Study of a New Method about Improving the Positioning Accuracy of Dual-satellites Passive Location System

2017 ◽  
Author(s):  
Yanrong Xue ◽  
Juan Du ◽  
Yuwei Li ◽  
Wenli Wang ◽  
Xin Zhang
Keyword(s):  
New Method ◽  
Passive Location ◽  
Positioning Accuracy ◽  
Location System

Sensor registration technique for passive location system

2009 ◽  
Author(s):  
Xiong Wei ◽  
Pan Xu-dong ◽  
Peng Ying-ning
Keyword(s):  
Passive Location ◽  
Location System ◽  
Sensor Registration

A New Method of Torque Compensation for High Speed Indexing Cam Mechanism

1999 ◽  
Vol 121 (2) ◽  
pp. 319-323 ◽  
Author(s):  
Teng Guilan ◽  
Fu Haibo ◽  
Zhou Weiyi
Keyword(s):  
Kinetic Energy ◽  
High Speed ◽  
Output Shaft ◽  
New Method ◽  
Linkage Mechanism ◽  
Energy Fluctuation ◽  
Positioning Accuracy ◽  
Input Shaft ◽  
Cam Mechanism

Severe vibration and poor positioning accuracy may occur in an indexing cam mechanism operating at a high speed. Torque fluctuation of the input shaft and the resulting fluctuation of kinetic energy of the mechanism may be the major cause of the vibration. In this paper a method is proposed to minimize the fluctuation by using a so-called “speed-varying flywheel” that produces an opposite kinetic energy fluctuation that can counteract the effect of the energy fluctuation. The flywheel is installed on the output shaft of an additional cam-linkage mechanism. The parameter of the cam-linkage mechanism is optimized. An example is given to demonstrate the effectiveness of this method.

scholarly journals A Virtualization Approach to Correct Systematic Errors in Measured TDOA and FDOA for Low Orbit Dual-Satellite Positioning Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Gang Li ◽  
Min Zhou ◽  
Hongwen Tang ◽  
Hongbin Chen
Keyword(s):  
Systematic Errors ◽  
Time Difference ◽  
Frequency Difference ◽  
Reference Station ◽  
Virtual Reference ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Location System ◽  
Measured Time

The low-orbit dual-satellite passive location system provides a cost-efficient and easy implementation platform, by which positions of unknown emitters on the Earth can be determined through measuring both the time and the frequency differences by two low-orbit satellites in space. However, in reality, this dual-satellite location system has low positioning accuracy because of the existence of systematic errors. In this paper, in order to address the problem of low positioning accuracy in low-orbit dual-satellite systems, a virtualization approach, consisting of the establishment of the virtual reference station and virtual frequency conversion, is proposed to correct systematic errors in the system. Specifically, we first analyze the coming source of systematic errors in the dual-satellite location system, and then, a virtual reference station and virtual frequency are constructed to correct errors in the measured time difference of arrival and the frequency difference of arrival, respectively. Simulation results show that systematic errors caused by the measured time difference of arrival can be significantly reduced, and the correction efficiency, defined as a ratio between remaining errors after implementing the proposed method over uncorrected ones, for the measured frequency difference of arrival, largely relies on both the virtual frequency and the transmission frequency of reference stations.

A blind signal detection algorithm for passive location system based on troposcatter

2018 ◽  
Vol 10 (10) ◽  
pp. 1128-1133
Author(s):  
Zan Liu ◽  
Xihong Chen ◽  
Qiang Liu ◽  
Zedong Xie
Keyword(s):  
Signal Detection ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Ensemble Empirical Mode Decomposition ◽  
Passive Location ◽  
Intrinsic Mode Functions ◽  
Location System ◽  
Blind Signal ◽  
Mode Decomposition ◽  
Signal Simulation

AbstractTo improve detection performance of passive location system based on troposcatter, we propose a blind signal detection algorithm. According to our algorithm, complementary ensemble empirical mode decomposition decomposes the received signal into several intrinsic mode functions (IMFs). To reconstruct the signal and background noises, difference between the entropy of adjacent IMFs is utilized as a standard. Different IMFs are utilized to estimate threshold of energy detection algorithm and energy level of received signal. Simulation examples indicate that the proposed algorithm can blindly and effectively detect the signal.

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