Performance Enhancement of Land Vehicle Positioning Using Multiple GPS Receivers in an Urban Area

Song, Jong-Hwa; Jee, Gyu-In

doi:10.3390/s16101688

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…e former is provided through an independent network of monitoring stations and a dedicated integrity channel, such as satellite-based augmentation system (SBAS) and ground-based augmentation system (GBAS), and the latter is provided by Receiver Autonomous Integrity Monitoring (RAIM) [4,5]. With more and more visible satellites from multiconstellations being possible to be received at the same time, the multiple hypothesis solution separation (MHSS) algorithm and the range consensus (RANCO) algorithm were representatively proposed to deal with the multiple satellites fault for RAIM [6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Modified Range Consensus Algorithm Based on GA for Receiver Autonomous Integrity Monitoring

Zhao

Jian

et al. 2020

Mathematical Problems in Engineering

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With the considerable increase of visible satellites for positioning, the fault detection and identification performance of Range Consensus (RANCO) algorithm for Receiver Autonomous Integrity Monitoring (RAIM) will significantly be improved. However, the calculation amount of RANCO algorithm will exponentially increase for the sharp addition of visible satellite subsets. This paper proposes a modified RANCO algorithm based on genetic algorithm (GA-RANCO) for RAIM to inhibit the exponentially expanded calculation amount. To reduce the calculation amount in searching the optimal minimal necessary subset (MNS), the preselection step is developed to speed up the convergence process of GA-RANCO. It is executed to exclude the chromosome-represented MNS for which the count of faulty satellites will exceed the upper limit of independent simultaneous satellite faults to be monitored. Mathematical simulations are introduced to determine the GA parameters, and simulation experiments under different schemes are designed to evaluate the performance of GA-RANCO algorithm. Results illustrate that the time consumption under a large number of visible satellites of GA-RANCO is much lower than that of RANCO and the faulty detection and identification performance of GA-RANCO is the same as that of RANCO.

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Section: Introductionmentioning

confidence: 99%

A Modified Range Consensus Algorithm Based on GA for Receiver Autonomous Integrity Monitoring

Zhao

Jian

et al. 2020

Mathematical Problems in Engineering

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“…In these approaches, RFID tags are arranged in the road or on both sides of a tunnel’s edges, and vehicle location techniques based on the received RFID signal strengths are presented. Specifically, GPS errors are more common in dense urban areas, requiring complex positioning algorithms to achieve an effective position triangulation [ 25 ]. Finally, the growing interest in addressing the challenges of the internet-of-things (IoT) [ 15 , 26 ] and infrastructure-to-vehicle (I2V) communication systems [ 27 , 28 ] brings us to the conclusion that embedding RFID technology in road facilities is likely to become a reality in the near future [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments

Oya

Martı́n-Clemente

Fort

et al. 2018

Sensors

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This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. In addition, the system can be easily extended to consider any other street facilities, such as dumpsters or traffic lights. Furthermore, the system can perform the inventory process at night and at a vehicle’s usual speed, thus avoiding interfering with the normal traffic flow of the road. Moreover, the proposed system exploits the benefits of the passive RFID technologies over active RFID, which are typically employed on inventory and vehicular routing applications. Since the performance of passive RFID is not obvious for the required distance ranges on these in-motion scenarios, this paper, as its main contribution, addresses the problem in two different ways, on the one hand theoretically, presenting a radio wave propagation model at theoretical and simulation level for these scenarios; and on the other hand experimentally, comparing passive and active RFID alternatives regarding costs, power consumption, distance ranges, collision problems, and ease of reconfiguration. Finally, the performance of the proposed on-board system is experimentally validated, testing its capabilities for inventory purposes.

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“…Some methods can improve the accuracy, and some even can satisfy autonomous vehicles’ high precision position needs [ 6 ]. Song et al [ 7 ] in multiple Global Positioning System (GPS) information reception studies, proposed a positioning algorithm for multiple receivers to enhance positioning performance in urban areas. Lu et al [ 8 ] proposed a direct position determination (DPD) algorithm that is superior in terms of high estimation accuracy and strong resolution capability.…”

Section: Introductionmentioning

confidence: 99%

An Extended Kalman Filter and Back Propagation Neural Network Algorithm Positioning Method Based on Anti-lock Brake Sensor and Global Navigation Satellite System Information

Qin

et al. 2018

Sensors

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Telematics box (T-Box) chip-level Global Navigation Satellite System (GNSS) receiver modules usually suffer from GNSS information failure or noise in urban environments. In order to resolve this issue, this paper presents a real-time positioning method for Extended Kalman Filter (EKF) and Back Propagation Neural Network (BPNN) algorithms based on Antilock Brake System (ABS) sensor and GNSS information. Experiments were performed using an assembly in the vehicle with a T-Box. The T-Box firstly use automotive kinematical Pre-EKF to fuse the four wheel speed, yaw rate and steering wheel angle data from the ABS sensor to obtain a more accurate vehicle speed and heading angle velocity. In order to reduce the noise of the GNSS information, After-EKF fusion vehicle speed, heading angle velocity and GNSS data were used and low-noise positioning data were obtained. The heading angle speed error is extracted as target and part of low-noise positioning data were used as input for training a BPNN model. When the positioning is invalid, the well-trained BPNN corrected heading angle velocity output and vehicle speed add the synthesized relative displacement to the previous absolute position to realize a new position. With the data of high-precision real-time kinematic differential positioning equipment as the reference, the use of the dual EKF can reduce the noise range of GNSS information and concentrate good-positioning signals of the road within 5 m (i.e. the positioning status is valid). When the GNSS information was shielded (making the positioning status invalid), and the previous data was regarded as a training sample, it is found that the vehicle achieved 15 minutes position without GNSS information on the recycling line. The results indicated this new position method can reduce the vehicle positioning noise when GNSS information is valid and determine the position during long periods of invalid GNSS information.

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Performance Enhancement of Land Vehicle Positioning Using Multiple GPS Receivers in an Urban Area

Cited by 5 publications

References 13 publications

A Modified Range Consensus Algorithm Based on GA for Receiver Autonomous Integrity Monitoring

A Modified Range Consensus Algorithm Based on GA for Receiver Autonomous Integrity Monitoring

Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments

An Extended Kalman Filter and Back Propagation Neural Network Algorithm Positioning Method Based on Anti-lock Brake Sensor and Global Navigation Satellite System Information

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