Publicação
Development of autonomous and reusable devices for 3d localization and communication, integrated into protective clothing for high temperatures and in unstructured environments
| Resumo: | The availability of a reliable and accurate indoor positioning system (IPS) for emergency responders during on-duty missions is regarded as an essential tool to improve situational awareness of both the emergency responders and the incident commander. This tool would facilitate the mission planning, coordination and accomplishment, as well as, decrease the number of on-duty deaths. Due to the absence of global positioning system (GPS) signal in indoor environments, many other signals and sensors have been proposed for indoor usage. However, the challenging scenarios faced by emergency responders imply explicit restrictions and requirements on the design of an IPS, making the use of some technologies, techniques, and methods inadequate on these scenarios. Alongside with the position information, monitoring physiological and environmental parameters is also vital to improve the emergency responders’ safety. So, to monitor all these parameters, a cyber -physical system (CPS), designated by PROTACTICAL CPS, is proposed. This system aims to improve the decision making at several emergency responders’ operation stages (e.g., emergency responder, teams, and incident commander), and is capable of detecting, in real-time, life-threatening scenarios. Different sensor nodes, called node-PROTACTICAL, are integrated into a personal protective equipment (PPE) to acquire the desired parameters. Two wireless networks are used to send the acquired information to the incident commander, a wireless body sensor network (WBSN) and an Ad-Hoc network. The former relies on the ZigBee technology and is responsible for managing the communication with the nodes-PROTACTICAL. On the other hand, the Ad-Hoc network relies on Wi-Fi technology and is responsible for the communication between the PPE and the incident commander. For the estimation of the emergency responder’s position, a hybrid IPS integrated into the PROTACTICAL CPS is proposed. This IPS is based on an indirect remote positioning topology and is composed of three modules (radio signal-based, IMU-based, and data fusion). The present work focuses essentially on the design and evaluation of an IPS for emergency responders. This involves the definition of the specific requirements, selection of technologies, evaluation of positioning methods and their combination to overcome the limitations imposed by the emergency responders’ scenarios. For the radio signal-based module, the ultra-wideband (UWB) technology was selected because of its immunity to noise and high accuracy of the ranging measurements. A measurement campaign was carried out to assess the performance of the ranging measurements under different propagation conditions and, the worst scenario occurs when the signal is blocked by the human body. So, non-line-ofsight (NLOS) identification and error mitigation algorithms are proposed to reduce the ranging measurement error under NLOS conditions. Then, four positioning algorithms are compared and evaluated under different conditions (e.g., environments with different propagation conditions, static and dynamic target, and with or without NLOS influence due to the human body). The previous study confirmed some weaknesses that can be compensated by another positioning method and thus a pedestrian dead reckoning (PDR) system based on foot-mounted inertial sensors is proposed and evaluated. This system is capable of, simultaneously, estimating the distance travelled and the emergency responder’s attitude. An extended Kalman filter (EKF) aided by zero velocity updates (ZUPT) is implemented to refine the emergency responder’s position and heading. Finally, a data fusion algorithm based on a Kalman filter is proposed to combine the UWB and PDR estimates. The data fusion algorithm is assisted by a decision-making algorithm that rejects the UWB position estimation when two or more ranging measurements are in NLOS. The performance of the data fusion method is assessed with three UWB positioning algorithms. |
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| Autores principais: | Ferreira, André Filipe Gonçalves |
| Assunto: | Data Fusion Emergency Responders Indoor Positioning Systems Kalman Filter Pedestrian Dead Reckoning Unknown and Unstructured Environments UWB Ambientes Desconhecidos e Não Estruturados Equipas de Emergência Filtro de Kalman Fusão de Dados Sistemas de Posicionamento Indoor |
| Ano: | 2018 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The availability of a reliable and accurate indoor positioning system (IPS) for emergency responders during on-duty missions is regarded as an essential tool to improve situational awareness of both the emergency responders and the incident commander. This tool would facilitate the mission planning, coordination and accomplishment, as well as, decrease the number of on-duty deaths. Due to the absence of global positioning system (GPS) signal in indoor environments, many other signals and sensors have been proposed for indoor usage. However, the challenging scenarios faced by emergency responders imply explicit restrictions and requirements on the design of an IPS, making the use of some technologies, techniques, and methods inadequate on these scenarios. Alongside with the position information, monitoring physiological and environmental parameters is also vital to improve the emergency responders’ safety. So, to monitor all these parameters, a cyber -physical system (CPS), designated by PROTACTICAL CPS, is proposed. This system aims to improve the decision making at several emergency responders’ operation stages (e.g., emergency responder, teams, and incident commander), and is capable of detecting, in real-time, life-threatening scenarios. Different sensor nodes, called node-PROTACTICAL, are integrated into a personal protective equipment (PPE) to acquire the desired parameters. Two wireless networks are used to send the acquired information to the incident commander, a wireless body sensor network (WBSN) and an Ad-Hoc network. The former relies on the ZigBee technology and is responsible for managing the communication with the nodes-PROTACTICAL. On the other hand, the Ad-Hoc network relies on Wi-Fi technology and is responsible for the communication between the PPE and the incident commander. For the estimation of the emergency responder’s position, a hybrid IPS integrated into the PROTACTICAL CPS is proposed. This IPS is based on an indirect remote positioning topology and is composed of three modules (radio signal-based, IMU-based, and data fusion). The present work focuses essentially on the design and evaluation of an IPS for emergency responders. This involves the definition of the specific requirements, selection of technologies, evaluation of positioning methods and their combination to overcome the limitations imposed by the emergency responders’ scenarios. For the radio signal-based module, the ultra-wideband (UWB) technology was selected because of its immunity to noise and high accuracy of the ranging measurements. A measurement campaign was carried out to assess the performance of the ranging measurements under different propagation conditions and, the worst scenario occurs when the signal is blocked by the human body. So, non-line-ofsight (NLOS) identification and error mitigation algorithms are proposed to reduce the ranging measurement error under NLOS conditions. Then, four positioning algorithms are compared and evaluated under different conditions (e.g., environments with different propagation conditions, static and dynamic target, and with or without NLOS influence due to the human body). The previous study confirmed some weaknesses that can be compensated by another positioning method and thus a pedestrian dead reckoning (PDR) system based on foot-mounted inertial sensors is proposed and evaluated. This system is capable of, simultaneously, estimating the distance travelled and the emergency responder’s attitude. An extended Kalman filter (EKF) aided by zero velocity updates (ZUPT) is implemented to refine the emergency responder’s position and heading. Finally, a data fusion algorithm based on a Kalman filter is proposed to combine the UWB and PDR estimates. The data fusion algorithm is assisted by a decision-making algorithm that rejects the UWB position estimation when two or more ranging measurements are in NLOS. The performance of the data fusion method is assessed with three UWB positioning algorithms. |
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