Land vehicle positioning in urban area by integrated GPS/BeiDou/OBD-II/MEMS IMU

Lim, JoonHoo; Choi, Kwang Ho; Kim, La-Woo

doi:10.1109/icite.2016.7581329

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…The author [10] designed a combined navigation mode that combines the advantages of the two positioning methods, which is suitable for the application of high-precision relative alignment of linked targets. Lim [11] proposed an effective hybrid positioning method for urban ground vehicles. In order to improve the availability of satellite positioning in urban areas, this method integrates GPS/BeiDou receivers, OBD-II (Onboard Diagnostic II) equipment and MEMS IMU (Micro Electro Mechanical System Inertial Measurement Unit).…”

Section: Related Researchmentioning

confidence: 99%

Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

Sun

2021

Sustainability

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The development of 5G network slicing technology, combined with the application scenarios of vehicle–road collaborative positioning, provides end-to-end, large-bandwidth, low-latency, and highly reliable flexible customized services for Internet of Vehicle (IoV) services in different business scenarios. Starting from the needs of the network in the business scenario oriented to co-location, we researched the application of 5G network slicing technology in the vehicle–road cooperative localization system. We considered scheduling 5G slice resources. Creating slices to ensure the safety of the system, provided an optimized solution for the application of the vehicle–road coordinated positioning system. On this basis, this paper proposes a vehicle–road coordinated combined positioning method based on Beidou. On the basis of Beidou positioning and track estimation, using the advantages of the volumetric Kalman model, a combined positioning algorithm based on CKF was established. In order to further improve the positioning accuracy, vehicle characteristics could be extracted based on the traffic monitoring video stream to optimize the service-oriented positioning system. Considering that the vehicles in the urban traffic system can theoretically only travel on the road, the plan can be further optimized based on the road network information. It was preliminarily verified by simulation that this research idea has improved the relative single positioning method.

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Section: Related Researchmentioning

confidence: 99%

Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

Sun

2021

Sustainability

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“…Usually, the number of observable satellites in satellite navigation system is about 15 at a certain time. 41 It has been proved that when the loss of positioning accuracy is not well, the calculation amount could be reduced effectively after selecting a suitable number of well-distributed satellites. 42,43 Calculate the azimuth and elevation angle of the observable satellites Set the observation point as the origin, the long axis of the earth ellipsoid as the X-axis, the short half axis of the earth ellipsoid as the Y-axis, and the normal of the earth ellipsoid as the Z-axis, thus, the carrier coordinate system is constructed.…”

Section: The Problem Of Navigation Satellite Selectionmentioning

confidence: 99%

Section: The Problem Of Navigation Satellite Selectionmentioning

confidence: 99%

A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler

Xia

Zhi

et al. 2020

International Journal of Distributed Sensor Networks

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In various applications of satellite navigation and positioning, it is a key topic to select suitable satellites for positioning solutions to reduce the computational burden of the receiver in satellite selection system. Moreover, in order to reduce the processing burden of receivers, the satellite selection algorithm based on Gibbs sampler is proposed. First, the visible satellites are randomly sampled and divided into a group. The group is regarded as an initial combination selection scheme. Then, the geometric dilution of precision is chosen as an objective function to evaluate the scheme’s quality. In addition, the scheme is updated by the conditional probability distribution model of the Gibbs sampler algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. Furthermore, an “adaptive perturbation” strategy is introduced to improve the global searching ability of the algorithm. Finally, the extensive experimental results demonstrate that when the number of selected satellite is more than 6, the time that the proposed algorithm with the improvement of “adaptive perturbation” takes to select satellite once is 43.7% of the time that the primitive Gibbs sampler algorithm takes. And its solutions are always 0.1 smaller than the related algorithms in geometric dilution of precision value. Therefore, the proposed algorithm can be considered as a promising candidate for satellite navigation application systems.

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“…Reference [3] designed a Sage-Husa Kalman filter based on UD decomposition for the divergence phenomenon of conventional filters. Reference [4] proposed a method to integrate different sensors to correct the inertial velocity for the hybrid positioning of urban vehicles. In terms of big data fusion, reference [5] proposed the optimization of dynamic data from different data sources and proposes the big data fusion based on dynamic feature selection from different data sources.…”

Section: Introductionmentioning

confidence: 99%

The Model Research on Location Fusion Algorithm with Big Data Selection and Accuracy Correction

Zhang¹,

Zhao²,

Zhao³

et al. 2018

dtcse

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As the requirements of smart, reliable and precise location for a vehicle, the model of fusion location algorithm with big data selection and accuracy correction is established to achieve reliable and low-cost fusion location. In this paper, the data of simple inertial navigation and the data of various positioning system sources with different errors are intelligently selected, and Kalman filtering is used to fuse the location information by the function of algorithm model, and the four kinds of location information of GPS, SINS, DR and TDOA are chosen to simulate fusion algorithm. The simulation results in MATLAB environment show that the proposed fusion location algorithm model is efficient to improve the accuracy and reliability of the location algorithm.

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Land vehicle positioning in urban area by integrated GPS/BeiDou/OBD-II/MEMS IMU

Cited by 6 publications

References 5 publications

Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler

The Model Research on Location Fusion Algorithm with Big Data Selection and Accuracy Correction

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