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检索条件"主题词=distributed detection"

共 624 条记录，以下是201-210 订阅

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detection Performance Comparison of Two-Sensor Parallel and Tandem distributed detection Networks

Detection Performance Comparison of Two-Sensor Parallel and ...

引用

IEEE Communications Society (ComSoc)/AFCEA/IEEE Military Communications Conference (MILCOM)

作者： Sun, Xingjian Cao, Lei Viswanathan, Ramanarayanan Univ Mississippi Dept Elect & Comp Engn University MS 38677 USA

ISBN: (纸本)9781665439565

For detecting deterministic signals corrupted by correlated Gaussian noise in a two-sensor distributed detection network, we study and compare the detection performance of the parallel topology with the tandem topology. It is known that under certain conditions, optimum sensor rules are in the form of single-threshold in both topologies. In other cases, by formulating the distributed detection problem as a nonlinear integer programming problem, suboptimal solutions for sensor rules are generated by the genetic algorithm. The analysis is also extended to 2-bit sensor reports to the fusion center.

关键词： Bivariate Gaussian distributed detection Genetic algorithm Parallel and tandem topology

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Robust distributed detection with limited range sensors

Robust distributed detection with limited range sensors

引用

32nd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Ermis, Erhan Baki Saligrama, Venkatesh Boston Univ Boston MA 02215 USA

ISBN: (纸本)1424407281

We consider a multi-target detection problem over a sensor network (SNET) with limited range sensors and communication constraints, which complements the decentralized detection problem where all sensors observe the same target. We consider sensing models where the signal power from targets undergoes a power-law decay. The task is to determine the locations of the targets while minimizing false alarms and communication between sensors. We extend the well-known FDR framework to solve the multi-target detection problem.

关键词： distributed detection non-ideal models robustness DTFDR multi-object detection

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Sequentially distributed detection and Data Fusion with Two Sensors

Sequentially Distributed Detection and Data Fusion with Two ...

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7th International Conference on Communications, Signal Processing, and Systems (CSPS)

作者： Li Cheng Harbin Engn Univ Coll Underwater Acoust Engn Harbin Peoples R China

ISBN: (纸本)9789811365041;9789811365034

The relationship of decision rule of sensor for each other is relevant to data fusion, so different topological networks of sensors usually results in different performances. This paper considers the sequential network fusion with two sensors in some detail and compares its performance with that of single detection and fusion. In this paper, the detection model is specified for binary hypotheses testing problem. In particular, this paper supposes that Bayesian risk cost of different decisions and the prior probability distribution of two hypotheses are known. Finally, this paper simulates the probabilities of error and Bayesian risk by these fusion rules with corresponding to different values of prior probabilities of two hypotheses by these fusion methods. And compared to single detection and fusion, the performance of sequential detection and fusion is better.

关键词： distributed detection Single detection and fusion Optimal fusion Sequential network fusion

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Serial distributed detection performance analysis in wireless sensor networks under noisy channel

Serial distributed detection performance analysis in wireles...

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5th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Yin, Liping Wang, Ying Yue, Dian-wu Dalian Maritime Univ Coll Informat Sci & Technol Dalian 116026 Peoples R China

ISBN: (纸本)9781424436927

In this paper, we consider the performance of serial distributed detection in wireless sensor networks (WSNs) under the assumption that the local decisions made by sensors are transmitted over noisy channels. Different from the parallel fusion, where the local results are directly sent to the fusion center, in serial fusion, local results are transmitted to the fusion center through multi-hop, short-range communications. We derive a fusion decision rule for serial signal detection, which takes the channel noise into account. And the simulation results show that the performance of serial distributed detection is inferior to that of parallel distributed detection, especially when the number of sensors is large. However, serial distributed detection utilizes short-range, multi-hop transmission, so it can be used as an energy-efficient distributed detection scheme for wireless sensor networks.

关键词： distributed detection serial WSN noisy channel energy conservation

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TRAFFIC ESTIMATION FOR MAC PROTOCOLS IN distributed detection WIRELESS SENSOR NETWORKS

TRAFFIC ESTIMATION FOR MAC PROTOCOLS IN DISTRIBUTED DETECTIO...

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20th European Signal Processing Conference (EUSIPCO)

作者： Aldalahmeh, Sami Ghogho, Mounir Univ Leeds Leeds LS2 9JT W Yorkshire England

ISBN: (纸本)9781467310680

A major challenge in designing MAC protocols for wireless sensor networks (WSN) is the uncertainty about the traffic offered by network, which usually forces conservative assumptions leading to a degradation in throughput and delay performance. Traffic estimation is discussed here in the context of the distributed detection WSNs (DD-WSNs). We approach this issue by first showing that the traffic has a Poisson distribution via stochastic geometry tools. Then the traffic is estimated via two algorithms, the least conditional maximum a priori (lcMAP) estimator and the regularized maximum likelihood estimator (rMLE). To measure the correlation between supplied communication resources and needed resources by the WSN, we propose the supply demand ratio (SDR) as a metric. Simulation results shows that both estimators achieve a performance close to the optimal MAP estimator under low channel SNR, hence transmission energy can be saved. Furthermore, the rMLE achieves the optimal SDR via choosing regularization factor value.

关键词： Traffic estimation distributed detection stochastic geometry wireless sensor networks

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A Chi-squared Approximation-based Weighting Method for distributed detection

A Chi-squared Approximation-based Weighting Method for Distr...

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IEEE Radar Conference (RadarConf)

作者： Lu, Jing Zhou, Shenghua Feng, Tieshan Tong, Zeyou Natl Lab Radar Signal Proc Xian Peoples R China Xidian Univ Xian 710071 Peoples R China China Acad Launch Vehicle Technol Beijing 100076 Peoples R China

ISBN: (纸本)9781728153681

In the distributed radar, signal fusion-based detection can exploit more information from local radars to yield higher detection performance, but most of existing signal fusion-based detection algorithms implicitly demand that the local test statistics to be fused have an identical kind of statistical distributions. Meanwhile, in the distributed generalized likelihood ratio test (GLRT), the weights over local test statistics dismiss after replacing unknown parameters with their maximum likelihood estimates and thus lead to an inappropriate equal-weighting test. In this paper, we consider how to fuse heterogeneous local test statistics with linear weights for a global test statistic in the distributed radar system. The global test statistic is approximated as a Chi-square distributed random variable and local weights are designed to maximize the probability of detection under a given false alarm rate. Numerical results show that better detection performance is achieved through this weighting method. Meanwhile, the Chi-square approximation performs well even in the right tail part of its distribution and thus the false alarm rate can be accurately and conveniently controlled.

关键词： distributed radar system distributed detection weighting method generalized likelihood ratio test

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CHANNEL AWARE SENSOR SELECTION IN distributed detection SYSTEMS

CHANNEL AWARE SENSOR SELECTION IN DISTRIBUTED DETECTION SYST...

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10th IEEE Workshop on Signal Processing Advances in Wireless Communications

作者： Ahmadi, Hamid R. Vosoughi, Azadeh Univ Rochester ECE Dept Rochester NY 14627 USA

ISBN: (纸本)9781424436958

We propose a novel censoring scheme for the distributed detection problem in a wireless sensor network (WSNs) with N sensors, where the channels between the sensors and the fusion center (FC) is subject to fading and noise. To achieve the best tradeoff between energy efficiency and detection reliability, the FC forms the maximum ratio combing (MRC) fusion rule by integrating the partial knowledge of fading channel state information (CSI) and the local sensor performance indices, finds the best set of K (K < N) sensors that maximizes the total detection probability in the Neyman-Pearson (NP) sense, and informs the selected sensors via one bit feedback. The FC learns the Rayleigh flat fading channels, utilizing training symbols sent by the sensors, via applying minimum mean square error (MMSE) channel estimator. Assuming the sensors employ BPSK to modulate their binary local decisions, we derive the MRC fusion rule that depends on the channel estimates and the sensors' performance indices, and incorporates the effect of channel estimation error. Simulation results are provided to support the analytical derivations.

关键词： Censoring channel estimation error distributed detection partial channel state information

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Cross-layer Communication Power Allocation for distributed detection in Wireless Sensor Network

Cross-layer Communication Power Allocation for Distributed D...

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4th IET International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN)

作者： Liu, Xiangyang Bai, Wenbin Cheng, Xiaoying Pan, Jin Xian Commun Inst Dept 1 Xian 710106 Shaanxi Peoples R China

ISBN: (纸本)9781849195072

For wireless sensor network specialized in distributed detection application, communication power of each sensor should dedicate to improve the total detection performance of the system and its utilization should be energy efficient. There is a balance point for communication power. Above the point, it is difficult to improve the system's detection performance. Below it, it is easy to improve system's detection performance by increasing the communication power of sensor node. Therefore, a method was given to guide the seeking of the balance point. Specifically, the objective is to determine the balance point according to the variations of global probability of detection versus channel SNR and allocate the communication power of each node according to the point. Numerical simulation shows that the method is practical and feasible.

关键词： power allocation cross-layer design distributed detection wireless sensor network Rayleigh-fading channel

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Online Linear Compression with Side Information for distributed detection of High Dimensional Signals 20

Online Linear Compression with Side Information for Distribu...

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20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Khanduri, Prashant Theagarajan, Lakshmi Narasimhan Varshney, Pramod K. Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Indian Inst Technol Palakkad Dept Elect Engn Palakkad 678557 Kerala India

ISBN: (纸本)9781538665282

In this paper, we propose a novel near-optimal linear compression strategy at the local sensors for the distributed detection of unknown high dimensional signals in a wireless sensor network (WSN). The WSN consists of multiple sensors distributed in a region of interest (RoI) and a fusion center (FC). The signal is assumed to be unknown to the local sensors and the FC;however, we assume that the sensors have some side information about the signal to be detected. Specifically, the sensors possess the knowledge of the signs of the individual components of the signal vector. Using this sign information, we design a linear compression strategy which is employed by the local sensors to compress the collected spatio-temporal data before forwarding it to the FC. We analytically show that the proposed compression strategy can achieve near-optimal error exponents. Further, the proposed compression strategy provides robust performance which is unaffected by the signal dimension as opposed to other state-of-the-art compression strategies whose error exponents are shown to decay with the signal dimension.

关键词： Wireless sensor networks distributed detection linear compression dimensionality reduction

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Radar sensor networks with distributed detection capabilities

Radar sensor networks with distributed detection capabilitie...

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2008 IEEE Radar Conference

作者： Pescosolido, Loreto Barbarossa, Sergio Scutari, Gesualdo Univ Roma La Sapienza INFO COM Dept Via Eudossiana 18 I-00184 Rome Italy

ISBN: (纸本)9781424415380

The goal of this work is to propose a distributed detection method for a network of radars interchanging their measurements through pulse-position modulation. The proposed approach does not need the presence of a fusion center and it is then fully decentralized. The approach is robust against node failures, as the only requirement to get the network gain is that the whole network remains connected, i.e., for every pair of nodes, there is a path, possibly composed of multiple hops, joining them. The decentralized approach is based on a distributed consensus mechanism. However, when conventional consensus algorithms are implemented over realistic channels, the receiver noise gives rise to an error on the final decision statistic that linearly increases with time. We avoid this inconvenient by properly modifying the consensus algorithm to make it suitable for communications over noisy channels. We analyze the performance of the proposed system considering the presence of both observation and communication noise present in the interaction among the radars. In particular, we show that even with a non-coherent integration, the whole system is able to achieve a sensitivity gain equal to the number of radars.

关键词： Radar sensor networks distributed detection consensus algorithms

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