A Novel Cycle Slips Detection Model for the High Precision Positioning

Yin, Lu; Li, Shuangzhi; Deng, Zhongliang; Zhu, Di

doi:10.1109/access.2018.2890694

Cited by 11 publications

(9 citation statements)

References 29 publications

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“…Liu Wenqiang et al [30] introduced a point cloud segmentation and recognition method based on three-dimensional convolutional neural networks (3-D CNNs) to determine the different components of the catenary cantilever devices. Yin et al [31] proposed a complementary symmetric geometry-free (CSGF) method that makes the detection of cycle slips more comprehensive and accurate. Lingfeng et al [32] established a junction temperature model based on a multiple linear stepwise regression algorithm and used it to extract high-precision intersection online temperatures.…”

Section: High-precision Information Data Acquisition Technologymentioning

confidence: 99%

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

Chen¹,

Zuo²,

Geng³

et al. 2023

Preprint

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The operation status of manufacturing equipment is directly related to the reliability of the operation of manufacturing equipment and the continuity of operation of the production system. Based on the analysis of the operation status of manufacturing equipment and its characteristics, it is proposed that the concept of assessing the operation status of manufacturing equipment can be realized by applying real-time acquisition of accurate inspection data of important parts of weak motion units and comparing them with their motion status evaluation criteria. Through the study of the application characteristics of fractional-order calculus theory, a differential data fusion model based on the fractional-order differential operator is established. The advantages of Internet of Things (IoT）technology and fractional order differential fusion algorithm are integrated to obtain real-time high-precision data of the operating parameters of manufacturing equipment, and the research objective of operating condition assessment of manufacturing equipment is realized. The feasibility and effectiveness of the method are verified by the application of the method in machining center operation status assessment.

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Section: High-precision Information Data Acquisition Technologymentioning

confidence: 99%

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

Chen¹,

Zuo²,

Geng³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Liu Wenqiang et al [17] introduced a point cloud segmentation and recognition method based on three-dimensional convolutional neural networks (3-D CNNs) to determine the different components of the catenary cantilever devices. Lu Yin et al [18] proposed a complementary symmetric geometry-free (CSGF) method is, which makes the detection of cycle slips more comprehensive and accurate. Shao Lingfeng et al [19] established the junction temperature model is based on the multiple linear stepwise regression algorithm, and used it to extract high-precision intersection online temperature.…”

Section: 1 Introductionmentioning

confidence: 99%

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

Zuo¹,

Chen²

2023

Preprint

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In engineering practice, various types of information data are affected by many factors during the collection process. For example, information data measurement errors are caused by equipment performance and the working environment. During the transmission of detection information, the signal distortion caused by energy loss and signal interference causes unpredictable detection errors in the collected information data. Through the study of fractional calculus theory, it was found that it is suitable for studying nonlinear, non-causal, and non-stationary signals, and has the dual functions of improving detection information and enhancing signal strength. Therefore, under the influence of many factors, we applied the fractional difference algorithm to the field of information data processing. Multi-sensor detection data fusion algorithm based on the fractional partial differential equation was adopted to establish its online detection data. A multi-sensor detection data fusion algorithm based on a fractional partial differential equation is established, which effectively fuses the information data detection errors caused by various influencing factors and greatly improves the detection accuracy of information data. The effectiveness of this method is proved through its application in an experiment.

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“…Therefore, the correct detection and repair of cycle slips has become a very important step in high-accuracy data processing [1][2].…”

Section: Introductionmentioning

confidence: 99%

“…It is assumed that the noise terms of the carrier phase observations in each frequency are independent in time and are identical in variance, i.e., 1 2 3…”

mentioning

confidence: 99%

A Real-Time Cycle Slip Detection and Repair Method Based on Ionospheric Delay Prediction for Undifferenced Triple-Frequency BDS Signals

et al. 2021

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The detection and repair of cycle slips are key steps in high-accuracy GNSS (Global Navigation Satellite System) data processing using carrier phase observations. BDS (BeiDou Navigation Satellite System) triple-frequency observations provide better combinations for cycle slip detections and repairs compared to dual-frequency observations. Although a number of algorithms have been developed and may correctly detect cycle slips most of the time, the reliability of empirical thresholds methods cannot be guaranteed. In this study, an adaptive threshold is proposed for three sets of triple-frequency Geometry-Free (GF) pseudorange minus phase combinations to improve the cycle slip detection performance and reduce the false alarm rate of the cycle slip detection by combining the predicted epoch-differenced ionospheric delays under active ionospheric conditions. Moreover, in the cycle slip repair, the integral combined cycle slips are determined by directly rounding the estimated float-combined cycle slips, which will lead to a repair error if the between-epoch ionospheric variation is large. In this study, a new rounding method considering the predicted epoch-differenced ionospheric delays is proposed, and it is proven that the new method has a higher success rate for estimating the integer value of a cycle slip than the traditional method. The performance of the newly proposed method is validated by using static BDS triple-frequency observations that contain simulated cycle slips. BDS triple-frequency observations were collected at 30-s sampling intervals under active ionospheric conditions. The results show that this method can successfully detect and repair all slips of more than one cycle. In addition, dynamic BDS data collected with a vehiclebased receiver at a 1-s sampling intervals are processed, and the results show that the proposed method is also effective in the detection and repair of cycle slips in dynamic data.

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A Novel Cycle Slips Detection Model for the High Precision Positioning

Cited by 11 publications

References 29 publications

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

A Real-Time Cycle Slip Detection and Repair Method Based on Ionospheric Delay Prediction for Undifferenced Triple-Frequency BDS Signals

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