In this study, we investigate the problem of detecting time epochs when zero-velocity updates can be applied in a foot-mounted inertial navigation (motion tracking) system. We examine three commonly used detectors: the acceleration moving variance detector, the acceleration magnitude detector, and the angular rate energy detector. We demonstrate that all detectors can be derived within the same general likelihood ratio test framework given the different prior knowledge about the sensor signals. Further, by combining all prior knowledge, we derive a new likelihood ratio test detector. Subsequently, we develop a methodology to evaluate the performance of the detectors. Employing the developed methodology, we evaluate the performance of the detectors using leveled ground, slow (approx. 3 km/h) and normal (approx. 5 km/h) gait data. The test results are presented in terms of detection versus false-alarm probability. Our preliminary results shows that the new detector performs marginally better than the angular rate energy detector that outperforms both the acceleration moving variance detector and the acceleration magnitude detector.

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-A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RFbased inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

This paper aims to evaluate the performance gains that can be obtained by introducing cooperative localization in an indoor firefighter localization system, through the use of scenariobased simulations. Robust and accurate indoor localization for firefighters is a problem that is not yet resolved. Foot-mounted inertial navigation systems (INS) have been examined for first responder localization, but they have an accumulating position error that grows over time. By using ultrawideband (UWB) ranging between the firefighters and combining range measurements with position and uncertainty estimates from the foot-mounted INS via a cooperative localization approach it is possible to reduce the position error significantly.An error model for the position estimates received from single and dual foot-mounted INS is proposed based on experimental results, and it contains a scaling error which depends on the distance travelled and a heading error which grows linearly over time. The position error for dead-reckoning systems depends on the type of movement. Similarly, an error model for the UWB range measurements was designed where the range measurements experience a bias and variance, which is determined by the number of walls between the transmitter and receiver.By implementing these error models in a scenario-based simulation environment it is possible to evaluate the performance gain of different cooperative localization algorithms. A centralized extended Kalman Filter (EKF) algorithm has been implemented, and the position accuracy and heading improvements are evaluated over a smoke diving operation scenario. The cooperative localization scheme reduces the position errors by up to 70% in a scenario where a three-person smoke diver team performs a search and rescue operation.