Synthetic experiments are employed to investigate the possibility of using focused imaging to reconstruct the subsurface structure. The technique of focusing two arrays of receivers on a subsurface point and cross correlating the outputs is known as the split array cross correlation (SACC) processing. Each point in a subsurface grid is assumed to be the source of scattered Huygens wavelets. The SACC processing gives the relative strengths of the scatterers. A correlation image is constructed from diffracted and reflected signals using the SACC processing. It shows the locations and the strengths of the Huygens sourcelets. Post correlation stack results show the diffraction pattern is enhanced relative to that of the reflection. The SACC processing works for known impulsive sources and continuously radiating random sources. Numerical model experiments were made for an assemblage of wedges, which gives rise to reflections from the facets and diffractions from the apexes and the ‘‘V’’ bottoms. The synthetic seismograms are computed based on the impulse solution for reflection and diffraction from a rigid wedge, adapted from the Biot–Tolstoy impulse theory of diffraction. The controlled source correlation image shows the diffractors and the portions of plain surfaces where reflections occur. The correlation image region is bounded by the ellipse of constant travel time from source to scatterer to receiver. The source and the receiver are at the foci of the ellipse. The correlation image of continuously radiating sources shows high intensities at the diffractors and the mirror images of the sources in the reflecting planes.
The frequency signal displays are not efficient for analyzing nonstationary signals because of their inability to represent frequency changes over time. In fact, because most of the signals are real, nonstationary, and time varying, analyzing the signals in the time–frequency domain to estimate the instantaneous frequency of a signal is inevitable. The methods of estimating the instantaneous frequency of the multicomponent signals are divided into three groups, which include the methods using signal phase derivatives that are sensitive to noise, methods that calculate the number of zero points of the signal and consider the signal frequency equal to half the frequency of the zero points and are suitable for signals that can be imagined as stationary, and methods based on time–frequency distributions and distributions such as Wigner for instantaneous frequency calculations and more for instantaneous frequency calculations on nonstationary noise signals that exhibit varied time–frequency distributions. In this article, a new hybrid algorithm is used to evaluate different distribution criteria and comparing their performance in investigating one or more features of time–frequency distributions, such as resolution and energy concentration.
Detection of a noisy signal is a complex process. Many radar systems are working in an environment where the signal processing parts cannot overcome the effects of interference sources due to their high power. These sources of conflict may completely erode the signal or may make a mistake in deciding. It may make the return of the echoes of the goals difficult. To solve this problem, the detector processor can use a new algorithm to estimate noise power and then can set the threshold in different positions of the cell under test. The proposed algorithm, by differentiating between homogeneous and interference environments in a multitarget structure, selects a set of reference cells that surround the cell under test to estimate the unknown noise/clutter and determine the effective threshold. Then, to evaluate the performance of cell averaging of constant false alarm rate (CA-CFAR), censored mean level detector CFAR (CMLD-CFAR), and excision CFAR (EX-CFAR) detectors, we compared threshold, false alarm, and detection probability in terms of different correlation coefficients. The values were obtained using simulation by MATLAB software. The simulation results show that the excision parameter, by adding to the window of the reference cells that surround the cell under test, reduces the effects of background noise on the received signal. We conclude from the proposed method that the hybrid detector not only has higher quality detection interactions in heterogeneous environments but also has relatively less computational complexity than CA-CFAR, CMLD-CFAR, and EX-CFAR detectors.
In this paper, we propose a method for applying the time and frequency domain's representation to multicomponent signals. Our discussion is based on the method of ridge detection extraction taking into account the time and frequency domain by following the demodulation method, and the numerical results obtained by applying this method are evident compared to other methods that do not use demodulation. The simulation carried out on the examine signals indicates that the signal estimation can be accessed by the initial estimation of the information carrier signals. In both noisy and noise-free environments, the frequency-time-based observation method is more accurate than the other methods.
Telecommunication systems, especially digital ones, are mostly known to be immune to noise given their extensive range of applications. This study aimed to investigate the methods and tools used for the analysis of multicomponent signals input to high-frequency digital subsystems, including the analysis of changes in its electrical behavior. This research mainly focuses on analyzing a high-frequency telecommunication subsystem, recording the results, investigating the system behavior against signals with different amplitudes and phases, detecting the received signals, and measuring the phase differences. The study extended the mono-component signals to multi-component signals and accurately extracted the statistical signal specifications using analytic signals in the time-frequency domain. To this end, a method was proposed based on the switch matrix to relate the different components and parameters, and also a mathematical model based on the state-space equations was employed to evaluate the nonlinear system modes. Given that the decoupling of measurement parameters is a problem to be tackled from multiple aspects, the costs and test durations were also taken into calculations in addition to considering all the detection methods for interference signals, reliability and time under test.
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