Abstract
In this paper, we present a new method for tracking moving target in a wireless sensor network based on the combination of Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Generalized Extended Kalman Filter (GEKF) (NGEKF). GEKF is one of the best positioning algorithm but using all sensors in target tracking and high energy consumption are its drawbacks. To overcome these drawbacks, the sensor scheduling problem is considered as finding the optimal sequence of the sensors to estimate the target position. Since, we have used NSGA-II as the best approach to select a proper sensor group. In this method, tracking of a moving node with eight reference sensors is simulated using a multiplicative measurement noise model in two different noise conditions (low noise and high noise). Simulation results have demonstrated that not only energy consumption is reduced but also the positioning precision is improved.
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FayaziBarjini, E., Gharavian, D. & Shahgholian, M. Target tracking in wireless sensor networks using NGEKF algorithm. J Ambient Intell Human Comput 11, 3417–3429 (2020). https://doi.org/10.1007/s12652-019-01536-3
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DOI: https://doi.org/10.1007/s12652-019-01536-3