Is cooperative localization in wireless body area networks accurate enough for motion capture applications?

The applications of Wireless Body Area Networks (WBANs) encompass several uses such as home activity monitoring, postural rehabilitation, or sportive gesture recording, which require motion capture. Such motion capture can be realized by acquiring the positions of on-body nodes, which can be deduced from device-to-device distance measurements. In distributed wireless networks, this ranging is generally realized by measuring characteristics of the radio channel between couples of nodes, such as the signal attenuation on data packets, or their time of flight. These methods have a limited accuracy, though, because of the variability of the radio channel, and produce positions estimations that are usually too coarse for motion capture. In this paper, we present a cooperative solution that improves the localization of such wireless on-body nodes in a Local Coordinate System (LCS). We adapt a cooperative Extended Kalman Filter (EKF) algorithm fed by inter-node range measurements through impulse Radio-Ultra Wideband (IR-UWB) Time Of Arrival (TOA) estimation. The cooperative approach relies on the multiplicity of links that results from the presence of multiple nodes on the body. Such collaboration provides spatial diversity and measurements redundancy that have the potential to improve the positioning accuracy. To evaluate this approach, we developed a complete protocol stack from the physical up to the localization application layer, in a discret-event simulator (WSNet). A Time Division Multiple Access (TDMA) Medium Access Control (MAC) is developed for maintaining the peer-to-peer handshake transactions between devices. Simulation results for various connectivity levels, show interesting gains on the average location precision of each node.