A spread spectrum system with a time domain processing device

1997 ◽  
Vol 44 (6) ◽  
pp. 447-452 ◽  
Author(s):  
Shiping He ◽  
T.K.Y. Lo ◽  
J. Litva
Keyword(s):  
Time Domain ◽  
Spread Spectrum ◽  
Processing Device

Postprocessing for Improved Accuracy and Resolution of Spread Spectrum Time-Domain Reflectometry

2019 ◽  
Vol 3 (6) ◽  
pp. 1-4 ◽  
Author(s):  
Naveen Kumar Tumkur Jayakumar ◽  
Evan Benoit ◽  
Samuel Kingston ◽  
Mashad Uddin Saleh ◽  
Michael Scarpulla ◽  
...  
Keyword(s):  
Time Domain ◽  
Spread Spectrum ◽  
Time Domain Reflectometry ◽  
Improved Accuracy

scholarly journals Sequence and spread spectrum time domain reflectometry for transmission line analysis

2007 ◽  
Author(s):  
Jacklyn Reis ◽  
Agostinho L. S. Castro ◽  
João C. W. A. Costa ◽  
Jaume R. I. Riu ◽  
Klas Ericson
Keyword(s):  
Transmission Line ◽  
Time Domain ◽  
Spread Spectrum ◽  
Time Domain Reflectometry ◽  
Line Analysis

A Novel Algorithm for Long Pseudo-Code Acquisition in Spread Spectrum Communication System

2014 ◽  
Vol 610 ◽  
pp. 905-909
Author(s):  
Chun Hui Ren ◽  
Zhong Quan He
Keyword(s):  
Time Domain ◽  
Spread Spectrum ◽  
Communication System ◽  
Binary Search ◽  
Spread Spectrum Communication ◽  
Specific Method ◽  
Capture Time ◽  
Reference Sequences ◽  
The Time Domain ◽  
Novel Algorithm

The capture of long Pseudo-Code code is the most important technology in spread spectrum system. we use XFAST,AVERAGE to solve this problem in old days. A new algorithm is proposed which based on the time domain samples and binary search according the autocorrelation of the Pseudo-Code (PN code) and improve the speed of the capture of long Pseudo-Code code in spread spectrum system. Firstly, received spread spectrum signal's simple rate is reduced to a quarter of the chip rate and determine with a specific method, then divide the local PN code into four parts and accumulated to a new sequence. finally, the synchronous pseudo-code is captured with the correlation of the two new reference sequences. Compared with conventional methods such as XFAST, capture time and precision are improved.

Spread Spectrum Time Domain Reflectrometry Applied to Electrical Systems in Nuclear Power Plants

2010 ◽  
Author(s):  
Gary M. Sandquist ◽  
Carl J. Sandquist
Keyword(s):  
Time Domain ◽  
Integrated Circuit ◽  
Spread Spectrum ◽  
Power Plants ◽  
Short Circuit ◽  
Time Domain Reflectometry ◽  
Nuclear Plant ◽  
Current Time ◽  
Electrical Systems ◽  
On Line

A recently developed technique “Spread Spectrum Time Domain Reflectometry” (SSTDR), and supporting test devices will be adapted and tested to monitor and diagnose nuclear plant electrical systems. Current time domain reflectometry methods cannot detect or locate small faults after arc fault events, because their impedance discontinuity is too small and transient to create a measurable reflection. However, on-line, unobtrusive SSTDR can detect and locate arc and other electrical faults when the (∼msec) short circuit returns a strong reflected signal. These observations have led to development of SSTDR. If SSTDR can be successfully adapted to present and future nuclear plant electrical systems, it will be possible to monitor, on-line, the integrity of the electrical system continuously and with only minor equipment modification and no consequential safety issues. An integrated circuit (IC) is under development at the University of Utah for applications in the aircraft industry that will be adapted and used for this proposed development.

Spread Spectrum Time Domain Reflectometry for Health Monitoring of Solar Arrays

2021 ◽  
Author(s):  
Joel B. Harley ◽  
Ayobami Edun ◽  
Cody Laflamme ◽  
Samuel Kingston ◽  
Evan Benoit ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Time Domain ◽  
Spread Spectrum ◽  
Time Domain Reflectometry ◽  
Solar Arrays

Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion

2021 ◽  
Vol 36 (2) ◽  
pp. 190-198
Author(s):  
Samuel Kingston ◽  
Hunter Ellis ◽  
Mashad Saleh ◽  
Evan Benoit ◽  
Ayobami Edun ◽  
...  
Keyword(s):  
Time Domain ◽  
Spread Spectrum ◽  
Complex Impedance ◽  
Time Domain Reflectometry ◽  
Steepest Descent ◽  
Model Parameters ◽  
Inversion Algorithm ◽  
Parametric Function ◽  
Descent Algorithm ◽  
Steepest Descent Algorithm

In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. The errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.

Sign in / Sign up

Export Citation Format

Share Document