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Decentralized Underwater Target Detection and Localization

IEEE SENSORS JOURNAL 2021年第2期21卷 2385-2399页

作者： Hu, Li Wang, Xiaodong Wang, Shilian Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China Columbia Univ Dept Elect Engn New York NY 10027 USA

This article considers the detection and localization of an underwater target by a sensor network consisting of an active acoustic source, multiple distributed passive sensors, and a fusion center (FC). As the reflected signal from the target could arrive with various directions, a set of collaborative sensors increase the detection probability. We first introduce the centralized generalized likelihood ratio test (GLRT) detector that utilizes the perfect information from sensor observations. In the case of a successful detection, this detector also provides the maximum likelihood estimate (MLE) of the target location. In order to meet the stringent power and bandwidth constraints in underwater sensor networks, we then propose the decentralized GLRT scheme, where sensor observations are quantized into a few bits of data and then transmitted to the FC. The quantization thresholds are optimized by maximizing the Kullback-Leibler divergence between the null and alternative hypotheses. While the existing scan statistic based detector assumes that the sensor array which can observe the reflected signal, is contained in a rectangle area, our proposed decentralized GLRT scheme incorporates the signal reflection model into the detector, and estimates the area of affected sensor array, thus achieving higher accuracy. Finally, we extend the decentralized GLRT detector to the scenario where data are transmitted over error-prone channels, which is not considered in the existing studies. Numerical results demonstrate that the decentralized GLRT detector with only a small number of quantization bits can achieve a similar detection performance as the centralized GLRT.

关键词： Detectors Object detection quantization (signal) Sensor fusion Maximum likelihood estimation Underwater target detection and localization underwater sensor network (USN) generalized likelihood ratio test (GLRT) multilevel quantization decentralized detection

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Quantizer Design for Distributed GLRT Detection of Weak Signal in Wireless Sensor Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2015年第4期14卷 2032-2042页

作者： Gao, Fei Guo, Lili Li, Hongbin Liu, Jun Fang, Jun Harbin Engn Univ Coll Informat & Commun Engn Harbin 150001 Peoples R China Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Univ Elect Sci & Technol China Natl Key Lab Sci & Technol Commun Chengdu 611731 Peoples R China

We consider the problem of distributed detection of a mean parameter corrupted by Gaussian noise in wireless sensor networks, where a large number of sensor nodes jointly detect the presence of a weak unknown signal. To circumvent power/bandwidth constraints, a multilevel quantizer is employed in each sensor to quantize the original observation. The quantized data are transmitted through binary symmetric channels to a fusion center where a generalized likelihood ratio test (GLRT) detector is employed to perform a global decision. The asymptotic performance analysis of the multibit GLRT detector is provided, showing that the detection probability is monotonically increasing with respect to the Fisher information (FI) of the unknown signal parameter. We propose a quantizer design approach by maximizing the FI with respect to the quantization thresholds. Since the FI is a nonlinear and nonconvex function of the quantization thresholds, we employ the particle swarm optimization algorithm for FI maximization. Numerical results demonstrate that with 2- or 3-bit quantization, the GLRT detector can provide detection performance very close to that of the unquantized GLRT detector, which uses the original observations without quantization.

关键词： Wireless sensor networks multilevel quantization distributed detection particle swarm optimization algorithm (PSOA)

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Multibit Decentralized Detection Through Fusing Smart and Dumb Sensors Based on Rao Test

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2020年第2期56卷 1391-1405页

作者： Cheng, Xu Ciuonzo, Domenico Rossi, Pierluigi Salvo Armed Police Coll PAP Dept Informat & Commun Engn Chengdu 610213 Peoples R China Univ Naples Federico II I-80138 Naples Italy Kongsberg Digital N-3189 Horten Norway

We consider decentralized detection of an unknown signal corrupted by zero-mean unimodal noise via wireless sensor networks. We assume the presence of both smart and dumb sensors: the former transmit unquantized measurements, whereas the latter employ multilevel quantizations (before transmission through binary symmetric channels) in order to cope with energy and/or bandwidth constraints. The data are received by a fusion center, which relies on a proposed Rao test, as a simpler alternative to the generalized likelihood ratio test (GLRT). The asymptotic performance analysis of the multibit Rao test is provided and exploited to propose a (signal-independent) quantizer design approach by maximizing the noncentrality parameter of the test-statistic distribution. Since the latter is a nonlinear and nonconvex function of the quantization thresholds, we employ the particle swarm optimization algorithm for its maximization. Numerical results are provided to show the effectiveness of the Rao test in comparison to the GLRT and the boost in performance obtained by (multiple) threshold optimization. Asymptotic performance is also exploited to define detection gain measures allowing to assess gain arising from use of dumb sensors and increasing their quantization resolution.

关键词： Intelligent sensors quantization (signal) Wireless sensor networks Sensor phenomena and characterization Optimization Probability density function Decentralized detection (DD) multilevel quantization Rao test threshold optimization wireless sensor networks (WSNs)

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Optimization of multilevel Error Diffusion Based on Pixel Distribution 4th

Optimization of Multilevel Error Diffusion Based on Pixel Di...

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4th China Academic Conference on Printing and Packaging (CACPP)

作者： Li, Yukun Wang, Yigang Li, Shi Hangzhou DianZi Univ Sch Media & Design Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9789811000720;9789811000706

To improve the visual effect of multilevel halftone image, a multilevel quantization interval division method based on pixel distribution and a dynamic error limits method are presented. First, the impact of quantization intervals on the mean square error (MSE) of the image is analyzed. According to that, quantization intervals optimization is presented to make the number of pixels in each interval equal based on the pixel distribution of original image. That optimization leads to uneven quantization intervals. Then, a dynamic error limit of error diffusion method is utilized to minimize the statistical error between the resulted image and the original one. The results show that the peak signal-to-noise ratio (PSNR) of proposed method is increased about 2 dB compared with the Floyd-Steinberg algorithm. And the efficiency of our quantization is nearly twice of Octree quantization algorithm. The resulted images receive acceptable visual effect.

关键词： multilevel halftone Error diffusion multilevel quantization Dynamic error

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multilevel QUANTIZER DESIGN FOR DECENTRALIZED DETECTION IN WIRELESS SENSOR NETWORKS

MULTILEVEL QUANTIZER DESIGN FOR DECENTRALIZED DETECTION IN W...

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IEEE China Summit & International Conference on Signal and Information Processing

作者： Gao, Fei Guo, Lili Li, Hongbin Liu, Jun Fang, Jun Harbin Engn Univ Coll Informat & Commun Engn Harbin Peoples R China Stevens Inst Technol ECE Dept Hoboken NJ 07030 USA Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China UESTC Natl Key Lab Commun Chengdu Peoples R China

ISBN: (纸本)9781479919482

We consider the problem of distributed detection involving multiple sensor nodes to jointly detect the presence of an unknown signal. To circumvent power/bandwidth constraints, a multilevel quantizer is employed in each sensor to quantize the original observation. The quantized data are transmitted through distortion channels to a fusion center where a generalized likelihood ratio test (GLRT) detector is employed to perform a global decision. We propose a quantizer design approach by maximizing the Fisher information with respect to the quantization thresholds. Numerical results demonstrate that with 2- or 3-bit quantization, the GLRT detector can provide detection performance very close to that of the unquantized GLRT detector which uses the original observations without quantization.

关键词： Wireless sensor networks multilevel quantization distributed detection

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Enhancing Channel Reciprocity of Secret Key Generation Scheme by Using Modified Polynomial Regression Method

Enhancing Channel Reciprocity of Secret Key Generation Schem...

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Joint International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM) / 11th AUN/SEED-Net Regional Conference on Computer and Information Engineering (RCCIE)

作者： Yuliana, Mike Wirawan Suwadi Endroyono Suryani, Titiek Inst Teknol Sepuluh Nopember Fac Elect Technol Dept Elect Engn Surabaya Indonesia

ISBN: (纸本)9781538675090

Channel reciprocity is a very crucial component in establishing a secret key generation scheme. Non-simultaneous measurement conditions and noise cause low channel reciprocity, which is indicated by measurements of channel parameters that are not perfectly identical in both users. The stages of the secret key generation scheme that directly quantifies the channel parameters will have an impact on the high difference in the bits produced. In this paper, we propose the use of Modified Polynomial Regression methods to enhance channel reciprocity that would lower the rate of key disagreement between two users. We also propose a combination of the Modified Polynomial Regression method with multilevel quantization to overcome the trade-off between performance parameters, i.e. the key disagreement rate and key generation rate. The test results conducted in an indoor wireless environment show that our proposed scheme has better performance compared to the existing scheme in terms of increasing reciprocity, key generation rate and decreasing key disagreement rate. The resulting secret key has also fulfilled the randomness requirements set by the National Institutes of Standards and Technology statistical suite.

关键词： channel reciprocity secret key generation Modified Polynomial Regression multilevel quantization the performance parameter

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Multi-bit Decentralized Detection of a Weak Signal in Wireless Sensor Networks with a Rao test 23

Multi-bit Decentralized Detection of a Weak Signal in Wirele...

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23rd IEEE International Conference on Digital Signal Processing (DSP)

作者： Cheng, Xu Ciuonzo, Domenico Rossi, Pierluigi Salvo Armed Police Coll PAP Chengdu Sichuan Peoples R China Network Measurement & Monitoring NM2 Srl Naples Italy Kongsberg Digital AS Trondheim Norway

ISBN: (纸本)9781538668122;9781538668115

We consider decentralized detection (DD) of an unknown signal corrupted by zero-mean unimodal noise via wireless sensor networks (WSNs). To cope with energy and/or bandwidth constraints, we assume that sensors adopt multilevel quantization. The data are then transmitted through binary symmetric channels to a fusion center (FC), where a Rao test is proposed as a simpler alternative to the generalized likelihood ratio test (GILT). The asymptotic performance analysis of the multi-bit Rao test is provided and exploited to propose a (signal-independent) quantizer design. Numerical results show the effectiveness of Rao test in comparison to (ART and the performance gain obtained by threshold optimization.

关键词： Decentralized detection (DD) multilevel quantization Rao test wireless sensor networks (WSNs)

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Maximum average entropy-based quantization of local observations for distributed detection

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DIGITAL SIGNAL PROCESSING 2022年第0期123卷 103427-103427页

作者： Wahdan, Muath A. Altinkaya, Mustafa A. Izmir Inst Technol Fac Engn Dept Elect & Elect Engn Izmir Turkey

In a wireless sensor network, multilevel quantization is necessary to find a compromise between minimizing the power consumption of sensors and maximizing the detection performance at the fusion center (FC). The previous methods have been using distance measures such as J-divergence and Bhattacharyya distance in this quantization. This work proposes a different approach based on the maximum average entropy of the output of the sensors under both hypotheses and utilizes it in a Neyman-Pearson criterion-based distributed detection scheme to detect a point source. The receiver operating characteristics of the proposed maximum average entropy (MAE) method in quantizing sensor outputs have been evaluated for multilevel quantization both when the sensor outputs are available error-free at the FC and when non-coherent M-ary frequency shift keying communication is used for transmitting MAE based multilevel quantized sensor outputs over a Rayleigh fading channel. The simulation studies show the success of the MAE in the cases of both error-free fusion and where the effect of the wireless channel has been incorporated. As expected, the performance improves as the level of quantization increases and with six-level quantization approaches the performance of non-quantized data transmission. (C)& nbsp;2022 Elsevier Inc. All rights reserved.

关键词： Distributed detection Decentralized detection multilevel quantization Information theoretic distance measures Wireless sensor networks

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multilevel QUANTIZER DESIGN FOR DECENTRALIZED DETECTION IN WIRELESS SENSOR NETWORKS

MULTILEVEL QUANTIZER DESIGN FOR DECENTRALIZED DETECTION IN W...

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IEEE China Summit and International Conference on Signal and Information Processing

作者： Fei Gao Lili Guo Hongbin Li Jun Liu Jun Fang Coll. of Inf. & Commun. Eng. Harbin Eng. Univ. Harbin China

ISBN: (纸本)9781479919499

关键词： Wireless sensor networks multilevel quantization Distributed detection

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