAPR). Then, an alternative projection (AP) method is proposed to reduce the PAPR of the transmit waveforms. The AP method can devise the waveforms with constant modulus. Both the proposed methods can perform radar and communication function in different directions. Finally, several simulation results are given to verify the effectiveness of the proposed methods.

关键词： waveform design integrated radar and communication spectral sharing waveform synthesis

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A Blind Direction of Arrival and Mutual Coupling Estimation Scheme for Nested array 11

A Blind Direction of Arrival and Mutual Coupling Estimation ...

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

作者： Shen, Jinqing Li, Jianfeng Zhu, Beizuo Ye, Changbo Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum Minisny Ind & Informat Technol Nanjing 211106 Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

Generally, nested array (NA) is susceptible to mutual coupling due to the dense subarray, which seriously degrades the performance. To address this issue, we design an array switching-based scheme to achieve the blind direction of arrival (DOA) and mutual coupling estimation in this paper. Specifically, by exploiting the inherent sparse structural characteristics of NA, we first switch the sparse subarray on to perform initial DOA estimation, which enables to offer the well-performed estimates free from the severe mutual coupling effect. Subsequently, the unambiguous angles are determined with low complexity by utilizing the received signal of the whole NA. Furthermore, the contaminated steering vector is reconstructed and a quadratic optimization problem is established to estimate the mutual coupling coefficients. Finally, re-estimation is conducted to obtain the refined estimates. Numerical simulations demonstrate the superiority of the proposed scheme.

关键词： nested array direction of arrival mutual coupling array switching

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Blind channel estimation in multicode CDMA system with antenna array

Blind channel estimation in multicode CDMA system with anten...

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2nd ieee sensor array and multichannel signal processing workshop

作者： Melvasalo, M Koivunen, V Helsinki Univ Technol Signal Proc Lab FIN-02015 Helsinki Finland

ISBN: (纸本)0780375513

This paper addresses the problem of blind channel estimation in a multicode DS-CDMA system in multipath environment using antenna array at the receiver. Long code CDMA system model is employed. Multicode transmission is used to provide a higher data rate to a mobile user and receiver antenna array improves the signal to interference and noise ratio (SINR). First we extend blind multicode channel estimation methods to CDMA receiver with multiple antennas. Subspace channel estimation is employed with two different pre-processing schemes. We also extend the principal component channel estimation method used for antenna array CDMA receiver to a multicode model. The performances of the proposed methods are compared in simulation using mean square error measure and bit error rates. Different numbers of interfering users are used in simulations and the impact of code selection is considered.

关键词： signal to noise ratio

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Receiver Antenna Allocation for Joint Sensing and Communications 13

Receiver Antenna Allocation for Joint Sensing and Communicat...

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

作者： van der Werf, Ids Leus, Geert Chepuri, Sundeep Prabhakar Delft Univ Technol Delft Netherlands Indian Inst Sci Bengaluru India

ISBN: (纸本)9798350344820;9798350344813

We describe the problem of joint sensing and communications (JSAC) using an antenna array where some antennas are used for sensing and some others for communications. The problem is to jointly optimize the sensing and communications performance at the receive side through respectively the CramerRao bound (CRB) on the source angles and the variance of the sources after applying a minimum variance distortionless response (MVDR) beamformer. Both criteria are derived under a two-source scenario and optimized for any position of the two sources. Here one of the sources is considered the source of interest, while the other one models the interference. The performance criteria for sensing and communications are mathematically similar and depend only on the angular difference between the two sources. As a result, they can be elegantly combined and jointly optimized. Our findings are corroborated by simulations under different parameter settings.

关键词： Convex optimization Cramer-Rao bound sensor selection joint sensing and communication multi-target estimation

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Compressive Sensing based Direction-of-Arrival Estimation in MIMO Radars in Presence of Strong Jamming via Blocking Matrix 10

Compressive Sensing based Direction-of-Arrival Estimation in...

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

作者： Liu, Beiyi Gui, Guan Matsushita, Shin-ya Xu, Li Akita Prefectural Univ Dept Elect & Informat Syst Akita 0150055 Japan Nanjing Univ Posts & Telecommun Coll Telecommun & Informat Engn Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781538647523

The performances of the traditional anti-jamming DOA methods for the colocated MIMO radar system will be seriously deteriorated when the number of the snapshots is small. In this paper, a compressive sensing (CS)-based anti-jamming DOA estimation with only a few snapshots is proposed. In the new DOA estimation, the information on the direction of strong jamming is used to construct a blocking matrix that can block the jamming component effectively. Hence, only the desired signal component is left after preprocessing with the blocking matrix. Then, the DOA estimation problem with a blocking matrix is formulated as a sparse recovery problem, and it is solved by the orthogonal matching pursuit (OMP) algorithm. We compare the proposed method with the traditional CS-based method and the traditional anti-jamming DOA methods. Numerical results demonstrate that the proposed method outperforms the traditional methods.

关键词： Jamming Direction-of-arrival estimation Estimation MIMO radar Sparse matrices sensor arrays Matching pursuit algorithms"

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Compressed Sensing Radar Surveillance Networks

Compressed Sensing Radar Surveillance Networks

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

作者： Schmidt, Aurora Harley, Joel B. Moura, Jose M. F. Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

ISBN: (纸本)9781467310710

We study the problem of sensor fusion in a simplified radar surveillance application. A potentially large number of narrowband radars with isotropic antennas monitor a two-dimensional area for an unknown number of targets. We use techniques from compressive sensing to distribute efficient projections of network observations, allowing for reconstruction of the target scene using a single snapshot of sensor data. We avoid the use of a fusion node, allowing all radars to individually estimate target locations after iterative communication with neighboring sensors. We study the robustness of the discretization of continuous target locations, comparing estimation performance of basis pursuit reconstruction methods to a sparse estimator based on a model-robust formulation. We test the approach on simulated scenarios, showing tradeoffs in the resolution of target localization as well as the communication bandwidths required for this inter-radar cooperation scheme.

关键词： distributed radar sensor fusion consensus compressed sensing noise-aware basis pursuit model robust estimation

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Multi-bit Decentralized Detection of a Non-cooperative Moving Target Through a Generalized Rao Test 11

Multi-bit Decentralized Detection of a Non-cooperative Movin...

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

作者： Cheng, Xu Ciuonzo, Domenico Rossi, Pierluigi Salvo Wang, Xiaodong Shi, Longfei Natl Univ Def Technol CEMEE Changsha Peoples R China Armed Police Coll PAP Beijing Peoples R China Univ Naples Federico II Naples Italy NTNU Trondheim Norway Columbia Univ ECE New York NY 10027 USA

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

We consider decentralized detection (DD) of an uncooperative moving target via wireless sensor networks (WSNs), measured in zero-mean unimodal noise. To address energy and bandwidth limitations, the sensors use multi-level quantizers. The encoded bits are then reported to a fusion center (FC) via binary symmetric channels. Herein, we propose a generalized Rao (G-Rao) test as a simpler alternative to the generalized likelihood ratio test (GLRT). Further, the asymptotic performance of a trajectory-clairvoyant (multi-bit) Rao test is leveraged to develop an offline and per-sensor quantizer design. Simulations show the appeal of G-Rao test with respect to the GLRT, and the gain in detection by using multiple bits for quantization.

关键词： Decentralized detection Generalized Rao test GLRT multibit quantizer wireless sensor networks

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