A Study on Localization in Wireless Sensor Networks using Frequency Diversity for Mitigating Multipath Effects

Lázaro, Antonio; Girbau, David; Moravek, Patrik; Villarino, R.

doi:10.5755/j01.eee.19.3.3701

Cited by 10 publications

(4 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For this, signal propagation models such as the Log-distance [10] and Two-ray Ground Reflection Model (TGRM) [17] are used. In [18], the authors use the frequency diversity in the wireless channel to reduce the multipath effect on the distance estimation. Similarly, in [19], the authors propose the Optimal Multi-channel Trilateration Positioning Algorithm (OMCT) to find the global optimal parameter values and prevent the algorithm from falling into local optimum.…”

Section: Related Workmentioning

confidence: 99%

Indoor Positioning System Using Synthetic Training and Data Fusion

et al. 2021

View full text Add to dashboard Cite

Indoor Positioning Systems (IPSs) are used to estimate the position of mobile devices in indoor environments. Fingerprinting is the most used technique because of its higher accuracy. However, this technique requires a labor-intensive training phase that measures the Received Signal Strength Indicator (RSSI) at all Reference Points (RPs) locations. On the other hand, model-based IPSs use signal propagation models to estimate distances from RSSI. Thus, they do not require expensive training but result in higher positioning errors. In this work, we propose SynTra-IPS (Synthetic Training Indoor Positioning System), a hybrid approach between a fingerprint and a model-based IPS that uses synthetic, simulated datasets combined with data fusion techniques to eliminate the fingerprint collection cost. In our solution, we use the map of the scenario, with known anchor nodes' positions and the log-distance signal propagation model, to generate several synthetic, model-based, fingerprint training datasets. In the online phase of our solution, the positions estimated by the several synthetic datasets using K-Nearest Neighbors (KNN) are combined using data fusion techniques into a single, more accurate position. We evaluated the performance of our SynTra solution in a real-world, large-scale environment using mobile devices with Bluetooth Low Energy (BLE) technology, and we compared our solution to classic approaches from the literature. Our results show that SynTra can locate mobile devices with an average error of only 2.36 m while requiring no real-world environment training.

show abstract

Section: Related Workmentioning

confidence: 99%

Indoor Positioning System Using Synthetic Training and Data Fusion

et al. 2021

View full text Add to dashboard Cite

show abstract

“…To reduce the influence of multipath effects on the accuracy of single-channel positioning algorithms, multi-channel localization algorithms based on multipath cancellation technology have been proposed. The algorithm proposed by Llizaro et al uses the frequency diversity of signals of multiple channels to suppress the negative influence of multipath effects on the location results of RSSI-based positioning algorithms [17]. However, this algorithm simply averages the RSSI values of different frequencies without modelling the signal relationship between different paths.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the multipath effect of wireless signals, the accuracy of positioning based on RSSI is usually not high in indoor environments. In order to overcome the influence of the multipath effect on the accuracy of RSSI-based localization, the diversity of different channel signals has been employed to improve this accuracy in multipath environments [13,17,18]. The multi-channel localization algorithm utilizes the difference of different channel signals to fit the parameters in the signal propagation model.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Multi-Channel Trilateration Localization Algorithm by Radio-Multipath Multi-Objective Evolution in RSS-Ranging-Based Wireless Sensor Networks

Fang

Chen

2020

Sensors

View full text Add to dashboard Cite

The Global Positioning System (GPS) is unable to provide precise localization services indoors, which has led to wireless sensor network (WSN) localization technology becoming a hot research issue in the field of indoor location. At present, the ranging technology of wireless sensor networks based on received signal strength has been extensively used in indoor positioning. However, wireless signals have serious multipath effects in indoor environments. In order to reduce the adverse influence of multipath effects on distance estimation between nodes, a multi-channel ranging localization algorithm based on signal diversity is herein proposed. In real indoor environments, the parameters used for multi-channel localization algorithms are generally unknown or time-varying. In order to increase the positioning accuracy of the multi-channel location algorithm in a multipath environment, we propose an optimal multi-channel trilateration positioning algorithm (OMCT) by establishing a novel multi-objective evolutionary model. The presented algorithm utilizes a three-edge constraint to prevent the traditional multi-channel localization algorithm falling into local optima. The results of a large number of practical experiments and numerical simulations show that no matter how the channel number and multipath number change, the positioning error of our presented algorithm is always smaller compared with that of the state-of-the-art algorithm.

show abstract

“…Ancak, sızıntıdan alıcılara eğitim dizisi gönderme işlemi mümkün olmadığından ilgili yöntemler SDBH'lerdeki sızıntıların konumlandırılması için uygun değildir. [15], [16]'da, alınan sinyal gücü tabanlı konum tespitinde çok yollu kanal etkisinin azaltılması için frekans çeşitlemesi yöntemi kullanılmıştır. Frekans çeşitlemesi yönteminde gönderilmek istenen veri birden fazla sayıda taşıyıcı frekans kullanılarak gönderilir.…”

Section: Introductionunclassified

Investigation of positioning of the leakages in underwater natural gas pipelines in time and frequency selective acoustic channel

Mahmutoğlu¹,

Türk²

2020

Pamukkale J Eng Sci

View full text Add to dashboard Cite

Önemli bir enerji kaynağı olan doğalgaz genelde sualtından da geçen doğalgaz boru hatları vasıtasıyla taşınmaktadır. Sualtı doğalgaz boru hatları korozyon ve gemi, balıkçılık faaliyetleri başta olmak üzere çeşitli nedenlerden dolayı delinebilir. Bu yüzden, sızıntıların algılanması ve konumlandırılması enerji güvenirliğinin sağlanmasında ve doğal yaşamın korunmasında önemli bir role sahiptir. Bu çalışmada, sualtı doğalgaz boru hatlarındaki sızıntıların konumlandırılması için yeni bir yöntem olarak sinyal gücü tabanlı eğri uydurma yöntemi önerilmiştir. Önerilen yöntemin performansı, gerçek bir sualtı doğalgaz boru hattının parametrelerinin ve zamanla değişen (hareketli deniz yüzeyi, sualtı akıntıları vb. nedeniyle) çok yollu ikili seçici sualtı akustik kanalının kullanıldığı benzetim çalışmalarıyla analiz edilmiştir. Nümerik sonuçlar, oldukça gerçekçi olan bu zamanla değişen çok yollu sualtı akustik kanalında sızıntıların kilometrelerce uzaktan deniz dalga yüksekliği ve ortam gürültüsüne bağlı olarak düşük hatalarla konumlandırılabileceği gösterilmiştir. Natural gas, which is an important energy source, is generally transported through natural gas pipelines that also pass through underwater. Underwater natural gas pipelines can be punctured for various reasons, especially for corrosion and shipping, fishing activities. Thus, detection and localization of the leakages has a crucial role in ensuring energy reliability and preserving the natural life. In this study, a novel signal strength based curve fitting method was proposed for positioning the leakages in the underwater natural gas pipelines. The performance of this method was analyzed by simulation studies using the parameters of a real life underwater natural gas pipeline and a time-varying (because of moving sea surface, underwater currents etc.) multipath doubly selective underwater acoustic channel. Numerical results show that for this time-varying multipath underwater acoustic channel, which is quite realistic, leakages can be positioned with low errors from kilometers away depending on the ambient noise and the sea wave height.

show abstract

A Study on Localization in Wireless Sensor Networks using Frequency Diversity for Mitigating Multipath Effects

Cited by 10 publications

References 16 publications

Indoor Positioning System Using Synthetic Training and Data Fusion

Indoor Positioning System Using Synthetic Training and Data Fusion

An Optimal Multi-Channel Trilateration Localization Algorithm by Radio-Multipath Multi-Objective Evolution in RSS-Ranging-Based Wireless Sensor Networks

Investigation of positioning of the leakages in underwater natural gas pipelines in time and frequency selective acoustic channel

Contact Info

Product

Resources

About