Unmanned ship gravity and magnetic measurement method and system

Abstract

The present invention discloses an unmanned vessel gravity and magnetic measurement method and system, belonging to the field of geophysical exploration technology. The method comprises acquiring real-time attitude data of the unmanned vessel to generate tilt compensation parameters; adjusting the data acquisition frequency based on the tilt compensation parameters to generate a positioning enhancement signal; triggering the acquisition of operational data based on the positioning enhancement signal to generate raw gravity data and raw magnetic data; extracting magnetic field gradient mutation points in the raw magnetic data to generate wave characteristic parameters; fusing the tilt compensation parameters, wave characteristic parameters, and raw gravity data to generate wave noise compensation values; and correcting the wave noise compensation values ​​to generate target gravity field data. The method utilizes three core technical systems: dynamic tilt closed-loop compensation, magnetic gradient-wave characteristic mapping modeling, and precise time alignment triggering. These systems can effectively overcome the interference effects of wave noise on the gravity field and achieve a significant improvement in the spatiotemporal synchronization of gravity and magnetic measurements.

Description

Technical Field

[0001] The present invention relates to the field of geophysical exploration technology, and in particular to an unmanned vessel gravity and magnetic measurement method and system. Background Art

[0002] Existing shipborne gravity and magnetic measurement technology has systematic flaws in dynamic ocean environments. Conventional workboats are susceptible to attitude deviations caused by wave action, resulting in insufficient effective measurement time for gravity sensors, seriously affecting data collection continuity.

[0003] Existing compensation technology relies on independent attitude solution of inertial navigation, but its real-time performance has matching defects with the wave frequency dynamic characteristics, and it cannot accurately eliminate high-frequency interference.

[0004] More importantly, the asynchronous acquisition mode used by discrete sensors induces data time-scale misalignment, resulting in significant distortion of the spatial characteristics of the geological body in the subsequent three-dimensional inversion process. Summary of the Invention

[0005] To solve the above problems, the present invention provides an unmanned vessel gravity and magnetic measurement method, which adopts three core technical systems: dynamic tilt closed-loop compensation, magnetic gradient-wave characteristic mapping modeling, and time-precision alignment triggering. It can effectively overcome the interference of wave noise on the gravity field and achieve a leap in the spatiotemporal synchronization of gravity and magnetic measurements, providing an innovative solution for fine geological exploration in complex marine environments.

[0006] The above objectives can be achieved through the following solutions:

[0007] An unmanned vessel gravity and magnetic measurement method includes acquiring real-time attitude data of the unmanned vessel and generating tilt compensation parameters; adjusting a data acquisition frequency according to the tilt compensation parameters and generating a positioning enhancement signal; triggering acquisition of operation data based on the positioning enhancement signal to generate gravity raw data and magnetic raw data, wherein the magnetic raw data includes magnetic field gradient mutation points; extracting the magnetic field gradient mutation points in the magnetic raw data and generating wave characteristic parameters; fusing the tilt compensation parameters, the wave characteristic parameters and the gravity raw data to generate a wave noise compensation value; and generating target gravity field data based on the wave noise compensation value.

[0008] Optionally, generating the tilt compensation parameters includes: monitoring the waves acting on the hull to generate the roll angle and the pitch angle; calculating the theoretical horizontal calibration angle of the gravity probe base to generate a hydraulic compensation instruction; and executing the hydraulic compensation instruction to generate the tilt compensation parameters.

[0009] Optionally, generating the positioning enhancement signal includes: calculating the angle change based on the tilt compensation parameter to generate the fluctuation amplitude; when the fluctuation amplitude exceeds the preset tilt threshold, increasing the sampling frequency to a preset high frequency mode to generate the positioning enhancement signal.

[0010] Optionally, the generation of time-aligned gravity raw data and magnetic raw data includes: generating a timing pulse signal based on the positioning enhancement signal; generating an alignment trigger signal based on the transmission delay of the timing pulse signal; and transmitting the timing pulse signal in a branch channel based on the alignment trigger signal to generate time-aligned gravity raw data and magnetic raw data.

[0011] Optionally, generating wave characteristic parameters includes: obtaining the gradient change of adjacent sampling points based on the magnetic raw data; marking the time point when the gradient change exceeds a preset gradient threshold to generate a wave peak sequence; fitting the time distribution of the wave peak sequence to generate wave characteristic parameters.

[0012] Optionally, generating the wave noise compensation value includes: obtaining the acquisition timing of the gravity raw data; based on the wave characteristic parameters, matching the wave peak sequence through the acquisition timing to generate a real-time tilt compensation parameter; based on the real-time tilt compensation parameter, calculating the acceleration error component and the wave periodic residual component to generate the wave noise compensation value.

[0013] Optionally, generating target gravity field data based on the wave noise compensation value includes: constructing a dynamic filter based on the wave characteristic parameters; generating a gravity compensation residual through the dynamic filter based on the wave noise compensation value; and superimposing the gravity compensation residual onto the gravity original data to generate target gravity field data.

[0014] Optionally, the method further includes: fusing the target gravity field data with magnetic field values ​​at corresponding spatial positions in the original magnetic data to generate a standardized fused data set; and generating a three-dimensional physical property distribution map based on the standardized fused data set.

[0015] Optionally, generating a three-dimensional physical property distribution map includes: performing a regional field and local field separation operation based on the standardized fusion data set to generate a local gravity and magnetic anomaly data volume; constructing a gravity and magnetic anomaly matrix based on the local gravity and magnetic anomaly data volume; and generating a three-dimensional physical property distribution map based on the gravity and magnetic anomaly matrix.

[0016] Based on the same inventive concept, the present invention also provides an unmanned ship gravity and magnetic measurement system, which includes: a data acquisition module: used to obtain real-time posture data of the unmanned ship and generate inclination compensation parameters; a high-precision positioning module: used to adjust the data acquisition frequency according to the inclination compensation parameters and generate a positioning enhancement signal; a gravity and magnetic data synchronization module: used to trigger the acquisition of operation data based on the positioning enhancement signal, and generate gravity raw data and magnetic raw data, wherein the magnetic raw data contains magnetic field gradient mutation points; a magnetic field gradient analysis module: used to extract magnetic field gradient mutation points in the magnetic raw data and generate wave characteristic parameters; a wave noise compensation module: used to fuse the inclination compensation parameters, wave characteristic parameters and gravity raw data to generate wave noise compensation values; a gravity field construction module: used to generate target gravity field data based on the wave noise compensation value.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] The present invention reduces the gravity measurement deviation caused by wave disturbances through a two-way feedback mechanism of dynamic tilt compensation and positioning enhancement, and obtains more stable data quality compared with traditional ship-borne measurements; utilizes the sudden change characteristics of magnetic gradients to invert wave dynamic parameters, breaking through the spatiotemporal resolution limitations of existing wave sensing technology and providing higher-precision environmental noise characterization capabilities; the designed multi-source data fusion compensation model realizes full-dimensional analysis of wave noise, effectively improving the signal-to-noise ratio of gravity data; the construction of a time synchronization trigger architecture breaks through the limitations of traditional discrete clocks, ensures the spatiotemporal consistency of gravity and magnetic data, and lays the foundation for subsequent fusion modeling.

[0019] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 4 is a flow chart of the gravity and magnetic measurement method of an unmanned ship according to an embodiment of the present invention.

[0022] Figure 2 2 is a schematic diagram of heave compensation according to an embodiment of the present invention.

[0023] Figure 3 Schematic diagram of three-dimensional physical property distribution of an embodiment of the present invention.

[0024] Figure 4 1 is a schematic diagram of the system structure of the unmanned ship gravity and magnetic measurement method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0026] Reference Figure 1 One embodiment of the present invention proposes an unmanned ship gravity and magnetic measurement method. Through the three core technical systems of dynamic tilt closed-loop compensation, magnetic gradient-wave characteristic mapping modeling and time precise alignment triggering, it can effectively overcome the interference of wave noise on the gravity field and achieve a leap in the spatiotemporal synchronization of gravity and magnetic measurements, providing an innovative solution for fine geological exploration in complex marine environments.

[0027] The method of this embodiment specifically includes:

[0028] Obtain the real-time attitude data of the unmanned vessel and generate tilt compensation parameters;

[0029] Adjust the data acquisition frequency according to the tilt compensation parameters to generate positioning enhancement signals;

[0030] Based on the positioning enhancement signal, the trigger is used to collect operation data to generate gravity raw data and magnetic raw data, where the magnetic raw data contains the magnetic field gradient mutation points;

[0031] Extract the magnetic field gradient mutation points in the original magnetic data and generate wave characteristic parameters;

[0032] fusing the tilt compensation parameter, the wave characteristic parameter and the raw gravity data to generate a wave noise compensation value;

[0033] Correct the wave noise compensation value and generate target gravity field data.

[0034] Specifically, the inertial measurement unit is used to monitor the roll and pitch angles of the hull in real time, and the hydraulic compensation system is driven to dynamically correct the posture of the gravity probe base, thereby suppressing the acceleration error caused by waves. At the same time, the wave spectrum period and amplitude characteristics are inverted based on the gradient mutation point of the magnetic sensor. Combined with the timing delay correction strategy, the dual-channel synchronous acquisition of gravity and magnetism is triggered, and high-precision gravity field data is output through the wave noise compensation model, and finally a three-dimensional physical property distribution map is generated, which effectively solves the industry pain points of insufficient wave interference suppression and data inaccuracy in time and space in traditional ship-borne measurements.

[0035] Optionally, generating the tilt compensation parameter includes:

[0036] Monitor the waves acting on the hull and generate the roll angle and pitch angle; calculate the theoretical horizontal calibration angle of the gravity probe base and generate the hydraulic compensation instruction; execute the hydraulic compensation instruction to generate the tilt compensation parameters.

[0037] Specifically, the inertial measurement sensor is used to monitor the lateral and longitudinal wave forces on the hull in real time, and the original data of the roll angle and pitch angle are collected. The roll angle is obtained from the angle of rotation of the hull around the longitudinal axis, and the pitch angle is obtained from the angle of rotation of the hull around the transverse axis. According to the installation position of the gravity probe, the azimuth relationship between the base coordinate system and the hull coordinate system is constructed. Through the spatial rotation relationship between the base coordinate system and the hull coordinate system, the theoretical horizontal calibration angle of the gravity probe base is obtained based on the vector composite angle of the roll angle and the pitch angle. The hydraulic compensation instruction is calculated by the PID control algorithm. For the theoretical horizontal calibration angle ,have:

[0038] ,

[0039] Where n is the actual normal vector of the base, and k is the unit vector in the vertical direction of the earth's gravity field; the height of the base mounting platform is adjusted by the hydraulic servo mechanism to compensate for the base tilt caused by the change in the hull posture, so that the actual horizontal angle of the base approaches the theoretical horizontal calibration angle, and the inclination compensation parameters are generated based on the real-time compensation amount in the hydraulic displacement. Figure 2 The figure shows a schematic diagram of wave compensation.

[0040] Optionally, generating a positioning enhancement signal includes: calculating the angle change based on the tilt compensation parameter to generate a fluctuation amplitude; when the fluctuation amplitude exceeds a preset tilt threshold, increasing the sampling frequency to a preset high-frequency mode to generate a positioning enhancement signal.

[0041] Specifically, based on the tilt compensation parameters, the continuously collected roll and pitch angle data, for the fluctuation amplitude A, are:

[0042] ,

[0043] in, is the change between the current roll angle and the roll angle in the previous sampling period, is the change between the current pitch angle and the pitch angle in the previous sampling period, and the fluctuation amplitude A is the vector composite amplitude of the angle change in two adjacent sampling periods. When A exceeds the preset tilt angle threshold set based on historical statistical data, the sampling frequency is increased to the preset high-frequency mode, and the correction interval is shortened synchronously to generate a positioning enhancement signal.

[0044] For example, under conditions where the wave period is 6 seconds and the wave height is 1.5 meters, the inertial measurement unit measures a roll angle change of 12 degrees and a pitch angle change of 9 degrees within two consecutive seconds. At this time, the fluctuation amplitude is equal to 15 degrees, which exceeds the preset threshold and triggers the protection mechanism. The system increases the sampling rate to 50 Hz in advance, and the number of sample points in the same time period increases from 30 to 150 times. Compared with the measurement data when the preset threshold is not triggered, the high-frequency mode reduces the data omission rate in the wave peak stage from 17% to 3%. The beneficial effect of this verification example is that by dynamically adjusting the acquisition frequency strategy, the integrity of the measurement data in the stage of severe wave disturbance is improved, the data loss caused by the violent swaying of the hull is avoided, and the capture rate of abnormal points of magnetic gradient changes is ensured to meet the design requirements.

[0045] Optionally, generating time-aligned gravity raw data and magnetic raw data includes: generating a timing pulse signal based on a positioning enhancement signal; compensating for a transmission delay of the timing pulse signal to generate an alignment trigger signal; and based on the alignment trigger signal, transmitting the timing pulse signal in a branched manner to generate time-aligned gravity raw data and magnetic raw data.

[0046] Specifically, by analyzing the positioning enhancement signal, the propagation delay is dynamically compensated to obtain a synchronous clock reference, and a frequency-stable timing pulse signal is generated based on the synchronous clock reference. The response time difference between the gravity sensor and the magnetic sensor from receiving the trigger signal to the actual sampling is measured, and a delay correction value is set for the gravity sensor and the magnetic sensor. After timing adjustment, an alignment trigger signal is generated. For the alignment trigger signal T, there is:

[0047] ,

[0048] in The initial moment of the timing pulse ensures that the two sensors respond synchronously. 、 These are the delay corrections set for the gravity sensor and the magnetic sensor respectively; a star topology is used for branch transmission, and based on the alignment trigger signal, the timing pulse signal is simultaneously transmitted to the trigger interface of the gravimeter and magnetometer through equal-length differential cables to generate time-aligned gravity raw data and magnetic raw data.

[0049] Optionally, generating wave characteristic parameters includes: obtaining the gradient change of adjacent sampling points based on the original magnetic data; marking the time point when the gradient change exceeds the preset gradient threshold to generate a wave peak sequence; fitting the time distribution of the wave peak sequence to generate wave characteristic parameters.

[0050] Specifically, the absolute difference between the magnetic value of the next sampling point and the magnetic value of the previous sampling point is calculated, and the gradient of two adjacent points of the magnetic raw data is calculated to obtain the gradient change. When the gradient change exceeds the preset gradient threshold, the moment is recorded as a magnetic field anomaly point, and the occurrence time of the anomaly point is combined to generate a wave peak sequence. The time interval in the wave peak sequence is estimated by kernel density, and a probability density function is constructed:

[0051] ,

[0052] in is the wave period value, is the measured peak-to-peak interval of the ith wave, is the total number of wave cycles observed, is the smoothness of the distribution curve, The wave characteristic parameters are generated based on the probability density function as the contribution weight of each data point to the neighborhood probability.

[0053] For example, when the magnetic sensor measures a total of 3,600 sampling points within three consecutive minutes, point-by-point calculations show that the gradient changes at 125 seconds, 135 seconds, and 145 seconds are 1.2 nanotesla, 1.1 nanotesla, and 1.3 nanotesla, respectively, exceeding the preset gradient threshold of 0.8 nanotesla. These three moments are marked and a wave peak sequence is generated. The adjacent peak intervals are calculated to be 10 seconds and 10 seconds, respectively, and the average is 10 seconds. The ratio of the duration of 20 seconds to the total duration of 180 seconds is equal to 0.11, and a wave characteristic parameter is generated containing the arithmetic mean of the intervals between two consecutive peaks and the ratio of the duration of the peak sequence to the total observation time. The beneficial effect of this verification example is that through the intelligent identification of gradient mutation points and periodic fitting operations, the periodic characteristics of wave impacts can be accurately captured, providing reliable environmental dynamic characteristic parameters for subsequent gravity and magnetic data compensation, thereby improving the pertinence and effectiveness of wave noise filtering.

[0054] Optionally, generating a wave noise compensation value includes: obtaining an acquisition timing of raw gravity data; based on wave characteristic parameters, matching a wave peak sequence by the acquisition timing to generate a real-time tilt compensation parameter; based on the real-time tilt compensation parameter, calculating an acceleration error component and a wave periodic residual component to generate a wave noise compensation value.

[0055] Specifically, the time stamp corresponding to the original gravity data is obtained to form an acquisition time series array; the acquisition time series array is matched and located with the wave characteristic parameters through the key time point comparison algorithm, and the roll angle and pitch angle are synthesized by trigonometric functions to generate real-time tilt compensation parameters. For the real-time tilt compensation parameters; for the acceleration error component, there are:

[0056] ;

[0057] The real-time tilt compensation parameters , α is the roll angle, is the pitch angle, g is the local gravitational acceleration; for the periodic residual component of the wave ,

[0058] have:

[0059] ,

[0060] in, Determined by the inverse of the wave characteristic parameter T, is the phase angle of each frequency component; the dynamic coupling coefficient is obtained based on the wave characteristic parameters, and the wave noise compensation value is obtained by multiplying the acceleration error component, the wave periodic residual component and the dynamic coupling coefficient.

[0061] For example, when the wave peak sequence shows that the characteristic parameter is equal to 10 and the wave characteristic parameter is equal to 0.2, the real-time tilt compensation parameter measured at 0.3 after the corresponding peak at the time of gravity data acquisition is equal to 8. At this time, the acceleration error component is equal to 1.37. The wave frequency is equal to 0.1, and the phase angle of the frequency component is taken from the initial phase angle 38 of the magnetic gradient peak. At this time, the wave periodic residual component is equal to 0.48. When the dynamic coupling coefficient is 0.7, the wave noise compensation value is equal to 0.46. The beneficial effect of this verification example is that through multi-dimensional physical quantity coupling modeling, the static error caused by attitude tilt and the dynamic disturbance caused by wave impact are compensated at the same time, effectively eliminating the mixed ocean environment noise in the gravity measurement data.

[0062] Optionally, correcting the wave noise compensation value in the original gravity data to generate target gravity field data includes: constructing a dynamic filter based on wave characteristic parameters; generating a gravity compensation residual through the dynamic filter based on the wave noise compensation value; and superimposing the gravity compensation residual on the original gravity data to generate target gravity field data.

[0063] Specifically, based on the wave average period and amplitude coefficient of the wave characteristic parameters, the upper and lower cutoff frequencies of the bandpass filter are calculated and the order is set to construct a dynamic filter; the wave noise compensation value is input into the dynamic filter for time domain convolution to obtain the gravity compensation residual. ,have:

[0064] ,

[0065] in, The filter coefficients are generated by the normalized Hanning window function according to the cutoff frequency. is the wave noise compensation value; the gravity compensation residual and the original gravity data are aligned according to the timestamp and then scalar superposition is performed to generate the target gravity field data.

[0066] Optionally, the method further includes: fusing the target gravity field data with the magnetic field values ​​of corresponding spatial positions in the magnetic raw data to generate a standardized fused data set; and generating a three-dimensional physical property distribution map based on the standardized fused data set.

[0067] Optionally, generating a three-dimensional physical property distribution map includes: performing regional field and local field separation operations based on a standardized fusion data set to generate a local gravity and magnetic anomaly data volume; constructing a gravity and magnetic anomaly matrix based on the local gravity and magnetic anomaly data volume; and generating a three-dimensional physical property distribution map based on the gravity and magnetic anomaly matrix.

[0068] Specifically, the target gravity field data is converted into gridded data in the standard earth coordinate system. The synchronous magnetic raw data is mapped to the same coordinate grid after magnetic declination correction. The ratio of the inverse of the gravity field standard deviation to the magnetic induction intensity range is obtained through normalization processing to standardize the fused data set. The standardized fused data set is subjected to wavelet decomposition to eliminate high-frequency noise and generate a local gravity and magnetic anomaly data volume. The local gravity and magnetic anomaly data volume is subjected to Kirchhoff integral migration processing to establish a three-dimensional space node outlier matrix. For the three-dimensional space node outlier matrix Q, we have:

[0069] ,

[0070] in is the gravity Poisson's ratio weight term, is the magnetization intensity proportional factor, is the unit volume gravity sensitivity coefficient, is the unit volume magnetization response coefficient, is the magnetic susceptibility difference; the constrained least squares method is used to solve the physical property parameter equations. The inversion objective function is equal to the F-norm square of the difference between the observed anomaly matrix and the theoretical model plus the regularization term, where the regularization coefficient is adaptively adjusted according to the model roughness to generate a three-dimensional physical property distribution map, such as Figure 3 Shown is a schematic diagram of three-dimensional physical property distribution.

[0071] Based on the same inventive concept, Figure 4 As shown, the present invention also provides an unmanned ship gravity and magnetic measurement system, the system comprising:

[0072] Data acquisition module: used to obtain the real-time attitude data of the unmanned ship and generate tilt compensation parameters;

[0073] High-precision positioning module: used to adjust the data acquisition frequency according to the tilt compensation parameters and generate positioning enhancement signals;

[0074] Gravity and magnetic data synchronization module: used to trigger the acquisition of operation data based on the positioning enhancement signal, generate gravity raw data and magnetic raw data, where the magnetic raw data includes the magnetic field gradient mutation point;

[0075] Magnetic field gradient analysis module: used to extract magnetic field gradient mutation points in the original magnetic data and generate wave characteristic parameters;

[0076] Wave noise compensation module: used to integrate tilt compensation parameters, wave characteristic parameters and gravity raw data to generate wave noise compensation values;

[0077] Gravity field construction module: used to correct the wave noise compensation value and generate target gravity field data.

[0078] It should be noted that the electrical connections between the above-mentioned units do not necessarily mean direct connections of lines. Indirect connections are applicable to the embodiments of the present invention as long as the purpose of the present invention is achieved. The above description is only an exemplary embodiment of the present invention and is not intended to limit the scope of the present invention.

[0079] That is, any equivalent changes and modifications made according to the teachings of the present invention are still within the scope of the present invention. Those skilled in the art will readily conceive of other embodiments of the present invention after considering the disclosure of the specification and practical truths. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary technical means in the art not described herein.

Claims

1. A gravity and magnetic measurement method using an unmanned vessel, characterized in that: The method comprises: Obtain the real-time attitude data of the unmanned vessel and generate tilt compensation parameters; Adjusting the data acquisition frequency according to the tilt compensation parameter to generate a positioning enhancement signal; Based on the positioning enhancement signal, triggering the collection of operation data, generating gravity raw data and magnetic raw data, wherein the magnetic raw data includes a magnetic field gradient mutation point; Extracting magnetic field gradient mutation points in the raw magnetic data to generate wave characteristic parameters, wherein generating wave characteristic parameters includes: Based on the raw magnetic data, obtaining gradient changes of adjacent sampling points; Marking the time point when the gradient change exceeds a preset gradient threshold, and generating a wave peak sequence; Fitting the time distribution of the wave peak sequence to generate wave characteristic parameters; The inclination compensation parameter, the wave characteristic parameter, and the original gravity data are integrated to generate a wave noise compensation value, wherein generating the wave noise compensation value includes: Obtaining a collection time sequence of the raw gravity data; Based on the wave characteristic parameters, the real-time tilt compensation parameters are generated by matching the wave peak sequence through the acquisition timing; Based on the real-time tilt compensation parameters, the acceleration error component and the wave periodic residual component are calculated to generate the wave noise compensation value; Target gravity field data is generated based on the wave noise compensation value.

2. The unmanned ship gravity and magnetic measurement method according to claim 1, characterized in that: Generating the tilt compensation parameter includes: Monitor the waves acting on the hull and generate roll and pitch angles; Calculate the theoretical horizontal calibration angle of the gravity probe base and generate hydraulic compensation instructions; The hydraulic compensation instruction is executed to generate an inclination compensation parameter.

3. The gravity and magnetic measurement method using an unmanned ship according to claim 1, characterized in that: Generating a positioning enhancement signal includes: Calculating the angle change based on the tilt compensation parameter to generate a fluctuation amplitude; When the fluctuation amplitude exceeds the preset tilt angle threshold, the sampling frequency is increased to the preset high-frequency mode to generate a positioning enhancement signal.

4. The gravity and magnetic measurement method using an unmanned vessel according to claim 1, characterized in that: Generating time-aligned gravity and magnetic raw data includes: generating a timing pulse signal based on the positioning enhancement signal; generating an alignment trigger signal based on the transmission delay of the timing pulse signal; Based on the alignment trigger signal, the timing pulse signal is transmitted in a branched manner to generate time-aligned gravity raw data and magnetic raw data.

5. The unmanned ship gravity and magnetic measurement method according to claim 1, characterized in that: The generating target gravity field data based on the wave noise compensation value includes: constructing a dynamic filter based on the wave characteristic parameters; Based on the wave noise compensation value, a gravity compensation residual is generated through the dynamic filter; The gravity compensation residual is superimposed on the original gravity data to generate target gravity field data.

6. The unmanned ship gravity and magnetic measurement method according to claim 1, characterized in that: Also includes: fusing the target gravity field data with the magnetic field values ​​at corresponding spatial positions in the original magnetic data to generate a standardized fused data set; A three-dimensional physical property distribution map is generated based on the standardized fusion data set.

7. The unmanned ship gravity and magnetic measurement method according to claim 6, characterized in that: Generating a three-dimensional physical property distribution map includes: Based on the standardized fusion data set, performing a regional field and a local field separation operation to generate a local gravity and magnetic anomaly data volume; constructing a gravity and magnetic anomaly matrix based on the local gravity and magnetic anomaly data volume; Based on the gravity and magnetic anomaly matrix, a three-dimensional physical property distribution map is generated.

8. A gravity and magnetic measurement system applied to the gravity and magnetic measurement method of an unmanned vessel according to any one of claims 1 to 7, characterized in that: The system comprises: Data acquisition module: used to obtain the real-time attitude data of the unmanned ship and generate tilt compensation parameters; High-precision positioning module: used to adjust the data acquisition frequency according to the tilt compensation parameters and generate a positioning enhancement signal; Gravity and magnetic data synchronization module: used to trigger the acquisition of operation data based on the positioning enhancement signal, generate gravity raw data and magnetic raw data, where the magnetic raw data includes the magnetic field gradient mutation point; Magnetic field gradient analysis module: used to extract magnetic field gradient mutation points in the magnetic raw data and generate wave characteristic parameters; Wave noise compensation module: used to fuse the tilt compensation parameters, wave characteristic parameters and gravity raw data to generate wave noise compensation values; Gravity field construction module: used to generate target gravity field data based on the wave noise compensation value.

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