Indoor Localization Enhancement Based on Time of Arrival Using Sectoring Method

Daraj, Ahmed K.; Mohammad, Alhamzah T.; Mosleh, Mahmood F.

doi:10.5815/ijisa.2020.03.01

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…In this work, a new technique based on dynamic mechanisms based on ToA and RSS was proposed to mitigate NLoS and regressive signals. In some scenarios, the ToA method was better than the RSS method like in distances exceed (25) m with average errors (0.2) m. Whereas, in distances under (25) m, the RSS method was better with average errors (0.3) m. The ToA with the proposed technique is slightly outperformed RSS in distances above (25) m and specific in the LoS scenario.…”

Section: Discussionmentioning

confidence: 91%

“…To introduce the Indoor Localization scheme, many methods are used; ToA and RSSI [23,24] are commonly accepted methods. The exact distance is as follows, according to [25]:…”

Section: Indoor Localizationmentioning

confidence: 99%

“…In order to facilitate 2-D placement, ToA measurements must be made with respect to the signals from at least the reference points. For ToA-based systems, the one-way propagation distance is estimated as [25]:…”

Section: Toa Measurementmentioning

confidence: 99%

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Performance Enhancements of the Indoor Localization System Based on Dynamic ToA and RSS Mechanisms

Abbas

Abed

Alhyani

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

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Localization is the process of estimating the position of targets indoors or outdoors. In indoor scenarios, there are challenges to using the Global Positioning System (GPS) according to multipath environments which is the main reason. The techniques which are widely used for indoor positioning are Time of Arrival (ToA) and Receive Signal Strength (RSS). The key issues that led to elevate errors are the Non-Line of Sight (NLoS) and multipath. Many researchers are trying to address these problems using various propose techniques they approach an accuracy depending on their proposed algorithms. In this paper, a new approach is based on dynamic mechanisms to choose specific values of the path loss exponent (c) and Gaussian variable (Xr) to match the specific environment that straight each transmitter and receiver individually based on ToA and RSS. The idea depends on taking into account the location of each recipient, which differs from the other in terms of the number of barriers that separate him and the sender. To apply the proposed system, a case study building is chosen for such a task. Also, the Wireless Insite Software (WIS) was used to simulate such building and evaluate the proposed algorithm. In such a proposal, 30 Receivers (RXs), and 3Transmitters (TXs) were deployed in suitable locations through the case study. The result obtained by WIS is supported by a special algorithm implemented by the MATLAB package to achieve the average error. The results show that the proposed scheme improves the accuracy which does not exceed (0.331) m and (0.251) m based on RSS and ToA measurement respectively in the distance above (25) m. The ToA with the proposed technique is slightly outperformed RSS in distances above (25) m and specific in the Line of Sight (LoS) scenario.

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Section: Discussionmentioning

confidence: 91%

“…To introduce the Indoor Localization scheme, many methods are used; ToA and RSSI [23,24] are commonly accepted methods. The exact distance is as follows, according to [25]:…”

Section: Indoor Localizationmentioning

confidence: 99%

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Performance Enhancements of the Indoor Localization System Based on Dynamic ToA and RSS Mechanisms

Abbas

Abed

Alhyani

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

Self Cite

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“…ToA measurements must be made with respect to signals from at least the reference points in order to facilitate 2-D placement. The one-way propagation distance (di) is estimated for ToA-based systems as [30]:…”

Section: Toa Methodsmentioning

confidence: 99%

Improving Indoor Localization System Using a Partitioning Technique Based on RSS and ToA

Mosleh

Abed

Hamza

2021

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Designing a localization system for an indoor environment faces more challenges because of multipath and interference problems. In this field, the most important techniques used for such environment, are RSS and ToA which need to be improved especially from more interference because of the huge multipath problems. In this paper, a case study of a selected building is chosen in order to apply the proposed technique of this research. Such proposal is based on the PT ‎ of the area in the case study into MZ. Each zone is allocated special values for the parameters used to estimate the target positions. WI package is used to simulate the case study area and apply such proposal based on RSS and ToA. The results confirm that the estimated locations are close to the real locations by the average error of (2.8) meter and (0.192) meter for ToA corresponding one zone and four zones ‎respectively. ‎ In contrast, the results of our experiment show that the accuracy is improved from an average error of (2.4) meter and (0.217) meter for RSS corresponding one zone and four zones ‎respectively‎. Such results confirm that dividing the case study area into more zones leads to more accuracy.

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“…Various indoor positioning models have been developed in the literature using different techniques, including range-based techniques such as Time of Arrival (ToA) [10], Angle of Arrival (AoA) [11], and RSSI fingerprint matching algorithms [12]. Wireless technologies such as WiFi, Bluetooth, Radio Frequency Identification Device (RFID), UltraWideband (UWB), and LoRaWAN are considered by several researchers in developing indoor models.…”

Section: Related Workmentioning

confidence: 99%

LoRaWAN Based Indoor Localization Using Random Neural Networks

et al. 2022

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Global Positioning Systems (GPS) are frequently used as a potential solution for localization applications. However, GPS does not work indoors due to a lack of direct Line-of-Sight (LOS) satellite signals received from the End Device (ED) due to thick solid materials blocking the ultra-high frequency signals. Furthermore, fingerprint localization using Received Signal Strength Indicator (RSSI) values is typical for localization in indoor environments. Therefore, this paper develops a low-power intelligent localization system for indoor environments using Long-Range Wide-Area Networks (LoRaWAN) RSSI values with Random Neural Networks (RNN). The proposed localization system demonstrates 98.5% improvement in average localization error compared to related studies with a minimum average localization error of 0.12 m in the Line-of-Sight (LOS). The obtained results confirm LoRaWAN-RNN-based localization systems suitable for indoor environments in LOS applied in big sports halls, hospital wards, shopping malls, airports, and many more with the highest accuracy of 99.52%. Furthermore, a minimum average localization error of 13.94 m was obtained in the Non-Line-of-Sight (NLOS) scenario, and this result is appropriate for the management and control of vehicles in indoor car parks, industries, or any other fleet in a pre-defined area in the NLOS with the highest accuracy of 44.24%.

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Indoor Localization Enhancement Based on Time of Arrival Using Sectoring Method

Cited by 7 publications

References 23 publications

Performance Enhancements of the Indoor Localization System Based on Dynamic ToA and RSS Mechanisms

Performance Enhancements of the Indoor Localization System Based on Dynamic ToA and RSS Mechanisms

Improving Indoor Localization System Using a Partitioning Technique Based on RSS and ToA

LoRaWAN Based Indoor Localization Using Random Neural Networks

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