Interfering Mobile Target Motion Planning in Wireless Sensor Networks

In surveillance related Wireless Sensor Networks (WSNs) applications, mobile targets can utilize intelligent motion planning in robotics to avoid detection, which could impose great threats on the sensor field. In this paper, we propose countermeasures against mobile target motion planning. The proposed solution enables the sensors to interfere the localization and map generation on mobile targets so as to expose them in the sensor field. We compare the behaviors of a mobile target in naive mode, smart mode with Simultaneous Location And Mapping (SLAM) and interfered mode where sensor nodes use different puzzle algorithms to disturb it. The simulation results show that the puzzle algorithms can interfere SLAM on mobile targets and enhance the target detection performance in a WSN. We also build an experimental testbed with Iris motes and a mobile robot to validate our solution.