Otim, Timothy
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Otim
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Timothy
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Estadística, Informática y Matemáticas
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Publication Open Access Impact of body wearable sensor positions on UWB ranging(IEEE, 2019) Otim, Timothy; Bahillo, Alfonso; Díez, Luis E.; López Iturri, Peio; Falcone Lanas, Francisco; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónIn recent years, Ultrawideband (UWB) has become a very popular technology for time of flight (TOF) based localization and tracking applications but its human body interactions have not been studied yet extensively. Most UWB systems already proposed for pedestrian ranging have only been individually evaluated for a particular wearable sensor position. It is observed that wearable sensors mounted on or close to the human body can raise line-of-sight (LOS), quasi-line-of-sight (QLOS), and non-line-of-sight (NLOS) scenarios leading to significant ranging errors depending on the relative heading angle (RHA) between the pedestrian, wearable sensor, and anchors. In this paper, it is presented that not only does the ranging error depend on the RHA, but on the position of the wearable sensors on the pedestrian. Seven wearable sensor locations namely, fore-head, hand, chest, wrist, arm, thigh and ankle are evaluated and a fair comparison is made through extensive measurements and experiments in a multipath environment. Using the direction in which the pedestrian is facing, the RHA between the pedestrian, wearable sensor, and anchors is computed. For each wearable sensor location, an UWB ranging error model with respect to the human body shadowing effect is proposed. A final conclusion is drawn that among the aforementioned wearable locations, the fore-head provides the best range estimate because it is able to set low mean range errors of about 20 cm in multipath conditions. The fore-head's performance is followed by the hand, wrist, ankle, arm, thigh, and chest in that order.Publication Open Access Effects of the body wearable sensor position on the UWB localization accuracy(MDPI, 2019) Otim, Timothy; Díez, Luis E.; Bahillo, Alfonso; López Iturri, Peio; Falcone Lanas, Francisco; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónOver the years, several Ultrawideband (UWB) localization systems have been proposed and evaluated for accurate estimation of the position for pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence, the accuracy obtained is subject to a given wearable sensor position. This paper is focused on studying the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, forehead, and hand, on the localization accuracy. According to our results, the forehead and the chest provide the best and worst body sensor location for tracking a pedestrian, respectively. With the wearable sensor at the forehead and chest position, errors lower than 0.35 m (90th percentile) and 4 m can be obtained, respectively. The reason for such a contrast in the performance lies in the fact that, in non-line-of-sight (NLOS) situations, the chest generates the highest multipath of any part of the human body. Thus, the large errors obtained arise due to the signal arriving at the target wearable sensor by multiple reflections from interacting objects in the environment rather than by direct line-of-sight (LOS) or creeping wave propagation mechanism.Publication Open Access Towards sub-meter level UWB indoor localization using body wearable sensors(IEEE, 2020) Otim, Timothy; Bahillo, Alfonso; Enrique Díez, Luis; López Iturri, Peio; Falcone Lanas, Francisco; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónThanks to its ability to provide sub-meter level positioning accuracy, Ultrawideband (UWB) has found wide use in several wireless body area network (WBAN) applications such as ambient assisted living, remote patient management and preventive care, among others. In spite of the attractiveness of UWB, it is not possible to achieve this level of accuracy when the human body obstructs the wireless channel, leading to a bias in the Time of Flight (TOF) measurements, and hence a detection of position errors of several meters. In this paper, a study of how a sub-meter level of accuracy can be achieved after compensating for body shadowing is presented. Using a Particle Filter (PF), we apply UWB ranging error models that take into consideration the body shadowing effect and evaluate them through simulations and extensive measurements. The results show a significant reduction in the median position error of up to 75 % and 82 % for simulations and experiments, respectively, leading to the achievement of a sub-meter level of localization accuracy.