Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

Otim, Timothy; Díez, Luis Enrique; Bahillo, Alfonso; López-Iturri, Peio; Falcone, Francisco

doi:10.20944/preprints201909.0266.v1

Cited by 17 publications

(14 citation statements)

References 27 publications

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“…Absolute mean position accuracy of popular on-body wearable positions using UWB TOF [7]. Only the head position can generate an error that is similar to tripod (best case scenario without any obstruction).…”

Section: Figurementioning

confidence: 99%

“…For instance, TAGs are positioned at the wrist, head, ankle for tracking of patients in hospitals, miners trapped in mines, and inmates in prisons, respectively. However, as investigated by [7] and [28], these positions have varying levels of accuracy [see - Fig. 1] mainly, because in NLOS each position leads to the different propagation characteristics of the localization signal.…”

Section: A Selection Of Body Wearable Sensor Positionmentioning

confidence: 99%

“…where z i,t is the measured range between the i th ANC at the position a x,i , a y,i , a z,i , and TAG with current position estimates at p x , p y and p z defined in (7). After predicting the next state, the measurements from sensors are used to correct the predicted state.…”

Section: Resampling Stratifiedmentioning

confidence: 99%

“…In both sets of simulations, the PF algorithm in the previous section is implemented with the setup configurations and parameter settings tabulated in Table 2. The coordinates of the first ground-truth points were the initial inputs into the state vector in (7). As illustrated in the previous section, the range were generated by adding the appropriate noise i.e., ψ i , S i to the Euclidean distance according to (14).…”

Section: Positioning Performance Simulationmentioning

confidence: 99%

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Towards Sub-Meter Level UWB Indoor Localization Using Body Wearable Sensors

et al. 2020

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Thanks 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. INDEX TERMS Body wearable sensors, Human body shadowing, Localization, Ranging, Ultrawideband, Time of Flight, Particle Filter I. INTRODUCTION With rapid developments of computer and miniaturization technologies, wearable sensors are becoming an important part of our daily lives. With a market expected to grow to $ 70 billion in 2025 [1], wearables are widely used in several applications such as in sport science, rehabilitation, medical monitoring, surveillance, among others [2]-[4]. Therefore, they can be attached to shoes, eyeglasses, earrings, clothing, gloves and watches, etc of the user of the wearable. Collecting precise user localization information is one of the salient capabilities of wearables [5]. In fact, according to [6], a sub-meter level of localization accuracy is envisaged for several wireless body area networks (WBAN). Currently, Global Navigation Satellite System (GNSS) is the most widely spread localization technology in outdoor environments.

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Section: Figurementioning

confidence: 99%

Section: A Selection Of Body Wearable Sensor Positionmentioning

confidence: 99%

Section: Resampling Stratifiedmentioning

confidence: 99%

Section: Positioning Performance Simulationmentioning

confidence: 99%

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Towards Sub-Meter Level UWB Indoor Localization Using Body Wearable Sensors

et al. 2020

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“…Depending on antenna design, or antenna position relative to external objects, it is possible to encounter frequency selective fading [ 35 , 36 ]. To analyze the impact of frequency fading in timestamp detection, consider UWB channel 9 with the spectral mask profile power spectral density, illustrated in Figure 8 , having a selective fading of

at carrier frequency and frequency decaying factor of

.…”

Section: Timestamp Estimation In the 802154z Standardmentioning

confidence: 99%

Timestamp Estimation in P802.15.4z Amendment

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Palade

Puşchiţă

et al. 2020

Sensors

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Due to the known issue that the ranging in the 802.15.4™-2015 standard is prone to external attacks, the enhanced impulse radio (EiR), a new amendment still under development, advances the secure ranging protocol by encryption of physical layer (PHY) timestamp sequence using the AES-128 encryption algorithm. This new amendment brings many changes and enhancements which affect the impulse-radio ultra-wideband (IR-UWB) ranging procedures. The timestamp detection is the base factor in the accuracy of range estimation and inherently in the localization precision. This paper analyses the key parts of PHY which have a great contribution in timestamp estimation precision, particularly: UWB pulse, channel sounding and timestamp estimation using ciphered sequence and frequency selective fading. Unlike EiR, where the UWB pulse is defined in the time domain, in this article, the UWB pulse is synthesized from the power spectral density mask, and it is shown that the use of the entire allocated spectrum results in a decrease in risetime, an increase in pulse amplitude, and an attenuation of lateral lobes. The paper proposes a random spreading of the scrambled timestamp sequence (STS), resulting in an improvement in timestamp estimation by the attenuation lateral lobes of the correlation. The timestamp estimation in the noisy channels with non-line-of-sight and multipath propagation is achieved by cross-correlation of the received STS with the locally generated replica of STS. The propagation in the UWB channel with frequency selective fading results in small errors in the timestamp detection.

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Ultra-Low-Power Range Error Mitigation for Ultra-Wideband Precise Localization

Angarano

Salvetti

Mazzia

et al. 2022

Lecture Notes in Networks and Systems

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Precise and accurate localization in outdoor and indoor environments is a challenging problem that currently constitutes a significant limitation for several practical applications. Ultra-wideband (UWB) localization technology represents a valuable low-cost solution to the problem. However, non-line-of-sight (NLOS) conditions and complexity of the specific radio environment can easily introduce a positive bias in the ranging measurement, resulting in highly inaccurate and unsatisfactory position estimation. In the light of this, we leverage the latest advancement in deep neural network optimization techniques and their implementation on ultra-low-power microcontrollers to introduce an effective range error mitigation solution that provides corrections in either NLOS or LOS conditions with a few mW of power. Our extensive experimentation endorses the advantages and improvements of our low-cost and power-efficient methodology.

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Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

Cited by 17 publications

References 27 publications

Towards Sub-Meter Level UWB Indoor Localization Using Body Wearable Sensors

Towards Sub-Meter Level UWB Indoor Localization Using Body Wearable Sensors

Timestamp Estimation in P802.15.4z Amendment

Ultra-Low-Power Range Error Mitigation for Ultra-Wideband Precise Localization

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