Abstract
In wireless sensor networks, spatially distributed nodes provide location-dependent sensor information. Therefore, knowledge about the 3D position of all nodes is crucial for the numerous applications that require autonomous mobility. Furthermore, to acquire the nodes' poses and the complete 6D network constellation, the 3D orientation of each node is also required. While many theoretical localization concepts exist for wireless sensor networks, there is still a lack of reliable system and localization concepts which enable robust real-time tracking in real-world scenarios. Therefore, we present a system approach based on an advanced 24 GHz wireless local positioning system, providing distance and angle measurements between pairs of nodes. Furthermore, an extended Kalman filter based localization algorithm is proposed, which evaluates these measurements to track the time varying 6D poses of all nodes in the network. Because only relative measurements are available, one node is chosen to define a joint navigation system. Hence, the proposed system works without any previously installed infrastructure or prior information of the network. The system and localization algorithm are validated by measurements performed in a mobile wireless sensor network comprising six nodes in an indoor scenario with strong multipath propagation. However, despite the challenging environment, the system allows for a stable and accurate 6D pose estimation of all robots in the network with 3D positioning root mean square errors of 6 to 15cm.
Highlights
Wireless sensor networks (WSNs) comprise multiple nodes, each equipped with one or more sensors, with applications that include industrial monitoring, logistics, automotive safety [1], [2], and exploration by mobile robots in hazardous or global positioning system (GPS)-denied areas [3], [4]
We present a system concept for full 6D tracking of multiple nodes in a mobile cooperative WSN, as illustrated in Fig. 1, by evaluating the node-to-node distance and angle measurements provided by secondary radar systems in an extended Kalman filter (EKF)
The localization does not require any prior information on the network and relies only on relative cooperative angle of arrival (AOA) and round-trip time of flight (RTOF) measurements between the nodes, provided by secondary frequency modulated continuous wave (FMCW) radars
Summary
Wireless sensor networks (WSNs) comprise multiple nodes, each equipped with one or more sensors, with applications that include industrial monitoring, logistics, automotive safety [1], [2], and exploration by mobile robots in hazardous or global positioning system (GPS)-denied areas [3], [4]. The authors of [4] and [13] used an EKF with multiple anchors to track a single node using RTOA and AOA in 6D and in 3D (2D position and heading), respectively While these works did successfully perform localization tasks, all of them reduced the problem complexity by not estimating the orientation, tracking only a single target, using multiple anchor nodes at known locations, or a combination of these. We present a system concept for full 6D tracking of multiple nodes in a mobile cooperative WSN, as illustrated, by evaluating the node-to-node distance and angle measurements provided by secondary radar systems in an EKF.
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