Improving Clock Prediction Algorithm for BDS-2/3 Satellites Based on LS-SVM Method

The satellite clock prediction is crucial to support real-time global satellite precise positioning services. Currently, the clock prediction for the Chinese BeiDou navigation satellite system (BDS) is still challenging to satisfy the precise positioning applications. Based on the exploration of existing prediction models, an improved model combing the spectrum analysis model (SAM) and the least-squares support-vector machine (LS-SVM) is proposed especially for BDS-2/3 satellites. Considering satellite-specific characteristics, the parameters of the LS-SVM method are optimized satellite by satellite, including input length, regularization and kernel parameters. The improved model is evaluated by comparing the predicted clocks of existing methods and the improved model. The bias of the predicted clock offsets are within ±1.0 ns for most medium Earth orbits (MEOs) over three hours employing the improved model, which is better than that of the existing methods and can be applied for several real-time precise positioning applications. The predicted clock offsets are further evaluated by applying clock corrections to precise point positioning (PPP) in both static and kinematic modes for 10 international GNSS service (IGS) Multi-GNSS Experiment (MGEX) stations, including five stations in the Asia-Pacific region. According to the practical engineering experience, 2 dm and 5 dm are defined for static and kinematic PPP, respectively, as a convergence threshold. Then, in the static PPP, the improved model is demonstrated to be effective, and positioning accuracies of some stations obtain more than 15% improvements on average for each direction, which enables them to get sub-decimeter positioning, especially in the Asia-Pacific region. In the kinematic PPP, the improved model performs much better than the others in terms of both the convergence time and the positioning accuracy. The convergence time can be shortened from 1.0 h to below 0.5 h, while the positioning accuracies are enhanced by 16.3%, 10.8%, and 18.9% on average in east, north, and up direction, respectively.

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Improving Short Term Clock Prediction for BDS-2 Real-Time Precise Point Positioning

Sensors ◽

10.3390/s19122762 ◽

2019 ◽

Vol 19 (12) ◽

pp. 2762 ◽

Cited By ~ 3

Author(s):

Lina He ◽

Hairui Zhou ◽

Yuanlan Wen ◽

Xiufeng He

Keyword(s):

Real Time ◽

Precise Point Positioning ◽

Service Providers ◽

Convergence Time ◽

Asia Pacific ◽

Position Accuracy ◽

Point Positioning ◽

Clock Prediction ◽

Improved Model ◽

Better Than

Although there are already several real-time precise positioning service providers, unfortunately, not all users can use the correction information due to either cost of the service and limitation of their equipment or out of the service coverage. An alternative way is to enhance the accuracy of the predicted satellite clocks for precise real-time positioning. Based on the study of existing prediction models, an improved model combing the spectrum analysis (SA) and the generalized regression neural network (GRNN) model is proposed especially for BeiDou satellite navigation system (BDS)-2 satellites. The periodic terms and GRNN-related parameters including length and interval of sample data, as well as a smooth factor, are optimized satellite by satellite to consider satellite-specific characteristics for all the fourteen BDS-2 satellites. The improved model is validated by comparing the predicted clocks of existing models and the improved model with precisely estimated ones. The bias of the predicted clock is within ±0.5 ns over three hours and better than that of the other models and can be used for several real-time precise applications. The clock prediction is further evaluated by applying clock corrections to precise point positioning (PPP) in both static and kinematic mode for eight IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) stations in the Asia-Pacific region. In the static PPP, the improved model is validated to be effective, and position accuracies of some IGS MGEX stations achieve more than 30.0% improvements on average for each component, which enables us to obtain sub-decimeter positioning. In the kinematic PPP, the improved model performs much better than the others in terms of both the convergence time and the position accuracy. The convergence time can be shortened from 1–2 h to 0.5–1 h, while the position accuracy is enhanced by 15.4%, 21.6% and 19.3% on average in east, north and up component, respectively.

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Precise Point Positioning Using the Regional BeiDou Navigation Satellite Constellation

Journal of Navigation ◽

10.1017/s0373463313000842 ◽

2014 ◽

Vol 67 (3) ◽

pp. 523-537 ◽

Cited By ~ 7

Author(s):

Aigong Xu ◽

Zongqiu Xu ◽

Xinchao Xu ◽

Huizhong Zhu ◽

Xin Sui ◽

...

Keyword(s):

Real Time ◽

Precise Point Positioning ◽

Satellite System ◽

Convergence Time ◽

Asia Pacific ◽

Satellite Orbits ◽

Navigation Satellite ◽

Asia Pacific Region ◽

Point Positioning

On 27 December 2012 it was announced officially that the Chinese Navigation Satellite System BeiDou (BDS) was able to provide operational services over the Asia-Pacific region. The quality of BDS observations was confirmed as comparable with those of GPS, and relative positioning in static and kinematic modes were also demonstrated to be very promising. As Precise Point Positioning (PPP) technology is widely recognized as a method of precise positioning service, especially in real-time, in this contribution we concentrate on the PPP performance using BDS data only. BDS PPP in static, kinematic and simulated real-time kinematic mode is carried out for a regional network with six stations equipped with GPS- and BDS-capable receivers, using precise satellite orbits and clocks estimated from a global BDS tracking network. To validate the derived positions and trajectories, they are compared to the daily PPP solution using GPS data. The assessment confirms that the performance of BDS PPP is very comparable with GPS in terms of both convergence time and accuracy.

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Brian Herbert Kay 1944–2017

Historical Records of Australian Science ◽

10.1071/hr17022 ◽

2018 ◽

Vol 29 (1) ◽

pp. 36

Author(s):

Michael F. Good ◽

Scott A. Ritchie ◽

Darryl McGinn ◽

Richard C. Russell

Keyword(s):

Public Health ◽

Well Being ◽

Asia Pacific ◽

Pacific Region ◽

Asia Pacific Region ◽

The World ◽

History Of ◽

Young Researchers ◽

Better Than ◽

Scientific Achievements

Brian Kaywas a renowned entomologist and arbovirologistwhoworked in academia and with local and international governments to make major and lasting improvements in public health. Particular highlights were the first ever elimination of a saltmarsh mosquito in the world and elimination of dengue from many hamlets and villages in Vietnam. He is also remembered for the development of the careers of many young researchers in Australia and overseas. When thinking of Brian Kay, three things come to mind immediately. First, Brian was a great character–a man of fun and passion and always good to be around. He had a great cheeky smile. Second, Brian was deeply committed to the careers and well-being of those around him–exemplified no better than how he acted so caringly for the Queensland Institute of Medical Research (QIMR) staff when he served for several years as Chairman of the QIMR Staff Association; and third, Brian was an outstanding entomologist, biologist, scientist. Here, we give a little history of his background and attempt to distil a few of Brian's many scientific achievements and paint a picture of a man who was greatly admired and loved by those who worked alongside him in various parts of the world, but predominantly in Australia and the Asia Pacific Region.

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Does Five-Factor Model Perform Better Than Three Factor Model? Evidence from Developed Countries of The Asia Pacific Region

iRASD Journal of Economics ◽

10.52131/joe.2021.0302.0030 ◽

2021 ◽

Vol 3 (2) ◽

pp. 119-132

Author(s):

Ume Salma Akbar ◽

Niaz Ahmed Bhutto ◽

Suresh Kumar Oad Rajput

Keyword(s):

Factor Model ◽

Five Factor Model ◽

Explanatory Power ◽

Developed Countries ◽

Asia Pacific ◽

Size Factor ◽

Pacific Region ◽

Asia Pacific Region ◽

Three Factor ◽

Better Than

This study evaluates whether the “Fama-French five-factor model” can explain the variations in expected returns better than the “three-factor model.” Using the stock returns and accounting variable data from DataStream for 1,300 plus listed firms across six developed countries of the Asia Pacific region, including; Australia, Hong Kong, Japan, Israel, New Zealand, and Singapore for the period of Jun-2006 to February-2020. The paper is the first to examine the “five-factor model” performance across the developed countries of the Asia Pacific region. The empirical findings reveal that the Asia Pacific region for the sample period earns an equity premium. In addition, results report the redundancy of size factor (SMB) and value factor (HML), while the profitability (RMW) and investment premium (CMA) are positive and significant. Moreover, the study used Gibbons, Ross, and Shanken (GRS) test to the asset pricing model. The GRS test results on the “five-factor model” compared with the “three-factor model” demonstrate that profitability and investment factors add significant explanatory power to the analysis in the Asia Pacific region.

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