A square root information filter for multi-GNSS real-time precise clock estimation

AbstractReal-time satellite orbit and clock estimations are the prerequisite for Global Navigation Satellite System (GNSS) real-time precise positioning services. To meet the high-rate update requirement of satellite clock corrections, the computational efficiency is a key factor and a challenge due to the rapid development of multi-GNSS constellations. The Square Root Information Filter (SRIF) is widely used in real-time GNSS data processing thanks to its high numerical stability and computational efficiency. In real-time clock estimation, the outlier detection and elimination are critical to guarantee the precision and stability of the product but could be time-consuming. In this study, we developed a new quality control procedure including the three standard steps: i.e., detection, identification, and adaption, for real-time data processing of huge GNSS networks. Effort is made to improve the computational efficiency by optimizing the algorithm to provide only the essential information required in the processing, so that it can be applied in real-time and high-rate estimation of satellite clocks. The processing procedure is implemented in the PANDA (Positioning and Navigation Data Analyst) software package and evaluated in the operational generation of real-time GNSS orbit and clock products. We demonstrated that the new algorithm can efficiently eliminate outliers, and a clock precision of 0.06 ns, 0.24 ns, 0.06 ns, and 0.11 ns can be achieved for the GPS, GLONASS, Galileo, and BDS-2 IGSO/MEO satellites, respectively. The computation time per epoch is about 2 to 3 s depending on the number of existing outliers. Overall, the algorithm can satisfy the IGS real-time clock estimation in terms of both the computational efficiency and product quality.

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A Decentralized Processing Schema for Efficient and Robust Real-time Multi-GNSS Satellite Clock Estimation

Remote Sensing ◽

10.3390/rs11212595 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2595

Author(s):

Jiang ◽

Gu ◽

Li ◽

Ge ◽

Schuh

Keyword(s):

Real Time ◽

High Frequency ◽

Precise Point Positioning ◽

High Rate ◽

Reference Network ◽

Satellite Clock ◽

Navigation Data ◽

Data Analyst ◽

New Strategy ◽

Clock Estimation

Real-time multi-GNSS precise point positioning (PPP) requires the support of high-rate satellite clock corrections. Due to the large number of ambiguity parameters, it is difficult to update clocks at high frequency in real-time for a large reference network. With the increasing number of satellites of multi-GNSS constellations and the number of stations, real-time high-rate clock estimation becomes a big challenge. In this contribution, we propose a decentralized clock estimation (DECE) strategy, in which both undifferenced (UD) and epoch-differenced (ED) mode are implemented but run separately in different computers, and their output clocks are combined in another process to generate a unique product. While redundant UD and/or ED processing lines can be run in offsite computers to improve the robustness, processing lines for different networks can also be included to improve the clock quality. The new strategy is realized based on the Position and Navigation Data Analyst (PANDA) software package and is experimentally validated with about 110 real-time stations for clock estimation by comparison of the estimated clocks and the PPP performance applying estimated clocks. The results of the real-time PPP experiment using 12 global stations show that with the greatly improved computational efficiency, 3.14 cm in horizontal and 5.51 cm in vertical can be achieved using the estimated DECE clock.

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Improving real-time clock estimation with undifferenced ambiguity fixing

GPS Solutions ◽

10.1007/s10291-019-0837-z ◽

2019 ◽

Vol 23 (2) ◽

Cited By ~ 4

Author(s):

Zhiqiang Dai ◽

Xiaolei Dai ◽

Qile Zhao ◽

Jingnan Liu

Keyword(s):

Real Time ◽

Real Time Clock ◽

Ambiguity Fixing ◽

Clock Estimation

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Real-time precise orbit determination for BDS satellites using the square root information filter

GPS Solutions ◽

10.1007/s10291-019-0827-1 ◽

2019 ◽

Vol 23 (2) ◽

Cited By ~ 3

Author(s):

Xiaolei Dai ◽

Yidong Lou ◽

Zhiqiang Dai ◽

Yun Qing ◽

Min Li ◽

...

Keyword(s):

Real Time ◽

Orbit Determination ◽

Precise Orbit Determination ◽

Square Root ◽

Precise Orbit ◽

Information Filter

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Aerocraft Real-Time Measured Data Processing Method Based on Combined Filtering

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.716-717.983 ◽

2014 ◽

Vol 716-717 ◽

pp. 983-986

Author(s):

Yan Li ◽

Hua Jun Liu ◽

Guang Lang Bian ◽

Miao Hui Liu

Keyword(s):

Data Processing ◽

Real Time ◽

Measured Data ◽

Control Procedure ◽

Time Data ◽

The Real ◽

Data Processing Method ◽

Real Time Data ◽

Processing Accuracy ◽

Real Time Data Processing

To solve the problems that resulted from using a certain filtering method alone to process the real-time data measured on aerocraft, a new method combined filter and Savitzky-Golay smoothing filter is proposed to process the real-time measuring data, which could classify and segment the measured data of aerocraft trajectory according to its priority and time domain. It could provide useful principle and control procedure of combined filters on different conditions to improve the filter efficiency, and the combined filtering results meet the needs of aerocraft real-time data processing accuracy in different measured sections.

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Effective Efficiency Advantage Assessment of Information Filter for Conventional Kalman Filter in GNSS Scenarios

Sensors ◽

10.3390/s19183858 ◽

2019 ◽

Vol 19 (18) ◽

pp. 3858 ◽

Cited By ~ 1

Author(s):

Zheng ◽

Wang ◽

Wang

Keyword(s):

Kalman Filter ◽

Data Processing ◽

Real Time ◽

Computational Cost ◽

Satellite System ◽

Hardware Platform ◽

Algorithm Efficiency ◽

Information Filter ◽

Global Navigation Satellite ◽

Cv Model

The Global Navigation Satellite System (GNSS) is a widely used positioning technique. Computational efficiency is crucial to applications such as real-time GNSS positioning and GNSS network data processing. Many researchers have made great efforts to address this problem by means such as parameter elimination or satellite selection. However, parameter estimation is rarely discussed when analyzing GNSS algorithm efficiency. In addition, most studies on Kalman filter (KF) efficiency commonly have defects, such as neglecting application-specified optimization and limiting specific hardware platforms in the conclusion. The former reduces the practicality of the solution, because applications that need such analyses on filters are often optimized, and the latter reduces its generality because of differences between platforms. In this paper, the computational cost enhancement of replacing the conventional KF with the information filter (IF) is tested considering GNSS application-oriented optimization conditions and hardware platform differences. First, optimization conditions are abstracted from GNSS data-processing scenarios. Then, a thorough analysis is carried out on the computational cost of the filters, considering hardware–platform differences. Finally, a case of GNSS dynamic differencing positioning is studied. The simulation shows that the IF is slightly faster for precise point positioning and much faster for the code-based single-difference GNSS (SDGNSS) with the constant velocity (CV) model than the conventional KF, but is not a good substitute for the conventional KF in the other algorithms mentioned. The real test shows that the IF is about 50% faster than the conventional KF handling code-based SDGNSS with the CV model. Also, the information filter is theoretically equivalent to and can produce results that are consistent with the Kalman filter. Our conclusions can be used as a reference for GNSS applications that need high process speed or real-time capability.

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Real-time estimation of multi-GNSS and multi-frequency integer recovery clock with undifferenced ambiguity resolution

10.5194/egusphere-egu2020-5270 ◽

2020 ◽

Author(s):

Yun Xiong ◽

Yongqiang Yuan ◽

Jiaqi Wu ◽

Xin Li ◽

Jiaxin Huang

Keyword(s):

Real Time ◽

Ambiguity Resolution ◽

Computation Time ◽

Time Estimation ◽

Global Navigation Satellite Systems ◽

Estimation Model ◽

Processing Efficiency ◽

Real Time Clock ◽

Clock Estimation ◽

Gnss Observations

<p>Precise clock product of global navigation satellite systems (GNSS) is an important prerequisite to support real-time precise positioning service. The developments of multi-constellation and multi-frequency GNSS open new requirements for real-time clock estimation. In this contribution, the estimation model of multi-GNSS and multi-frequency integer recovery clock (IRC) is developed to improve both the accuracy and efficiency of real-time clock estimates. In the proposed method, the undifferenced ambiguities are fixed to integers, thus the integer properties of the ambiguities are recovered and the accuracy of the clock estimates is also improved. Moreover, benefitting from the removal of large quantities of ambiguity parameters, the computation time is greatly reduced which can guarantee high processing efficiency of real-time clock estimates. Multi-GNSS observations from 150 globally distributed Multi-GNSS Experiment (MGEX) tracking stations were processed with the proposed model. Compared to the float satellite clocks, the precision of the real-time IRC with respect to CODE 30 s final multi-GNSS satellite clock products were improved by 53.0%, 42.7%, 63.7% and 33.9% for GPS, BDS, Galileo and GLONASS, respectively. The average computation time per epoch with multi-GNSS observations was improved by 97.1% compared to that of standard float clock estimation. Kinematic precise point positioning (PPP) ambiguity resolution was also performed with the derived real-time IRC products. Compared to the float PPP solutions, the position accuracy of the multi-GNSS IRC-based fixed solutions was improved by 77.2%, 49.7% and 52.7% from 24.2, 13.3 and 30.7 mm to 5.5, 6.7 and 14.5 mm for the east, north and up components, respectively. The results indicate that ambiguity fixing can be successfully achieved by using the derived the IRC products. In addition, the estimation model of multi-frequency IRC products is also investigated to promote the capability and application of real-time PPP AR under multi-frequency signals.</p>

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DEVELOPING AN AUTOMATED CONTROLLER FOR A SOLAR HEATING SYSTEM

Bulletin of the South Ural State University series Power Engineering ◽

10.14529/power210310 ◽

2021 ◽

Vol 21 (3) ◽

pp. 83-89

Author(s):

E. Amirgaliyev ◽

◽

M. Kunelbayev ◽

T. Sundetov

Keyword(s):

Data Processing ◽

Real Time ◽

Temperature Sensor ◽

Control Algorithm ◽

Heating System ◽

Temperature Sensors ◽

Solar Heating ◽

Real Time Clock ◽

Control And Monitoring System ◽

Clock Module

The paper discusses the development of an automated controller for a Mojo v3-based solar heating system. The developed system operates using 6 sensors (DS18B20 Dallas) expanding the platform's applicability. An in-tegrated system allows controlling temperature and heat using Dallas sensors. The control and monitoring system is implemented in the VHDL and VERILOG languages. A control algorithm has been developed that activates libraries and constants, a real-time clock module, temperature sensors, and server connection. When the server connection is established, the temperature sensor readings are recorded and saved in the XML file in the Ethernet module. XML facilitates data processing by automatically or manually interpreting spreadsheet programs.

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