Academic
Publications
Sequential Monte Carlo Radio-Frequency tomographic tracking

Sequential Monte Carlo Radio-Frequency tomographic tracking,10.1109/ICASSP.2011.5947223,Yunpeng Li,Xi Chen,Mark Coates,Bo Yang

Sequential Monte Carlo Radio-Frequency tomographic tracking   (Citations: 2)
BibTex | RIS | RefWorks Download
Radio Frequency (RF) tomographic tracking is the process of tracking moving targets by analyzing changes of attenuation in wireless transmissions. This paper presents a novel sequential Monte Carlo (SMC) method for RF tomographic tracking of a single target using a wireless sensor network. The algorithm incorporates on-line Expectation Maximization (EM) to estimate model parameters. Based on experimental measurements, we introduce a new measurement model for the attenuation caused by a target. We assess performance through numerical simulation and demonstrate that it significantly outperforms previous RF tomographic tracking procedures. The measurement model describes the relationship between the true state and the measurement values. In this paper, we propose a pixelfree measurement model for the attenuation caused by a target moving between a transmitter s and receiver r. The model is motivated by experimental data recorded in a sensor network deployed in an
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
Sort by: