scholarly journals An Improved Real-Time Transfer Alignment Algorithm Based on Adaptive Noise Estimation for Distributed POS

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 102119-102127 ◽  
Author(s):  
Bo Wang ◽  
Wen Ye ◽  
Yanhong Liu
Keyword(s):  
Real Time ◽  
Noise Estimation ◽  
Alignment Algorithm ◽  
Time Transfer ◽  
Transfer Alignment ◽  
Adaptive Noise

Energy Detection Based Estimation of Channel Occupancy Rate with Adaptive Noise Estimation

2012 ◽  
Vol E95-B (4) ◽  
pp. 1076-1084 ◽  
Author(s):  
Janne J. LEHTOMÄKI ◽  
Risto VUOHTONIEMI ◽  
Kenta UMEBAYASHI ◽  
Juha-Pekka MÄKELÄ
Keyword(s):  
Energy Detection ◽  
Noise Estimation ◽  
Occupancy Rate ◽  
Adaptive Noise ◽  
Channel Occupancy

An analysis of BDS-3 real-time PPP: Time transfer, positioning, and tropospheric delay retrieval

Measurement ◽  
2021 ◽  
Vol 172 ◽  
pp. 108871
Author(s):  
Yulong Ge ◽  
Shaoxin Chen ◽  
Tao Wu ◽  
Caoming Fan ◽  
Weijin Qin ◽  
...  
Keyword(s):  
Real Time ◽  
Tropospheric Delay ◽  
Time Transfer

scholarly journals Study on a Twice Transfer Alignment Based on Dual Model

2015 ◽  
Vol 2015 ◽  
pp. 1-5
Author(s):  
Shuai Chen ◽  
Runwu Zhong ◽  
Xiaohui Liu ◽  
Ahmed Alsaedi
Keyword(s):  
Kalman Filter ◽  
Convergence Time ◽  
Alignment Algorithm ◽  
Dual Model ◽  
Matching Method ◽  
Error Models ◽  
Transfer Alignment ◽  
Nonlinear Error ◽  
Dual Models ◽  
Rapid Transfer

This paper proposes a twice rapid transfer alignment algorithm based on dual models in order to solve the problems such as long convergence time, poor accuracy, and heavy computation burden resulting from the traditional nonlinear error models. The quaternion matching method based on quaternion error model along with the extended Kalman filter (EKF) is applied to deal with the large misalignment in the first phase. Then in the second transfer alignment phase, velocity plus attitude matching method as well as classical Kalman filter is adopted. The simulation and the results of vehicle tests demonstrate that this method combines the advantages of both nonlinear and linear error models with the guarantee of accuracy and fastness.

Using IGS RTS Products for Real-Time Subnanosecond Level Time Transfer

2018 ◽  
pp. 505-518 ◽  
Author(s):  
Guojun Li ◽  
Yuting Lin ◽  
Fengfeng Shi ◽  
Jialin Liu ◽  
Yuting Yang ◽  
...  
Keyword(s):  
Real Time ◽  
Time Transfer

scholarly journals A New Online Dynamic Testing Method for Noise of Broadcast Transmitter

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan-Shan Li ◽  
Jian Zhou ◽  
Xuan Wang
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Dynamic Testing ◽  
Noise Figure ◽  
Estimation Algorithm ◽  
Test Method ◽  
Noise Estimation ◽  
Experimental Simulation ◽  
Spectrum Estimation ◽  
Low Efficiency

Aiming at the shortcomings of traditional broadcast transmitter noise test methods, such as low efficiency, inconvenient data storage, and high requirements for testers, a dynamic online test method for transmitter noise is proposed. The principle of system composition and test method is given. The transmitter noise is real-time changing. The Voice Active Detection (VAD) noise estimation algorithm cannot track the transmitter noise change in real time. This paper proposes a combined noise estimation algorithm for VAD and dynamic estimation. By setting the threshold of the double-threshold VAD detection to be low, it can accurately detect the silent segment. The silent segment is used as a noise signal for noise estimation. For the nonsilent segment detected by the VAD, a minimum value search dynamic spectrum estimation algorithm based on the existence probability of the speech (IMCRA) is used for noise estimation. Transmitter noise is measured by calculating the noise figure (NF).The test method collects the input and output data of the transmitter in real time, which has better accuracy and real-time performance, and the feasibility of the method is verified by experimental simulation.

scholarly journals Real-time transfer of lentiviral particles by producer cells using an engineered coculture system

2019 ◽  
Vol 71 (5) ◽  
pp. 1019-1031
Author(s):  
Lauren M. Timmins ◽  
Riya S. Patel ◽  
Matthew S. Teryek ◽  
Biju Parekkadan
Keyword(s):  
Real Time ◽  
Time Transfer ◽  
Coculture System
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