Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm

Ping, Wu; Su, Shaojing; Zuo, Zhen; Xiao-jun, Guo; Sun, Bei; Wen, Xudong

doi:10.3390/s19112554

Cited by 89 publications

(53 citation statements)

References 28 publications

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“…Among the candidate methods are the linear closed-form method [9] where a linearization is performed to simplify the problem, which results in exacerbating the noise effect. Other techniques are based on combining weighted least squares and firefly algorithm [23], and 1 minimization [24]. In this paper, we adopt a maximum likelihood approach which can be pursued as follows [13]:…”

Section: A the Tdoa Approachmentioning

confidence: 99%

A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

Chen

Ballal

Saeed

et al. 2020

IEEE Wireless Commun. Lett.

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Section: A the Tdoa Approachmentioning

confidence: 99%

A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

Chen

Ballal

Saeed

et al. 2020

IEEE Wireless Commun. Lett.

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“…ToF can be improved by using the Bluetooth standard as a channel which mitigates the consequences of signal fading and inference (Giovanelli and Farella, 2018). TDoA uses the difference given by the arrival time of the signal sender and receiver (Wu et al, 2019). The difference is computed as being the multiplication between the speed of light in vacuum and the time difference.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Luminaire based Real-time Indoor Positioning for Assisted Living

Marin¹,

Bocicor²,

Molnar³

2020

Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering

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This paper presents an experimental evaluation on the accuracy of indoor localisation. The research was carried out as part of a European Union project targeting the creation of ICT solutions for older adult care. Current expectation is that advances in technology will supplement the human workforce required for older adult care, improve their quality of life and decrease healthcare expenditure. The proposed approach is implemented in the form of a configurable cyber-physical system that enables indoor localization and monitoring of older adults living at home or in residential buildings. Hardware consists of custom developed luminaires with sensing, communication and processing capabilities. They replace the existing lighting infrastructure, do not look out of place and are cost effective. The luminaires record the strength of a Bluetooth signal emitted by a wearable device equipped by the monitored user. The system's software server uses trilateration to calculate the person's location based on known luminaire placement and recorded signal strengths. However, multipath fading caused by the presence of walls, furniture and other objects introduces localisation errors. Our previous experiments showed that room-level accuracy can be achieved using software-based filtering for a stationary subject. Our current objective is to assess system accuracy in the context of a moving subject, and ascertain whether room-level localization is feasible in real time.

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“…The error has two components: A constant bias (positive or negative), b, and a zero-mean Gaussian noise. The SNR of any range difference signal is defined as [32]:…”

Section: Simulation Setupmentioning

confidence: 99%

Performance Comparison of Closed-Form Least Squares Algorithms for Hyperbolic 3-D Positioning

Khalaf-Allah

2019

JSAN

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An accurate 3-D wireless local positioning system (LPS) is a highly demanded tool for increasing safety in, e.g., emergency response and security operations. An LPS is an attractive approach that can meet stringent requirements and can achieve acceptable accuracies for a long time during extended operations in global navigation satellite system (GNSS)-denied environments. In this work, three closed-form (CF) least squares (LS) algorithms were considered, where two of them were adapted to exploit the knowledge about nuisance parameters for accurate 3-D positioning based on time difference of arrival (TDoA) measurements. The algorithms utilize the single set (SS) of the TDoA measurements, an extended SS (ExSS) of the TDoA measurements, or the full set (FS) of the TDoA measurements, and were denoted, respectively, as the CFSSLS, CFExSSLS, and CFFSLS solutions. The performance of the algorithms was investigated with simulations and real-world measurements, where the wireless system transmitters were placed in a quasi-coplanar arrangement. At moderate to high signal-to-noise ratio (SNR) levels, the CFSSLS solution has the best performance, followed by the CFExSSLS solution and then by the CFFSLS solution. At low SNR levels, the CFFSLS algorithm outperformed the other two algorithms. Both the CFSSLS and CFFSLS solutions estimate nuisance parameters that are utilized in refining the vertical position estimate of the receiver. The CFFSLS solution delivers more accurate refined vertical position estimates since it utilizes more nuisance parameters, i.e., more information. The experimental results confirmed the simulation study in which the CFFSLS algorithm outperformed the other two algorithms, where the experimental environment was dominated by total non-line-of-sight (NLoS) conditions and low SNR levels at the receiver to be located. Therefore, it is recommended to use the FS TDoA measurements for 3-D positioning in bad signal conditions, such as high noise levels and NLoS propagation.

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Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm

Cited by 89 publications

References 28 publications

A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

Intelligent Luminaire based Real-time Indoor Positioning for Assisted Living

Performance Comparison of Closed-Form Least Squares Algorithms for Hyperbolic 3-D Positioning

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