ETH - Indoor Positioning & Indoor Navigation


16:00 - 16:15	Johannes Schmid at KIT, Wilhelm Stork, Klaus D. Müller-Glaser: Infrastructure-independent person localization with IEEE 802.15.4 WSN In this paper, a new concept for infrastructure independent person localization by means of a wireless sensor network (WSN) in combination with a pedestrian dead reckoning device (PDR) is proposed. In an arbitrary in- and outdoor environment, each nodes position estimation is initialized upon its deployment by means of a MEMS based PDR device if no GPS signal is available at the deployment position and time (anchor node deployment). Every anchor node broadcasts its (estimated) position as well as an uncertainty parameter in regular intervals, and mobile nodes without inertial navigation capabilities (carried on the body of moving persons in the area of interest, on-body nodes) estimate their positions based on the received signal strength (RSS) and uncertainty information of all received packets. Additionally, a GPS-equipped subset of the anchor nodes allows for an improvement of the position estimation as soon as a GPS fix can be obtained at the deployment position. The uncertain position estimation of the networked nodes is enhanced during runtime based on the RSS values of packets received from neighboring nodes within one hop communication range.

16:15 - 16:30	Paolo Gamba, Emanuele Goldoni, Alberto Savioli (presenting author, University of Pavia): Performance Evaluation of an Hybrid RSSI-Inertial Localization Algorithm in IEEE 802.15.4 Wireless Sensor Networks In this work we present an evaluation of the performance of a range-based hybrid localization algorithm based on the Received Signal Strength Indicator (RSSI) and inertial data applied in a real world WSN. As can be found in literature, RSSI-based localization algorithms exhibit low accuracy due to the variability of the radio signal. Adding inertial information, such as accelerations values obtained by an Inertial Measurement Unit (IMU), in combination with an implementation of a dedicated data-fusion algorithm, it can provide a higher level of accuracy. In order to evaluate the accuracy gain, we compared the results obtained in the field using only RSSI data against the values provided with a hybrid localization system in the same environment.

16:30 - 17:00	Andreas Fink (presenting author, at University of Rostock), Helmut Beikirch, Matthias Voß, Christian Schröder: RSSI-based Indoor Positioning using Diversity and Inertial Navigation A substantial criterion with the use of wireless communication is the missing location information of the mobile participants. RSSI (Received Signal Strength Indicator)-based localization techniques are an easy and well known method to predict the position of an unknown node in indoor environments whereas additional methods are required for a sufficient accuracy. The distance-pending path loss is affected by strong variations, especially appearing as frequency specific signal dropouts. A diversity concept with redundant data transmission in different frequency bands can reduce the dropout probability. Not only the availability of the communication and the positioning, but also the accuracy of the localization can be increased with the diversity concept. Another improvement can be reached by a sensor fusion of RSSI-based position data with an Inertial Navigation System. First experimental results with miniaturized transceiver prototypes show that a good performance for precision and availability can also be reached with low infrastructural costs.

17:00 - 17:15	Ghazaleh Panahandeh (presenting author), Isaac Skog, Magnus Jansson: Calibration of the Accelerometer Triad of an Inertial Measurement Unit, Maximum Likelihood Estimation and Cramér-Rao Bound In this paper, a simple method to calibrate the accelerometer cluster of an inertial measurement unit (IMU) is proposed. The proposed method does not rely on using a mechanical calibration platform that rotates the IMU into different precisely controlled orientations. Although the IMU is rotated in different orientations, these orientations do not need to be known. Assuming that the IMU is stationary at each orientation, the norm of the input is considered equal to the gravity acceleration. As the orientations of the IMU are unknown, the calibration of the accelerometer cluster is stated as blind system identification problem where only the norm of the input to the system is known. Under the assumption that the sensor noises have white Gaussian distribution the system identification problem is solved using the maximum likelihood estimation method. The accuracy of the proposed calibration method is compared with the Cramér-Rao bound for the considered calibration problem.

17:15 - 17:30	Dave Zachariah (presenting author, at KTH), Magnus Jansson: Joint calibration of an inertial measurement unit and coordinate transformation parameters using a monocular camera An estimation procedure for calibration of a low-cost inertial measurement unit (IMU), using a rigidly mounted monocular camera, is presented. The parameters of a sensor model that captures misalignments, scale and offset errors are estimated jointly with the IMU-camera coordinate transformation parameters using a recursive Sigma-Point Kalman Filter. The method requires only a simple visual calibration pattern and moreover provides figures of merit of the estimates. A simulation study indicates the filters ability to reach subcentimeter and subdegree accuracy.

17:30 - 17:45	Ezzaldeen Edwan (presenting author, at University of Siegen), Fernando Suarez, Jieying Zhang, Otmar Loffeld: DCM based Attitude Estimation Using Low-cost IMU Aided by Distributed Accelerometers and Magnetometers In this paper, we describe the development and analyze the performance of a low-cost attitude and heading reference system (AHRS) realized through micro electrical mechanical system (MEMS) inertial sensors and magnetometers. Due to the poor performance of low-cost MEMS gyros and accelerometers, we aid a traditional inertial measurement unit (IMU) with low-cost distributed accelerometers. By doing so, we get two achievements: the first is an improvement in the angular rate knowledge because of the angular information computed from distributed accelerometers. The second improvement is in the acceleration knowledge as a result of the redundancy of accelerometers. Two cascaded filters will be used to estimate the attitude. The first filter fuses the angular information coming from the distributed accelerometers and the gyros and returns the angular rate. The second filter fuses the angular rate, specific force and magnetometer measurements and returns the estimated elements of the direction cosine matrix (DCM). Simulation results and real time experiments will be used to verify the efficiency of our approach.

17:45 - 18:00	Jeroen Hol (presenting author, at Xsens Technologies) and Maaike Elzinga: UWB/IMU Tracking Validation using an Optical System In this paper we report the results of a validation study of a 6DOF tracking system combining Ultra-Wideband measurements with low-cost MEMS inertial measurements. The tightly coupled system estimates position as well as orientation of the sensor unit. The comparison with the results from an optical system show robust and continuous tracking in a realistic indoor positioning scenario.

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