On the Accuracy of Inter-Vehicular Range Measurements Using GNSS Observables in a Cooperative Framework

Tahir, Muhammad; Afzal, Sayed Saad; Chughtai, Muhammad Saad; Ali, Khurram

doi:10.1109/tits.2018.2833438

Cited by 35 publications

(49 citation statements)

References 43 publications

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“…Equation (10) can be transformed into Equation (12) by using a Taylor series and the first-order partial derivatives to eliminate nonlinear terms [ 33 ].

with

…”

Section: Ivd Estimation Methodsmentioning

confidence: 99%

“…As seen in Figure 5 , since the satellite is far away from the vehicles, the pseudoranges of these two vehicles are assumed to be in parallel. Thus, the difference of the pseudoranges as [ 33 ]

…”

Section: Ivd Estimation Methodsmentioning

confidence: 99%

“…Tahir et al proposed several range measurement methods, including single and double differencing. The accuracy of the proposed methods is compared by actual field trails in different mobile environments [ 33 ]. In addition, Ansari also proposed a DSRC-based Vehicle-to-vehicle (V2V) real-time relative localization method and investigated the benefits of the proposed method [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Robust Inter-Vehicle Distance Measurement Using Cooperative Vehicle Localization

Wang

Zhuang

Yin

et al. 2021

Sensors

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Precise localization is critical to safety for connected and automated vehicles (CAV). The global navigation satellite system is the most common vehicle positioning method and has been widely studied to improve localization accuracy. In addition to single-vehicle localization, some recently developed CAV applications require accurate measurement of the inter-vehicle distance (IVD). Thus, this paper proposes a cooperative localization framework that shares the absolute position or pseudorange by using V2X communication devices to estimate the IVD. Four IVD estimation methods are presented: Absolute Position Differencing (APD), Pseudorange Differencing (PD), Single Differencing (SD) and Double Differencing (DD). Several static and dynamic experiments are conducted to evaluate and compare their measurement accuracy. The results show that the proposed methods may have different performances under different conditions. The DD shows the superior performance among the four methods if the uncorrelated errors are small or negligible (static experiment or dynamic experiment with open-sky conditions). When multi-path errors emerge due to the blocked GPS signal, the PD method using the original pseudorange is more effective because the uncorrelated errors cannot be eliminated by the differential technique.

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“…Equation (10) can be transformed into Equation (12) by using a Taylor series and the first-order partial derivatives to eliminate nonlinear terms [ 33 ].

with

…”

Section: Ivd Estimation Methodsmentioning

confidence: 99%

“…As seen in Figure 5 , since the satellite is far away from the vehicles, the pseudoranges of these two vehicles are assumed to be in parallel. Thus, the difference of the pseudoranges as [ 33 ]

…”

Section: Ivd Estimation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Inter-Vehicle Distance Measurement Using Cooperative Vehicle Localization

Wang

Zhuang

Yin

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…where D ab,k and H D,k are the first and the second term in (6), respectively. As for the other DGNSS methods [47], uncorrelated errors such as different multipath reflections, can be increased by differentiation. Furthermore, according to [45], statistical assumption of mutual independence can be reasonable on different pseudorange measurements but it cannot be assessed for the resulting DD estimation.…”

Section: Methodsology a Dgnss-based Rangingmentioning

confidence: 99%

A Cognitive Particle Filter for Collaborative DGNSS Positioning

2020

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The advances in low-latency communications networks and the ever-growing amount of devices offering localization and navigation capabilities opened a number of opportunities to develop innovative network-based collaborative solutions to satisfy the increasing demand for positioning accuracy and precision. Recent research works indeed, have fostered the concept of networked Global Navigation Satellite System (GNSS) receivers supporting the sharing of raw measurements with other receivers within the same network. Such measurements (i.e. pseudorange and Doppler) can be processed through Differential GNSS (DGNSS) techniques to retrieve inter-agent distances which can be in turn integrated to improve positioning performance. This paper investigates an improved Bayesian estimation algorithm for a sensorless, tight-integration of DGNSS-based collaborative measurements through a modified Particle Filter (PF), namely Cognitive PF. Differently from Extended Kalman Filter and Uscented Kalman Filter indeed, a PF natively support the non-Gaussian noise distribution which characterizes DGNSS-based interagent distances. The proposed Cognitive PF is hence designed, implemented and optimized according to the architecture of a proprietary Inertial Navigation System (INS)-free Global Navigation Satellite System (GNSS) software receiver. Experimental tests performed through realistic radio-frequency GNSS signals showed a remarkable improvement in positioning accuracy w.r.t. reference PF and EKF architectures.

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“…The main challenge of adopting CAVs relates to the ability of obtaining accurate position and timing information for critical applications. For example, in cooperative positioning, precise timing is required for range-based vehicle and infrastructure localization [7]. In addition, accurate positioning information is required for lane detection, route guidance, collision avoidance and emergency response [8]- [12].…”

Section: Introductionmentioning

confidence: 99%

GNSS Vulnerabilities and Existing Solutions: A Review of the Literature

et al. 2021

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This literature review paper focuses on existing vulnerabilities associated with global navigation satellite systems (GNSSs). With respect to the civilian/non encrypted GNSSs, they are employed for proving positioning, navigation and timing (PNT) solutions across a wide range of industries. Some of these include electric power grids, stock exchange systems, cellular communications, agriculture, unmanned aerial systems and intelligent transportation systems. In this survey paper, physical degradations, existing threats and solutions adopted in academia and industry are presented. In regards to GNSS threats, jamming and spoofing attacks as well as detection techniques adopted in the literature are surveyed and summarized. Also discussed are multipath propagation in GNSS and non line-of-sight (NLoS) detection techniques. The review also identifies and discusses open research areas and techniques which can be investigated for the purpose of enhancing the robustness of GNSS.

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On the Accuracy of Inter-Vehicular Range Measurements Using GNSS Observables in a Cooperative Framework

Cited by 35 publications

References 43 publications

Robust Inter-Vehicle Distance Measurement Using Cooperative Vehicle Localization

Robust Inter-Vehicle Distance Measurement Using Cooperative Vehicle Localization

A Cognitive Particle Filter for Collaborative DGNSS Positioning

GNSS Vulnerabilities and Existing Solutions: A Review of the Literature

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