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Target Tracking In Wireless Sensor Networks
Sunita Gola,Parikshit Munda
International Journal of Electronics and Computer Science Engineering , 2012,
Abstract: The problem being tackled here relates to the problem of target tracking in wireless sensor networks. It is a specific problem in localization. Localization primarily refers to the detection of spatial coordinates of a node or an object. Target tracking deals with finding spatial coordinates of a moving object and being able to track its movements. In the tracking scheme illustrated, sensors are deployed in a triangular fashion in a hexagonal mesh such that the hexagon is divided into a number of equilateral triangles. The technique used for detection is the trilateration technique in which intersection of three circles is used to determine the object location. While the object is being tracked by three sensors, distance to it from a fourth sensor is also being calculated simultaneously. The difference is that closest three sensors detect at a frequency of one second while the fourth sensor detects the object location at twice the frequency. Using the distance information from the fourth sensor and a simple mathematical technique, location of object ispredicted for every half second as well. The key thing to note is that the forth sensor node is not used for detection but only for estimation of the object at half second intervals and hence does not utilize much power. Using this technique, tracking capability of the system is increased.
Grid-based Mobile Target Tracking Mechanism in Wireless Sensor Networks  [cached]
Jui-Fa Chen,Ying-Hong Wang,Kuo-Feng Huang,Ting-Wei Chang
Journal of Communications , 2010, DOI: 10.4304/jcm.5.6.475-482
Abstract: The target tracking is one of the main issues in wireless sensor networks (WSNs). In the WSNs, the energy consumption is the most important factor for the network lifetime. In this paper, we utilize the advantage of the grid-based sensor networks to prolong the lifetime of the network. Therefore, we propose Grid-based Mobile Target Tracking Mechanism in Wireless Sensor Networks (GMTT). By the simulation results, we validated the proposed mechanism could efficiently reduce the energy consumption for target tracking.
Adaptive Sensor Activation Algorithm for Target Tracking in Wireless Sensor Networks
Wei Zhou,Weiren Shi,Xiaogang Wang,Kai Wang
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/515906
Abstract: Target tracking is an important application of wireless sensor networks where energy conservation plays an important role. In this paper, we propose an energy-efficient sensor activation protocol based on predicted region technique, called predicted region sensor activation algorithm (PRSA). The proposed algorithm predicts the moving region of target in the next time interval instead of predicting the accurate position, by analyzing current location and velocity of the target. We take these nodes within the predicted region as waiting-activation nodes and establish activation strategy. The fewest essential number of sensor nodes within the predicted region will be activated to monitor the target. Thus, the number of nodes that was involved in tracking the target will be decreased to save energy and prolong the network’s operational lifetime. The simulation results demonstrate the effectiveness of the proposed algorithm.
Multi-target Data Aggregation and Tracking in Wireless Sensor Networks  [cached]
Maarten Ditzel,Caspar Lageweg,Johan Janssen,Arne Theil
Journal of Networks , 2008, DOI: 10.4304/jnw.3.1.1-9
Abstract: This paper presents the results of a study on the effects of data aggregation for multi-target tracking in wireless sensor networks. Wireless sensor networks are normally limited in communication bandwidth. The nodes implementing the wireless sensor network are themselves limited in computing power and usually have a limited battery life. These observations are recognized and combined to come to efficient target tracking approaches. The main question to be answered is how to accurately track multiple targets crossing an area observed by a wireless sensor network, while limiting the amount of network traffic. Limiting the amount of network traffic reduces the required bandwidth and reduces the required energy. Various computing power aware data aggregation strategies are researched. They have been tested in a simulation environment and compared with each other. The results of the simulations clearly show the benefit of the new data aggregation strategies in terms of energy consumption and tracking accuracy.
A Survey on Target Tracking Techniques in Wireless Sensor Networks  [PDF]
K. Ramya,K. Praveen Kumar,V. Srinivas Rao
International Journal of Computer Science and Engineering Survey , 2012,
Abstract: Target Tracking as it moves through a sensor network has become an increasingly important application in Wireless Sensor Networks. This paper examines some of the target tracking techniques in use today. An analysis of each technique is presented along with it advantages, problems and possible improvements. There are seven main categories explored in this paper. The survey promotes overview of recent research literature along with their performance comparison and evaluation.
Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks  [PDF]
Xue Wang,Sheng Wang,Dao-Wei Bi,Jun-Jie Ma
Sensors , 2007, DOI: 10.3390/s7061001
Abstract: Target tracking is usually a challenging application for wireless sensor networks(WSNs) because it is always computation-intensive and requires real-time processing. Thispaper proposes a practical target tracking system based on the auto regressive movingaverage (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework.In the proposed framework, wireless sensor nodes act as peers that perform target detection,feature extraction, classification and tracking, whereas target localization requires thecollaboration between wireless sensor nodes for improving the accuracy and robustness.For carrying out target tracking under the constraints imposed by the limited capabilities ofthe wireless sensor nodes, some practically feasible algorithms, such as the ARMA modeland the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodesdue to their outstanding performance and light computational burden. Furthermore, aprogressive multi-view localization algorithm is proposed in distributed P2P signalprocessing framework considering the tradeoff between the accuracy and energyconsumption. Finally, a real world target tracking experiment is illustrated. Results fromexperimental implementations have demonstrated that the proposed target tracking systembased on a distributed P2P signal processing framework can make efficient use of scarceenergy and communication resources and achieve target tracking successfully.
A Scalable Multi-Target Tracking Algorithm for Wireless Sensor Networks
Songhwai Oh
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/938521
Abstract: Multi-target tracking is a representative real-time application of sensor networks as it exhibits different aspects of sensor networks such as event detection, sensor information fusion, multihop communication, sensor management, and real-time decision making. The task of tracking multiple objects in a wireless sensor network is challenging due to constraints on a sensor node such as short communication and sensing ranges, a limited amount of memory, and limited computational power. In addition, since a sensor network surveillance system needs to operate autonomously without human operators, it requires an autonomous real-time tracking algorithm which can track an unknown number of targets. In this paper, we develop a scalable real-time multi-target tracking algorithm that is autonomous and robust against transmission failures, communication delays, and sensor localization error. The algorithm is based on a rigorous probabilistic model and an approximation scheme for the optimal Bayesian filter. In particular, an extensive simulation study shows that there is no performance loss up to an average localization error of 0.7 times the separation between sensors and the algorithm tolerates up to 50% lost-to-total packet ratio and 90% delayed-to-total packet ratio. The proposed algorithm has been successfully applied to real-time multi-target tracking problems using wireless sensor networks.
Communication-aware algorithms for target tracking in wireless sensor networks  [PDF]
Bartlomiej Placzek
Computer Science , 2014, DOI: 10.1007/978-3-319-07941-7_7
Abstract: This paper introduces algorithms for target tracking in wireless sensor networks (WSNs) that enable reduction of data communication cost. The objective of the considered problem is to control movement of a mobile sink which has to reach a moving target in the shortest possible time. Consumption of the WSN energy resources is reduced by transferring only necessary data readings (target positions) to the mobile sink. Simulations were performed to evaluate the proposed algorithms against existing methods. The experimental results confirm that the introduced tracking algorithms allow the data communication cost to be considerably reduced without significant increase in the amount of time that the sink needs to catch the target.
An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks  [cached]
Zhijun Yu,Jianming Wei,Haitao Liu
EURASIP Journal on Advances in Signal Processing , 2009, DOI: 10.1155/2009/524145
Abstract: This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR) is chosen there as reference node for time difference of arrive (TDOA) calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.
Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks  [PDF]
Ying-Chih Chen,Chih-Yu Wen
Sensors , 2012, DOI: 10.3390/s121115308
Abstract: This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for thelocalization task. The proposed energy-efficient tracking algorithm allows each sub-clustermember to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for objectposition estimation.?
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