426 results about "Full waveform" patented technology

A physiological sensor device for attachment to a mammalian subject comprising an output transmitter, at least two physiological sensors each for sensing one of the subject's physiological parameters, and a controller operably in communication with the physiological sensors which controller communicates a signal comprising data representative of both the sensed physiological parameters to the output transmitter which operably transmits the signal to a remote location, wherein the controller comprises a multiplexer which operably switches the data from both the physiological sensors into a serial output signal. In a preferred embodiment, respiration is detected by a bend sensor including an elongate member and an electrical component mounted thereon which electrical component has an electrical property which varies in dependence on the extent of bending of the elongate member. Other parameters such as temperature and full waveform ECG may also be measured.

There is provided herein a system and method of seismic data collection for land and marine data that utilizes narrowband to monochromatic low-frequency non-impulsive sources designed to optimize the ability of migration/inversion algorithms to image the subsurface of the Earth, in particular, full-waveform inversion.

A method of determining seismic data velocity models comprising dip-guided full waveform inversion that obtains a better velocity model with less computational requirements. DG-FWI quickly converges to provide a better image, obtains better amplitudes, and relies less on lower frequencies. Improved image quality allows detailed seismic analyses, accurate identification of lithological features, and imaging near artifacts and other anomalies.

A method for detecting a vehicle comprising: providing a multi-channel scannerless full-waveform lidar system operating in pulsed Time-Of-Flight operation oriented towards a surface of the roadway to cover the detection zone; providing at least one initialization parameter; emitting pulses at an emission frequency; receiving reflections of the pulses from the detection zone; and acquiring and digitalizing a series of individual complete traces at each channel of system; identifying at least one detection in at least one of the traces; obtaining a height and an intensity for the detection; determining a nature of the detection to be one of an environmental particle detection, a candidate object detection and a roadway surface detection; if the nature of the detection is the candidate object detection, detecting a presence of a vehicle in the detection zone.

An improved method of estimating an earth model utilizes an acoustic Full Waveform Inversion (FWI) of seismic data in a pseudo-time coordinate system, in which the earth model m({tilde over (m)}) is parameterized with two lateral coordinates (x,y) and a vertical coordinate ({tilde over (z)}) which expresses vertical travel time of acoustic signals used to generate the seismic data.

Method for simultaneous full-wavefield inversion of gathers of source (or receiver) encoded geophysical data to determine a physical properties model for a subsurface region, especially suitable for surveys where fixed receiver geometry conditions were not satisfied in the data acquisition. First, a shallow time window of the data (202) where the fixed receiver condition is satisfied is inverted by simultaneous encoded (203) source inversion (205). Then, the deeper time window of the data (208) is inverted by sparse sequential source inversion (209), using the physical properties model from the shallow time window (206) as a starting model (207). Alternatively, the shallow time window model is used to simulate missing far offset data (211) producing a data set satisfying the stationary receiver assumption, after which this data set is source encoded (212) and inverted by simultaneous source inversion (214).

The invention discloses a hybrid-domain full wave form inversion method of central processing unit (CPU)/graphics processing unit (GPU) synergetic parallel computing. Compared with a traditional method, the method can be adopted to conduct the CPU/GPU synergetic parallel computing so as to obviously improve computing efficiency. The method enables a forward part of full wave form inversion to be placed to a time domain, namely forward is conducted in the time domain, the forward is converted to be conducted as the inversion in a frequency domain by the discrete fourier transform (DFT) being utilized, namely the DFT is adopted to pick wave field components corresponding to inversion frequency, and the inversion is conducted in the frequency domain from low frequency to high frequency. The method effectively resolves the problem of astringency of a standard time domain method, and avoids the problem that internal memory of wave form inversion of a standard three-dimensional frequency domain and a Laplace domain cannot be satisfied. The method is few in step, reduces computing expenses, and due to the fact the method can be adopted to conduct the CPU/GPU synergetic parallel computing, largely improves speed-up ratio of the computing method.

A technique for computing RMS values for sampled waveforms. More specifically, a technique for computing RMS values for periodic waveforms, using data taken from a full waveform, a half waveform or some other portion of a waveform is described. Each RMS calculation is based on a different algorithm and provides accurate, real time data.

The invention provides a seismic anisotropy parameter full waveform inversion method and device, and belongs to the field of seismic anisotropy parameter prediction in oil geophysical exploration. The method comprises the steps that (1) seismic data which are going to carry out anisotropy parameter inversion are acquired, namely observation wave field data; (2) denoising processing is carried out on the seismic data acquired in the step (1) to acquire denoised data; (3) by using the denoised data acquired in the step (2), and according to shot point and receiver point coordinates, a common midpoint gather is extracted to acquire seismic CMP gather information, and then the seismic CMP gather information is used to calculate the interval velocity of a horizontal stratum; (4) by using the interval velocity, which is acquired in the step (3), of the horizontal stratum, an initial model used for inversion is constructed in an interpolation mode; and (5) small perturbation is carried out on each parameter of the initial model to generate a model after parameter perturbation.

The invention relates to a frequency domain full-waveform inversion seismic velocity modeling method. The method comprises the following steps of: 1) acquiring an original seismic shot gather record, focus wavelet information and an initial model used by inversion; 2) analyzing information acquired in the step 1), and determining basic inversion parameters and a full-waveform inversion frame from low frequency to high frequency based on a forward modeling algorithm and an optimization algorithm; 3) calculating to acquire the most appropriate forward and inversion model network for different frequencies; 4) compressing data dimensions which participate in inversion by a principal component analysis method during low-frequency inversion; 5) judging whether projection matrix dimensions corresponding to different frequencies meet the threshold value conversion standard, if the conversion standard is met, performing a next step, and if the conversion standard is not met, returning to the step 4); 6) introducing a focus encoding method, and pressing crosstalk noise by a random phase encoding method; 7) judging whether an iteration stopping condition is met, if the iteration stopping condition is met, performing a next step, and if the iteration stopping condition is not met, returning to the step 6); and 8) if the inversion of all the frequencies is not finished, returning to the step 3) until the inversion of all the frequencies is finished, acquiring the final velocity model, and outputting the velocity model.

The invention discloses a full-fiber optical path full-waveform laser radar system. The laser radar system comprises a control unit, a laser source, a laser beam splitting unit, a laser emitting unit, a data reading reference position generating unit, a laser detecting unit, a data acquiring unit and a software unit. The control unit controls a pulse laser to emit laser pulses, and the laser pulses are divided into an emitted laser pulse beam, an emitted laser pulse waveform acquisition beam and an emitted laser pulse marking beam through the laser beam splitting unit; after being subjected to target scattering, the emitted laser pulse beam enters the data acquiring unit through the laser detecting unit to serve as the received laser pulse waveform to be acquired, and a human-computer interaction interface is provided by the software unit. The laser radar system breaks through the limitation that a convectional laser radar can only measure a limited amount of distance and intensity data, complete fiberization of a full-waveform laser radar optical path is achieved through fiber components, and the debugging flexibility and the system integration simplification of a full-waveform laser radar are effectively enhanced.

The invention discloses a full-waveform laser radar echo data gaussian decomposition method based on a genetic algorithm. The method is mainly formed by five steps including echo denoising, initial wave crest extracting, initial parameter estimating, waveform fitting and precision judging; when the precision of initial fitting meets the requirements, second fitting is not carried out, when the precision of the initial fitting does not meet the requirements, iteration fitting is carried out, and in each iteration, the fitting precision is improved by a method of increasing a gaussian component until a stopping condition is met; a gaussian function is used for fitting echo data of a full-waveform laser radar; and a gaussian filter method is adopted to filter noise of the echo data of the full-wave form laser radar, the number of initial gaussian components is confirmed by extracting a peak value point, an initial parameter range is estimated, fitting and precision adjusting are carried out on the echo data of the full-waveform laser through the genetic algorithm, an echo gaussian decomposition software system based on the genetic algorithm is manufactured, and echo decomposition operation is simplified.

A lidar three-dimensional imaging system based on a virtual instrument comprises a three-dimensional scene modeling module, a lidar testing system simulation environment modeling module, a full-waveform signal processing module and a three-dimensional reconstruction module. The three-dimensional scene modeling module comprises a three-dimensional model loading element used for setting background colors, visual angle control, illumination, a projection mode, a display model and other basic scene projects. The lidar testing system simulation environment modeling module comprises four modeling sub-modules which are a laser pulse model, an atmospheric transmission model, an object interaction model and a receiving unit model. The laser pulse model is used for simulating a laser source according to the wavelength, pulse width, energy and other characteristics of a laser. The atmospheric transmission model is used for simulating a tested atmospheric environment, so that a noise model is generated for acting on the laser. The object interaction model is used for simulating effects of the laser and a detected object, and the effects comprise mirror reflection, diffuse reflection, surface reflection and speckles. The receiving unit model is used for simulating detector noise and amplifier noise which are generated after sensing.

A system and computer-implemented method for determining properties of a subsurface region of interest from seismic data is disclosed. An embodiment of the method performs full waveform inversion by non-linear model update to compute a velocity model. The method includes obtaining actual seismic data representative of the subsurface region and an initial earth property model for the subsurface region, performing forward modeling using the initial earth property model to create modeled seismic data with similar acquisition specifications as the actual seismic data, calculating a residual between the actual seismic data and the modeled seismic data in a time or transform domain, and inverting the residual to generate a model produced by non-linear model update components. The system includes a data source, user interface, and processor configured to execute computer modules that implement the method.

Method for multi-parameter inversion using elastic inversion. This method decomposes data into offset/angle groups and performs inversion on them in sequential order. This method can significantly speed up convergence of the iterative inversion process, and is therefore most advantageous when used for full waveform inversion (FWI). The present inventive approach draws upon relationships between reflection energy and reflection angle, or equivalently, offset dependence in elastic FWI. The invention uses recognition that the amplitudes of small angle (near offset) reflections are largely determined by acoustic impedance alone (1), independent for the most part of Vp/Vs. Large angle (middle and far offset) reflections are affected by Ip, Vp/Vs (2) and other earth parameters such as density (3) and anisotropy. Therefore, the present inventive method decomposes data into angle or offset groups in performing multi-parameter FWI to reduce crosstalk between the different model parameters being determined in the inversion.

A full wave inversion (FWI) may utilize an Amplitude-Frequency-Differentiation (AFD) or a Phase-Frequency-Differentiation (PFD) operation to form a velocity model of a subterranean formation utilizing recovered low wavenumber data. Received seismic data is processes to isolate two data signals at different frequencies. In an AFD operation, the two data signals are summed and the data of the envelope of the summed function is used for the FWI. In a PFD operation, the phase data of the quotient of the two data signals is used for the FWI. The FWI proceeds iteratively utilizing either the AFD or PFD data or with single frequency data until the cost function of the AFD or PFD is satisfied.

A preserved-amplitude RTM-based FWI method is used to obtain an image of an explored subsurface formation. Model data corresponding to detected data is generated using a velocity model of the formation. Residuals representing differences between the modeled data and the detected data are back-propagated to then update the velocity model a local optimization based on a deconvolution formula employing a backward propagating wavefield and a forward propagating wavefield. Geophysical features of the formation are imaged based on the updated velocity model.

The invention discloses a laser radar echo full-waveform acquisition device with sampling point time location, and belongs to the technical field of earth observation laser radar remote sensing. The full-waveform acquisition device comprises a main control module, a high-speed ADC sampling module, a high-speed FIFO cache module, an interpolation delay line module, a high-speed coarse counter module, and a fine measurement coding module. All the modules except the high-speed ADC sampling module are implemented inside an FPGA. The invention aims to provide a laser radar echo full-waveform acquisition device for acquiring sampling point time location by a simple method. A frequency division clock synchronous with a high-speed ADC sampling clock is used as a rough counting clock, echo sampling point data is stored in a certain time interval under control, and the time interval between a main wave pulse and a coarse counting clock edge is finely measured by use of an interpolation delay chain, thereby obtaining an echo sampling point which has precise time location relative to laser transmitting main wave pulse. The laser radar echo full-waveform acquisition device with sampling point time location has the advantages of simple peripheral circuit, concise means of realization, flexible function interface configuration, and high cost performance.

The present invention relates to a seismic wave full waveform inversion method based on a least square gradient update speed model, comprising the following steps: 1) obtaining a sound wave equation of a seismic wave field in time domain; 2) constructing an initial speed model, setting a speed model update iteration number N and an allowed minimum error value epsilon; 3) constructing observation wave field data and calculating a wave field error vector of the wave field data; 4) constructing an object function; 5) calculating the object function to obtain a standard equation of seismic wave full waveform inversion; 6) introducing a speed model update gradient direction g<k> and an update amount step length alpha; 7) solving the speed model update gradient direction g<k> by using a least square method; 8) performing interpolation calculation for the update amount step length alpha; and 9) updating the speed model, wherein m<k>=m<k-1>+alpha*g<k>; when |alpha*g<k>| < epsilon or the update number of the speed model reaches the speed model update iteration number N, ending the update of the speed model; otherwise, entering into the step 3). The seismic wave full waveform inversion method of the present invention can quickly achieve update of the speed model, and can be widely applied in seismic wave full waveform inversion.

The invention discloses a full-waveform laser radar system based on coaxial two-channel data acquisition, breaks through the limit that a conventional laser radar can only measure a limited number of distance and strength data, and simultaneously solves the dead zone problem of non-coaxial laser radar detection. The full-waveform laser radar system based on coaxial two-channel data acquisition comprises a pulse laser, a laser transmitting and receiving unit, a data acquisition unit, a control unit and a software unit, wherein the control unit controls the pulse laser to transmit laser pulse; the laser pulse is divided into outgoing beam, acquisition card control signal generation beam and transmitted waveform recording beam after passing by the laser transmitting and receiving unit; the outgoing beam is scattered by a target, then collected into the data acquisition unit by the transmitting and receiving unit and collected as a receiving signal; and the software unit is used for providing a man-machine interaction interface. The system can store a complete waveform for transmitting and receiving the laser pulse, so that the detectivity of the full-waveform laser radar is effectively enhanced.

The invention discloses a tree species classification method based on a LiDAR (Light Detection and Ranging) false-vertical waveform model. The method comprises a step 1 of collecting data using an airborne small-light spot full-waveform LiDAR sensor, in order to obtain complete waveform information, wherein the sampling interval is 1ns; a step 2 of preprocessing LiDAR waveform data; a step 3 of establishing a false vertical wave through waveform structural decomposition and comprehensive waveform recombination; a step 4 of carrying out single tree segmentation and information integration; a step 5 of gathering point cloud attributes within in a single tree range and calculating a comprehensive waveform characteristic parameter; and a step 6 of carrying tree species classification with a support vector machine classifier. With the tree species classification method, acquired LiDAR energy signals can be enhanced; on the basis of single tree segmentation, comprehensive waveform characteristic variables are extracted from multiple dimensions, and thus classification accuracy of tree species in the subtropical forest is obtained and improved by a single data source; spatial and temporal variation of main tree species of a forest type can be well embodied; through experimental verification results, the method provided by the invention is improved by 10% in terms of overall precision compared with other LiDAR-employing tree species classification methods; and the Kappa coefficient is improved by 0.1.