Improved Semi-Bit Differential Acquisition Method for Navigation Bit Sign Transition and Code Doppler Compensation in Weak Signal Environment

2020 ◽  
Vol 73 (4) ◽  
pp. 892-911 ◽  
Author(s):  
M. Nezhadshahbodaghi ◽  
M. R. Mosavi ◽  
N. Rahemi
Keyword(s):  
Signal To Noise Ratio ◽  
Integration Time ◽  
Data Sets ◽  
Weak Signal ◽  
Differential Acquisition ◽  
Global Positioning ◽  
Signal Environment ◽  
Correlation Techniques ◽  
Transition Issues ◽  
Acquisition Method

The presence of code Doppler and navigation bit sign transitions means that the acquisition of global positioning system (GPS) signals is difficult in weak signal environments where the output signal-to-noise ratio (SNR) is significantly reduced. Post-correlation techniques are typically utilised to solve these problems. Despite the advantages of these techniques, the post-correlation techniques suffer from problems caused by the code Doppler and the navigation bit sign transitions. We present an improved semi-bit differential acquisition method which can improve the code Doppler and the bit sign transition issues in the post-correlation techniques. In order to overcome the phenomenon of navigation bit sign transitions, the proposed method utilises the properties of the navigation bit. Since each navigation bit takes as long as 20 ms, there would be 10 ms correlations duration integration time between the received signal and the local coarse/acquisition (C/A) code in which the navigation bit sign transitions will not occur. Consequently, this problem can be cancelled by performing 10 ms correlations in even and odd units separately. Compensation of the code Doppler is also accomplished by shifting the code phase of the correlation results. To validate the performance of our suggested method, simulations are performed based on three data sets. The results show that the quantity of required input SNR to detect at least four satellites in the proposed method is − 48·3 dB, compared with − 20 dB and − 9 dB, respectively, in traditional differential and non-coherent methods.

An Assisted GPS Acquisition Method using L2 Civil Signal in Weak Signal Environment

2004 ◽  
Vol 3 (1&2) ◽  
pp. 25-31 ◽  
Author(s):  
Deuk Jae Cho ◽  
Sang Jeong Lee ◽  
Chansik Park
Keyword(s):  
Weak Signal ◽  
Assisted Gps ◽  
Signal Environment ◽  
Acquisition Method

scholarly journals Design of Enhanced Rotation Locked Loop for Roll Angle Estimation of Rotating Vehicle in a Weak GPS Signal Environment

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 80
Author(s):  
Hun Im ◽  
Deok Lim ◽  
Sang Lee
Keyword(s):  
Computer Simulations ◽  
Signal To Noise Ratio ◽  
Signal Strength ◽  
Roll Angle ◽  
Weak Signal ◽  
Signal To Noise ◽  
Angle Estimation ◽  
Signal Environment ◽  
Noise Ratio

In order to estimate the roll angle of a rotating vehicle, an enhanced rotation locked loop (RLL) algorithm is proposed in this paper. The RLL algorithm estimates the roll angle by using the property that the power of the GPS signal measured at the receiver of a rotating vehicle changes periodically. However, in case the received GPS power is decreased, the performance of the conventional RLL algorithm degrades, or it cannot estimate the roll angle anymore, therefore, for operating the RLL algorithm in a weak signal environment, this paper designs a method to increase the signal-to-noise ratio (SNR) by overlapping multiple GPS signals’ correlator outputs and a method to compensate the decreased response of a rotation discriminator at low-signal strength. Through computer simulations, the performance of the proposed algorithm is verified and it is shown that the roll angle can be estimated stably even at a weak signal environment down to 29 dB–Hz of C/N0.

scholarly journals WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES

2021 ◽  
Vol 25 (Special) ◽  
pp. 1-56-1-62
Author(s):  
Sarah S. Mohammed ◽  
◽  
Maher K. Mahmood ◽  
Keyword(s):  
Signal To Noise Ratio ◽  
Probability Of Detection ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Multiple Correlation ◽  
Signal To Noise ◽  
Probability Of False Alarm ◽  
Auto Correlation ◽  
Simulation Results ◽  
Correlation Techniques

This study presents the performance of the auto-correlation methods for detecting weak signals, where the signal level is much less than the noise level. Double and triple auto-correlation techniques are used to improve the detection performance compared with the single autocorrelation. Simulation results obtained by MATLAB programs show that the multiple correlation techniques outperform the single correlation in terms of probability of detection and probability of false alarm versus signal to noise ratio SNR.

scholarly journals An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

2019 ◽  
Vol 73 (8) ◽  
pp. 893-901
Author(s):  
Sinead J. Barton ◽  
Bryan M. Hennelly
Keyword(s):  
Cosmic Ray ◽  
Data Sets ◽  
Biological Cells ◽  
Statistical Classification ◽  
Signal To Noise ◽  
Multivariate Statistical ◽  
Data Set ◽  
Artefact Removal ◽  
Single Capture ◽  
Acquisition Method

Cosmic ray artifacts may be present in all photo-electric readout systems. In spectroscopy, they present as random unidirectional sharp spikes that distort spectra and may have an affect on post-processing, possibly affecting the results of multivariate statistical classification. A number of methods have previously been proposed to remove cosmic ray artifacts from spectra but the goal of removing the artifacts while making no other change to the underlying spectrum is challenging. One of the most successful and commonly applied methods for the removal of comic ray artifacts involves the capture of two sequential spectra that are compared in order to identify spikes. The disadvantage of this approach is that at least two recordings are necessary, which may be problematic for dynamically changing spectra, and which can reduce the signal-to-noise (S/N) ratio when compared with a single recording of equivalent duration due to the inclusion of two instances of read noise. In this paper, a cosmic ray artefact removal algorithm is proposed that works in a similar way to the double acquisition method but requires only a single capture, so long as a data set of similar spectra is available. The method employs normalized covariance in order to identify a similar spectrum in the data set, from which a direct comparison reveals the presence of cosmic ray artifacts, which are then replaced with the corresponding values from the matching spectrum. The advantage of the proposed method over the double acquisition method is investigated in the context of the S/N ratio and is applied to various data sets of Raman spectra recorded from biological cells.

An Improved Acquisition Method for High-Order BOC-Modulated Signals Based on Fractal Geometry

2013 ◽  
Vol 846-847 ◽  
pp. 1185-1188 ◽  
Author(s):  
Hua Bing Wu ◽  
Jun Liang Liu ◽  
Yuan Zhang ◽  
Yong Hui Hu
Keyword(s):  
Fractal Geometry ◽  
Output Signal ◽  
Signal To Noise Ratio ◽  
High Order ◽  
Main Peak ◽  
Signal To Noise ◽  
Binary Offset Carrier ◽  
Simulation Results ◽  
Modulated Signals ◽  
Acquisition Method

This paper proposes an improved acquisition method for high-order binary-offset-carrier (BOC) modulated signals based on fractal geometry. We introduced the principle of our acquisition method, and outlined its framework. We increase the main peak to side peaks ratio in the BOC autocorrelation function (ACF), with a simple fractal geometry transform. The proposed scheme is applicable to both generic high-order sine-and cosine-phased BOC-modulated signals. Simulation results show that the proposed method increases output signal to noise ratio (SNR).

Automated phase attribute-based picking applied to reflection seismics

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. V141-V150 ◽  
Author(s):  
Emanuele Forte ◽  
Matteo Dossi ◽  
Michele Pipan ◽  
Anna Del Ben
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Method ◽  
Data Sets ◽  
Reflection Seismic ◽  
Instantaneous Phase ◽  
Whole Process ◽  
Specific Analysis ◽  
Reflection Seismics ◽  
Selection Of ◽  
Energy Package

We have applied an attribute-based autopicking algorithm to reflection seismics with the aim of reducing the influence of the user’s subjectivity on the picking results and making the interpretation faster with respect to manual and semiautomated techniques. Our picking procedure uses the cosine of the instantaneous phase to automatically detect and mark as a horizon any recorded event characterized by lateral phase continuity. A patching procedure, which exploits horizon parallelism, can be used to connect consecutive horizons marking the same event but separated by noise-related gaps. The picking process marks all coherent events regardless of their reflection strength; therefore, a large number of independent horizons can be constructed. To facilitate interpretation, horizons marking different phases of the same reflection can be automatically grouped together and specific horizons from each reflection can be selected using different possible methods. In the phase method, the algorithm reconstructs the reflected wavelets by averaging the cosine of the instantaneous phase along each horizon. The resulting wavelets are then locally analyzed and confronted through crosscorrelation, allowing the recognition and selection of specific reflection phases. In case the reflected wavelets cannot be recovered due to shape-altering processing or a low signal-to-noise ratio, the energy method uses the reflection strength to group together subparallel horizons within the same energy package and to select those satisfying either energy or arrival time criteria. These methods can be applied automatically to all the picked horizons or to horizons individually selected by the interpreter for specific analysis. We show examples of application to 2D reflection seismic data sets in complex geologic and stratigraphic conditions, critically reviewing the performance of the whole process.

scholarly journals New processing tools for weak and/or spatially overlapped macromolecular diffraction patterns

1999 ◽  
Vol 55 (10) ◽  
pp. 1733-1741 ◽  
Author(s):  
Dominique Bourgeois
Keyword(s):  
Signal To Noise Ratio ◽  
Data Sets ◽  
Signal To Noise ◽  
Weighting Method ◽  
Time Resolved ◽  
Accurate Evaluation ◽  
Profile Fitting ◽  
Integration Program ◽  
Diffraction Patterns ◽  
New Processing

Tools originally developed for the treatment of weak and/or spatially overlapped time-resolved Laue patterns were extended to improve the processing of difficult monochromatic data sets. The integration programPrOWallows deconvolution of spatially overlapped spots which are usually rejected by standard packages. By using dynamically adjusted profile-fitting areas, a carefully built library of reference spots and interpolation of reference profiles, this program also provides a more accurate evaluation of weak spots. In addition, by using Wilson statistics, it allows rejection of non-redundant strong outliers such as zingers, which otherwise may badly corrupt the data. A weighting method for optimizing structure-factor amplitude differences, based on Bayesian statistics and originally applied to low signal-to-noise ratio time-resolved Laue data, is also shown to significantly improve other types of subtle amplitude differences, such as anomalous differences.

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