高斯束射线追踪

Using the approximate high-frequency asymptotic methods to solve the scalar wave equation, we can get the eikonal equation and transport equation. Solving the eikonal equation by the method of characteristics provides a mathematical derivation of ray tracing equations. So, the ray tracing system is folly based on the approximate high-frequency asymptotic methods. If the eikonal is complex, more strictly, the eikonal is real value at the rays and complex outside rays, we can derive the Gaussian beam. This article mainly concentrates on the theory of Gaussian beam. To classical ray tracing theory, the Gaussina beam method (GBM) has many advantages. First, rays are no longer required to stop at the exact position of the receivers; thus time-consuming two-point ray tracing can be avoided. Second, the GBM yields stable results in regions of the wavefield where the standard ray theory fails (e.g., caustics, shadows zones and critical distance). Third, unlike seismograms computed by conventional ray tracing techniques, the GBM synthetic data are less influenced by minor details in the model representation. Here, I realize kinematical and dynamical system, and based on this, realize the GBM. Also, I give some mathematical examples. From these examples, we can find the importance and feasibility of the ray tracing system. Besides, I've studied about the reflection coefficient of inhomogeneous S-electromagnetic wave at the interface of conductive media. Basing on the difference of directions of phase shift constant and attenuation constant when the electromagnetic wave propagates in conductive medium, and using the boundary conditions of electromagnetic wave at the interface of conductive media, we derive the reflection coefficient of inhomogeneous S-electromagnetic wave, and draw the curves of it. The curves show that the quasi total reflection will occur when the electromagnetic wave incident from the medium with greater conductivity to the medium with smaller conductivity. There are two peak, values at the points of the critical angles of phase shift constant and attenuation constant, and the reflection coefficient is smaller than 1. This conclusion is different from that of total reflection light obviously.

高斯束偏移的方法及应用

Gaussian beam is the asymptotic solution of wave equation concentred at the central ray. The Gaussian beam ray tracing method has many advantages over ray tracing method. Because of the prevalence of multipath and caustics in complex media, Kirchhoff migration usually can not get satisfactory images, but Gaussian beam migration can get better results.The Runge-Kutta method is used to carry out the raytracing, and the wavefront construction method is used to calculate the multipath wavefield. In this thesis, a new method to determine the starting point and initial direction of a new ray is proposed take advantage of the radius of curvature calculated by dynamic ray tracing method.The propagation characters of Gaussian beam in complex media are investigated. When Gaussian beam is used to calculate the Green function, the wave field near the source was decomposed in Gaussian beam in different direction, then the wave field at a point is the superposition of individual Gaussian beams.Migration aperture is the key factor for Kirchhoff migration. In this thesis, the criterion for the choice of optimum aperture is discussed taking advantage of stationary phase analysis. Two equivalent methods are proposed, but the second is more preferable.Gaussian beam migration based on dip scanning and its procedure are developed. Take advantage of the travel time, amplitude, and takeoff angle calculated by Gaussian beam method, the migration is accomplished.Using the proposed migration method, I carry out the numerical calculation of simple theoretical model, Marmousi model and field data, and compare the results with that of Kirchhoff migration. The comparison shows that the new Gaussian beam migration method can get a better result over Kirchhoff migration, with fewer migration noise and clearer image at complex structures.

序列视觉信息整合的特性与机制

One of the great puzzles in the psychology of visual perception is that the visual world appears to be a coherent whole despite our viewing it through temporally discontinuous series of eye fixations. The investigators attempted to explain this puzzle from the perspective of sequential visual information integration. In recent years, investigators hypothesized that information maintained in the visual short-term memory (VSTM) could become visual mental images gradually during time delay in visual buffer and integrated with information perceived currently. Some elementary studies had been carried out to investigate the integration between VSTM and visual percepts, but further research is required to account for several questions on the spatial-temporal characteristics, information representation and mechanism of integrating sequential visual information. Based on the theory of similarity between visual mental image and visual perception, this research (including three studies) employed the temporal integration paradigm and empty cell localization task to further explore the spatial-temporal characteristics, information representation and mechanism of integrating sequential visual information (sequential arrays). The purpose of study 1 was to further explore the temporal characteristics of sequential visual information integration by examining the effects of encoding time of sequential stimuli on the integration of sequential visual information. The purpose of study 2 was to further explore the spatial characteristics of sequential visual information integration by investigating the effects of spatial characteristics change on the integration of sequential visual information. The purpose of study 3 was to explore the information representation of information maintained in the VSTM and integration mechanism in the process of integrating sequential visual information by employing the behavioral experiments and eye tracking technology. The results indicated that: (1) Sequential arrays could be integrated without strategic instruction. Increasing the duration of the first array could cause improvement in performance and increasing the duration of the second array could not improve the performance. Temporal correlation model was not fit to explain the sequential array integration under long-ISI conditions. (2) Stimuli complexity influenced not only the overall performance of sequential arrays but also the values of ISI at asymptotic level of performance. Sequential arrays still could be integrated when the spatial characteristics of sequential arrays changed. During ISI, constructing and manipulating of visual mental image of array 1 were two separate processing phases. (3) During integrating sequential arrays, people represented the pattern constituted by the objects' image maintained in the VSTM and the topological characteristics of the objects' image had some impact on fixation location. The image-perception integration hypothesis was supported when the number of dots in array 1 was less than empty cells, and the convert-and-compare hypothesis was supported when the number of the dot in array 1 was equal to or more than empty cells. These findings not only contribute to make people understand the process of sequential visual information integration better, but also have significant practical application in the design of visual interface.