Marine magnetometer performance detection method and related apparatus

Abstract

This application provides a method and related equipment for testing the performance of a marine magnetometer, belonging to the field of marine exploration and measurement technology. The method involves acquiring a first measurement dataset by collecting data from different magnetometers at the same location. Based on this first measurement dataset, intersection deviation is calculated to determine the initial measurement consistency of each magnetometer. By evaluating the consistency of multiple magnetometers measuring the same object, users can select multiple magnetometers with higher consistency for collaborative measurement, thereby reducing system measurement errors. Alternatively, a second measurement dataset is obtained by placing the magnetometer on a towed carrier and acquiring data from the carrier under different motion states at sea. Based on the second measurement dataset, data noise stability analysis is performed under different carrier motion states to determine the initial measurement stability of the magnetometer. This enables performance checks in the dynamic actual working environment of the ocean, improving the reliability of the test results.

Description

Technical Field

[0001] This application relates to the field of marine exploration and measurement technology, and in particular to a method and related equipment for testing the performance of a marine magnetometer. Background Technology

[0002] Marine magnetic surveying is an important tool for marine geological surveys, mineral resource exploration, and target detection. As a core measuring instrument, the performance of the magnetometer directly affects data quality and the reliability of interpretation results.

[0003] Currently, although there are some testing methods for magnetometers both domestically and internationally, they generally have the following shortcomings: 1) Most current performance measurements of magnetometers are static laboratory tests, which cannot reflect the performance of the instrument in the dynamic actual working environment of the ocean; 2) They do not consider the measurement errors that may occur in the collaborative system when multiple ships or multiple magnetometers are used to explore marine geology. Summary of the Invention

[0004] The main objective of this application is to propose a method and related equipment for testing the performance of a marine magnetometer, aiming to achieve reliable testing of the performance of a marine magnetometer in a dynamic marine working environment, thereby reducing system measurement errors.

[0005] To achieve the above objectives, one aspect of this application proposes a method for testing the performance of a marine magnetometer, comprising the following steps: Acquire a first measurement dataset from multiple magnetometers in a first test scenario; the first test scenario involves data acquisition from different magnetometers at the same location. Based on the first measurement dataset, the intersection deviation is calculated to determine the first measurement consistency of each magnetometer; Acquire a second measurement dataset of the magnetometer in a second test scenario; the second test scenario is that the magnetometer is set on a towed carrier, and the magnetometer data is collected when the towed carrier is in different motion states at sea; Based on the second measurement dataset, data noise stability analysis is performed under different carrier motion states to determine the first measurement stability of the magnetometer. The performance test results of the magnetometer are determined based on the first measurement consistency and the first measurement stability.

[0006] In some embodiments, the method for testing the performance of a marine magnetometer further includes the following steps: Obtain the third test dataset of the magnetometer in the third test scenario; the third test scenario is to continuously collect magnetometer data in a geomagnetic field quiescent environment area according to a preset sampling rate; The fourth-order difference and mean of the third test dataset are calculated, and the static noise level of the magnetometer at the preset sampling rate is determined based on the fourth-order difference and mean. The static noise level is added to the performance test results.

[0007] In some embodiments, the method for testing the performance of a marine magnetometer further includes the following steps: The third test dataset is filtered according to the desired time period to obtain the fourth test dataset; Power spectrum estimation is performed on the fourth test dataset to construct the data power spectral density; The noise amplitude at the target frequency point is extracted from the power spectral density of the data as the instrument sensitivity. Add the instrument sensitivity to the performance test results.

[0008] In some embodiments, the step of calculating the intersection deviation based on the first measurement dataset to determine the first measurement consistency of each magnetometer includes the following steps: Extract the first measurement point data in the first measurement line direction and the second measurement point data in the second measurement line direction from the first measurement dataset; Magnetic field strength measurement deviation analysis was performed on the data from the first measuring point and the data from the second measuring point respectively to obtain the first magnetic field anomaly value and the second magnetic field anomaly value. The crossover deviation value of the measurement line intersection point is calculated based on the first magnetic field anomaly value and the second magnetic field anomaly value; wherein the first magnetic field anomaly value and the second magnetic field anomaly value are derived from different magnetometer measurement data; The first measurement consistency of the magnetometer is determined based on the cross deviation value of each magnetometer at different measurement line intersection points.

[0009] In some embodiments, the method for testing the performance of a marine magnetometer further includes the following steps: Calculate the root mean square error between any two magnetometers based on the first measurement dataset; For each magnetometer to be analyzed, the second measurement consistency of the magnetometer to be analyzed is determined based on the root square error of the magnetometer to be analyzed and other magnetometers. Add the second measurement consistency to the performance test results.

[0010] In some embodiments, the step of performing data noise stability analysis based on the second measurement dataset under different carrier motion states to determine the first measurement stability of the magnetometer includes the following steps: Extract continuous magnetic force measurement data of each magnetometer under each carrier motion state from the second measurement dataset, and then determine the dynamic noise of the magnetometer under the carrier motion state based on the continuous magnetic force measurement data; The first measurement stability of the magnetometer is determined based on the dynamic noise of the magnetometer under different carrier motion states.

[0011] In some embodiments, the method for testing the performance of a marine magnetometer further includes the following steps: Extract the magnetic data and corresponding attitude data of each magnetometer at measurement points under different headings from the second measurement dataset; the attitude data of the measurement points comes from a triaxial attitude sensor. The magnetic data at each measurement point were corrected using an ellipsoidal fitting model. The standard deviation of the heading error is calculated based on the corrected magnetic data of all the measurement points and the attitude data of all the measurement points, and the second measurement stability is determined based on the standard deviation of the heading error. The second measurement stability is added to the performance test results of the magnetometer.

[0012] To achieve the above objectives, another aspect of this application provides a marine magnetometer performance testing system, comprising: The first module is used to acquire a first measurement dataset from multiple magnetometers in a first test scenario; the first test scenario is that different magnetometers are at the same location when magnetometer data is collected. The second module is used to calculate the intersection deviation based on the first measurement dataset and determine the first measurement consistency of each magnetometer. The third module is used to acquire the second measurement dataset of the magnetometer in the second test scenario; the second test scenario is that the magnetometer is set on a towed carrier, and the magnetometer data is collected when the towed carrier is in different motion states at sea. The fourth module is used to perform data noise stability analysis under different carrier motion states based on the second measurement dataset, and to determine the first measurement stability of the magnetometer. The fifth module is used to determine the performance test results of the magnetometer based on the first measurement consistency and the first measurement stability.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0014] To achieve the above object, on the other hand, an embodiment of the present application proposes a computer program product, including a computer program, which implements the above method when executed by a processor.

[0015] The embodiments of the present application at least include the following beneficial effects: The present application provides a method, system, electronic device, and program product for detecting the performance of a marine magnetometer. This solution obtains a first measurement data set by collecting magnetometer data when different magnetometers are at the same position, calculates the intersection deviation based on the first measurement data set, and determines the first measurement consistency of each magnetometer. By evaluating the consistency of multiple magnetometers in measuring the same object, users can select multiple magnetometers with higher consistency for collaborative measurement, thereby reducing the system measurement error. The magnetometer is set on a towing vehicle, and magnetometer data is collected when the towing vehicle is in different motion states at sea to obtain a second measurement data set. According to the second measurement data set, the data noise stability analysis under different vehicle motion states is carried out to determine the first measurement stability of the magnetometer, realizing the performance inspection in the actual working environment of the ocean dynamics and improving the reliability of the detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flowchart of the method for detecting the performance of a marine magnetometer provided by an embodiment of the present application; Figure 2 is a flowchart of the method for detecting the performance of a marine magnetometer provided by another embodiment of the present application; Figure 3 is a flowchart of the method for detecting the performance of a marine magnetometer provided by another embodiment of the present application; Figure 4 is a schematic diagram of the power spectral density provided by an embodiment of the present application; Figure 5 is Figure 1 a flowchart of step S102 in Figure 6 is a schematic diagram of the north-south direction survey line provided by an embodiment of the present application; Figure 7 is a flowchart of the method for detecting the performance of a marine magnetometer provided by another embodiment of the present application; Figure 8 is Figure 1 a flowchart of step S104 in Figure 9 is a schematic diagram of the "rice" - shaped survey line provided by an embodiment of the present application; Figure 10 is a flowchart of the method for detecting the performance of a marine magnetometer provided by another embodiment of the present application; Figure 11 is a schematic diagram of the hardware structure of the electronic device provided by an embodiment of the present application. <用户输入的文本中没有对应的内容 DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0020] While some single-point testing methods for magnetometers exist both domestically and internationally, a complete and systematic testing process that simulates the real marine working environment is lacking. Existing testing methods typically suffer from the following shortcomings: 1) They are mostly static laboratory tests, unable to simulate the impact of dynamic marine environments (such as towing attitude changes and seawater flow) on the instrument; 2) They lack standardized comparison procedures for consistency among multiple devices; 3) Noise assessments often rely on time-domain statistics, failing to effectively distinguish between instrument noise and environmental background noise, and lacking quantitative standards for frequency-domain analysis; 4) For magnetometers mounted on towed bodies, there is a lack of verification of the carrier's ability to eliminate interfering magnetic fields. Therefore, a scientific and standardized testing process for marine magnetometer performance indicators is urgently needed.

[0021] In view of this, this application provides a method and related equipment for testing the performance of a marine magnetometer. This method can simulate the real marine operating environment and comprehensively and quantitatively evaluate the static noise level, dynamic towing performance, multi-sensor consistency, and diurnal variation correction effectiveness of the magnetometer, thereby improving the reliability of marine magnetometer performance testing.

[0022] The marine magnetometer performance testing method provided in this application relates to the field of marine exploration and measurement technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle-mounted terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the marine magnetometer performance testing method, but is not limited to the above forms.

[0023] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0024] Figure 1 This is an optional flowchart of the marine magnetometer performance testing method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S105.

[0025] S101, acquire the first measurement dataset from multiple magnetometers in the first test scenario; the first test scenario is to collect magnetometer data when different magnetometers are in the same location. S102, calculate the intersection deviation based on the first measurement dataset, and determine the first measurement consistency of each magnetometer; S103, acquire the second measurement dataset of the magnetometer in the second test scenario; the second test scenario is that the magnetometer is set on the towed carrier and the magnetometer data is collected when the towed carrier is in different motion states at sea. S104, Based on the second measurement dataset, perform data noise stability analysis under different carrier motion states to determine the first measurement stability of the magnetometer; S105, Based on the first measurement consistency and the first measurement stability, determine the performance test result of the magnetometer.

[0026] Steps S101 to S105, as illustrated in this embodiment, involve acquiring a first measurement dataset by collecting data from different magnetometers at the same location. Based on this first measurement dataset, intersection deviation is calculated to determine the first measurement consistency of each magnetometer. By evaluating the consistency of multiple magnetometers measuring the same object, users can select multiple magnetometers with higher consistency for collaborative measurement, thereby reducing system measurement errors. Alternatively, a second measurement dataset is obtained by placing magnetometers on a towed carrier and collecting data from the carrier under different motion states at sea. Based on this second measurement dataset, data noise stability analysis is performed under different carrier motion states to determine the first measurement stability of the magnetometers. This enables performance checks in a dynamic marine working environment, improving the reliability of the detection results.

[0027] In step S101 of some embodiments, the first test scenario refers to a scenario where different magnetometers are used to collect magnetometer data at the same location, and a corresponding first measurement dataset is obtained under the first test scenario. Specifically, the first test scenario may be when at least two magnetometers pass through the same location along different measurement lines to collect data.

[0028] In step S102 of some embodiments, the cross deviation refers to the magnetic anomaly value at the intersection point of the same measurement line with other intersecting measurement lines (i.e., the difference in measured values ​​between the two measurement lines at that point). In this embodiment, the data of the two measurement lines at the intersection point come from different magnetometers. This embodiment can measure the first measurement consistency of each magnetometer with other magnetometers in terms of measurement deviation by calculating the cross deviation based on the first measurement dataset. This allows the user to select multiple magnetometers with higher consistency for collaborative measurement, thereby reducing system measurement errors.

[0029] In step S103 of some embodiments, the second test scenario refers to a scenario where a magnetometer is mounted on a towed carrier, and magnetometer data is collected when the towed carrier is in different motion states at sea. A corresponding second measurement dataset is obtained under the second test scenario. Specifically, the second test scenario can be a scenario where the towed carrier collects magnetometer data at different speeds at sea, a scenario where the towed carrier collects magnetometer data at different headings at sea, or a scenario where the towed carrier collects magnetometer data at both different speeds and different headings at sea.

[0030] In step S104 of some embodiments, data noise stability analysis is performed under different carrier motion states (such as different speeds or different headings) based on the second measurement dataset to determine the first measurement stability of the magnetometer. The first measurement stability characterizes the noise change of the measurement data of the magnetometer under different marine operating conditions and reflects the performance of the magnetometer in the dynamic actual working environment of the ocean.

[0031] In step S105 of some embodiments, the performance test results of the magnetometer are used to describe the performance test status of the magnetometer. It can be a performance test report, which includes at least performance indicators such as first measurement consistency and first measurement stability, and may further include a performance score value after weighted calculation of the values ​​of each performance indicator.

[0032] Please refer to Figure 2 In some embodiments, the marine magnetometer performance testing method of this application may also include, but is not limited to, the following steps: S201, Obtain the third test dataset of the magnetometer in the third test scenario; The third test scenario is to continuously collect magnetometer data in a geomagnetic field quiescent environment area according to a preset sampling rate; S202, calculate the fourth-order difference and mean of the third test dataset, and determine the static noise level of the magnetometer at the preset sampling rate based on the fourth-order difference and mean. S203 adds the static noise level to the performance test results.

[0033] Specifically, the third test scenario involves placing the magnetometer under test at a geomagnetic observatory or in a known geomagnetic quiescent environment. The magnetic sensor is fixed on a non-magnetic tripod, with no ferromagnetic interference in the vicinity. The magnetometer continuously collects geomagnetic field data for a period of time (e.g., at least 24 hours) at a preset sampling rate of at least 1 Hz, resulting in the third test dataset. Further, different sampling rates can be set, such as setting the sampling rates to 1 Hz, 2 Hz, and 4 Hz for 6 consecutive hours each. The static noise level S of the data at different sampling rates is then calculated. nThe collected data is preprocessed to remove data from periods of severe disturbance during geomagnetic storms.

[0034] Marine magnetometer static noise S n The calculation formula is expressed as follows: ; ; ; in, This represents the fourth-order difference calculation. This indicates the calculation of the mean. This represents the data collected by the magnetometer in the third test dataset. n is the number of data points participating in the calculation, and i is the data sequence number (1, 2, 3). ,n, , , The unit is nT (the unit of geomagnetic field value: nanoter, the same below).

[0035] Please refer to Figure 3 In some embodiments, the marine magnetometer performance testing method of this application may also include, but is not limited to, the following steps: S301, Filter the third test dataset according to the expected time period to obtain the fourth test dataset; S302, perform power spectrum estimation on the fourth test dataset, and then construct the data power spectral density; S303, extracts the noise amplitude at the target frequency point from the data power spectral density as the instrument sensitivity; S304, add instrument sensitivity to performance test results.

[0036] Specifically, the desired time period can refer to the period of relatively stable geomagnetic field at night. For example, the third test dataset includes 12 hours of continuous data collected during the period of relatively stable geomagnetic field at night. The fourth test dataset is obtained by extracting a continuous data period of relatively stable geomagnetic field at night from the third test dataset, with a duration of no less than 2 hours. The data in the fourth test dataset undergoes detrending and bandpass filtering. Then, the Welch method is used to estimate the power spectral density of the data, and the noise amplitude corresponding to the target frequency point (1Hz) is extracted as the instrument's sensitivity index. The details are as follows: The Welch method is the most commonly used power spectrum estimation method in engineering. It effectively reduces the estimation variance by segmenting the data, adding windows, and overlapping data.

[0037] Specifically, the data segmentation involves dividing the N-length magnetic measurement data sequence x[n] in the fourth test dataset into K segments, each segment having a length of H, with adjacent segments overlapping by 50%. The segmented data is represented as follows: x (i) [n]=x[n+iD],n=0,1,...,H 1; Where D is the inter-segment offset (D=H / 2 when there is a 50% overlap), and the number of segments .

[0038] Windowing involves applying a window function w[n] (such as the Hanning window or Hamming window) to each data segment to reduce spectral leakage. The windowed data is represented as follows: x w (i) [ n ]= x (i) [ n ]* w [ n ]; The Hanning window is commonly represented as follows: w [ n ]=0.5[1 cos( H 12 πn )], n =0,1,..., H 1; The energy normalization coefficients of the window function are expressed as follows: ; Perform a Discrete Fourier Transform on each segment of the windowed data to calculate the periodogram P, as shown below: ; ; The Welch power spectrum estimate is obtained by averaging the periodograms of all segments, as shown below: ; Corresponding frequency points: ,k =0,1,...,H / 2; For example, the power spectral density is as follows Figure 4 As shown.

[0039] For dynamic noise assessment of magnetometers, the focus is on the noise amplitude at a frequency of 1 Hz, which is used as the instrument sensitivity of the magnetometer. ; In addition, noise levels in different frequency bands can be calculated: Low frequency band (0.01-0.1Hz): reflects the effects of long-term instrument drift and diurnal variation.

[0040] Mid-frequency band (0.1-1Hz): Reflects the noise caused by the periodic motion of ocean waves.

[0041] High frequency band (1-10Hz): reflects the instrument's background noise and electronic noise.

[0042] Compared to the current method of using time-domain statistics for noise assessment, the noise assessment in this embodiment uses frequency-domain statistics, which can effectively distinguish between instrument noise and environmental background noise and provide a quantitative standard for frequency domain analysis.

[0043] Please refer to Figure 5 In some embodiments, step S102 may include, but is not limited to, the following steps: S401, Extract the first measuring point data in the first measuring line direction and the second measuring point data in the second measuring line direction from the first measurement dataset; S402, perform magnetic field strength measurement deviation analysis on the data from the first measuring point and the data from the second measuring point respectively, and obtain the first magnetic field anomaly value and the second magnetic field anomaly value accordingly; S403, calculate the crossover deviation value of the measurement line intersection point based on the first magnetic field anomaly value and the second magnetic field anomaly value; wherein, the first magnetic field anomaly value and the second magnetic field anomaly value come from different magnetometer measurement data; S404, determine the first measurement consistency of the magnetometer based on the crossover deviation value of each magnetometer at different measurement line intersection points.

[0044] In this embodiment, at least two identical magnetometer probes can be fixed side-by-side on the same towed carrier, with the probe spacing controlled at 5-10 meters to avoid mutual interference. Then, a sea-based measurement is conducted in calm sea area along a pre-set survey line. For example, a setup such as... Figure 6 The north-south survey line shown can be used to set up six magnetometers side by side to collect data along the south and north survey lines respectively, thus obtaining the first measurement dataset.

[0045] The crossover point deviation of each magnetometer observation value is calculated based on the first measurement dataset. The specific calculation process is as follows: Extract the first measurement point data TZ at the intersection of the north-south survey line Z and the east-west survey line J from the first measurement dataset. i (i is the number of north-south measurement lines), the second measurement point data TJ j (j represents the number of east-west survey lines).

[0046] The geomagnetic anomaly value at the intersection point is calculated using the following formula, taking the calculation of the first magnetic field anomaly value of the north-south survey line as an example: △TZi =TZ i - ; Among them, △TZ i This represents the geomagnetic anomaly value, in units of nT and TZ. i This represents the measured total intensity of the Earth's magnetic field, in nT. This represents the normal geomagnetic field value, which is a verifiable constant in nT; i=1,2,3 represents the number of north-south survey lines.

[0047] Similarly, calculate the second geomagnetic anomaly value ΔTJ at the intersection of the east-west survey lines. j .

[0048] The intersection deviation value M is calculated as follows: ; ; in, M represents the discrepancy between the measured values ​​at the intersection of the north-south and east-west survey lines, in units of nT; M represents the intersection deviation value, in units of nT; n represents the number of intersections between the north-south and east-west survey lines.

[0049] For each magnetometer, there are multiple intersection points at which it passes through, resulting in multiple intersection point deviation values. The average of these multiple intersection point deviation values ​​is used to calculate the cross deviation value of the magnetometer. This cross deviation value can measure the consistency observation error of the magnetometer (i.e., the first measurement consistency). Normally, this value should be better than 1.5nT.

[0050] Please refer to Figure 7 In some embodiments, the marine magnetometer performance testing method of this application may also include, but is not limited to, the following steps: S501, calculate the root mean square error between any two magnetometers based on the first measurement dataset; S502, For each magnetometer to be analyzed, determine the second measurement consistency of the magnetometer to be analyzed based on the root square error of the magnetometer to be analyzed and other magnetometers. S503 adds a second measurement consistency to the performance test results.

[0051] In this embodiment, after eliminating the influence of diurnal variation, the root mean square error between any two instruments is calculated. This value should be better than the requirement of ±2.0 nT. The specific calculation process of the root mean square error is as follows: Based on data from the geomagnetic diurnal variation observation station set up during the marine survey, the correction for diurnal variation influence during the survey was calculated. T t t is the measurement time (accurate to the second, the same below).

[0052] The following formula is used to calculate the measured values ​​of the two instruments at any given time after removing the effects of diurnal variation: F1t=V1 t + T t ; F2t=V2 t + T t ; Among them, V1 t V2 represents the measurement value of the first instrument at time t, in units of nT. t F1t and F2t represent the measured values ​​of the second instrument at time t, in nT; F1t and F2t represent the measured values ​​of the two instruments at time t after removing the effects of diurnal variation, in nT.

[0053] The root mean square error between any two instruments is calculated using the following formula: ; ; Where Ω represents the difference in the corrected measurement values ​​of the two instruments at time t, in nT; W represents the root mean square error between the two instruments, in nT.

[0054] For each magnetometer, there are multiple root mean square errors corresponding to other magnetometers. The average of these multiple root mean square errors is calculated to obtain the mean root mean square error of the magnetometer. This mean root mean square error is used to measure the consistency of the first measurement. Normally, this value should be better than 1.5nT.

[0055] Please refer to Figure 8 In some embodiments, step S104 may include, but is not limited to, the following steps: S601, extract the continuous magnetic force measurement data of each magnetometer under each carrier motion state from the second measurement dataset, and then determine the dynamic noise of the magnetometer under the carrier motion state based on the continuous magnetic force measurement data; S602, determine the first measurement stability of the magnetometer based on the dynamic noise of the magnetometer under different carrier motion states.

[0056] In this embodiment, the first test scenario specifically involves installing a magnetometer in a towed carrier (such as an underwater towed fish) and conducting a marine towed operation in accordance with marine magnetic measurement specifications. The towed process includes straight-line constant speed, change of direction, and speed change segments to conduct dynamic towed performance testing.

[0057] Specifically, continuous magnetic force measurement data for each magnetometer under each carrier motion state are extracted from the second measurement dataset, and then the dynamic noise S of the magnetometer under the carrier motion state is determined based on the continuous magnetic force measurement data. i, the calculation formula is: ; where n is the number of data points participating in the calculation, and i is the data sequence number 1, 2, 3, , n, 、 、 The calculations of 、 、 are in units of nT.

[0058] The first measurement stability includes speed-changing stability, course-changing stability, and may further include sampling rate-changing stability.

[0059] Speed-changing stability: Navigate at speeds of 6 kn, 8 kn, and 10 kn for 15 minutes in sequence; calculate the instrument dynamic noise level S i When the instrument is working properly at different speeds, its dynamic noise value S i ≤0.2 nT. Further, the dynamic noise at different speeds is comprehensively used to measure the speed-changing stability.

[0060] Course-changing stability: The measuring ship sails at a speed of 10 kn, maintaining a uniform straight-line state, and successively passes through the "rice" - shaped survey lines as shown in Figure 9 , with headings of 0°, 225°, 90°, 315°, 180°, 45°, 270°, and 135° in sequence; calculate the instrument dynamic noise level S i When the instrument sails at different headings, its dynamic noise value S i The [[ID=]38]≤0. (

[0061] Sampling rate-changing stability: Set the sampling rates to 1 Hz, 2 Hz, and 4 Hz in sequence and sail for 15 minutes; calculate the instrument dynamic noise level S i .

[0062] Please refer to Figure 10 , in some embodiments, the method for detecting the performance of the marine magnetometer in the embodiments of the present application may further include but is not limited to the following steps: S701, Extract the magnetic force data of each measurement point and the corresponding measurement point attitude data of each magnetometer at different headings from the second measurement dataset; the measurement point attitude data comes from a three-axis attitude instrument; S702, Correct the magnetic force data of each measurement point through an ellipsoid fitting model; S703, Calculate the standard deviation of the course error based on the corrected magnetic force data of all measurement points and the attitude data of all measurement points, and determine the second measurement stability according to the standard deviation of the course error; S704 adds a second measurement stability to the performance test results of the magnetometer.

[0063] In this embodiment, a triaxial magnetometer and a triaxial attitude meter are installed on the towed carrier. By establishing an ellipsoidal fitting model, the hard and soft magnetic interference of the carrier is eliminated, and the stability of the compensated magnetic data in different headings is verified (i.e., the second measurement stability).

[0064] First, the specific process for correcting the magnetic force data at the measurement point is as follows: S11, Error Modeling; The magnetometer output is m=[mx,my,mz]. T The actual Earth's magnetic field h=[hx,hy,hz] T The relationship is represented as follows: m=A h+b; Where A is a 3×3 matrix representing soft magnetic interference, calibration error, non-orthogonality error, etc.; b is a 3×1 vector representing hard magnetic interference. Further derivation yields the following correction formula: h=A 1 (m b); S12, ellipsoidal constraint; Ideally, ||h|| 2 =H 2 (constant).

[0065] Substituting into the correction formula, we get: (m b) T (A 1 ) T A 1 (m b)= H 2 Let M = (A 1 ) T A 1 Thus, the equation of the ellipsoid is obtained: (m b) T M(m b)= H 2 The physical meaning represented by the ellipsoid equation is that the disturbed measurement data m is distributed on an ellipsoid, and M and b can be obtained by fitting the ellipsoid.

[0066] S13, Solving by ellipsoid fitting; The above ellipsoid equation can be expanded into the following equation: ; Solve the above expansion equation using least squares: For N measurement points, construct matrix V (N×10): ; Solve for V θ =0, constrain ||θ||=1, and obtain the parameters of the ellipsoid equation expansion. Specifically, perform singular value decomposition on V, and take the right singular vector corresponding to the smallest singular value as the number θ=[a,b,c,f,g,h,p,q,r,d] T .

[0067] S14, Extract calibration parameters; Let the center of the ellipsoid be b. c , ,t=[ p , q , r ] T ; Solve for: Q b c = t, i.e. b c = Q 1 t; The shape matrix is ​​normalized to: ; ; Using the correction matrix L to represent M, and performing Cholesky decomposition on M, we obtain: M=LL T A 1 =L; For any measured value m, the correction formula is expressed as: h corrected =L(m b c ); The corrected magnetic field modulus should be a constant. F =||h corrected ||≈constant; S15, Heading stability verification; The towed vehicle can be rotated in the horizontal plane to collect data on multiple heading angles, record the magnetometer measurement value m (i.e., magnetic data at the measurement point) and the attitude sensor reference heading ψref,i (i.e., attitude data at the measurement point). It can be understood that this data can also come from a second measurement dataset.

[0068] Apply the correction formula h to each point i =L(m i b c After correction, calculate the total field value at each measurement point. .

[0069] Calculate the overall average: ; Calculate the total field standard deviation (reflecting heading stability): ; The heading error is calculated as follows: Magnetic heading angle: ; Heading error: ; Standard deviation of heading error: .

[0070] The second measurement stability can include the standard deviation of heading error and the standard deviation of the total field. This second measurement stability is used to measure the stability of the compensated magnetic data in different headings. Specifically, the verification criteria shown in Table 1 can be used to check whether the second measurement stability of the magnetometer is qualified.

[0071] Table 1

[0072] If the above criteria are met, it proves that the ellipsoid fitting model effectively eliminates carrier interference, and the measurement stability of the magnetometer in different headings meets the requirements.

[0073] In some embodiments, the effectiveness of diurnal variation correction for the magnetometer can also be verified. Specifically, the observation data of the magnetometer under test at a geomagnetic observation station is compared with the data of a fixed high-precision diurnal variation instrument, the residual between the two after diurnal variation correction is calculated, and the ability of the magnetometer to follow the diurnal variation of the geomagnetic field is evaluated.

[0074] In some embodiments, the magnetometer can also be tested for deep-sea pressure adaptability. Specifically, the magnetometer probe is placed in a pressure tank to simulate different water depth pressure environments, and the sealing of the magnetometer casing and the performance drift of the internal circuitry under high pressure are tested.

[0075] According to some embodiments of this application, a complete magnetometer performance evaluation report can be generated by calculating the above-mentioned core performance indicators of the instrument and referring to relevant industry standards. Specifically, the magnetometer performance evaluation report may include, but is not limited to, indicators such as first measurement consistency (used to measure the error consistency of multiple magnetometers working together), first measurement stability (used to measure the stability of the magnetometer under different actual marine carrier conditions), static noise level, instrument sensitivity, second measurement consistency (used to measure the root mean square error between the magnetometer and other magnetometers), second measurement stability (used to measure the stability of the compensated magnetic data in different headings), diurnal variation correction effectiveness, and deep-sea pressure adaptability.

[0076] Example 1: Static noise level test.

[0077] A certain model of marine magnetometer was selected as the test object. The test site was chosen at a geomagnetic observation station far from urban interference. The magnetometer probe was mounted on a non-magnetic tripod, with the probe height above the ground not less than 2 meters. After the equipment was powered on and warmed up for 30 minutes, continuous data recording began, with the sampling rate set to 1Hz, and continuous recording lasted for no less than 24 hours. Data from the calm period from 01:00 to 03:00 the next morning was collected. Using the method described in step B of this invention, the noise level of the magnetometer at 1Hz was calculated to be 0.008nT, which is better than the nominal specification of 0.01nT.

[0078] Example 2: Dynamic drag consistency test.

[0079] Two magnetometers (Magnet A and Magnetometer B) were mounted inside a towed fish made of non-magnetic material, which also carried a high-precision attitude sensor. The survey vessel traveled along the survey line at a speed of 6 knots. During the data processing stage, the triaxial orthogonal calibration model mentioned in the background of this invention was first applied to process the raw data, correcting for interference caused by the ferromagnetism of the carrier. Calculations showed that after removing the influence of the regional geomagnetic field gradient, the root mean square error of the measurements taken by the two instruments at the same point was 0.2 nT, meeting the consistency requirements of GJB 7537-2012.

[0080] Example 3: Verification of the effectiveness of diurnal variation correction.

[0081] During offshore operations, the magnetometer under test was placed at an onshore geomagnetic observation station and observed synchronously for 48 hours with a standard magnetometer at the station. Diurnal variation correction calculations were performed using the data from the magnetometer under test, and the calculation results were compared with the actual observations from the standard magnetometer. The results show that the corrected geomagnetic diurnal variation residual is less than 0.2 nT, indicating that the magnetometer has good stability and tracking ability.

[0082] This application also provides a marine magnetometer performance testing system, including: The first module is used to acquire a first measurement dataset from multiple magnetometers in a first test scenario; the first test scenario involves data acquisition from different magnetometers at the same location. The second module is used to calculate the intersection deviation based on the first measurement dataset and determine the first measurement consistency of each magnetometer. The third module is used to acquire the second measurement dataset of the magnetometer in the second test scenario. The second test scenario is that the magnetometer is set on the towed carrier and the magnetometer data is collected when the towed carrier is in different motion states at sea. The fourth module is used to perform data noise stability analysis under different carrier motion states based on the second measurement dataset, and to determine the first measurement stability of the magnetometer. The fifth module is used to determine the performance test results of the magnetometer based on the first measurement consistency and the first measurement stability.

[0083] It is understood that the methods described in the above method embodiments are applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0084] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including a tablet computer, a shipboard computer, or similar device.

[0085] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0086] Please see Figure 11 , Figure 11 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0087] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0088] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0089] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0090] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0091] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0092] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0093] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0094] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0096] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0097] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0098] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0099] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0100] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0101] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0102] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for testing the performance of a marine magnetometer, characterized in that, Includes the following steps: Acquire a first measurement dataset from multiple magnetometers in a first test scenario; the first test scenario involves data acquisition from different magnetometers at the same location. Based on the first measurement dataset, the intersection deviation is calculated to determine the first measurement consistency of each magnetometer; Acquire a second measurement dataset of the magnetometer in a second test scenario; the second test scenario is that the magnetometer is set on a towed carrier, and the magnetometer data is collected when the towed carrier is in different motion states at sea; Based on the second measurement dataset, data noise stability analysis is performed under different carrier motion states to determine the first measurement stability of the magnetometer. The performance test results of the magnetometer are determined based on the first measurement consistency and the first measurement stability.

2. The method for testing the performance of a marine magnetometer according to claim 1, characterized in that, The method for testing the performance of a marine magnetometer also includes the following steps: Obtain the third test dataset of the magnetometer in the third test scenario; the third test scenario is to continuously collect magnetometer data in a geomagnetic field quiescent environment area according to a preset sampling rate; The fourth-order difference and mean of the third test dataset are calculated, and the static noise level of the magnetometer at the preset sampling rate is determined based on the fourth-order difference and mean. The static noise level is added to the performance test results.

3. The method for testing the performance of a marine magnetometer according to claim 2, characterized in that, The method for testing the performance of a marine magnetometer also includes the following steps: The third test dataset is filtered according to the desired time period to obtain the fourth test dataset; Power spectrum estimation is performed on the fourth test dataset to construct the data power spectral density; The noise amplitude at the target frequency point is extracted from the power spectral density of the data as the instrument sensitivity. Add the instrument sensitivity to the performance test results.

4. The method for testing the performance of a marine magnetometer according to claim 1, characterized in that, The step of calculating the intersection deviation based on the first measurement dataset to determine the first measurement consistency of each magnetometer includes the following steps: Extract the first measurement point data in the first measurement line direction and the second measurement point data in the second measurement line direction from the first measurement dataset; Magnetic field strength measurement deviation analysis was performed on the data from the first measuring point and the data from the second measuring point respectively to obtain the first magnetic field anomaly value and the second magnetic field anomaly value. The crossover deviation value of the measurement line intersection point is calculated based on the first magnetic field anomaly value and the second magnetic field anomaly value; wherein the first magnetic field anomaly value and the second magnetic field anomaly value are derived from different magnetometer measurement data; The first measurement consistency of the magnetometer is determined based on the cross deviation value of each magnetometer at different measurement line intersection points.

5. The method for testing the performance of a marine magnetometer according to claim 1, characterized in that, The method for testing the performance of a marine magnetometer also includes the following steps: Calculate the root mean square error between any two magnetometers based on the first measurement dataset; For each magnetometer to be analyzed, the second measurement consistency of the magnetometer to be analyzed is determined based on the root square error of the magnetometer to be analyzed and other magnetometers. Add the second measurement consistency to the performance test results.

6. The method for testing the performance of a marine magnetometer according to claim 1, characterized in that, The step of performing data noise stability analysis based on the second measurement dataset under different carrier motion states to determine the first measurement stability of the magnetometer includes the following steps: Extract continuous magnetic force measurement data of each magnetometer under each carrier motion state from the second measurement dataset, and then determine the dynamic noise of the magnetometer under the carrier motion state based on the continuous magnetic force measurement data; The first measurement stability of the magnetometer is determined based on the dynamic noise of the magnetometer under different carrier motion states.

7. The method for testing the performance of a marine magnetometer according to claim 6, characterized in that, The method for testing the performance of a marine magnetometer also includes the following steps: Extract the magnetic data and corresponding attitude data of each magnetometer at measurement points under different headings from the second measurement dataset; the attitude data of the measurement points comes from a triaxial attitude sensor. The magnetic data at each measurement point were corrected using an ellipsoidal fitting model. The standard deviation of the heading error is calculated based on the corrected magnetic data of all the measurement points and the attitude data of all the measurement points, and the second measurement stability is determined based on the standard deviation of the heading error. The second measurement stability is added to the performance test results of the magnetometer.

8. A performance testing system for a marine magnetometer, characterized in that, include: The first module is used to acquire a first measurement dataset from multiple magnetometers in a first test scenario. The first test scenario involves collecting data from different magnetometers at the same location. The second module is used to calculate the intersection deviation based on the first measurement dataset and determine the first measurement consistency of each magnetometer. The third module is used to acquire the second measurement dataset of the magnetometer in the second test scenario; the second test scenario is that the magnetometer is set on a towed carrier, and the magnetometer data is collected when the towed carrier is in different motion states at sea. The fourth module is used to perform data noise stability analysis under different carrier motion states based on the second measurement dataset, and to determine the first measurement stability of the magnetometer. The fifth module is used to determine the performance test results of the magnetometer based on the first measurement consistency and the first measurement stability.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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