Cooperative localization using foot-mounted inertial navigation and ultrawideband ranging: a simulation study
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
This report aims to evaluate the performance gains that can be obtained by introducing cooperative localization in an indoor firefighter localization system, through the use of scenario-based simulations. Robust and accurate indoor localization for firefighters is a problem that is not yet resolved. Harsh environmental conditions and stringent size, weight, power and cost (SWaP-C) requirements are obstacles that have to be considered. Foot-mounted inertial navigation systems (INS) are being evaluated 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 these dead-reckoning systems depend upon the type of movement. Hence, the error model allows for varying position errors in order to mimic different movements that occur in typical firefighter operations. 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 the 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. The scenarios are designed to provide realistic movements of smoke divers in a search and rescue operation. A centralized extended Kalman Filter (EKF) algorithm has been implemented, and the position accuracy and heading improvements obtained through cooperative localization are evaluated over a smoke diving operation scenario.
Using the proposed cooperative localization scheme it was possible to reduce the position errors by up to 70% in a designed scenario, where a three-person smoke diver team performs a search and rescue operation in two small apartments, where varying sight- and heat conditions sometimes forces the firefighters to search close to the floor by crawling.
Place, publisher, year, edition, pages
2014. , 49 p.
UPTEC F, ISSN 1401-5757 ; 14046
IdentifiersURN: urn:nbn:se:uu:diva-234992OAI: oai:DiVA.org:uu-234992DiVA: diva2:758650
Swedish Defence Research Agency, FOI
Master Programme in Engineering Physics
Nyberg, TomasSternad, Mikael