Adaptive Control and Reconfiguration of Mobile Wireless Sensor Networks for Dynamic Multi-Target Tracking
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
We propose the adaptive control and reconfiguration schemes for mobile wireless sensor networks (MWSN) to achieve timely and accurate mobile multi-target tracking (MMTT) with cost-effective energy consumption. In particular, our proposed schemes can detect the mobile multi-targets' random appearance and disappearance in the clutter environments with high accuracy and low energy cost. We develop the optimal mutual-information based techniques to adaptively control the reconfiguration of the proposed MWSN by designing the Distributed/Decentralized Probability Hypothesis Density (DPHD) filtering algorithms. By dynamically adjusting the sensors' states, including their positions and activations, our schemes can efficiently improve the observabilities of the tracked multi-targets. We further analyze the asymptotic performance of our proposed schemes by deriving the upper-bounds of the detection-error probabilities. Also presented are the performance analyses which validate and evaluate our proposed adaptive control and reconfiguration schemes for MWSN in terms of the multi-target states estimation accuracy, the energy-consumption efficiency, and the robustness to the interference/noise. 2011 IEEE.
