Author(s)

Waleed Aldosari, Mohamed Zohdy

School of Engineering and Computer Science, Oakland University, Rochester Hills, USA.

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.

Jammer Detecting, Kalman Filter (KF), Linear Prediction (LP), Centroid Localization (CL), Jammer Received Signal Strength (JRSS), Multipath Signal, Indoor Location

Aldosari, W. and Zohdy, M. (2018) Localizing Jammer in an Indoor Environment by Estimating Signal Strength and Kalman Filter. Wireless Engineering and Technology, 9, 20-33. doi: 10.4236/wet.2018.92003.