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IJSTR >> Volume 9 - Issue 6, June 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616


[Full Text]



Dr. G. Kavitha, Dr. G. Kalaimani



Sensor Network, Target Tracking, Hybrid Backpropagation Rate Bound (HBRB), Particle filtering, RSSI.



This paper focused on extending the earlier work of the sensor node selection process. Focus on more challenging issues by utilizing the effective quantized data for tracking the target sensor network by considering the selecting problem with the quantized sensor data. In the proposed, scheme received signal strength indicator (RSSI) this is based on the sensor node position. From the reference fixed nodes and tags are placed at the know positions by utilizing the radio signal radiations to generate an accurate model of signal propagation. To perform the optimized tracking system are dynamically selecting the subset of sensors. The one step-look ahead posterior method of Hybrid Backpropagation Rate Bound (HRBR) used to measure the sensor selection of state estimating the error are proposed. To compute the posterior method of HRBR are employed Particle filtering as well as estimating the target selection state. Simulation results show the proposed posterior HBRB based on the method outperforms by accurate target tracking by selecting a quantized node.



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