Localizing a jammer in an indoor environment in
wireless sensor networks becomes a significant research problem due to the ease
of blocking the communication between legitimate nodes. An adversary may emit
radio frequency to prevent the transmission between nodes. In this paper, we
propose detecting the position of the jammer indoor by using the received
signal strength and Kalman filter (KF) to reduce the noise due to the multipath
signal caused by obstacles in the indoor environment. We compare our work to
the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL).
We observed that the Kalman filter has better results when estimating the
distance compared to other algorithms.
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