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

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>

scholarly journals A new algorithm for considering green communication and excellent sensing performance in cognitive radio networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772093313 ◽  
Author(s):  
Tangsen Huang ◽  
Xiangdong Yin ◽  
Qingjiao Cao
Keyword(s):  
Real Time ◽  
Spectrum Sensing ◽  
Computation Time ◽  
Time Spectrum ◽  
Fusion Center ◽  
Local Data ◽  
Green Communication ◽  
Processing Efficiency ◽  
The Real ◽  
Sensing Performance

Multi-node cooperative sensing can effectively improve the performance of spectrum sensing. Multi-node cooperation will generate a large number of local data, and each node will send its own sensing data to the fusion center. The fusion center will fuse the local sensing results and make a global decision. Therefore, the more nodes, the more data, when the number of nodes is large, the global decision will be delayed. In order to achieve the real-time spectrum sensing, the fusion center needs to quickly fuse the data of each node. In this article, a fast algorithm of big data fusion is proposed to improve the real-time performance of the global decision. The algorithm improves the computing speed by reducing repeated computation. The reinforcement learning mechanism is used to mark the processed data. When the same environment parameter appears, the fusion center can directly call the nodes under the parameter environment, without having to conduct the sensing operation again. This greatly reduces the amount of data processed and improves the data processing efficiency of the fusion center. Experimental results show that the algorithm in this article can reduce the computation time while improving the sensing performance.

Improving real-time clock estimation with undifferenced ambiguity fixing

GPS Solutions ◽  
2019 ◽  
Vol 23 (2) ◽  
Author(s):  
Zhiqiang Dai ◽  
Xiaolei Dai ◽  
Qile Zhao ◽  
Jingnan Liu
Keyword(s):  
Real Time ◽  
Real Time Clock ◽  
Ambiguity Fixing ◽  
Clock Estimation

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

2019 ◽  
Vol 93 (12) ◽  
pp. 2515-2528 ◽  
Author(s):  
Xingxing Li ◽  
Yun Xiong ◽  
Yongqiang Yuan ◽  
Jiaqi Wu ◽  
Xin Li ◽  
...  
Keyword(s):  
Real Time ◽  
Ambiguity Resolution ◽  
Time Estimation ◽  
Real Time Estimation

Multi-GNSS real-time clock estimation using sequential least square adjustment with online quality control

2018 ◽  
Vol 93 (7) ◽  
pp. 963-976 ◽  
Author(s):  
Wenju Fu ◽  
Guanwen Huang ◽  
Qin Zhang ◽  
Shengfeng Gu ◽  
Maorong Ge ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Least Square ◽  
Real Time Clock ◽  
Online Quality Control ◽  
Clock Estimation

Multi-GNSS real-time clock estimation using the dual-thread parallel method

2018 ◽  
Vol 62 (9) ◽  
pp. 2518-2528 ◽  
Author(s):  
Zhiqiang Dai ◽  
Xiaolei Dai ◽  
Qile Zhao ◽  
Zhixiong Bao ◽  
Chenggang Li
Keyword(s):  
Real Time ◽  
Parallel Method ◽  
Real Time Clock ◽  
Clock Estimation

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

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xiang Zuo ◽  
Xinyuan Jiang ◽  
Pan Li ◽  
Jungang Wang ◽  
Maorong Ge ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Computational Efficiency ◽  
High Rate ◽  
Control Procedure ◽  
Square Root ◽  
Essential Information ◽  
Real Time Clock ◽  
Information Filter ◽  
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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