A method and system for correcting the attitude of an airborne transient electromagnetic bird coil

Abstract

This invention discloses a method and system for correcting the attitude of an airborne transient electromagnetic pod coil, belonging to the field of airborne geophysical exploration. It includes: a surface-scanning industrial camera module for real-time acquisition of image information of the suspended coil; an industrial-grade integrated navigation module for outputting inertial navigation data; a time synchronization and data acquisition module for establishing a time unification mechanism; a vision processing module for extracting visual features from the images processed by the time unification mechanism; an inertial navigation calculation module for obtaining the inertial navigation state of the coil attitude angle through angular velocity integration; a data fusion and attitude estimation module for performing fusion calculations based on the combined visual features and inertial navigation state to obtain the fusion result; and a projected area and magnetic moment calculation module for calculating the coil's projected area to the ground and the effective emitted magnetic moment component based on the fusion result. This invention reduces the system complexity and electromagnetic interference risk caused by multiple inertial navigation systems, and improves the detection accuracy and stability of airborne transient electromagnetic data.

Description

Technical Field

[0001] This invention belongs to the field of airborne geophysical exploration technology, and particularly relates to a method and system for correcting the attitude of an airborne transient electromagnetic pod coil. Background Technology

[0002] Airborne Transient Electromagnetic (AEM) is a highly efficient geophysical exploration method that enables rapid detection of subsurface electrical structures by transmitting transient electromagnetic fields in the air and receiving the response signals from the subsurface medium. This system is typically mounted on a helicopter and generates an excitation magnetic field through a large transmitting coil suspended beneath the fuselage. To achieve sufficient detection depth, the transmitting coil often has a diameter exceeding 20 meters and ideally should remain parallel to the ground during flight to maximize the vertical component of the transmitted magnetic field's effect on the subsurface target.

[0003] However, in actual flight, due to airflow disturbances, mechanical vibrations, and the flexible structure of the coil itself, the transmitting coil undergoes complex dynamic deformations and attitude shifts, including multi-degree-of-freedom movements such as roll, pitch, and yaw, causing its plane to no longer be parallel to the ground. Existing technologies often employ high-precision inertial navigation modules (IMU / INS) deployed at multiple coil nodes to estimate coil attitude. However, this approach suffers from high system complexity, significant electromagnetic interference risk, difficulty in capturing continuous deformation features, and challenges in data fusion across multiple modules. Furthermore, relying solely on visual methods is insufficient for accurate 3D reconstruction due to the lack of an absolute attitude reference. Therefore, effectively acquiring the real-time attitude and deformation state of the flexible coil during flight while ensuring measurement accuracy has become a key technological bottleneck for improving the quality of transient electromagnetic data in aviation. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a method and system for correcting the attitude of an aviation transient electromagnetic pod coil, thereby resolving the issues present in the prior art.

[0005] To achieve the above objectives, the present invention provides a system for correcting the attitude of an aircraft transient electromagnetic pod coil, comprising:

[0006] A surface scanning industrial camera module is used to acquire image information of the suspension coil in real time;

[0007] An industrial-grade integrated navigation module is used to output inertial navigation data, including coil plane attitude angles, position, and time synchronization signals.

[0008] The time synchronization and data acquisition module is used to establish a time unification mechanism between the camera and the industrial-grade integrated navigation module;

[0009] The visual processing module is used to extract the geometric features of the coil boundaries from the image processed by the time unification mechanism to obtain visual features;

[0010] The inertial navigation calculation module is used to obtain the time series of coil attitude angles through angular velocity integration, and to obtain the inertial navigation state based on the time series of coil attitude angles;

[0011] The data fusion and attitude estimation module is used to combine the visual features and the inertial navigation state to perform fusion calculation of coil attitude and deformation parameters to obtain the fusion result;

[0012] The projected area and magnetic moment calculation module is used to calculate the coil's projected area to the ground and the effective emitted magnetic moment component based on the fusion result.

[0013] Optionally, the time synchronization and data acquisition module includes:

[0014] The hardware trigger channel is used to directly drive camera exposure and inertial navigation data sampling via a unified clock pulse;

[0015] A software timestamp unit is used to mark timestamps on image frames;

[0016] The data caching and matching unit is used to cache and timestamp the received image frames and inertial navigation data.

[0017] A time delay compensation mechanism is used to monitor timestamp deviations in real time and perform dynamic corrections.

[0018] The data integrity detection unit is used to compare and detect camera frame numbers and inertial navigation time series.

[0019] Optionally, the vision processing module includes:

[0020] The image preprocessing unit performs irradiance equalization, lens distortion correction, and noise suppression operations.

[0021] The boundary extraction unit is used to extract the coil contour point set using a gradient threshold-based edge detection algorithm.

[0022] Curve fitting unit, used to fit closed polygon curves on a set of boundary points using the least squares method;

[0023] The data quality assessment unit is used to determine the confidence level of the boundary identification results.

[0024] The feature compensation unit is used to compensate for missing feature points using temporal proximity interpolation.

[0025] Optionally, the inertial navigation calculation module includes:

[0026] An angular velocity integral unit is used to update the attitude rotation matrix using the antisymmetric matrix of the angular velocity.

[0027] The attitude angle conversion unit is used to convert the angular velocity components output by the gyroscope into the attitude angle change rate.

[0028] Position correction unit, used to introduce GPS position correction and velocity closed-loop compensation;

[0029] The coordinate transformation unit is used to map the position of any point on the coil in the body coordinate system to the ground coordinate system;

[0030] The attitude smoothing unit is used to smooth the attitude curve using sliding window averaging and low-pass filtering.

[0031] Optionally, the data fusion and attitude estimation module includes:

[0032] The state vector definition unit is used to define a state vector that includes coil position, velocity, attitude angle, and deformation parameters;

[0033] Prediction model unit, used for predicting the time evolution of state vectors driven by inertial navigation data;

[0034] The observation model unit is used to establish nonlinear geometric constraints between visual features and inertial navigation state;

[0035] The core of the fusion algorithm is used to achieve multimodal feature fusion using extended Kalman filtering or Transformer structures;

[0036] An adaptive weight adjustment unit is used to dynamically adjust the fusion weights of vision and inertial navigation based on data confidence.

[0037] Optionally, the projected area and magnetic moment calculation module includes:

[0038] The projection point set acquisition unit is used to obtain the projection contour point set of the coil boundary in the ground coordinate system;

[0039] Area calculation unit, used to calculate the projected area using the polygon area calculation formula;

[0040] The normal angle calculation unit is used to calculate the angle between the coil plane normal vector and the ground normal vector using the vector dot product formula;

[0041] The effective component calculation unit is used to calculate the vertical effective component of the emitted magnetic moment based on the projected area and the included angle of the normal.

[0042] The data output unit is used to store the coil attitude angle, the projected area to the ground, and the effective magnetic moment component parameters.

[0043] The present invention also provides a method for correcting the attitude of the coil of an aircraft transient electromagnetic pod, for implementing the aforementioned system, the method comprising the following steps:

[0044] Real-time acquisition of image information of suspension coils using a surface scanning industrial camera;

[0045] The inertial navigation data output by the industrial-grade integrated navigation module includes coil plane attitude angles, position, and time synchronization signals.

[0046] The image information and the inertial navigation data are synchronized in time.

[0047] Visual features are obtained by extracting the geometric features of the coil boundaries from the image processed by the time-unified mechanism.

[0048] The time series of coil attitude angles is obtained by integrating the angular velocity, and the inertial navigation state is obtained based on the time series of coil attitude angles;

[0049] The coil attitude and deformation parameters are fused and calculated by combining the visual features and the inertial navigation state; and the coil's projected area to the ground and the effective emitted magnetic moment component are calculated based on the fused calculation results.

[0050] Optionally, the expression for calculating the projected area of ​​the coil on the ground is:

[0051] ;

[0052] In the formula, Let k represent the smoothed projected area at time t, k represent the frame index within the window, and t represent the current frame index. Let m represent the projected area of ​​the k-th frame, and m be the window length.

[0053] Optionally, the expression for calculating the effective emitted magnetic moment component is:

[0054] ;

[0055] In the formula, M eff Indicates the effective magnetic moment, denoted by α, cosα represents the vertical projection coefficient caused by attitude tilt, N is the number of coil turns, and I is the emission current.

[0056] The present invention also provides a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described thereon.

[0057] Compared with the prior art, the present invention has the following advantages and technical effects:

[0058] This invention achieves the organic fusion of visual and inertial navigation information, significantly improving the accuracy of coil spatial attitude and deformation recognition without increasing additional hardware complexity. Traditional solutions require high-precision inertial navigation modules to be deployed at multiple nodes of the transmitting coil to estimate attitude distribution, which increases system weight and complexity. This invention requires only a single combined navigation module with an under-body camera to perform the same measurement function, resulting in a simpler structure and higher system integration.

[0059] This invention establishes a dynamic mapping relationship between coil attitude and visual features through a deep fusion algorithm, effectively identifying non-rigid changes in the pod coil caused by airflow disturbances and gravitational deformation during flight. Traditional pure inertial navigation calculations only provide overall attitude information and struggle to capture deformation features; pure visual methods lack spatial orientation references and are susceptible to vibration and viewing angle changes. By fusing attitude angle, velocity, and position data output by inertial navigation with coil geometric images obtained by a camera, this invention can simultaneously recover the coil's spatial attitude and geometric shape, achieving joint estimation of attitude changes and structural deformation.

[0060] The fusion results of this invention can be directly used to calculate the effective component of the transmitted magnetic moment and to correct the attitude of the pod collar system. When there is an angle between the coil plane and the ground, only the vertical component can participate in the effective transmitted magnetic field. By using the attitude angle and the projected area to the ground obtained through fusion estimation, the effective magnetic moment component in the vertical direction can be accurately calculated, thereby correcting the signal attenuation caused by attitude deviation. This result can be used for post-processing correction of detection data after flight, improving the consistency between the calculated transmitted field strength and the received signal amplitude, and enhancing the physical interpretability of the data.

[0061] This invention possesses strong system adaptability and scalability. While achieving its core functions, the system is compatible with different models of industrial cameras and integrated navigation modules, and adaptable to various flight platforms and coil structures. The visual recognition and data fusion algorithms can be adjusted or trained according to the complexity of the detection mission to meet the accuracy requirements of different flight environments. The system is lightweight, consumes little power, and is highly robust, making it suitable for long-endurance continuous flight operations. Attached Figure Description

[0062] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0063] Figure 1 This is a schematic diagram of the overall system structure according to an embodiment of the present invention;

[0064] Figure 2 This is a schematic diagram of the installation and spatial arrangement according to an embodiment of the present invention;

[0065] Figure 3 This is a flowchart of the vision and inertial navigation fusion algorithm according to an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram illustrating the calculation of the coil projected area and attitude correction in an embodiment of the present invention;

[0067] Figure 5 This is a schematic diagram illustrating the application scenario of the present invention in actual flight testing, as an embodiment of the present invention. Detailed Implementation

[0068] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0069] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0070] Example 1.

[0071] This invention focuses on the pod coil system in an airborne transient electromagnetic detection system. The coil system typically includes a transmitting coil, a receiving coil, and sometimes a compensation coil. During actual flight detection, the coils experience attitude shifts and elastic deformation due to factors such as airflow disturbances, structural elasticity, and inertial response. This causes the coil's plane to no longer be parallel to the ground, affecting the vertical component of the transmitted magnetic field and the amplitude of the received signal. Traditional methods usually rely on installing inertial navigation modules at multiple coil nodes to estimate attitude. However, this approach suffers from problems such as complex equipment, difficult deployment, and susceptibility to signal interference, making it difficult to accurately reflect the instantaneous state of the coils.

[0072] This embodiment relates to an attitude measurement and data correction auxiliary method for an airborne transient electromagnetic detection system. The invention utilizes a surface-scanning industrial camera mounted on the belly of a helicopter and an industrial-grade integrated navigation module (IMU / INS) mounted on the plane of a flexible transmitting coil to identify attitude changes and deformations of the transmitting coil during flight, and calculate its projected area to the ground for transmitting magnetic moment correction and improving the accuracy of detection data.

[0073] This invention utilizes visual perception and integrated navigation fusion technology to achieve high-precision estimation of the coil's three-dimensional attitude and projection geometry without adding extra hardware. It leverages the pose and time synchronization information provided by a single inertial navigation module, combined with coil images acquired by a camera.

[0074] This embodiment presents a novel method that integrates visual and inertial navigation data. By utilizing attitude, position, and time synchronization information provided by inertial navigation and combining it with coil geometry images acquired by a camera, it achieves comprehensive measurement of the attitude changes, deformation characteristics, and projected area of ​​a flexible coil in the air. This fusion strategy not only reduces the number of hardware deployments and lowers system complexity but also avoids electromagnetic interference problems, providing a reliable foundation for data correction and magnetic moment compensation in aerospace transient electromagnetic systems.

[0075] This embodiment provides a method for correcting the attitude of an aerospace transient electromagnetic pod coil. The method includes the following steps: acquiring image information of the suspended coil in real time using a surface scanning industrial camera; outputting inertial navigation data containing the coil's planar attitude angle, position, and time synchronization signal from an industrial-grade integrated navigation module; performing time unification between the image information and the inertial navigation data; extracting visual features from the coil boundary geometric features of the image after time unification; obtaining the time series of the coil attitude angle through angular velocity integration, and obtaining the inertial navigation state based on the time series of the coil attitude angle; performing fusion calculation of the coil attitude and deformation parameters by combining the visual features and the inertial navigation state; and calculating the coil's ground projection area and effective emitted magnetic moment component based on the fusion calculation results.

[0076] The specific system structure and installation method are as follows: The system structure of this embodiment adopts a dual-source fusion design with a single camera and a single integrated navigation module working in tandem. This aims to achieve high-precision measurement of the attitude, deformation, and ground projection area of ​​the flexible aerial transmitting coil without increasing the hardware burden on the coil or the risk of electromagnetic interference. The system consists of an area-scanning industrial camera module, an industrial-grade integrated navigation module (IMU / INS), a time synchronization and data acquisition unit, and a data processing and fusion computing unit. The area-scanning camera is used to acquire real-time images of the coil's shape, the integrated navigation module provides position, attitude, and time information, and the data acquisition and fusion unit achieves spatiotemporal registration and unified modeling of the two.

[0077] In terms of structural layout, the area-scanning industrial camera is fixedly mounted under the fuselage of the helicopter, with its optical axis pointing towards the center of the transmitting coil suspended below the fuselage. This arrangement allows for continuous observation of the overall outline and deformation state of the coil during flight. The camera's imaging performance should meet the requirements of a resolution of no less than 5 megapixels and a frame rate of no less than 125 Hz to ensure complete capture of boundary information even at high flight speeds or when coil jitter is significant, avoiding image blurring or undersampling. To improve the geometric stability of the system, sufficient redundancy must be allowed within the camera's field of view during installation, ensuring that the coil remains within the effective imaging area within a suspension height range of 50–70 meters.

[0078] The transmitting coil is typically composed of a regular polygonal conductor structure, approximately twenty meters in diameter. Each side is rigid but possesses a degree of elasticity, undergoing deformation under disturbance. The connections between sides are often movable joints. During flight, it is susceptible to complex deformations caused by airflow disturbances and gravity, including roll, pitch, and yaw attitude changes along three axes, as well as edge warping or semi-rigid torsion at polygonal corners. This dynamic deformation directly affects the angle between the coil's plane normal and the ground normal, thus influencing the effective component of the transmitting magnetic moment. This invention utilizes an industrial-grade integrated navigation module installed on the coil's plane to measure the coil's attitude angles (roll, pitch, yaw), three-axis velocities, latitude and longitude, altitude, and UTC synchronization time in real time, forming a high-precision data source for attitude reference and time reference.

[0079] To achieve the unification of visual observation and inertial navigation measurement, this invention establishes the geometric mapping relationship between the camera coordinate system, the inertial navigation coordinate system, and the ground coordinate system. The coordinates of any spatial point in different coordinate systems can be represented by a rigid body transformation model as follows:

[0080] ;

[0081] Among them, P cam P represents the 3D coordinate vector (3×1) of the same point in the camera coordinate system. earth R represents a three-dimensional coordinate vector (3×1) of a point in a ground coordinate system / geographic coordinate system; cam2earth T is a 3×3 rotation matrix from the camera coordinate system to the ground coordinate system, used to describe the attitude relationship between the camera coordinate system and the ground coordinate system; cam2earth Let be the translation vector (3×1) of the camera coordinate system origin in the ground coordinate system, describing the camera's position in the ground coordinate system. The rotation matrix is ​​determined by the attitude angles output by the integrated navigation module, and its expression is:

[0082] ;

[0083] in, θ and ψ represent the roll angle, pitch angle, and yaw angle, respectively. This represents the rotation matrix for rotating about the x-axis by φ. This represents the rotation matrix for rotating about the y-axis by θ. Let ψ be the rotation matrix representing the rotation about the z-axis. Through the above coordinate transformation model, camera imaging data and inertial navigation attitude data can be mapped to a unified spatial reference frame, providing a geometric basis for subsequent visual-inertial data fusion and coil projection area calculation.

[0084] During the installation and calibration phase, after the camera is fixed, imaging calibration and distortion correction must be completed on the ground to ensure image measurement accuracy. The integrated navigation module should be securely mounted on the coil plane structure so that the output attitude data can represent the overall motion state of the coil. Pre-flight static calibration yields the initial extrinsic parameter relationship (R0, T0), which is used as the initial value for dynamic fusion during flight. During flight, visual and inertial navigation data are synchronized using UTC time as a unified reference; the accuracy of timestamp registration directly affects the accuracy of attitude estimation and projected area calculation.

[0085] Furthermore, this invention fully considers the unique characteristics of the transient electromagnetic detection environment in airborne systems during system design. Due to the presence of strong pulsed currents within the transmitting coil, installing multiple inertial navigation modules on polygonal surfaces or nodes would not only increase structural weight and power supply complexity but could also interfere with the electromagnetic field distribution. This invention achieves dual-source data fusion through a single combined navigation module in conjunction with an under-fuselage camera, effectively reducing system integration complexity and electromagnetic interference risks, while ensuring the independence and complementarity of attitude reference and geometric observation.

[0086] Furthermore, the specific implementation of data acquisition and time synchronization is based on the time synchronization and data acquisition module, which is used to establish a unified time mechanism between the camera and the industrial-grade integrated navigation module. The time synchronization and data acquisition module includes: a hardware trigger channel for directly driving camera exposure and inertial navigation data sampling via a unified clock pulse; a software time stamping unit for marking image frames with timestamps; a data caching and matching unit for caching and matching received image frames and inertial navigation data with timestamps; a delay compensation mechanism for real-time monitoring of timestamp deviations and dynamic correction; and a data integrity detection unit for comparing and detecting camera frame sequence numbers and inertial navigation time sequences.

[0087] The specific process includes: The data acquisition and time synchronization module of this invention is a key link in achieving effective fusion of visual and inertial navigation information. Its design goal is to ensure the consistency of the two types of heterogeneous data in both time and spatial dimensions, enabling subsequent fusion algorithms to perform calculations and reconstructions under a strictly aligned time reference. To this end, the system adopts a unified UTC time reference and establishes a high-precision frame-level timestamp registration and data caching mechanism to ensure that the synchronization error between image frames and inertial navigation outputs is controllable within the millisecond range.

[0088] In the typical operating mode of an airborne transient electromagnetic detection system, the area-scanning industrial camera and the industrial-grade integrated navigation module operate independently. The camera acquires images at a fixed frame rate, no less than 125 Hz, which can cover the dynamic characteristics of the coil's attitude changes during flight. The integrated navigation module outputs data such as attitude angle, angular velocity, linear velocity, latitude and longitude, altitude, and UTC timestamp at high frequencies (typically in the 100 Hz range). These two types of data are physically independent. Without time synchronization, attitude information and image information will mismatch, leading to coil shape reconstruction errors.

[0089] To achieve high-precision time consistency, this invention employs a unified time reference—two-way registration strategy. The integrated navigation module serves as the system's master clock source, and its output data includes high-precision UTC time stamps. All camera-acquired image frames are timestamped using this time reference. A synchronization channel is established between the camera and the inertial navigation module via a data acquisition unit. This channel can be implemented through hardware trigger signals or software time stamping. The hardware triggering method directly drives camera exposure and inertial navigation data sampling using a unified clock pulse, suitable for flight measurement missions with extremely high time synchronization accuracy requirements. The software time stamping method relies on a high-precision system clock to timestamp image frames at the acquisition end, suitable for systems with high real-time requirements. This invention supports compatible switching between the two synchronization methods to adapt to different platform and mission requirements.

[0090] During data acquisition, the output data from the camera and inertial navigation module are transmitted to the onboard data processing unit via independent communication links. The onboard unit is responsible for buffering and matching the received image frames and inertial navigation data, using timestamps for nearest-neighbor pairing to form time-series consistent observation data pairs (It, St), where It represents the camera image at time t, and St represents the inertial navigation attitude and position data at the corresponding time. To eliminate the uneven intervals caused by different sampling frequencies, this invention introduces a linear interpolation and inertial navigation integration compensation strategy during registration. That is, attitude angles and position quantities are interpolated between inertial navigation data to make them completely correspond to the image frame time, thereby achieving frame-level synchronization.

[0091] The time-synchronized data is stored in time-series format and transmitted to the ground processing system for subsequent use by the vision-inertial navigation fusion algorithm. Since airborne reconnaissance missions are typically conducted in environments with strong electromagnetic interference and wind disturbances, the system specifically considers a time delay compensation mechanism for the acquisition link. Communication delays, data write delays, and buffer differences between the camera and inertial navigation ends all introduce synchronization errors. This invention monitors and dynamically corrects timestamp deviations in real time at the acquisition end, keeping the time error throughout the entire link within a controllable range, thereby ensuring a one-to-one correspondence between attitude data and image data in the fusion calculation.

[0092] To further improve timing stability, this invention employs a data integrity detection and frame loss re-sampling strategy. The airborne unit compares the camera frame sequence number with the inertial navigation time series. When an abnormal interval or time drift is detected, it can automatically trigger re-registration or data supplementation to avoid subsequent calculation errors caused by attitude-image mismatch. In addition, the system automatically generates a time alignment report after the flight mission, which records the synchronization accuracy, trigger delay, and abnormal frame ratio of each data channel as a basis for data quality assessment.

[0093] Through the above design, this invention establishes a unified time mechanism for the entire process from acquisition to processing, ensuring strict synchronization between camera image data and integrated navigation output under UTC reference. This time synchronization system is a prerequisite for the vision-inertial navigation fusion algorithm, directly determining the accuracy of coil attitude reconstruction and projected area calculation. Its simple structure and strong compatibility allow it to be used in various types of aerospace transient electromagnetic systems, providing a stable timing foundation and traceable synchronization records for subsequent algorithm modules.

[0094] Furthermore, the specific implementation of visual processing and geometric feature extraction is completed based on the visual processing module, which is used to extract the geometric features of the coil boundaries of the image after processing by the time unification mechanism to obtain visual features.

[0095] The visual processing module includes: an image preprocessing unit for performing irradiance equalization, lens distortion correction, and noise suppression operations; a boundary extraction unit for extracting coil contour point sets using a gradient threshold-based edge detection algorithm; a curve fitting unit for fitting closed polygon curves onto the boundary point set using the least squares method; a data quality assessment unit for determining the confidence level of the boundary recognition results; and a feature compensation unit for compensating for missing feature points using temporal proximity interpolation.

[0096] The specific process includes: after completing system installation and time synchronization, the present invention continuously acquires images of the transmitting coil using an area scanning industrial camera, and completes image preprocessing, geometric feature extraction and morphological analysis in the ground data processing stage to extract the two-dimensional projection features of the coil during flight, providing reliable visual input for subsequent attitude fusion and three-dimensional reconstruction.

[0097] An area-scanning industrial camera acquires coil images at a fixed frame rate, with a sampling frequency of no less than 125 Hz, effectively capturing the dynamic deformation of the coil during flight. The raw images acquired by the camera first enter an image preprocessing module, which sequentially performs irradiance equalization, lens distortion correction, and noise suppression operations to restore the true geometric shape of the coil edges. Distortion correction is based on a camera intrinsic parameter model, and its basic form can be expressed as:

[0098] ;

[0099] Among them, (x d ,y d (x) represents the coordinates of the distorted pixel. c ,y c (x) represents the corrected coordinates, k1 represents distortion model parameter 1, k2 represents distortion model parameter 2, k3 represents distortion model parameter 3, and x represents the x-coordinate. d The x-coordinate of a pixel in a distorted image, y d The x-coordinate represents the ordinate of a pixel in a distorted image. c The x-coordinate of the pixel in the corrected image is represented by y. c This represents the ordinate of the pixels in the corrected image. This represents the distortion correction mapping function, determined by camera calibration. This correction model is obtained through static ground calibration and is used to ensure the geometric accuracy of the projection measurements.

[0100] The preprocessed image enters the coil boundary extraction module. Since the transmitting coil appears as a closed polygon or approximately circular structure in the image with high contrast, the edge detection algorithm can reliably identify its outer edge. In specific implementations, this invention can employ a gradient threshold-based Canny algorithm or an adaptive edge enhancement algorithm to extract the coil's contour point set. If the flight environment has a complex background or uneven illumination, a deep learning segmentation model can be introduced to achieve automatic identification of the coil region. The extracted coil boundary point set is represented as follows:

[0101] ;

[0102] Where P represents the set of boundary points of the coil profile, (x i ,y i ) represents the location of the boundary point in the image plane coordinates, i is the boundary point index, and n is the number of boundary points.

[0103] To improve the continuity of geometric representation, this invention uses the least squares method to fit the closed polygon curve on the boundary point set and establishes the topological relationship of the boundary sequence. By sorting the boundary points by polar angle, the sequential description of the closed contour P′={(x1′,y1′),…,(xn′,yn′)} can be obtained. This data structure is the basis for subsequent attitude transformation and projected area calculation.

[0104] At the visual geometry level, the camera imaging model adopts the standard pinhole projection model. Let the spatial point Pcam = [X, Y, Z]. T In the camera coordinate system, the pixel projection position (u,v) in three dimensions can be represented as:

[0105] ;

[0106] Where u is the column coordinate (horizontal) in the pixel coordinate system, v is the row coordinate (vertical) in the pixel coordinate system, K is the camera intrinsic parameter matrix, and R world2cam t world2cam These represent the rotation matrix from the world / ground coordinate system to the camera coordinate system and the translation vector from the world / ground coordinate system to the camera coordinate system, respectively. X is the x-coordinate of the spatial point in the world coordinate system, Y is the y-coordinate of the spatial point in the world coordinate system, and Z is the z-coordinate of the spatial point in the world coordinate system. This projection relationship is used to establish the constraint relationship between the image plane points and the spatial geometry, which is the geometric basis for the fusion of visual and inertial navigation data.

[0107] For each frame of image, this invention jointly calculates the image coordinates of the coil boundary points with the camera pose and extrinsic parameters to recover the two-dimensional projection shape of the coil in the ground coordinate system. Based on the aforementioned coordinate mapping relationship:

[0108] ;

[0109] The boundary points observed by the camera can be transformed from the camera coordinate system to the ground coordinate system. After this transformation, the set of projection points of the coil on the ground plane (Z=0) can be directly used to calculate the area of ​​the closed region. Through a sequence of consecutive frames of images, the dynamic trajectory of the coil's shape changing over time can be obtained, which can be used for subsequent deformation analysis and attitude estimation.

[0110] During implementation, the vision processing module also performs data quality assessment and anomaly detection functions. When the camera captures data due to changes in lighting, motion blur, or partial occlusion, the system will determine the confidence level of the boundary recognition results. If a low-confidence frame is detected, the system will automatically use temporal proximity interpolation to compensate for missing feature points, thereby ensuring the continuity and integrity of the visual data in the time series.

[0111] Furthermore, the specific implementation of inertial navigation data calculation and attitude reference is completed based on the inertial navigation calculation module. The inertial navigation calculation module is used to obtain the time series of coil attitude angles through angular velocity integration, and to obtain the inertial navigation state based on the time series of coil attitude angles.

[0112] The inertial navigation calculation module includes: an angular velocity integration unit, used to update the attitude rotation matrix using the antisymmetric matrix of angular velocity; an attitude angle transformation unit, used to convert the angular velocity components output by the gyroscope into attitude angle change rates; a position correction unit, used to introduce GPS position correction and velocity closed-loop compensation; a coordinate transformation unit, used to map the position of any point on the coil in the body coordinate system to the ground coordinate system; and an attitude smoothing unit, used to smooth the attitude curve using sliding window averaging and low-pass filtering methods.

[0113] The specific process includes: the industrial-grade integrated navigation module (IMU / INS) of this invention is installed on the transmitting coil plane to output the coil's attitude angle, velocity, position, and time information in real time. Inertial navigation data plays two main roles in the vision-inertial navigation fusion algorithm: first, it provides attitude angles and position coordinates to establish an external spatial reference for camera images; second, using angular velocity and linear velocity as input, it predicts the coil's motion state and attitude change trend during flight through integration and rotational propagation equations.

[0114] The inertial navigation module consists of a high-precision three-axis gyroscope and an accelerometer, whose measurement outputs correspond to angular velocity and specific force, respectively. Within a small time step, the coil attitude change can be obtained by integrating the angular velocity. Let time t... k The angular velocity vector is ωk=[ωx,ωy,ωz] T Then its attitude rotation matrix R k The update can be represented as:

[0115] ;

[0116] Among them, R k Let R be the attitude rotation matrix at time k. k+1 Let be the attitude rotation matrix at time k+1, [ωk] be the antisymmetric matrix of angular velocity, Δt be the time interval between adjacent sampling times, and exp(.) denote the matrix exponential mapping. This expression describes the propagation law of attitude in discrete time steps and is the basic form of attitude update in inertial navigation.

[0117] When attitude angles are expressed using Euler angles (roll angle ϕ, pitch angle θ, yaw angle ψ), their differential relationship can be written as:

[0118] ;

[0119] In the formula, Indicates the rate of change of roll angle. Indicates the rate of change of pitch angle. Indicates the rate of change of yaw angle. Represents the angular velocity component about the x-axis. Represents the angular velocity component about the y-axis. This represents the angular velocity component around the z-axis. This formula is used to convert the angular velocity components output by the gyroscope into the attitude angle change rate, and the time series of the attitude angle can be obtained by integration. To suppress accumulated errors, the integrated navigation system introduces GPS position correction and velocity closed-loop compensation during the solution process, resulting in highly stable attitude and position calculation results.

[0120] The inertial navigation system simultaneously outputs the three-dimensional velocity components (VN, VE, VU) of the coil's center of mass and geographical location parameters (latitude and longitude λ, φ, ..., φ, elevation h). These parameters define the absolute orientation of the coil plane in the geographic coordinate system, providing pose constraints for the spatial transformation from camera imaging coordinates to ground coordinates. The overall coordinate transformation relationship can be described by the following equation:

[0121] ;

[0122] Among them, R body2earth Determined by the attitude angles calculated by the inertial navigation system, T represents the rotation matrix (3×3) from the body coordinate system to the ground coordinate system. body2earth Determined by latitude, longitude, and elevation, P represents the translation vector (3×1) of the origin of the body coordinate system in the ground coordinate system. body P represents the coordinate vector (3×1) of a point in the body / vehicle coordinate system. earth This represents the coordinate vector (3×1) of a point in the ground coordinate system. Through this transformation, the position of any point on the coil in the body coordinate system can be mapped to the ground coordinate system, achieving geometric unification of visual and inertial navigation measurement results.

[0123] To ensure data continuity and real-time performance, the inertial navigation system (INS) output is recorded at a high frequency (typically ≥100 Hz) and precisely correlated with camera image frames using UTC timestamps. When INS data is missing or briefly abnormal, the system compensates by linear extrapolation of angular velocity and acceleration from the preceding and following moments, maintaining the temporal continuity of attitude calculation.

[0124] The inertial navigation calculation module of this invention also has an attitude stability assessment mechanism. Because the coil may oscillate violently or partially twist during flight, the attitude angle output by the inertial navigation system will experience high-frequency fluctuations in a short period. The system smooths the attitude curve using a sliding window averaging and low-pass filtering method, ensuring that the attitude input maintains physical continuity during the vision-inertial navigation fusion stage.

[0125] Inertial navigation data plays the role of "spatial reference" in the whole system, including: providing dynamic attitude reference for camera extrinsic parameters so that image coordinates can be accurately projected onto the ground coordinate system; providing real-time attitude angle of the coil plane in three-dimensional space so as to provide directional constraints for the calculation of the ground projection area and effective magnetic moment; and providing time synchronization and position reference so that visual observation and spatial attitude maintain a strict one-to-one correspondence.

[0126] In summary, this invention achieves real-time acquisition and propagation of coil attitude through high-precision inertial navigation calculation, establishing a strict mapping relationship from inertial navigation coordinates to ground coordinates. The output of this module is completely aligned with camera image data in both time and space, providing a stable and reliable attitude reference for subsequent vision-inertial navigation fusion algorithms. This results in high geometric consistency and physical interpretability for coil shape reconstruction and ground projection area calculation.

[0127] Furthermore, the specific implementation of visual-inertial navigation data fusion and attitude joint estimation is completed based on the data fusion and attitude estimation module. The data fusion and attitude estimation module is used to perform fusion calculation of coil attitude and deformation parameters by combining the visual features and the inertial navigation state to obtain the fusion result.

[0128] The data fusion and attitude estimation module includes: a state vector definition unit, used to define a state vector containing coil position, velocity, attitude angle, and deformation parameters; a prediction model unit, used to predict the time evolution of the state vector driven by inertial navigation data; an observation model unit, used to establish nonlinear geometric constraints between visual features and inertial navigation state; a fusion algorithm core, used to achieve multimodal feature fusion using extended Kalman filtering or Transformer structure; and an adaptive weight adjustment unit, used to dynamically adjust the fusion weights of vision and inertial navigation based on data confidence.

[0129] The specific process includes: after completing image preprocessing, geometric feature extraction, and inertial navigation attitude calculation, this invention achieves attitude estimation and deformation recognition of the flexible transmitting coil during flight by jointly modeling visual and inertial navigation information. This fusion process aims to comprehensively utilize the high-frequency attitude and velocity information of inertial navigation and the spatial geometric constraints of vision to obtain the coil's global attitude, ground projection geometry, and deformation trend, providing accurate physical input for subsequent magnetic moment correction.

[0130] This invention employs a multimodal fusion algorithm framework to map two types of heterogeneous observation information to a common state-space model under a unified temporal and spatial reference. The system state vector is defined as:

[0131] ;

[0132] Where, x t p represents the system state vector at time t. t v represents the position vector of the coil center in the ground coordinate system. t Let θt be the velocity vector of the coil center in the ground coordinate system, θt=[ϕt,θt,ψt] be the coil attitude angle vector (roll, pitch, yaw), and s be the velocity vector of the coil center in the ground coordinate system. t Here, is the deformation parameter vector of the coil, used to describe the boundary geometry changes, and t represents the time index. The predictive model for the evolution of this state vector over time is driven by inertial navigation data:

[0133] ;

[0134] Among them, u t For input quantities (including angular velocity and acceleration), w t This refers to process noise, reflecting the uncertainties caused by airflow disturbances and structural elasticity. This represents the state transition function.

[0135] At the observation layer, the vision module provides a set of projection boundary feature points of the coil in the ground coordinate system:

[0136] ;

[0137] These observations and state variables are subject to nonlinear geometric constraints. Based on the camera projection model and attitude transformation relationship:

[0138] ;

[0139] Where h(⋅) represents the projection function from the three-dimensional spatial state to the image plane, and r t This model addresses observation noise. It establishes a correspondence between visual features and inertial navigation states, forming the basis for the joint estimation of observation equations.

[0140] To robustly estimate coil attitude under dynamic flight conditions, this invention employs a fusion algorithm framework based on recursive optimization. The fusion core consists of two parts: an inertial navigation prediction subsystem and a visual correction subsystem.

[0141] The inertial navigation prediction subsystem updates the state variables over time using the attitude propagation equation based on angular velocity and acceleration data to obtain short-term predicted coil attitude and position. The visual correction subsystem then constrains and corrects the inertial navigation predicted attitude based on the coil projection profile observed by the camera, thereby offsetting the cumulative effects of inertial navigation drift and integral error.

[0142] In mathematical implementation, this joint estimation process can employ either Extended Kalman Filtering (EKF) or a deep feature fusion method based on a Transformer structure. For the former, the update equation is:

[0143] ;

[0144] Among them, K t H is the Kalman gain matrix. t Let R be the Jacobian matrix of the observation model at the current estimate. t Let I be the observation noise covariance matrix, and let x be the identity matrix. t|t-1 Let x represent the prior state estimate at time t. t|tP represents the posterior state estimate at time t. t|t-1 Let P represent the prior estimation error covariance matrix. t|t This represents the posterior estimation error covariance matrix. Through this update mechanism, the system dynamically balances the weights of inertial navigation prediction and visual observation at each sampling time, achieving high-precision attitude and position estimation.

[0145] For the deep learning-based implementation, this invention employs a Transformer architecture to construct a multimodal feature fusion model. The visual input consists of feature encoding vectors from coil images, while the inertial navigation input includes sequential information such as attitude angles, angular velocities, velocities, and timestamps. Through a multi-head attention mechanism, the model can capture the coupling relationship between attitude changes and deformation patterns in both the temporal and modal dimensions, achieving joint estimation at the feature level. This structure can adaptively adjust the fusion weights of vision and inertial navigation under different flight conditions, thereby improving the algorithm's robustness and dynamic response capability.

[0146] During the fusion result output stage, this invention can simultaneously obtain the coil's spatial attitude angle, deformation parameters, and ground projection area. The attitude angle is output from θt in the fused state vector, the coil deformation parameters are estimated by st, and the ground projection area is calculated from the projection point set. For each frame of data, the system outputs the coil's attitude matrix Rcoil2earth and the coil plane normal vector ncoil after fusion; subsequently, only the vertical component needs to be taken when calculating the effective magnetic moment.

[0147] To ensure fusion stability, this invention incorporates a data confidence weighting mechanism. When visual observation is affected by environmental interference (such as changes in illumination or partial occlusion), the system automatically reduces the weight of visual features, relying on inertial navigation prediction to maintain attitude continuity. When flight is stable and visual observation is clear, the visual correction weight is increased to offset inertial navigation drift. This adaptive weight adjustment strategy effectively improves the attitude estimation accuracy and robustness of the system under different airflow conditions.

[0148] Furthermore, the specific implementation of calculating the coil projected area and obtaining the effective magnetic moment component is completed based on the projected area and magnetic moment calculation module. The projected area and magnetic moment calculation module is used to calculate the coil's projected area to the ground and the effective emitted magnetic moment component based on the fusion result.

[0149] The projected area and magnetic moment calculation module includes: a projection point set acquisition unit, used to obtain the projection contour point set of the coil boundary in the ground coordinate system; an area calculation unit, used to calculate the projected area using the polygon area calculation formula; a normal angle calculation unit, used to calculate the angle between the coil plane normal vector and the ground normal vector using the vector dot product formula; an effective component acquisition unit, used to calculate the vertical effective component of the emitted magnetic moment based on the projected area and the normal angle; and a data output unit, used to save the coil attitude angle, the projected area to the ground, and the effective magnetic moment component parameters.

[0150] The specific process includes: after obtaining the coil's spatial attitude and deformation parameters after visual-inertial navigation fusion, the present invention further calculates the coil's projected area relative to the ground and its effective emitted magnetic moment component. This process is a key step in achieving physical closed-loop operation of the entire system, directly related to the post-processing and amplitude correction accuracy of airborne transient electromagnetic detection data.

[0151] Ideally, the coil should remain parallel to the ground, with its emitted magnetic moment pointing completely vertically downwards, maximizing the impact of its electromagnetic field on the underground medium. However, in actual flight, the coil is affected by wind disturbances, inertial response, and its own flexible structure, causing its plane to form an angle relative to the ground. In this case, the coil's plane normal vector n... coil With ground normal vector n earth An angle α is formed between the two sides, which reduces the effective vertical component of the emitted magnetic moment, resulting in energy loss and signal deviation. This invention accurately calculates this angle and the resulting change in magnetic moment by fusing attitude calculation and visual morphological information.

[0152] (1) Calculation of the projected area of ​​the coil to the ground.

[0153] Based on the aforementioned visual boundary extraction and pose estimation results, the point set Q={(x) of the coil boundary in the ground coordinate system can be obtained. i ′,y i The point set {i=1,2,…,n} represents the projected profile of the coil on the ground plane (Z=0). Since the coil structure is approximately a closed polygon, its projected area can be calculated using plane geometry formulas:

[0154] ;

[0155] in, This represents the projected area of ​​the coil boundary on the ground plane. This represents the x-coordinate of the i-th projection point in the ground plane coordinate system. This represents the y-coordinate of the i-th projection point in the ground plane coordinate system. This represents the y-coordinate of the (i+1)th projection point. Let x represent the x-coordinate of the (i+1)th projection point, ensuring the closure of the area calculation. This formula is known as the "shoelace formula" for polygon area calculation, and its advantages lie in its simplicity, clear geometric meaning, and insensitivity to errors in the point sequence.

[0156] In practical calculations, to reduce the impact of image noise and pose perturbations, this invention employs a time window smoothing strategy. Specifically, the area of ​​the projection point set over several consecutive frames is calculated, and then the moving average is taken as the steady-state projection area of ​​the current frame.

[0157] ;

[0158] in, Let k represent the smoothed projected area at time t, k represent the frame index within the window, and t represent the current frame index. Let m represent the projected area of ​​the k-th frame, and m be the window length. This method can effectively filter out area fluctuations caused by flight attitude perturbations and improve the stability of area estimation.

[0159] (2) Calculation of the angle between attitude angle and normal.

[0160] The normal vector of the coil plane in the ground coordinate system can be obtained from the attitude matrix R. coil2earth The third column vector is determined as follows:

[0161] ;

[0162] Where, n coil R represents the normal vector of the coil plane in the ground coordinate system. coil2earth The rotation matrix from the coil coordinate system to the ground coordinate system is represented by n, and the surface normal vector is defined as n. earth =[0,0,1] T The angle α between the two can be obtained from the vector dot product formula:

[0163] ;

[0164] Where α represents the angle between the coil plane normal and the ground normal, and n earth Let α represent the ground normal vector, and ||·|| represent the vector L2 norm. This angle reflects the degree of inclination of the coil plane relative to the ground. When the coil is parallel to the ground, α=0 and cosα=1; when the coil experiences attitude deviation, the value of cosα decreases, and the corresponding transmission efficiency decreases.

[0165] (3) Calculation of effective emission magnetic moment components.

[0166] The design magnetic moment of the transmitting coil can be expressed as: .

[0167] Where N is the number of coil turns, I is the transmitting current, S is the coil design area (ideal planar area), and M0 represents the coil design magnetic moment. When the coil attitude changes, the actual vertical effective component acting on the ground is:

[0168] ;

[0169] This expression indicates that the larger the coil tilt angle, the smaller the effective component of the emitted magnetic moment in the vertical direction relative to the ground. Due to the elastic deformation of the coil during flight, its actual area A... real It may not be completely consistent with the design value S. This invention uses the projected area A obtained from the fusion algorithm. proj As the basis for estimating the actual effective area, the corrected result is:

[0170] ;

[0171] In the formula, M eff Indicates the effective magnetic moment (vertical component). The smoothed projected area is represented by α, and cosα represents the vertical projection coefficient caused by attitude tilt. This formula comprehensively considers both coil deformation (area change) and attitude offset (normal angle), and is a precise correction model for the emitted magnetic moment. The calculated Meff can be directly used in the post-processing stage of the probe data to perform amplitude correction on the signal.

[0172] (4) Correction and data output.

[0173] During the data output phase, this invention saves the coil attitude angle, ground projection area, and effective magnetic moment component obtained from the fusion calculation as independent parameters. For each flight time t, the system output is as follows:

[0174] ;

[0175] A proj (t) represents the projected area at time t, α(t) represents the normal angle at time t, and M eff (t) represents the effective magnetic moment component at time t. These results are compiled and quality checked by the ground station after the flight, and ultimately used for attitude correction and magnetic moment compensation calculations of the probe signal. By processing the raw electromagnetic response data according to M... eff Normalization can eliminate signal deviations caused by coil attitude fluctuations and deformations, and improve the comparability of data and the accuracy of inversion.

[0176] (5) Methodological advantages and feasibility.

[0177] The coil projected area and magnetic moment correction method of the present invention has the following characteristics:

[0178] High geometric and physical consistency: All calculations are based on the fused actual attitude and morphology data, avoiding empirical assumptions.

[0179] Real-time and post-processing compatibility: Although data processing is primarily performed on the ground, the method can calculate key parameters in real time, providing a consistent framework for flight monitoring and post-correction.

[0180] Simple and adaptable: The formula depends only on basic geometry and attitude information, and is applicable to different coil sizes, structures and flight platforms.

[0181] like Figure 1 The diagram illustrates the main components of the invention and their interrelationships, including a surface-scanning industrial camera mounted on the fuselage of a helicopter, an industrial-grade integrated navigation module mounted on the plane of the transmitting coil, a synchronization signal module, a local acquisition and storage module, a local main control module, and a remote data processing server. This diagram visually demonstrates the collaborative relationship between visual acquisition and inertial navigation measurement, as well as the data flow. The industrial camera and the attitude measurement module of the integrated navigation system store the data stream locally. The images from the industrial camera and the attitude measurement data are synchronized together via the PPS (Pulse Per Second) of the integrated navigation module. The local main control module is used for the measurement and control of the entire device, ensuring the coordinated operation of all modules, and storing the data in a specific format through a file system. After data acquisition and storage are complete, the remote processing server performs data fusion calculations to obtain the correction parameters corresponding to each time period of the full data stream.

[0182] like Figure 2 The diagram illustrates the relative positions of the helicopter, the suspended pod, and the flexible transmitting coil. The transmitting coil has a polygonal or near-circular structure and is suspended at a height of approximately 30 to 60 meters. An area-array camera is fixed beneath the helicopter's fuselage, with its optical axis pointing towards the center of the coil, covering the entire coil area. An industrial-grade integrated navigation module is mounted on the coil's plane to output the coil's attitude angles, position, and time synchronization signals in real time. This figure reflects the system's installation conditions and observation geometry under actual flight conditions.

[0183] like Figure 3 The diagram illustrates the main steps from data acquisition to result output, including image acquisition and distortion correction, coil boundary extraction, inertial navigation attitude and position data acquisition, time synchronization processing, multimodal feature fusion, and coil attitude and deformation estimation. This flowchart explains the temporal and spatial matching mechanism between the two types of data, as well as the main parameters output by the fusion algorithm.

[0184] like Figure 4 The diagram illustrates the spatial relationship between the transmitting coil in the air and the ground plane, indicating the angle between the coil's plane normal and the ground normal. When the coil experiences attitude deviation, its projected area onto the ground changes accordingly, and the effective transmitting magnetic moment of the vertical component decreases accordingly.

[0185] like Figure 5 The diagram illustrates typical flight conditions at the test range and in the test area. During stable flight, the helicopter's camera continuously acquires images, while the integrated navigation module records attitude and position data in real time. This diagram demonstrates the system's feasibility and data synchronization characteristics under real-world conditions. Reliable data can be obtained through data processing and correction; the diagram identifies the detected target locations, which match the data accurately.

[0186] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An airborne transient electromagnetic bird coil attitude correction system, characterized by, include: A surface scanning industrial camera module is used to acquire image information of the suspension coil in real time; An industrial-grade integrated navigation module is used to output inertial navigation data, including coil plane attitude angles, position, and time synchronization signals. The time synchronization and data acquisition module is used to establish a time unification mechanism between the camera and the industrial-grade integrated navigation module; The visual processing module is used to extract the geometric features of the coil boundaries from the image processed by the time unification mechanism to obtain visual features; The visual processing module includes: an image preprocessing unit for performing irradiance equalization, lens distortion correction, and noise suppression operations; a boundary extraction unit for extracting coil contour point sets using a gradient threshold-based edge detection algorithm; a curve fitting unit for fitting closed polygon curves onto the boundary point sets using the least squares method; a data quality assessment unit for determining the confidence level of the boundary recognition results; and a feature compensation unit for compensating for missing feature points using temporal proximity interpolation. The inertial navigation calculation module is used to obtain the time series of coil attitude angles through angular velocity integration, and to obtain the inertial navigation state based on the time series of coil attitude angles; The data fusion and attitude estimation module is used to combine the visual features and the inertial navigation state to perform fusion calculation of coil attitude and deformation parameters to obtain the fusion result; The projected area and magnetic moment calculation module is used to calculate the coil's projected area to the ground and the effective emitted magnetic moment component based on the fusion result.

2. The airborne TEM bird coil attitude correction system of claim 1, wherein, The time synchronization and data acquisition module includes: The hardware trigger channel is used to directly drive camera exposure and inertial navigation data sampling via a unified clock pulse; A software timestamp unit is used to mark timestamps on image frames; The data caching and matching unit is used to cache and timestamp the received image frames and inertial navigation data. A time delay compensation mechanism is used to monitor timestamp deviations in real time and perform dynamic corrections. The data integrity detection unit is used to compare and detect camera frame numbers and inertial navigation time series.

3. The airborne TEM bird coil attitude correction system of claim 1, wherein, The inertial navigation calculation module includes: An angular velocity integral unit is used to update the attitude rotation matrix using the antisymmetric matrix of the angular velocity. The attitude angle conversion unit is used to convert the angular velocity components output by the gyroscope into the attitude angle change rate. Position correction unit, used to introduce GPS position correction and velocity closed-loop compensation; The coordinate transformation unit is used to map the position of any point on the coil in the body coordinate system to the ground coordinate system; The attitude smoothing unit is used to smooth the attitude curve using sliding window averaging and low-pass filtering.

4. The airborne TEM bird coil attitude correction system of claim 1, wherein, The data fusion and attitude estimation module includes: The state vector definition unit is used to define a state vector that includes coil position, velocity, attitude angle, and deformation parameters; Prediction model unit, used for predicting the time evolution of state vectors driven by inertial navigation data; The observation model unit is used to establish nonlinear geometric constraints between visual features and inertial navigation state; The core of the fusion algorithm is used to achieve multimodal feature fusion using extended Kalman filtering or Transformer structures; An adaptive weight adjustment unit is used to dynamically adjust the fusion weights of vision and inertial navigation based on data confidence.

5. The airborne TEM bird coil attitude correction system of claim 1, wherein, The projected area and magnetic moment calculation module includes: The projection point set acquisition unit is used to obtain the projection contour point set of the coil boundary in the ground coordinate system; Area calculation unit, used to calculate the projected area using the polygon area calculation formula; The normal angle calculation unit is used to calculate the angle between the coil plane normal vector and the ground normal vector using the vector dot product formula; The effective component calculation unit is used to calculate the vertical effective component of the emitted magnetic moment based on the projected area and the included angle of the normal. The data output unit is used to store the coil attitude angle, the projected area to the ground, and the effective magnetic moment component parameters.

6. A method for calibrating the attitude of an airborne transient electromagnetic bird coil, characterized in that, For implementing the system as described in claim 1, the method includes the following steps: Real-time acquisition of image information of suspension coils using a surface scanning industrial camera; The inertial navigation data output by the industrial-grade integrated navigation module includes coil plane attitude angles, position, and time synchronization signals. The image information and the inertial navigation data are synchronized in time. Visual features are obtained by extracting the geometric features of the coil boundaries from the image processed by the time-unified mechanism. The time series of coil attitude angles is obtained by integrating the angular velocity, and the inertial navigation state is obtained based on the time series of coil attitude angles; The coil attitude and deformation parameters are fused and calculated by combining the visual features and the inertial navigation state; and the coil's projected area to the ground and the effective emitted magnetic moment component are calculated based on the fused calculation results.

7. The method of correcting the attitude of an airborne TEM bird coil of claim 6, wherein, The expression for calculating the projected area of ​​the coil on the ground is: ； In the formula, Let k represent the smoothed projected area at time t, k represent the frame index within the window, and t represent the current frame index. Let m represent the projected area of ​​the k-th frame, and m be the window length.

8. The method for correcting the attitude of the coil of an aerospace transient electromagnetic pod according to claim 7, characterized in that, The expression for calculating the effective emitted magnetic moment component is: ； In the formula, Meff represents the effective magnetic moment. denoted by α, cosα represents the vertical projection coefficient caused by attitude tilt, N is the number of coil turns, and I is the emission current.

9. A computer comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method as described in claim 6.

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