16 results about "Sound speed profile" patented technology

This invention discloses a sound velocity profile assimilation and inversion method and system based on dual physical data driving. The method includes: performing adaptive observation and sparse characterization of the sound propagation path to obtain the sparse characterization results; performing long-term noise cross-correlation calculation and passive time delay self-calibration to obtain the virtual sound source arrival time series after absolute time delay reference correction; performing constraint verification through a physical-data dual-driven, dual-stream coupled generative inversion network; acquiring a broadband electromagnetic response time series and performing cross-medium electromagnetic-acoustic joint inversion constraints to obtain a strongly constrained calibrated full-depth sound velocity profile; and performing ensemble Kalman filtering assimilation and uncertainty propagation based on POD order reduction. This invention can quantify the uncertainty of the inversion results. As a sound velocity profile assimilation and inversion method and system based on dual physical data driving, this invention can be widely applied in the field of underwater acoustic engineering technology.

This invention relates to the field of underwater acoustic positioning and topographic detection in marine environments, providing a rapid calculation method and system for the incident angle and propagation time of a direct sound ray between two points. The method includes: dividing seawater into layers based on a sound velocity profile; adaptively dividing the incident angle interval according to a preset comprehensive error threshold; calculating the horizontal displacement and propagation time of the sound ray corresponding to different incident angles; and constructing an interpolation coefficient table through third-order polynomial fitting; combining the piecewise displacement of the water depth intervals where the sound ray originates and terminates, obtaining the third-order polynomial fitting coefficients of the horizontal displacement with respect to the incident angle from the polynomial interpolation coefficient table, constructing a cubic equation with respect to the incident angle, solving it using the Cardano method, and iteratively obtaining the incident angle correction value according to a preset angle error threshold; calculating the propagation time; and finally outputting the incident angle and propagation time of the sound ray. This method replaces layer-by-layer calculation with interpolation modeling, achieving high accuracy, rapid convergence, and coefficient table reuse.

The application discloses a kind of temperature sound velocity parameter measurement methods in ice based on rod longitudinal vibration mode inversion, belong to ice layer acoustic measurement technical field, including the following steps: S1, layout thin stick, and vibration signal is collected;S2, vibration signal is analyzed, and the resonance frequency set of thin stick longitudinal vibration is obtained;S3, construct non-uniform longitudinal vibration model, and according to the resonance frequency set of thin stick longitudinal vibration is inverted, and the thin stick Young's modulus distribution is obtained;S4, thin stick Young's modulus distribution is mapped as thin stick along the temperature distribution of axial direction, and thin stick along the temperature distribution of axial direction is regarded as the equivalent representation of ice layer along corresponding depth direction temperature distribution;S5, obtain sound velocity profile.The application excites and measures the longitudinal vibration response of thin stick in ice layer, utilizes the sensitive characteristics of thin stick longitudinal vibration mode to material parameter change under non-uniform thermal environment, realizes the inversion estimation of ice layer internal temperature distribution and sound velocity profile.

The application relates to the technical field of wind tunnel flexible nozzle profile control devices, in particular to a continuous transonic wind tunnel liquid control flexible nozzle sound speed profile maintaining method, which comprises the following steps: calculating the total load of each support node of the flexible nozzle sound speed profile, assembling a node support mechanism to a flexible plate of the flexible nozzle, the node support mechanism comprising a mechanical locker, each node returning to a mechanical zero position and locking the mechanical locker; giving a sound speed nozzle shaping instruction of a hydraulic servo control system, unlocking the mechanical locker, and making the flexible nozzle profile run to the sound speed nozzle profile from the mechanical zero position through coordinated control of the hydraulic servo system; under the condition that the sound speed nozzle profile dynamic adjustment meets the control precision requirement, locking the mechanical locker, and the hydraulic servo system exiting the dynamic adjustment state, and the mechanical locker providing locking force to maintain the sound speed nozzle profile. The purpose of making the flexible nozzle sound speed profile more stable is achieved.

The present application relates to the technical field of flow velocity prediction model construction, and particularly relates to a method for constructing a flow velocity prediction model based on a thermocline adaptive loss. The method comprises the following steps: in the process of shipborne sailing, low-frequency full-water-depth flow velocity background field data and medium-high-frequency target water layer high-resolution flow velocity data are obtained by using a multi-frequency acoustic Doppler current profiler, sound velocity profile data and unified space-time reference data are synchronously obtained, and a multi-source original observation data set is formed; sound velocity gradient data is calculated based on the sound velocity profile data, a thermocline interval is identified, and thermocline structure identification information is generated; under the constraint of the thermocline structure identification information, adaptive layered three-dimensional sound ray tracking calculation is performed on each wave beam measurement unit of the preset multi-frequency ADCP; by means of adaptive layered sound ray tracking and high-frequency detail reservation, the present application overcomes the measurement distortion caused by the dramatic change of sound velocity in the thermocline in the traditional method, and obtains a high-precision flow velocity field of the key water layer.

This invention discloses a siltation early warning method based on the fusion of towed sonar and multi-source hydrological parameters, belonging to the field of underwater topographic monitoring and engineering safety early warning technology. The method first plans the survey lines for the target area and simultaneously collects multibeam sonar bathymetry data, CTD multi-parameter data, platform attitude data, tow cable status data, positioning and navigation data, and time synchronization information during towed platform operation. Then, it performs time alignment, outlier removal, missing value compensation, and noise suppression on the multi-source data. A sound velocity profile is constructed based on the CTD multi-parameter data, and the sound velocity of the multibeam sonar bathymetry data is corrected. Geometric compensation is also performed by combining platform attitude data, tow cable status data, and positioning and navigation data. Finally, the corrected bathymetry data is... The results are mapped to a preset coordinate system to construct an underwater cross-section model, a grid elevation model, or a bed sediment point cloud model for the current time period. Historical baseline models are retrieved for coordinate unification, overlapping area identification, and adaptive registration. Based on this, elevation difference analysis, slope change analysis, regional thickness statistics, and calculations of sediment thickness, changed area, and sediment volume are performed. Furthermore, short-term trend predictions are made by combining historical observations from multiple time periods with environmental driving factors such as flow velocity, tide level, temperature, salinity, turbidity, and sediment content. Finally, a warning level is generated based on a risk threshold, and warning information is output. This invention improves the comparability of multi-time period towed sonar measurement results and the accuracy of sediment identification, enabling continuous monitoring, quantitative analysis, and proactive warning of bed sedimentation status in target areas. It is applicable to port channels, inland waterways, estuaries, reservoir areas, and near-shore engineering areas.

This invention belongs to the technical field of seawater sound velocity profile inversion, and particularly relates to a method and apparatus for seawater sound velocity profile inversion based on the HMC algorithm. The method includes the following steps: interpolating and preprocessing historical sound velocity profile data and decomposing it using empirical orthogonal functions to obtain empirical orthogonal function expressions; calculating the time required for sound velocity propagation at different depths using the empirical orthogonal function expressions; using time as observation data, modeling the inversion algorithm based on the HMC sampling algorithm principle to obtain a result dataset; calculating the mean and standard deviation of the result dataset to obtain empirical orthogonal function values; and using the HMC algorithm to invert the empirical orthogonal function values ​​to reconstruct the seawater sound velocity profile, thus completing the inversion of the seawater sound velocity profile. This invention can accurately calculate the relationship between parameters using the constructed target distribution function and efficiently complete the inversion of seawater sound velocity profiles using the HMC sampling algorithm, providing a new method for seawater sound velocity profile inversion.

This application relates to the technical field of wind tunnel flexible nozzle profile control devices, specifically, to a method for maintaining the sonic profile of a continuous transonic wind tunnel hydraulically controlled flexible nozzle. The method includes the following steps: calculating the total load on each support node of the flexible nozzle's sonic profile; assembling the node support mechanism onto the flexible plate of the flexible nozzle; the node support mechanism includes a mechanical locking device; returning each node to its mechanical zero position; and locking the mechanical locking device; giving the hydraulic servo control system a sonic nozzle forming command; unlocking the mechanical locking device; and allowing the flexible nozzle profile to move from its mechanical zero position to the sonic nozzle profile through coordinated control by the hydraulic servo system; when the dynamic adjustment of the sonic nozzle profile meets the control accuracy requirements, locking the mechanical locking device; the hydraulic servo system exits the dynamic adjustment state; and the mechanical locking device provides the locking force to maintain the sonic nozzle profile. This achieves the goal of maintaining a more stable sonic profile of the flexible nozzle.

The present application relates to a kind of based on the combination navigation precision promotion method of fusion hydrological information, belong to inertial navigation technical field, comprising the following steps: S1, based on the hydrological information of target navigation sea area, the sound speed profile of target navigation sea area and its each water layer beam angle are calculated;S2, based on the sound speed profile of the target navigation sea area and each water layer beam angle, obtain corrected doppler measurement speed;S3, based on the equivalent refraction after beam incidence angle, the compensated doppler measurement speed after the corrected doppler measurement speed is compensated;S4, the compensated doppler measurement speed and inertial navigation speed are fused, and the corrected ship or underwater vehicle navigation solution result is obtained.The present application fuses hydrological environment data and inertial navigation data, and the position accuracy and reliability of ship or underwater vehicle in long time autonomous navigation are greatly improved.

This invention discloses a passive sound source localization method using deep-sea, vertically distributed hydrophones, belonging to the fields of marine engineering, underwater acoustics engineering, array signal processing, and sonar technology. The method groups all hydrophones in pairs. Within each group, the received signal spectrum is resampled based on sound velocity profile information and an assumed sound source distance. A cost function is constructed by combining all hydrophones. The peak position of the cost function represents the estimated sound source distance. Based on the sound source distance estimation, a modified Fourier transform is performed on the received spectrum of the hydrophones. The peak position of the transform output represents the estimated sound source depth. This method is well-suited for situations with a small number of hydrophones. Furthermore, this method offers faster computation speed.

The application discloses a method for obtaining ocean sound velocity profile based on self-organizing competitive neural network, and relates to the field of ocean sound velocity profile. First, a sample profile of historical sound velocity profile is expressed as an average value plus a form of orthogonal empirical function vector multiplied by corresponding profile coefficients An; then, historical sea surface parameters Xn are processed; An in S1 and the historical sea surface parameters Xn in S2 are combined to form a sample training vector; a self-organizing competitive neural network algorithm is used to train the sample set, and an artificial neuron topological structure is formed; then, real-time sea surface parameters are obtained, and the real-time sea surface parameters are input into the neuron topological structure to obtain An corresponding to the real-time sea surface parameters; finally, the sample profile is expressed as the form of An by combining the historical average sound velocity profile, the EOF vector and the real-time EOF coefficient, and a real-time ocean sound velocity profile is obtained. The application can improve the precision of the obtained sound velocity profile by exploring the relationship between the sound velocity profile and the sea surface remote sensing parameters in the sample data through the artificial neural network.

This application relates to a method and apparatus for reconstructing sound velocity profiles. The method includes: acquiring geographic location information, topographic information, and time information of a currently collected target sea area; inputting the geographic location information, topographic information, and time information as input data into a pre-constructed sound velocity profile prediction model, whereby the sound velocity profile prediction model predicts the sound velocity profile based on the input data to obtain a corresponding predicted sound velocity profile; wherein the sound velocity profile prediction model is constructed based on a nonlinear regression model and an autoregressive moving average model. The method of this application fully considers time-varying factors when predicting sound velocity profiles, thereby making the factors considered when predicting the sound velocity profile of a target sea area more comprehensive, which effectively improves the accuracy of the sound velocity profile prediction results.

The application discloses a kind of underwater acoustic navigation positioning method and system without equivalent sound velocity estimation, method includes: obtaining the sound velocity profile data of positioning operation sea area;And layout receiving array, realize receiving end and the high-precision clock synchronization of all transmitting beacon;Receiving end receives the sending signal of individual transmitting beacon, decoding obtains the position, transmission time and transmission depth of each transmitting beacon, and records the absolute time and receiving depth of signal arrival, and then calculates the propagation time of each signal;Wherein;Sound velocity profile data, and transmitting beacon position, receiving depth and propagation time are used as input, abandon traditional approximate model of equivalent sound velocity, directly based on the physical model of sound ray propagation Calculation of the estimated propagation time corresponding to the virtual target position, and the target position is solved by optimization algorithm iteration to make the estimated propagation time match the actual propagation time;Output target estimated position that meets the iteration stop condition, realize underwater acoustic navigation positioning.

The application provides a buoy cooperative underwater positioning system based on multipath suppression and sound velocity profile correction, and has the characteristics that the system comprises an intelligent buoy network module, a sound velocity measurement module, a signal suppression module and a cooperative positioning module; the intelligent buoy network module is used for constructing a positioning reference network through a plurality of buoys distributed in space in a target water area; the sound velocity measurement module is used for obtaining sound velocity distribution information of an underwater environment; the signal suppression module is used for identifying and suppressing multipath propagation interference in an underwater acoustic channel; and the positioning solution module is used for obtaining an accurate three-dimensional space position of an underwater target; through the cooperative positioning mechanism of multipath inversion suppression and trajectory prediction constraint, the underwater target positioning system achieves the technical effects of high positioning accuracy, strong stability and good robustness in a complex underwater acoustic environment.