A MBOC Signal Tracking Algorithm based on Split Processing Technique

2019 ◽  
Author(s):  
Tengfei Da ◽  
Xueyong Xu ◽  
Xiaowei Cui ◽  
Guifeng Fan ◽  
Mingquan Lu
Keyword(s):  
Processing Technique ◽  
Tracking Algorithm ◽  
Signal Tracking

ROBUST SONIC LOG TRACKING USING A MULTI-RESOLUTION APPROACH

2021 ◽  
Author(s):  
Ting Lei ◽  
◽  
Michiko Hamada ◽  
Adam Donald ◽  
Takeshi Endo ◽  
...  
Keyword(s):  
Sudden Change ◽  
Processing Technique ◽  
Tracking Algorithm ◽  
Signal Loss ◽  
Tracking Accuracy ◽  
Signal Processing Technique ◽  
Waveform Data ◽  
Sonic Log ◽  
Tracking Process ◽  
Sonic Logs

Borehole acoustic logging is an acquisition method that is regarded as the most efficient and reliable method to measure subsurface rock elastic property. It plays an important role in both well construction and reservoir evaluation. The acquisition is carried out downhole by firing a transducer and then collecting waveforms at an array of receivers. A signal processing technique such as the slowness-time-coherence method is used to process array waveform data to resolve slownesses from different arrivals. To label these slowness values, a classification algorithm is then required to first determine if a primary (P) or a secondary (S) arrival exists or not, and then label out the existing ones at each depth of the entire logging interval to deliver continuous compressional and shear slowness logs. Such a process is referred as automatic sonic log tracking process. Clearly, it is of great importance to be able to track log as accurately as possible. Traditional approaches either use predefined slowness or arrival time boundary to distinguish them or treats slowness peaks in consecutive depths like “moving particles” and use a particle tracking algorithm to estimate their trace. However, such a tracking algorithm is often challenged by a sudden change in formation types at bed boundary, fine-scale heterogeneity, downhole logging noise, as well as unpredicted signal loss due to bad borehole shape or gas influx. Consequently, the tracking process is often a tricky task that requires heavy manual quality control and relabeling process, which poses significant bottleneck for a timely delivery of sonic logs for downstream petrophysical and geomechanical applications. In this paper, we propose a new physical based multi-resolution tracking algorithm that can improve the robustness of the tracking process. The new algorithm is inspired by the fact that different resolution sonic logs can sense different rock volumes and therefore response differently to a thin layer or an interval with bad borehole conditions. It works by grouping slowness-time peaks with different resolutions to form clusters, which are then tracked by the connecting with its neighboring depths. As different resolution slownesses are physically constrained by the convolution response of heterogeneous layers, the cluster-based multi-resolution tracking approach exhibits better logging depth continuity than the traditional single-resolution methods. Outliers due to noise can be confidently avoided. Finally, remaining gaps due to shoulder bed boundary can be patched by a convolution constrained optimization process from coherences from different resolutions. This new approach is therefore referred as a multi-resolution approach and can significantly improve sonic log tracking accuracy than the single resolution approach. This new algorithm has been tested on several sonic logging field data and demonstrates robust tracking performance of sonic P&S logs. Additionally, with the multi-resolution processing, sonic logs with different resolution can be reliably obtained and a high-quality high-resolution sonic log can also be automatically delivered, which can then be used to match resolution of other petrophysical logs for various types of interpretation.

scholarly journals Research on Acquisition and Tracking Algorithm of Global Satellite Positioning Receiver Based on UWB

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Li Yang ◽  
Danshi Sun ◽  
Haote Ruan
Keyword(s):  
Influence Factor ◽  
Three Dimensional ◽  
Doppler Frequency ◽  
Pulse Generation ◽  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Signal Tracking ◽  
Satellite Positioning ◽  
Working Principle ◽  
Satellite Signal

In order to overcome the problems of the traditional algorithm, such as the time-consuming execution of acquisition instructions, low signal tracking accuracy, and low signal capture accuracy, a global satellite positioning receiver acquisition and tracking algorithm based on UWB technology is designed in this study. On the basis of expounding the pulse generation method and working principle in UWB technology, this paper analyzes in detail the characteristics of UWB technology, such as antimultipath, low power consumption, and strong penetration. Then, on the basis of window function filtering, in the process of three-dimensional search of global satellite positioning signal, firstly, the satellite signal entering the GPS software receiver is processed by RF front-end mixing and AD sampling, and then, the signal tracking and navigation message solving are completed according to the relationship between the influence factor and Doppler frequency offset. The experimental results show that the execution time of the acquisition instruction of the proposed algorithm varies between 1129 ms and 1617 ms; the signal tracking accuracy ranges between 0.931 and 0.951, and the signal capture accuracy ranges between 93.3% and 95.6%, which proves that the proposed algorithm has achieved the design expectation.

scholarly journals Two-Step Galileo E1 CBOC Tracking Algorithm: When Reliability and Robustness Are Keys!

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Aleksandar Jovanovic ◽  
Cécile Mongrédien ◽  
Youssef Tawk ◽  
Cyril Botteron ◽  
Pierre-André Farine
Keyword(s):  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Multipath Mitigation ◽  
Binary Offset Carrier ◽  
Signal Tracking ◽  
Gps Navigation ◽  
Tracking Process ◽  
Galileo Satellite ◽  
Navigation Signals ◽  
Reliability And Robustness

The majority of 3G mobile phones have an integrated GPS chip enabling them to calculate a navigation solution. But to deliver continuous and accurate location information, the satellite tracking process has to be stable and reliable. This is still challenging, for example, in heavy multipath and non-line of sight (NLOS) environments. New families of Galileo and GPS navigation signals, such as Alternate Binary Offset Carrier (AltBOC), Composite Binary Offset Carrier (CBOC), and Time-Multiplex Binary Offset Carrier (TMBOC), will bring potential improvements in the pseudorange calculation, including more signal power, better multipath mitigation capabilities, and overall more robust navigation. However, GNSS signal tracking strategies have to be more advanced in order to profit from the enhanced properties of the new signals.In this paper, a tracking algorithm designed for Galileo E1 CBOC signal that consists of two steps, coarse and fine, with different tracking parameters in each step, is presented and analyzed with respect to tracking accuracy, sensitivity and robustness. The aim of this paper is therefore to provide a full theoretical analysis of the proposed two-step tracking algorithm for Galileo E1 CBOC signals, as well as to confirm the results through simulations as well as using real Galileo satellite data.

Tracking algorithm of video echo signal based on big data processing

2021 ◽  
pp. 1-9
Author(s):  
Ying Chang ◽  
Qinghua Zhu
Keyword(s):  
Big Data ◽  
Feature Fusion ◽  
Rapid Development ◽  
Data File ◽  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Echo Signal ◽  
Signal Tracking ◽  
Operation Speed ◽  
Target Data

With the rapid development of many storage devices and other science and technology, continuous discussion on the role of video target tracking technology in the practical application of photoelectric weapons, guidance systems and security tracking systems has become the current research direction of computer vision and artificial intelligence. The purpose of this study is to explore the differences and characteristics of different algorithms, and provide theoretical and methodological support for the realization of video echo signal tracking in complex environment. For echo signal tracking algorithm only uses a single feature to track, it is particularly easy to cause tracking failure. Therefore, this study uses a method of multi feature fusion to establish the observation model. From the four aspects of gray, color, shape and texture, these four visual characteristics are very representative. In order to study the tracking accuracy, stability and real-time performance of the algorithm, pedestrian, vehicle and face are used as tracking targets to verify the tracking performance of the algorithm in different environments. Using the technical analysis of big data to find the target data file can improve the search speed of the target data and the operation speed of the tracking algorithm. The experimental results show that, in terms of accuracy, the simplest gray feature is only 0.42, and CN feature is improved by about 14% compared with the gray feature. It takes less time to find the target data file by index file method than by traversing the file name method.

Optimal signal tracking algorithm for GNSS signal using moving set-point LQG system

2013 ◽  
Vol 11 (6) ◽  
pp. 1214-1222 ◽  
Author(s):  
Sanghoon Jeon ◽  
Chongwon Kim ◽  
Ghangho Kim ◽  
Ojong Kim ◽  
Changdon Kee
Keyword(s):  
Tracking Algorithm ◽  
Signal Tracking ◽  
Set Point ◽  
Optimal Signal
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