Cooperative Scheme ToA‐RSSI and Variable Anchor Positions for Sensors Localization in 2D Environments

Zaidi, Monji; Bouazzi, Imen; Usman, Mohammed; Shamim, Mohammed Zubair M.; Singh, Ninni; Gunjan, Vinit Kumar

doi:10.1155/2022/5069254

Cited by 7 publications

(4 citation statements)

References 55 publications

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“…Then, the centroid algorithm is proposed through the end point optimization. In [46], it was analyzed that the RSSI distribution has a higher accuracy at a small distance, while the ToA method has a higher accuracy when RSSI is at a long distance. Therefore, a wireless sensor positioning method for TOA-RSSI for a 2D environment was proposed, and the analysis showed that the method had a significant effect.…”

Section: Optimization Based On Database Matching Methodsmentioning

confidence: 99%

Research Progress of Wireless Positioning Methods Based on RSSI

Chen,

Ma,

Zhang

et al. 2024

Electronics

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Location-based services are now playing an integral role in the development of emerging industries, such as the Internet of Things, artificial intelligence and smart cities. Although GPS, Beidou and other satellite positioning technologies are becoming more and more mature, they still have certain limitations. In order to meet the needs of high-precision positioning, wireless positioning is proposed as a supplementary technology to satellite positioning, in which the Received Signal Strength Indication (RSSI) is one of the most popular positioning methods. In this paper, the application scenarios, evaluation methods and related localization methods of wireless positioning based on RSSI are studied. Secondly, the relevant optimization methods are analyzed and compared from different angles, and the methods of RSSI data acquisition are described. Finally, the existing problems and future development trends in RSSI positioning methods are expounded, which has certain reference significance for further research on RSSI localization.

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Section: Optimization Based On Database Matching Methodsmentioning

confidence: 99%

Research Progress of Wireless Positioning Methods Based on RSSI

Chen,

Ma,

Zhang

et al. 2024

Electronics

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“…In the work presented MATLAB based simulation results are presented which as more accurated than LSSVR-based or RSSI-TOA-based localization methods. Zaldi and friends propose a method based on selection of the localization technique as RSSI or ToA based on the anchors [23]. The RSSI method is used for small distances and the ToA method is preferred for greater distances and call their method as Combined Advantages of ToA-RSSI (CA ToA-RSSI).…”

Section: Related Workmentioning

confidence: 99%

Relative Localization of Wireless Sensor Nodes by Using the RSSI and ToA based distance estimations

TAMER

2023

DEUFMD

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Wireless sensor network is a popular area for both academic research and commercial applications. A wireless sensor network is made up of several sensor nodes connected over various wireless infrastructures such as Wi-Fi, Bluetooth, ZigBee, or WiMAX. Determining the relative or absolute position of the sensor nodes is essential information for many applications. In this work, we present a novel method for estimating the position of sensor nodes using the Received Signal Strength Indicator and Time of Arrival metrics of the preferred wireless communication infrastructure. Localization results based on both of the metrics and comparison of them with respect to distance between the nodes are presented, and a novel combined method using both the RSSI and ToA based distance estimations is presented. The proposed method estimates the position of the WSN using both methods, but the result of a single method is preferred depending on the distance between the nodes since within the first 5 m. The RSSI based method is superior to ToA and for farther distances ToA outperforms RSSI. The measurement results show that the combined method reduces the estimation error and performs better than both methods it is based on.

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“…For simple scenarios, validation of a 2D ray-tracer has been proved by comparison with measured data [37]. The ray-tracing technique is also used to generate multipath fingerprints for localization methods based on DOA, time difference of arrival or received signal strength [38][39][40]. However, real-time ray-tracing calculation is time-consuming in complex environments because of its high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Radar Target Localization with Multipath Exploitation in Dense Clutter Environments

et al. 2023

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The performance of classic radar geometry based on the line-of-sight (LOS) signal transmitted from radar to the target in the free space is affected by multipath echoes in urban areas, where non-line-of-sight (NLOS) signals reflected by obstacles are received by the radar. Based on prior information of the urban situation, this article proposes a novel two-stage localization algorithm with multipath exploitation in a dense clutter environment. In the offline stage, multipath propagation parameters of uniformly distributed samples in the radar field of view are predicted by the ray-tracing technique. In the online stage, a rough location of the target is estimated by the maximum similarity between measurements and the predicted parameters of reference samples at different locations. The similarity is described by the likelihood between measurements and the predicted multipath parameters with respect to all possible associated hypotheses. A gating threshold is derived to exclude less likely hypotheses and reduce the computational burden. The accurate target location is acquired by a non-linear least squares (NLS) optimization of the associated multipath components. Simulation results in various noise conditions show that the proposed method provides robust and accurate target localization results under dense clutter conditions, and the offline pre-calculation of ray-tracing ensures the real-time performance of the proposed localization algorithm. The root mean square error (RMSE) of simulation results shows the advantage of the proposed method over the existing method. The presented results suggest that the proposed method can be applied to NLOS target localization applications in complex environments.

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Cooperative Scheme ToA‐RSSI and Variable Anchor Positions for Sensors Localization in 2D Environments

Cited by 7 publications

References 55 publications

Research Progress of Wireless Positioning Methods Based on RSSI

Research Progress of Wireless Positioning Methods Based on RSSI

Relative Localization of Wireless Sensor Nodes by Using the RSSI and ToA based distance estimations

Radar Target Localization with Multipath Exploitation in Dense Clutter Environments

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