Target tracking in internet of things based on sensing subtraction and compressed sensing

Abstract

A target tracking algorithm based on compressed sensing and sensing subtraction was proposed in this paper. We presented the concept of sensing subtraction, combined sensing subtraction and compressed sensing, sparsely sampled the distributed sensing information in Internet of Things (IoT), and reconstructed sensing subtraction matrix by compressed sensing theory, and then located and tracked moving target by sensing subtraction method. Simulation results show that the proposed algorithm recovers sensing data well, and the sparse sampling strategy reduces network communication traffic and improves the energy-efficiency of system.