Title: Simultaneous Localization of Multiple Jammers and Receivers Using Probability Hypothesis Density
Author(s): Sriramya Bhamidipati, Grace Xingxin Gao
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 940 - 944
Cite this article: Bhamidipati, Sriramya, Gao, Grace Xingxin, "Simultaneous Localization of Multiple Jammers and Receivers Using Probability Hypothesis Density," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 940-944.
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Abstract: Now-a-days, the availability of low-cost jammers in the commercial market is increasing. Due to this, there has been a rising risk of multiple jammers, not just one. However, it is challenging to locate multiple jammers because the traditional way of jammer localization via multilateration only works for one jammer. In addition, during attack the positioning capability of the receivers is compromised due to their inability to track the GPS signals. We propose our Simultaneous Localization of Multiple Jammers and Receivers (SLMR) algorithm by utilizing the signal power received at a network of receivers. Our algorithm not only locates multiple jammers, but also utilizes the jammers as additional navigation signals for positioning the receivers. In particular, we design a non-linear Gaussian Mixture Probability Hypothesis Density Filter over a graphical framework, which is optimized using Levenberg-Marquardt minimizer. Under the presence of multiple simulated jammers, we validate that our proposed SLMR algorithm is able to simultaneously locate multiple jammers and receivers, even though the number of jammers is unknown.