Distributed detection has been studied for several decades. Nov 05, 2020 a data fusion methodology to process data coming from the airport surface detection equipment asde and modes multilateration sensors in airport surface is presented and evaluated. A clustered distributed detection system is configured by a fuzzy logic system and a fuzzy cmeans clustering algorithm. Wireless sensor network, cluster, distributed detection, fusion rule, stochastic geometry. I have actively pursued research on distributed detection and data fusion over the last decade, which ultimately interested me in writing this book. Distributed fault detection via particle filtering and decision fusion qi cheng, pramod k. A general block diagram of this application with one data fusion node is given in fig. The approach, called sensor network integration through pheromone fusion, or snipf, provides an endtoend demonstration that integrates selfcontained sensorcommunication nodes with novel swarming algorithms to detect foot and vehicular. Distributed signal detection and data fusion in multisensor systems have been extensively studied in last decades varshney 1996. A swarming agent architecture provides a distributed, decentralized, agentbased computing environment applicable to groundbased surveillance. His 1997 distributed detection and data fusion springerverlag, a culmination of his pioneering work that began in 1983, was the first book published. The book will also serve as a useful reference for practicing engineers and researchers. The glrtbased fusion rule significantly improves detection performance compared with the counting rule.
For example, barkat and varshney treat the problem of identifying events in a distributed radar system where each device makes a local detection decision and sends these results to a fusion center which then merges this data to make a. Pdf can addition of noise improve distributed detection. Belcastro nasa langley research center mail stop hampton, va 23681 celeste. Distributed detection and fusion in a large wireless. Optimal data fusion in multiple sensor detection systems ieee. Varshney was a james scholar, a bronze tablet senior, and a fellow. Varshney, 2005 distributed detection and fusion in a large wireless sensor network of random size, eurasip journal on wireless communications and.
Even though most multisensor data fusion applications have been developed relatively recently, the notion of data fusion has always been around. May 01, 2012 varshney literally wrote the book on distributed detection theory. Target detection with distributed terahertz sensors yang. Varshney, distributed detection with mul tiple sensors. Many papers focused on the problem of distributed detection with constrained system resources 710. Lateral movement detection using distributed data fusion. Fusing heterogeneous data for detection under nonstationary dependence, hao he, arun subramanian, pramod k. Distributed data fusion for networkcentric operations book cover. One example of such a system is distributed detection using multisensor networks as described by varshney in 3 and further discussed in 4, 5, 6. Klamer, decision fusion in a wireless sensor network with a large number of sensors, in proc. Department of electrical and computer engineering, department of computer science university of illinois at urbanachampaign email. Sensors free fulltext a softhard combination decision fusion. Dec 06, 2012 distributed detection and data fusion signal processing and data fusion kindle edition by varshney, pramod k download it once and read it on your kindle device, pc, phones or tablets.
Design of the parallel fusion network, consisting of a number of local detectors and a fusion center, is the subject of section 3. His 1997 distributed detection and data fusion springerverlag, a culmination of his pioneering work that began in 1983, was the first book. Professor varshney also serves as the director of case. Distributed detection in a large wireless sensor network. In the context of distributed detection, the byzantine sensor problem is. Fusion and filtering in distributed intrusion detection. Varshney, compressed distributed detection and estimation, data fusion in wireless sensor network. Pdf distributed detection and fusion in a large wireless.
He is the author of distributed detection and data fusion, published by springerverlag in 1997. His 1997 distributed detection and data fusion springerverlag, a culmination of his pioneering work that began in 1983, was the first book published on the topic and has been cited extensively. The global decision is obtained at the data fusion center based on and, or, and k n rule. Distributed detection with fusion was an active research. The signal detection optimization problem involving the determination of the stochastic resonance probability density function pdf for a. Fusionbased volcanic earthquake detection and timing in. Varshney, engin masazade, priyadip ray, and ruixin niu fundamentals of distributed estimation. Pdf ebooks can be used on all reading devices immediate ebook.
Sandell 6 first proposed a distributed detection algorithm in the case of two sensors. The distributed detection experiments with 2, 3, and 180 sensors are performed. A distributed compressed sensing for images based on block measurements data fusion. It is often argued that accuracy or other similar generalization performance metrics must be sacrificed in order to gain interpretability. While the need for distributed data compression is still the dominant issue, during. Learning the quality of sensor data in distributed.
Fusion centre fc dar det slutliga beslutet tas om en forandring i aktuella parametrar har intraffat eller ej. Workshop on human interpretability in machine learning whi. Varshney, fellow, ieee abstract data fusion and distributed detection have been studied extensively, and numerous results have been obtained during the past two decades. Distributed data fusion for networkcentric operations 1st. With the recent proliferation of serviceoriented architectures soa, cloud computing technologies, and distributed interconnected systems, distributed fusion is taking on a larger role in a variety of applicationsfrom environmental monitoring and crisis management to intelligent buildings and defense. Can addition of noise improve distributed detection performance. Distributed detection and fusion in a large wireless sensor. Jun 25, 2018 an answer using distributed detection and data fusion theory authors. Related work although distributed detection has been a very active. It is assumed that the reader has been exposed to detection theory. Distributed detection and data fusion signal processing. Particularly, the design of optimal and suboptimal local decision and fusion rules has been extensively investigated. Distributed detection in the presence of byzantine attacks core.
This fusion rule can achieve a very good systemlevel detection performance even at very low. Further results on distributed bayesian signal detection. Blind adaptive decision fusion for distributed detection. Such arguments, however, fail to acknowledge that the overall decision. A bayesian sampling approach to decision fusion using. No scalable and efficiency in wireless sensor network. On noiseenhanced distributed inference in the presence of byzantines, mukul gagrani, pranay sharma, venkata sriram siddhardh nadendla, aditya vempaty, and pramod varshney. Distributed fault detection via particle filtering and. Magestate i channelaware distributed detection in wireless. Us7480395b2 decentralized detection, localization, and.
Optimal fusion rule for distributed detection in clustered wireless. As artificial intelligence is increasingly affecting all parts of society and life, there is growing recognition that human interpretability of machine learning models is important. Distributed detection in tree topologies with byzantines. Conventional radar signal detection is carried out by a single radar and is based on conventional statistical decision theory. Electrical engineering and computer science college of. More recently, niu et al studied the problem in a distributed sensor system, where a decision fusion rule was developed based on the total number of detections made by local sensors. An answer using distributed detection and data fusion theory authors. In this paper, we show how the linear dimensionality reduction of heterogeneous data speci. A number of special cases including conditionally independent local observations and identical detectors are considered. Michels department of eecs jhm technologies 335 link hall, syracuse university p.
Varshney s distributed detection methods provide a more effective means of target detection by using a cooperative team of multiple sensors compared to using a single radar or sonar element. Sensor network research includes various detection, tracking, and localization applications 14, ranging from geophysical studies 57, to health monitoring systems 810, and military applications 11. T tsao, m slamani, p varshney, d weiner, h schwarzlander, s borek. Dec 01, 2006 a distributed detection and decision fusion scheme is proposed for a wireless sensor network wsn consisting of a large number of sensors. Distributed detection and data fusion signal processing and. Distributed detection and fusion in a large wireless sensor network. Drawing on the work of leading experts around the world, distributed data fusion for. I have actively pursued research on distributed detection and data fusion over the last decade, which.
Energy harvesting, wireless sensor networks, distributed detection, cognitive. Target detection is one of the primary tasks in radar signal processing. Pdf distributed change detection based on a consensus. Distributed detection and its applications with energy. A data fusion methodology to process data coming from the airport surface detection equipment asde and modes multilateration sensors in airport surface is presented and evaluated.
Distributed detection theory and data fusion december 21, 199yfinal, may 1, 1996 sept. Buy this book isbn 9781461219040 digitally watermarked, drmfree included format. Performing organization names and aooresses syracuse university electrical engineering and computer science dept. Pdf distributed detection and data fusion researchgate. Varshney department of electrical engineering and computer science, syracuse university, 335 link hall, syracuse, ny 2441240, usa email. A statistical signal processing perspective, iet international book series on sensing. Distributed detection in wireless sensor networks pramod k. This concept has been applied to numerous fields and new applications are being explored constantly. It is assumed that networks, which are in the focus of many researchers, all the nodes in the network can generate local decision is distributed detection e. Jan 01, 2014 in distributed detection systems, the detection performance relies heavily on the knowledge of the joint pdf under hypotheses h 0 and h 1. The application driver for this research was distributed radar with a central command fusion centre. Varshney 7 derived an optimum fusion rule when binary local decisions were given in a multiple sensor detection problem.
He has served as a consultant to several major companies. At the fusion center, the total number of detections reported by local sensors are employed for hypothesis testing. Decision fusion with correlated observations has been studied in 46. Here, we consider the problem of estimating joint pdf under h 1 for distributed cfar detection systems varshney, 1997 that has great practical relevance. Simulation results are presented for the cases when partial or complete channel knowledge are available at the fusion center. Professor varshney has two broad areas of current research. A bayesian sampling approach to decision fusion using hierarchical models biao chen, member, ieee, and pramod k. Data fusion aims to obtain information of greater quality 4. Lateral movement detection using distributed data fusion ahmed fawaz. Despite the progress achieved over the past two decades, it has not been shown whether this phenomenon plays a role in distributed detection. He has expertise in distributed sensor networks and data fusion, detection and estimation theory, wireless communications, physical layer security, image processing, and radar. For thz applications, the noise distribution of thz radar system is measured to validate the availability of the distributed cacfar detection. The recent emergence of wireless sensor networks wsns has added a new dimension to dd system design. In 3, the optimum decision fusion rule has been obtained under the conditional independence assumption.
Use features like bookmarks, note taking and highlighting while reading distributed detection and data fusion signal processing and data fusion. Distributed data fusion for networkcentric operations. Optimal data fusion in multiple sensor detection systems. Can addition of noise improve distributed detection.
Energyefficient decision fusion for distributed detection in. Target detection with distributed terahertz sensors yang yu. Distributed detection and data fusion springerlink. The optimal chair varshney decision fusion rule for dis tributed detection has. Sandell have recently treated the bayesian detection problem with distributed sensors. W du, j deng, ys han, pk varshney, j katz, a khalili. We also apply the technique of serial data fusion with early stopping to.
Social learning for resilient data fusion against data falsification attacks. This book represents the best body of thinking on the emerging topic of distributed data fusion, including varied aspects of the problem itself and a multitude of approaches to address the. Tsitsiklis 31, varshney 32, viswanathan and varshney 33, and blum et al. We consider the problem of decision fusion in a distributed detection. Data fusion is required for intrusion resiliency to obtain a holistic view of the system state that can be acted upon without overwhelming the analyses. For example, optimal decision fusion for multisensor detection systems was studied in 1980s by chair and varshney 11 and thomopoulos et al. Robust distributed maximum likelihood estimation with. These studies were focused on devising the optimal decision and fusion strategies that maximize the system performanceof a given network.
Ab the problem of distributed bayesian signal detection is addressed. Distributed data fusion for networkcentric operations 1st edition. A witnessbased approach for data fusion assurance in. Multisensor data fusion is a key enabling technology in which information from a number of sources is integrated to form a unified picture 1. We present an optimum data fusion structure given the detectors. Varshney, prashant khanduri, pranay sharma, shan zhang, pramod k. Varshney, optimal data fusion in multiple sensor detection systems, ieee trans. Effective malicious node detection and data fusion under. Stochastic resonance, distributed detection, decision fusion. N2 the problem of distributed bayesian signal detection is addressed. In this paper we used flexible distributed data fusion solutions that can easily adapt to. The problem is reformulated and a new design approach is presented that allows the use of efficient optimization algorithms.
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