scholarly journals A New Method for Multipath Filtering in GPS Static High-Precision Positioning

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2704
Author(s):  
Ke Han ◽  
Canyang Tang ◽  
Zhongliang Deng
Keyword(s):  
Wavelet Transform ◽  
White Noise ◽  
High Precision ◽  
Edge Effect ◽  
High Frequency ◽  
Wavelet Packet ◽  
Weighted Average ◽  
Double Difference ◽  
Precision Positioning ◽  
High Frequency Part

It is well known that multipath is one of the main sources of errors in GPS static high precision positioning of short baselines. Most algorithms for reducing multipath manipulate the GPS double difference (DD) observation residuals as input signal in GPS signal processing. In the traditional multipath mitigation methods, applying the wavelet transform (WT) to decompose the GPS DD observation residuals for identifying the multipath disturbance cannot effectively filter out the white noise of the high frequency part of the signal, and it is prone to edge effect. In this paper, for extracting multipath, a wavelet packet algorithm based on two-dimensional moving weighted average processing (WP-TD) is proposed. This algorithm can not only effectively filter out the white noise of the high frequency part of the signal, but also weaken the influence of the edge effect. Furthermore, considering the repeatability of multipath error in static positioning, we propose a method for determining the level of wavelet packet decomposition layers which make multipath extraction more effectively. The experimental results show that the corrected positioning accuracy is 14.14% higher than that of the traditional wavelet transform when applying the obtained multipath to DD coordinate sequences for position correction.

DEPSO With DTCWT Algorithm for Multimodal Medical Image Fusion

2021 ◽  
Vol 12 (4) ◽  
pp. 78-97
Author(s):  
Hassiba Talbi ◽  
Mohamed-Khireddine Kholladi
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Medical Image ◽  
Low Frequency ◽  
Weighted Average ◽  
Optimization Method ◽  
Absolute Maximum ◽  
Complex Wavelet Transform ◽  
Medical Image Fusion

In this paper, the authors propose an algorithm of hybrid particle swarm with differential evolution (DE) operator, termed DEPSO, with the help of a multi-resolution transform named dual tree complex wavelet transform (DTCWT) to solve the problem of multimodal medical image fusion. This hybridizing approach aims to combine algorithms in a judicious manner, where the resulting algorithm will contain the positive features of these different algorithms. This new algorithm decomposes the source images into high-frequency and low-frequency coefficients by the DTCWT, then adopts the absolute maximum method to fuse high-frequency coefficients; the low-frequency coefficients are fused by a weighted average method while the weights are estimated and enhanced by an optimization method to gain optimal results. The authors demonstrate by the experiments that this algorithm, besides its simplicity, provides a robust and efficient way to fuse multimodal medical images compared to existing wavelet transform-based image fusion algorithms.

scholarly journals An Iterative Hybrid Harmonics Detection Method Based on Discrete Wavelet Transform and Bartlett–Hann Window

2020 ◽  
Vol 10 (11) ◽  
pp. 3922 ◽  
Author(s):  
Guishuo Wang ◽  
Xiaoli Wang ◽  
Chen Zhao
Keyword(s):  
Wavelet Transform ◽  
Steady State ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Detection Method ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Detection Accuracy ◽  
Harmonic Detection ◽  
High Frequency Part

The current signal harmonic detection method(s) cannot reduce the errors in the analysis and extraction of mixed harmonics in the power grid. This paper designs a harmonic detection method based on discrete Fourier transform (DFT) and discrete wavelet transform (DWT) using Bartlett–Hann window function. It improves the detection accuracy of the existing methods in the low frequency steady-state part. In addition, it also separates the steady harmonics from the attenuation harmonics of the high frequency part. Simulation results show that the proposed harmonic detection method improves the detection accuracy of the steady-state part by 1.5175% compared to the existing method. The average value of low frequency steady-state amplitude detection of the proposed method is about 95.3375%. At the same time, the individual harmonic components of the signal are accurately detected and recovered in the high frequency part, and separation of the steady-state harmonics and the attenuated harmonics is achieved. This method is beneficial to improve the ability of harmonic analysis in the power grid.

Wavelet Transform Denoise of PCB Drilling Force Signal

2012 ◽  
Vol 500 ◽  
pp. 26-31 ◽  
Author(s):  
Yun Peng Qu ◽  
Cheng Yong Wang ◽  
Li Juan Zheng ◽  
Yue Xian Song
Keyword(s):  
Wavelet Transform ◽  
White Noise ◽  
Wavelet Packet ◽  
Simple Calculation ◽  
Drilling Force ◽  
Noise Interference ◽  
Force Signal ◽  
Micro Drilling ◽  
Non Stationary Signal ◽  
Micro Drill

In the PCB micro drilling, because the force signal is tiny, and when the micro-drill drill to a certain degree of multilayer PCB, alternate force signals will not appear obvious, through to the drilling force signal analysis, we can know the drill bit position and the materials to the influence of the drill failure, so the drilling force signals denoise seems extremely important. In the processing of the non-stationary signal, traditional signal processing method has a certain extent of insufficient, using the wavelet packet decomposition signal, the white noise variance and amplitude decrease with the increase of wavelet scales, but the signal variance and amplitude has nothing to do with the wavelet transform. According to the view of the signal energy, first of all, we make the multiscale decomposition of the signal, then, by using some of the wavelet packet that has efficient energy to reconstruct the original signal. Comparing with the traditional threshold denoising ,using this method in the test signal to deal with the noise can effectively eliminate the white noise interference, and has good denoising effects besides the simple calculation.

A De-Noising Algorithm for ECG Signals Based on FIR Filter and Wavelet Transform

2011 ◽  
Vol 271-273 ◽  
pp. 247-252
Author(s):  
Lei Shi ◽  
Yu Juan Si ◽  
Liu Qi Lang ◽  
Cheng Yao ◽  
Li Li Liu
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Bandpass Filter ◽  
Clinical Analysis ◽  
Fir Filters ◽  
Synthesis Algorithm ◽  
Baseline Drift ◽  
Ecg Signals ◽  
High Frequency Part ◽  
Muscle Moments

This paper adopts a synthesis algorithm which combines FIR filters and wavelet threshold de-noising method to complete ECG de-noising. Firstly, we designed a FIR equiripple bandpass filter using Matlab FDATool to remove baseline drift, power interference and the high frequency part of muscle moments. Then we adopted an improved wavelet threshold de-noising algorithm to remove the remaining muscle moments with less decomposing levels. The algorithm was implemented on Matlab platform. The experimental results show that the algorithm is simple in design and has less calculation and good de-noising effect, which is superior to conventional wavelet threshold de-noising algorithm, and can be used in clinical analysis.

High-Precision Positioning of Galvano Scanners by Structural Design Using Node of Vibration Modes

2011 ◽  
Vol 131 (3) ◽  
pp. 275-282
Author(s):  
Kenta Seki ◽  
Hiroaki Matsuura ◽  
Makoto Iwasaki ◽  
Hiromu Hirai ◽  
Soichi Tohyama
Keyword(s):  
High Precision ◽  
Structural Design ◽  
Vibration Modes ◽  
Precision Positioning

Development of a thin high-frequency and high-precision magnetic probe array in Sino-United Spherical Tokamak

2021 ◽  
Vol 92 (5) ◽  
pp. 053518
Author(s):  
Zhengbo Cheng ◽  
Yi Tan ◽  
Zhe Gao ◽  
Shouzhi Wang ◽  
Binbin Wang ◽  
...  
Keyword(s):  
High Precision ◽  
High Frequency ◽  
Magnetic Probe ◽  
Spherical Tokamak ◽  
Probe Array
Sign in / Sign up

Export Citation Format

Share Document