A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

Chen, Hui; Ballal, Tarig; Saeed, Nasir; Alouini, Mohamed‐Slim; Al-Naffouri, Tareq Y.

doi:10.1109/lwc.2020.2986756

Cited by 42 publications

(18 citation statements)

References 25 publications

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“…Over 90% of the final positioning errors of the proposed approach are smaller than 0.065 m in the absence of cycle slips, and smaller than 0.102 m in the presence of cycle slips. The proposed positioning method markedly outperforms a recently published TDoA-CPDoA algorithm [65], and the proposed fusion-based position estimation, i.e., Algorithm 1. Despite outperforming the algorithm based on TDoA measurements, the TDoA-CPDoA algorithm [65] and the proposed fusion-based position estimation do not resolve the integer ambiguity.…”

Section: E Positioning Accuracy Performancementioning

confidence: 91%

“…The proposed positioning method markedly outperforms a recently published TDoA-CPDoA algorithm [65], and the proposed fusion-based position estimation, i.e., Algorithm 1. Despite outperforming the algorithm based on TDoA measurements, the TDoA-CPDoA algorithm [65] and the proposed fusion-based position estimation do not resolve the integer ambiguity. As a consequence, their positioning accuracies are substantially worse than the full proposed approach depicted in Fig.…”

Section: E Positioning Accuracy Performancementioning

confidence: 91%

See 1 more Smart Citation

Carrier Phase-Based Synchronization and High-Accuracy Positioning in 5G New Radio Cellular Networks

Fan

Tian

et al. 2022

IEEE Trans. Commun.

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Inspired by excellent precision of carrier phase positioning, this paper presents a new carrier phase positioning technique for 5G new radio cellular networks with a focus on clock synchronization and integer ambiguity resolution. A carrier-phase based clock offset estimation method is first proposed to achieve precise clock synchronization among base stations, and proved to achieve the Cramér-Rao Lower Bound (CRLB) asymptotically. A fusion method is developed to fuse the estimated positions of a mobile station (MS) based on time-difference-of-arrival, with the estimated position changes based on the temporal changes of carrier phase measurements. While circumventing the integer ambiguities of the carrier phase measurements, the fusion method provides quality interim estimates of the MS positions, at which the measurements can be linearized to resolve the integer ambiguities. As a result, precise MS positions can be obtained based on the disambiguated carrier phase measurements. Numerical simulations show that the proposed carrier phase positioning can achieve a centimeterlevel accuracy in wireless cellular networks.

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Section: E Positioning Accuracy Performancementioning

confidence: 91%

Section: E Positioning Accuracy Performancementioning

confidence: 91%

Carrier Phase-Based Synchronization and High-Accuracy Positioning in 5G New Radio Cellular Networks

Fan

Tian

et al. 2022

IEEE Trans. Commun.

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“…Therefore, different delay times can be estimated from phase differences of sinusoids by which the optical signal is moduled [34]. For PDOA, one obvious advantage is that it can be combined with other positioning techniques such as RSSI and ToF/TDOA where it can significantly improve the accuracy [35], [36], [37]. In [38] a differential PDOA method with sub-decimeter accuracy is demonstrated.…”

Section: ) Angle-of-arrival (Aoa)mentioning

confidence: 99%

“…However, the PDOA technique is limited to cases in which the transmitter separation remains small. For large areas, the actual phase difference of the signals cannot be computed uniquely, as phase is restricted to the range [0, 2π), and longer delays would create ambiguities (phase wrapping) [35].…”

Section: ) Angle-of-arrival (Aoa)mentioning

confidence: 99%

LiFi Positioning for Industry 4.0

Kouhini

Kottke

et al. 2021

IEEE J. Select. Topics Quantum Electron.

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Precise position information is considered as the main enabler for the implementation of smart manufacturing systems in Industry 4.0. In this article, a time-of-flight based indoor positioning system for LiFi is presented based on the ITU -T recommendation G.9991. Our objective is to realize positioning by reusing already existing functions of the LiFi communication protocol which has been adopted by several vendors. Our positioning algorithm is based on a coarse timing measurement using the frame synchronization preamble, similar to the ranging, and a fine timing measurement using the channel estimation preamble. This approach works in various environments and it requires neither knowledge about the beam characteristics of transmitters and receivers nor the use of fingerprinting. The new algorithm is validated through both, simulations and experiments. Results in an 1m × 1m × 2m area indicate that G.9991-based positioning can reach an average distance error of a few centimeters in three dimension. Considering the common use of lighting in indoor environments and the availability of a mature optical wireless communication system using G.9991, the proposed LiFi positioning is a promising new feature that can be added to the existing protocols and enhance the capabilities of smart lighting systems further for the benefit of Industry 4.0.

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“…LPS and GNSS are categorized through the physical property measured for providing target location: time [10], power [11], phase [12], angle [13], frequency [14], or combinations of these methodologies [15] [16].…”

Section: Introductionmentioning

confidence: 99%