Non-Line-of-Sight Identification for Indoor Positioning Using Ultra-WideBand Radio Signals

Yan, Junlin; Tiberius, C.C.J.M.; Bellusci, Giovanni; Janssen, G. C. A. M.

doi:10.1002/navi.31

Cited by 10 publications

(9 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Marano et al (2010) and (Wymeersch et al 2012) propose machine learning based methods to classify received signals into LOS and NLOS signals. NLOS detection method based on statistical hypothesis testing are proposed in Yan et al 2013) where both time-and received signal strength-based UWB signal measurements are used. While some of the above approaches provide quite accurate identification, but a full channel impulse response is required in almost all of the methods which is inconvenient for real-time positioning based on simple mobile devices.…”

Section: Uwb Signal Ranging Errorsmentioning

confidence: 99%

“…The ranging accuracy is degraded in NLOS signals due to the change in their physical signal characteristics. Therefore identifying and mitigating NLOS signals has been looked into widely for high accuracy indoor positioning and ranging (Casas et al 2006;Benedetto and Giunta 2007;Ismail et al 2008;Alsindi et al 2009;Marano et al 2010;Montorsi, Pancaldi, and Vitetta 2011;Wymeersch et al 2012;Yan et al 2013).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Detection of UWB ranging measurement quality for collaborative indoor positioning

Jing

Bonenberg

Pinchin

et al. 2015

Journal of Location Based Services

View full text Add to dashboard Cite

Wireless communication signals have become popular alternatives for indoor positioning and navigation due to lack of navigation satellite signals in such environments. The signal characteristics determines the method used for positioning as well as the positioning accuracy. Ultra-wideband (UWB) signals, with a typical bandwidth of over 1 GHz, overcome multipath problems in complicated environments. Hence potentially achieves centimetre level ranging accuracy in open areas. However, signals can be disrupted when placed in environments with obstructions and cause large ranging errors. This paper proposes a ranging measurement quality indicator (RQI) which detects the UWB measurement quality based on the received signal strength pattern. With a detection validity of more than 83%, the RQI is then implemented in a ranging based collaborative positioning system. The relative constraint of the collaborative network is adjusted adaptively according to the detected RQI. The proposed detection and positioning algorithm improves positioning accuracy by 80% compared to non-adaptive collaborative positioning.

show abstract

Section: Uwb Signal Ranging Errorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detection of UWB ranging measurement quality for collaborative indoor positioning

Jing

Bonenberg

Pinchin

et al. 2015

Journal of Location Based Services

View full text Add to dashboard Cite

show abstract

“…As the necessity of indoor positioning has emerged, various positioning methods have been proposed, such as wireless local area network‐based or WIFI‐based (Landa et al., 2019; Mazuelas et al., 2009; Syed & Arslan, 2011), ultra‐wideband‐based (Kok et al., 2015; Pagès & Vilà‐Valls, 2019; Yan et al., 2013), radio‐frequency identification‐based (Saab & Nakad, 2011; Tang & Kim, 2010), Bluetooth‐based (Ai et al., 2019), and long‐term evolution‐based (Abdallah et al., 2019; Shin et al., 2019) algorithms. Each of these algorithms has pros and cons (Mautz, 2012), and a suitable method may vary depending on the indoor environment and the user.…”

Section: Introductionmentioning

confidence: 99%

One‐way deep indoor positioning system for conventional GNSS receiver using paired transmitters

Park

Han²,

Kim

et al. 2021

Navigation

View full text Add to dashboard Cite

Generally, GNSS‐based indoor navigation systems use repeaters or pseudolites. However, these methods are vulnerable to multipath errors and require additional information, including the repeater or pseudolite position. In this study, we propose a novel one‐way indoor positioning system using GNSS signal transmitters. Our system uses paired transmitters, each of which broadcasts the same set of satellite signals. The autocorrelation functions of the combined signals are analyzed as the overlap of each individual autocorrelation function. The estimated position can be determined along the track between the transmitters. The multipath error is absorbed by the clock bias and does not cause position bias error. Furthermore, the proposed system can be applied in current commercial GNSS receivers directly. A theoretical analysis of the pseudorange, user position, multipath error, and signal power is included and supported by simulation results. A field test was conducted to confirm the feasibility of the proposed system.

show abstract

“…In NLOS identification, the goal is to detect the existence of a NLOS condition between a transmitter and a receiver [ 29 ]. It can be performed by analyzing the received signals, or analyzing the variance of range estimates from a single source [ 30 , 31 ]. In NLOS mitigation, the goal is to reduce the effect of the ranging errors in NLOS conditions [ 32 , 33 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems

Yin

Cui

et al. 2015

Sensors

View full text Add to dashboard Cite

The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA estimation and support vector machine (SVM) regression-based ranging error mitigation is proposed in this paper. The proposed method can estimate the TOA precisely by measuring the randomness of the received signals and mitigate the ranging error without the recognition of the channel conditions. The entropy is used to measure the randomness of the received signals and the FP can be determined by the decision of the sample which is followed by a great entropy decrease. The SVM regression is employed to perform the ranging-error mitigation by the modeling of the regressor between the characteristics of received signals and the ranging error. The presented numerical simulation results show that the proposed approach achieves significant performance improvements in the CM1 to CM4 channels of the IEEE 802.15.4a standard, as compared to conventional approaches.

show abstract

Non-Line-of-Sight Identification for Indoor Positioning Using Ultra-WideBand Radio Signals

Cited by 10 publications

References 18 publications

Detection of UWB ranging measurement quality for collaborative indoor positioning

Detection of UWB ranging measurement quality for collaborative indoor positioning

One‐way deep indoor positioning system for conventional GNSS receiver using paired transmitters

Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems

Contact Info

Product

Resources

About