Performance characteristics of acoustic direction finders of localized broadband signal sources

2021 ◽  
Author(s):  
V.K. Khokhlov ◽  
A.K. Likhoedenko
Keyword(s):  
Signal Processing ◽  
Correlation Function ◽  
Cross Correlation ◽  
Supply Voltage ◽  
Directivity Pattern ◽  
Performance Characteristics ◽  
Signal Source ◽  
Signal To Noise ◽  
Direction Finder ◽  
Broadband Signal

In this paper, we substantiate main performance characteristics of the regression algorithm of a two-channel direction finder of localized sources of broadband signal against the background of interference distributed in space, invariant to radiated power and supply voltage. We analyze mutual statistical characteristics of broadband signals in a two-channel direction finder. Based on the method of canonical decomposition in complex form, we show the cross-correlation function of processes at the outputs of direction finder antennas when operating on a localized signal source against the background of interference distributed in space. For invariance of performance characteristics, we consider the application of sign transformation to signals and analyze the dependence of a cross-correlation function of the input signals after the sign transformation at different signal-to-noise ratios. We show the formation of a directivity pattern in a correlation direction finder with signal-to-noise ratio more than 1. For direction-finding of localized signal source, we substantiated a regression algorithm with discrete-analog signal processing, where sign processing based on standard digital hardware components is used. The invariance of the algorithm to supply voltage is shown by representing Boolean functions as expressions of conjunction, disjunction, and negation. The regression algorithm is substantiated in the time domain. We obtain the expressions for mean and variance of the calculated statistics for direction-finding of localized signal source against the background of interference distributed in space. We show the possibility of formation of a directivity pattern with completely suppressed side lobes. The algorithm functions at signalto-noise ratios up to 1. The algorithms can be used in passive acoustic and hydroacoustic direction finders, as well as direction finders with ultra-wideband signals with computer-based signal processing.

Nondestructive Testing Method in Artificial Intelligence Real Time Systems

2004 ◽  
Vol 97-98 ◽  
pp. 71-76
Author(s):  
Egidijus Kazanavicius ◽  
Antanas Mikuckas ◽  
Irena Mikuckiene
Keyword(s):  
Signal Processing ◽  
Correlation Function ◽  
Nondestructive Testing ◽  
Cross Correlation ◽  
Reduction Method ◽  
Reference Signal ◽  
Floating Point ◽  
Real Time Systems ◽  
Reflected Signal ◽  
Time Systems

Modern sonar and radar measurement systems are widely used in the field of nondestructive testing for a long time. Usually reference signal is emitted towards the object to be investigated and we get a signal, which is the sum of reference signal reflected from different plies. The task of signal processing is to determine time instances corresponding positions of certain ply, which allow analyzing structure of object. Usually the cross correlation function (CCF) of transmitted sequence and received sequence is calculated. If peaks were clearly identified in the cross correlation function (CCF), it would be easy to determine time instances. Due to the noise some coherent peaks, additive to the expected peaks, appear on the CCF, which are confusing in regard to the clear distinction of target. In order to cancel effects of noise as much as possible some measures have to be taken for data manipulation noise cancellation, such as averaging, inverse filtering and so on. These signal-processing methods need a lot of floating point floating point operations and are time consuming. That is why the usage of such ultrasonic systems is limited in real time systems, which are the base for self-organizing systems. Amount of calculations depends on the length of reference signal, the length of reflected signal to be processed and the noise reduction method used in such system. A new system with reduced amount of calculations is considered in this article. In this system only parts of reflected signal corresponding peaks of CCF are processed. These parts are defined in acquisition mode and afterwards system enters measurement mode. New noise reduction method based on wavelet transforms coefficients thresholding is applied in this system. The length of reference signal impacts system noise immunity and amount of calculations. The main problem in ultrasonic non-destructive testing systems is to cancel out effects of the noise. The optimal length of reference signal for wavelet based signalprocessing method is defined. All these measures allowed significantly reduce amount of calculations in the self-organizing systems.

Problems of Signal Processing in Ultrasonic Gas Flow Measurement

2017 ◽  
Vol 870 ◽  
pp. 209-214
Author(s):  
Volker Hans
Keyword(s):  
Signal Processing ◽  
Correlation Function ◽  
Cross Correlation ◽  
Bluff Body ◽  
Modulation Frequency ◽  
Ultrasonic Waves ◽  
Cross Correlation Function ◽  
Ultrasound Wave ◽  
Symmetric Density ◽  
The Cross

Vortex measuring methods with ultrasound are distinguished by small bluff bodies, low pressure losses and high sensitivity. The ultrasound wave is modulated by the vortices behind the bluff body. The modulation frequency represents the flow velocity and can be determined by well-known demodulation procedures.Cross correlation methods use the natural turbulences in a fluid. Because of the skewed density function of the velocity components the maximum of the cross correlation function does not represent the transit time of the turbulences between two ultrasonic barriers. Processing of the complex modulated signal is very difficult because the phase of the signal can reach very high values and can not be considered unambiguously. It is advantageous to simplify the signal processing by artificially generated vortices by a small bluff body. It results in a symmetric density distribution and symmetric cross correlation function. Furthermore, it results in a self-monitoring system. Alternatively, two different carrier frequencies can be applied to the two ultrasonic waves. In the cross correlation function the carrier frequencies are eliminated automatically.

Research on Improved Code Phase Acquisition Algorithm for BOC(pn,n) Signal

2013 ◽  
Vol 427-429 ◽  
pp. 1794-1798
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li
Keyword(s):  
Correlation Function ◽  
Cross Correlation ◽  
Search Algorithm ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Low Snr ◽  
Auto Correlation ◽  
Auto Correlation Function ◽  
Parallel Code ◽  
Improved Algorithm

Auto correlation function of BOC signal has the character of milti-values, so acquistion of BOC signal can not simply transplant the algorithm of GPS signal. For this reason, parallel code phase search algorithm and cross correlation characteristics of BOC signal are analyzed. And then, the validity of parallel code phase search algorithm on BOC signal are simulated. After that, point to the insufficiency of parallel code phase search algorithm on the acquisiton of BOC signal at low SNR(signal to noise ratio), an improved acquisition algorithm is presented and used to analyze BOC signal. The results show that the improved algorithm is applicable to BOC(pn, n) signal where p is an integer, which expands the application aera of parallel code phase search algorithm; and that the improved algorithm can improve SNR of acquisition about 15dB compared with that of parallel code phase search algorithm, that is to say, the improved algorithm can enhance acquisiton sensitivity of receivers obviously, which is very important to the design of acquisiton algorithm in receivers.

Wavelet Digital Watermarking Algorithm on the Basis of SVD Decomposition

2013 ◽  
Vol 333-335 ◽  
pp. 1056-1059 ◽  
Author(s):  
Ji Lin Wang
Keyword(s):  
Correlation Function ◽  
Wavelet Transform ◽  
Digital Watermarking ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Intermediate Frequency ◽  
Singular Value ◽  
Signal To Noise ◽  
Value Decomposition ◽  
Svd Decomposition

Based on SVD decomposition, an digital watermarking algorithm with the method of wavelet transform is proposed. By means of singular value decomposition to realize blind extracting, the watermarking image is embedded into intermediate frequency sub bands of wavelet composition. Finally, applying normalized cross-correlation function (NC) and peak signal to noise ratio (PSNC), it has proved that this algorithm has better invisibility and robustness.

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