Simultaneous Localization of Multiple Jammers and Receivers Using Probability Hypothesis Density

Bhamidipati, S. and Gao, G.
Citation:

To appear, IEEE ION PLANS, April 2018.

Abstract:

Now-a-days, the availability of low-cost jammers in the commercial market is increasing. There has been a rising risk of multiple jammers, instead of 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 GPS signals.

We propose a novel Simultaneous Localization of Multiple Jammers and Receivers (SLMR) algorithm by utilizing the GPS 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 Gaussian Mixture Probability Hypothesis Density (GM-PHD) Filter over a graphical framework, which is optimized using Levenberg-Marquardt minimizer to locate multiple jammers and receivers.

We validate our algorithm using both simulation and live GPS jamming data. Under different levels of simulated jamming strengths, we demonstrate that our SLMR locates unknown number of multiple jammers and network of receivers accurately. For field analysis, we utilize our data collected using 3 receivers during the DT-NAVFEST, a live GPS jamming event where multiple jammer scenarios were executed.

Publication Status:
To Appear
Publication Type:
Proceedings
Publication Date:
06/01/2018
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