An active method and system for suppressing motion noise of an airborne electromagnetic receiving sensor

Abstract

This application belongs to the field of airborne geophysical exploration technology, specifically a method and system for actively suppressing motion noise from an airborne electromagnetic receiving sensor. The receiving coil and the cancelling coil are coaxially and coplanarly mounted on the same carrier structure, with their centers coinciding and their normal directions aligned. The cancelling coil is arranged around the receiving coil. An inertial measurement unit is used to acquire the motion state information of the receiving coil in real time. A signal processing unit is used to obtain the real-time attitude angle and real-time angular velocity of the receiving coil through attitude calculation based on the motion state information. A control unit is used to calculate the compensation current value based on the real-time attitude angle and real-time angular velocity of the receiving coil. A constant current drive unit outputs the compensation current to drive the cancelling coil to generate a compensation magnetic field. This application can suppress motion noise generated by the receiving coil cutting through the geomagnetic field under all operating conditions in real time.

Description

Technical Field

[0001] This application belongs to the field of airborne geophysical exploration technology, specifically a method and system for active suppression of motion noise from airborne electromagnetic receiving sensors. Background Technology

[0002] Airborne transient electromagnetic method (AEEM) is a highly efficient non-contact geophysical exploration technique widely used in mineral resource exploration, groundwater detection, geological structure mapping, and environmental monitoring. Its basic principle involves transmitting a pulsed primary field to the subsurface via an airborne transmitting coil. During the primary field's shutdown period, a receiving coil observes the secondary decaying magnetic field induced by the subsurface medium, thereby inverting the subsurface electrical structure. However, in actual flight operations, factors such as airflow disturbances, flight attitude adjustments, and pod mechanical vibrations cause continuous attitude changes and mechanical vibrations in the receiving coil, resulting in it cutting magnetic field lines and introducing strong motion noise into the received signal. This noise is characterized by a large dynamic range, wide frequency coverage, and strong non-stationarity, and it highly overlaps with the spectrum of late-stage trace signals containing deep geological information, severely reducing the signal-to-noise ratio of the detection data and limiting the detection depth and interpretation accuracy of the airborne electromagnetic system.

[0003] Existing technologies face systemic bottlenecks in the field of airborne electromagnetic motion noise suppression, making it difficult to meet the stringent requirements of deep-earth exploration. These bottlenecks primarily include: most solutions employ passive mechanical vibration reduction or signal post-processing, which not only fail to eliminate noise at its source during the acquisition phase but also suffer from large processing delays and high algorithm complexity, making them unsuitable for the real-time demands of airborne exploration. The compensation architecture generally has defects. Most existing active compensation schemes are open-loop control, lacking a real-time motion state perception and feedback mechanism based on inertial measurement. They cannot adaptively adjust parameters according to changes in operating conditions such as flight attitude and ambient temperature. The compensation accuracy is severely affected by interference and drift, and the robustness is poor. The current technology cannot simultaneously meet the requirements of low-frequency high-current compensation and high-frequency fine adjustment. Therefore, existing airborne electromagnetic detection technologies have technical problems such as the inability to suppress motion noise in real time during the acquisition stage, poor compensation effect for large dynamic non-stationary noise, and easy distortion of effective signals, which directly restrict the detection depth and accuracy of airborne electromagnetic systems. Summary of the Invention

[0004] This application provides a method and system for active noise suppression of airborne electromagnetic receiving sensors, which solves the problems of poor real-time noise suppression, insufficient dynamic range, and low compensation accuracy in the prior art.

[0005] The first aspect of this application provides an active noise suppression system for an airborne electromagnetic receiving sensor, comprising: A receiving coil is used to receive electromagnetic response signals generated by underground targets. A cancellation coil is used to generate a compensation magnetic field to actively cancel the motion noise generated by the receiving coil due to attitude changes. The receiving coil and the cancellation coil are mounted on the same carrier structure in a coaxial and coplanar arrangement, with their centers coinciding and their normal directions being consistent. The cancellation coil is arranged around the receiving coil. An inertial measurement unit is used to acquire the motion state information of the receiving coil in real time; The signal processing unit is used to obtain the real-time attitude angle and real-time angular velocity of the receiving coil through attitude calculation based on the motion state information. The control unit is used to calculate the compensation current value based on the real-time attitude angle and real-time angular velocity of the receiving coil. The constant current drive unit outputs a compensation current to drive the canceling coil to generate a compensation magnetic field.

[0006] Furthermore, the constant current driving unit adopts a two-stage compensation current source structure that combines coarse compensation and fine compensation, including a coarse compensation branch and a fine compensation branch. The output currents of the two branches are superimposed to drive the canceling coil to generate a compensation magnetic field.

[0007] Furthermore, the coarse compensation current provided by the coarse compensation branch is equal to the attitude compensation coefficient multiplied by the real-time attitude angle of the receiving coil, plus the angular velocity compensation coefficient multiplied by the real-time angular velocity of the receiving coil. The fine compensation current provided by the fine compensation branch is equal to the error compensation gain multiplied by the residual motion noise after coarse compensation.

[0008] Furthermore, under the constraints of the electromechanical coupling constraint model, the optimal combination of system parameters is designed, and the structural parameters of the cancellation coil, the time constant of the constant current drive unit, and the control parameters of the initialization control unit are configured according to the optimal combination of system parameters. The control parameters include the initial values ​​of the attitude compensation coefficient, the initial values ​​of the angular velocity compensation coefficient, and the initial values ​​of the error compensation gain. The design process includes: The objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The design variables are the structural parameters of the cancellation coil, the attitude compensation coefficient, the angular velocity compensation coefficient and the error compensation gain, and the time constant of the constant current drive unit, while satisfying the constraints of the electromechanical coupling constraint model. An optimization algorithm is used to iteratively solve the objective function until it converges to the minimum value, thus obtaining the optimal combination of system parameters.

[0009] Furthermore, the electromechanical coupling constraint model includes: The dynamic motion noise is defined as the sum of an attitude modulation term, an angular velocity induced term, and a higher-order perturbation term, wherein the attitude modulation term is adjusted according to a state weight function; The superposition of dynamic motion noise, the compensation magnetic field generated by the cancellation coil, and the residual motion noise after coarse compensation satisfies the system's magnetic field balance relationship. The values ​​of the number of turns and the radius of the cancellation coil are located within the range that makes the structural sensitivity function value less than a preset threshold; The time constant of the constant current drive unit satisfies the constraints of the first-order dynamic differential equation.

[0010] Furthermore, during flight, the control unit compares the real-time collected attitude angle and angular velocity data with the operating condition identification threshold library to determine the current flight operating condition; Based on the sensitivity of the parameters of attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain under the current flight conditions, an adaptive learning rate is selected. With the goal of minimizing the residual motion noise after coarse compensation, a recursive least squares algorithm is used to update the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain in real time according to the selected adaptive learning rate.

[0011] A second aspect of this application provides a method for actively suppressing motion noise of an airborne electromagnetic receiving sensor, employing the active motion noise suppression system for an airborne electromagnetic receiving sensor provided in the first aspect embodiment, comprising: Before flight operations, under the constraints of the electromechanical coupling constraint model, the optimal combination of system parameters is solved. Based on the optimal combination of system parameters, the structural parameters of the cancellation coil, the initial values ​​of the attitude compensation coefficient of the control unit, the initial values ​​of the angular velocity compensation coefficient and the initial values ​​of the error compensation gain, and the time constant of the constant current drive unit are configured. During flight, the real-time attitude angle and real-time angular velocity of the receiving coil are obtained through the inertial measurement unit; The coarse compensation current is calculated based on the real-time attitude angle and real-time angular velocity of the receiving coil, and coarse compensation is performed. Calculate the residual motion noise after coarse compensation; The fine compensation current is obtained by multiplying the error compensation gain by the residual motion noise after coarse compensation. The coarse compensation current and the fine compensation current are superimposed to obtain the final compensation current, which is used to drive the cancellation coil to generate a compensation magnetic field.

[0012] Furthermore, under the constraints of the electromechanical coupling constraint model, the optimal parameter combination of the system is solved, including: The objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The design variables are the structural parameters of the cancellation coil, the attitude compensation coefficient, the angular velocity compensation coefficient and the error compensation gain, and the time constant of the constant current drive unit, while satisfying the constraints of the electromechanical coupling constraint model. An optimization algorithm is used to iteratively solve the objective function until it converges to the minimum value, thus obtaining the optimal combination of system parameters.

[0013] Furthermore, during flight, attitude angle and angular velocity data are collected in real time and compared with the operating condition identification threshold library to determine the current flight operating condition; Based on the sensitivity of the parameters of attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain under the current flight conditions, an adaptive learning rate is selected. With the goal of minimizing the residual motion noise after coarse compensation, a recursive least squares algorithm is used to update the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain in real time according to the selected adaptive learning rate.

[0014] Furthermore, a recursive least squares algorithm is employed to update the attitude compensation coefficients, angular velocity compensation coefficients, and error compensation gain in real time based on the selected adaptive learning rate, including: The attitude compensation coefficients are updated as follows: , in, This represents the attitude compensation coefficient for the next moment. The attitude compensation coefficient at the current moment. The attitude compensation coefficients are adaptive learning rates. The residual motion noise after coarse compensation at the current moment. The attitude angle at the current moment; The update method for the angular velocity compensation coefficient is as follows: , in, This is the angular velocity compensation coefficient for the next moment. The angular velocity compensation coefficient at the current moment. The adaptive learning rate is the angular velocity compensation coefficient. The angular velocity at the current moment; The error compensation gain is updated as follows: , in, The error compensation gain for the next time step. This is the error compensation gain at the current moment. For error compensation gain adaptive learning rate, This represents the residual motion noise after coarse compensation at the previous moment.

[0015] Compared with the prior art, the beneficial effects of this application are as follows: The embodiments of this application can calculate and output compensation current in real time, driving the cancellation coil to generate a compensation magnetic field that is equal in magnitude and opposite in direction to the geomagnetic field. It can suppress motion noise caused by changes in magnetic flux within the receiving coil due to the geomagnetic field and compensation magnetic field during the signal acquisition stage, effectively avoiding saturation of the receiving system, significantly improving the signal-to-noise ratio and geological interpretation accuracy of airborne electromagnetic detection data, and suppressing motion noise generated by the receiving coil cutting the geomagnetic field under all operating conditions in real time. Attached Figure Description

[0016] Figure 1 A structural block diagram of an active noise suppression system for an airborne electromagnetic receiving sensor provided in this application embodiment; Figure 2 This is a structural block diagram of the constant current drive unit provided in the embodiments of this application; Figure 3 This is a flowchart illustrating an active noise suppression method for an airborne electromagnetic receiving sensor, as provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0018] To address the issues of poor real-time performance, insufficient dynamic range, and inability to suppress motion noise at its source in existing airborne electromagnetic detection systems, this application first constructs a coaxial, coplanar integrated receiving-canceling coil system. An inertial measurement unit is integrated to acquire real-time motion state information such as attitude angles and angular velocities of the receiving coil. A compensation current combining coarse and fine compensation currents simultaneously meets the requirements for rapid compensation during large attitude changes and high-precision compensation during stable flight. Under the constraints of an electromechanical coupling model, the optimal combination of system parameters is designed, and the parameters of the coarse and fine compensation currents are updated in real-time during flight. Finally, a closed-loop adaptive control strategy is used to calculate and output the compensation current in real-time, driving the cancelling coil to generate a compensation magnetic field equal in magnitude but opposite in direction to the geomagnetic field within the coil. This suppresses the motion noise generated by the receiving coil cutting through the geomagnetic field by inhibiting the change in magnetic flux of the geomagnetic field within the receiving coil.

[0019] See Figure 1 As shown, this application provides an active noise suppression system for an airborne electromagnetic receiving sensor, comprising: A receiving coil is used to receive electromagnetic response signals generated by underground targets. A cancellation coil is used to generate a compensating magnetic field to actively cancel the motion noise generated by the receiving coil due to attitude changes. The receiving coil and the cancellation coil are mounted coaxially and coplanarly on the same carrier structure, with their centers coinciding and their normal directions aligned. The cancellation coil is positioned around the receiving coil, with its geometric center coinciding with that of the receiving coil. This ensures that the compensating magnetic field is aligned with the induction direction of the receiving coil, improving compensation efficiency and reducing additional magnetic field distortion. Depending on the application requirements, the cancellation coil can be implemented using a single-turn structure, a multi-turn structure, or a segmented structure.

[0020] An inertial measurement unit (IMU) is used to acquire the motion state information of the receiving coil in real time. The IMU can be fixedly mounted on the frame of the receiving coil or on a mounting platform rigidly connected to the receiving coil to ensure that the IMU and the receiving coil have consistent motion characteristics. The IMU includes at least a three-axis accelerometer and a three-axis angular velocity sensor to acquire the acceleration and angular velocity information of the receiving coil during flight in real time. Furthermore, a magnetometer can be integrated to form a nine-axis IMU system to improve attitude calculation accuracy and long-term stability.

[0021] The signal processing unit is used to obtain the real-time attitude angle and real-time angular velocity of the receiving coil through attitude calculation based on the motion state information; the real-time attitude angle of the receiving coil includes roll angle, pitch angle and yaw angle, and the angular velocity and motion rate of change parameters of the receiving coil in each direction are obtained simultaneously.

[0022] The control unit is used to calculate the compensation current value based on the real-time attitude angle and real-time angular velocity of the receiving coil. A constant current drive unit outputs a compensation current to drive the cancellation coil to generate a compensation magnetic field. To ensure that the system has real-time compensation capability, a control unit is connected to the constant current drive unit. The control unit calculates the compensation current value based on the real-time attitude angle and real-time angular velocity of the receiving coil and sends a control command to the constant current drive unit. The constant current drive unit outputs the corresponding compensation current according to the control command to drive the cancellation coil to generate a compensation magnetic field.

[0023] Because the attitude of the receiving coil continuously changes during the operation of the aviation electromagnetic system, the amplitude of motion noise dynamically varies with the attitude angle and angular velocity. When the aircraft is subjected to airflow disturbances or maneuvering, the tilt angle of the receiving coil can change by several degrees or even tens of degrees, resulting in significant motion noise; while during stable flight, the motion noise is at an extremely low level. Therefore, the compensation system needs to have both a large output dynamic range and extremely high current regulation resolution. To this end, the constant current drive unit in this embodiment adopts a two-stage compensation current source structure that combines coarse compensation and fine compensation.

[0024] See Figure 2As shown, the secondary compensation current source includes a coarse compensation branch and a fine compensation branch. The output currents of the two branches are superimposed to drive the cancellation coil to generate a compensation magnetic field. The output relationship is as follows: , In the formula: To ultimately compensate for the current, For coarse compensation current, For precise current compensation.

[0025] The coarse compensation branch rapidly establishes a compensation magnetic field based on the real-time attitude angle of the receiving coil. Its compensation current is directly calculated from the attitude change. The coarse compensation current equals the attitude compensation coefficient multiplied by the real-time attitude angle of the receiving coil, plus the angular velocity compensation coefficient multiplied by the real-time angular velocity of the receiving coil. , In the formula: For the real-time attitude angle of the receiving coil, To receive the real-time angular velocity of the coil, The attitude compensation coefficient is... This is the angular velocity compensation coefficient.

[0026] The coarse compensation branch is mainly responsible for compensating for motion noise caused by large attitude changes, so that the compensation magnetic field can quickly approach the target value.

[0027] To improve compensation accuracy, a fine compensation branch is set up on top of the coarse compensation. The fine compensation branch makes a small correction based on the residual motion noise after coarse compensation, and its fine compensation current is expressed as: , in: The residual motion noise after coarse compensation. This is the error compensation gain. The final compensation current of the cancellation coil. It can be represented as: , The compensation current is output to the cancelling coil via a constant current drive circuit, generating a compensation magnetic field. Based on the magnetic field model of the center of a circular coil, the compensation magnetic field generated by the cancelling coil satisfies: , in: To counteract the compensating magnetic field generated by the coil, The permeability of free space, To offset the number of coil turns, To compensate for the coil radius, For the final compensation current.

[0028] When the receiving coil undergoes an attitude change, the following condition is met: , in: For dynamic motion noise, The number of turns of the receiving coil. For the effective area of ​​the receiving coil, To receive the equivalent geomagnetic field component in the normal direction of the receiving coil, For time.

[0029] For common small-angle vibrations in aerospace electromagnetic systems, the following are examples: , Furthermore, we can obtain: ; In the formula: The intensity of the ambient geomagnetic field.

[0030] Therefore, dynamic motion noise is related to both the real-time attitude angle and real-time angular velocity of the receiving coil, while the compensation magnetic field is related to the final compensation current, the number of coil turns, and the coil size. This can be addressed by adjusting the final compensation current. To compensate the magnetic field satisfy: , This enables real-time active cancellation of motion noise.

[0031] To ensure that the compensation system itself does not introduce additional noise, in one example, the constant current drive unit can use a low-noise reference source, a low-temperature drift precision resistor network, and a closed-loop constant current control structure; at the same time, a combination of analog filtering and digital filtering is used to suppress current ripple, so that the output current noise is lower than the background noise level of the receiving system.

[0032] The active noise suppression system for airborne electromagnetic receiver sensors requires initial system setup, which includes setting the optimal combination of system parameters. This optimal combination includes the structural parameters of the cancellation coil, the initial values ​​of the attitude compensation coefficient, the initial values ​​of the angular velocity compensation coefficient and the error compensation gain, as well as the time constant of the constant current drive unit. The process includes: Under the constraints of the electromechanical coupling constraint model, the objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The design variables are the structural parameters of the cancellation coil, the attitude compensation coefficient, the angular velocity compensation coefficient and the error compensation gain, as well as the time constants of the coarse compensation branch and the fine compensation branch (the time constant of the constant current drive unit), and the constraints of the electromechanical coupling constraint model are satisfied. An optimization algorithm is used to iteratively solve the objective function until it converges to the minimum value, thus obtaining the optimal combination of system parameters.

[0033] The electromechanical coupling constraint model imposes strict feasible region boundaries on design variables during the optimization process, specifically in the following four aspects: Firstly, at the level of noise generation mechanism, the expression for dynamic motion noise is restricted to a superposition of three terms: attitude modulation term multiplied by the state weight function, plus angular velocity induced term multiplied by the state weight function, plus higher-order perturbation term. The dynamic motion noise is thus expressed as: , in, For dynamic motion noise, For attitude modulation term, For the state weight function, This is the angular velocity induced term. For higher-order perturbation terms, This refers to the real-time attitude angles (roll angle, pitch angle, yaw angle) of the receiving coil. To receive the real-time angular acceleration of the coil, This represents the unmodeled disturbance term.

[0034] Attitude modulation term: The change in the projected component of the geomagnetic field caused by the change in the normal direction of the receiving coil, corresponding to... The term is the main source of low-frequency, large-amplitude motion noise; Angular velocity induced term: The rate of change of magnetic flux caused by dynamic rotation, corresponding to... The term is the main source of mid-frequency motion noise; Higher-order disturbance terms: Nonlinear error terms introduced by angular acceleration and structural micro-vibration, including factors such as structural flexible deformation, installation errors and environmental magnetic interference.

[0035] The structural parameters (number of turns and radius of the compensation coil) and control parameters (attitude compensation coefficient, angular velocity compensation coefficient and error compensation gain) in the design variables must ensure that the compensation magnetic field and the dynamic motion noise satisfy the constraint relationship of the expression of the dynamic motion noise; otherwise, the feasible solution is not valid.

[0036] Secondly, at the level of physical laws, the system's magnetic field balance requires that the sum of the compensation magnetic field, the motion noise magnetic field, and the residual motion noise after coarse compensation be strictly zero. The residual motion noise after coarse compensation is further decomposed into four components: the magnetic field spatial distortion caused by the geometric discretization error and manufacturing tolerance of the cancellation coil; the amplitude attenuation and phase lag caused by the non-ideal response of the constant current drive unit; the compensation timing deviation caused by the attitude calculation error and time synchronization error of the inertial measurement unit; and the background magnetic interference introduced by local disturbances in the geomagnetic field and the magnetization effect of the carrier structure. The superposition of these four types of errors constitutes the total error that the fine compensation branch needs to correct.

[0037] Based on the above error decomposition, the electromechanical coupling constraint model is extended as follows: ; In the formula: It is the structural domain coupling mapping function, which represents the magnetic field modulation mapping relationship caused by the attitude angle, corresponding to the coarse compensation branch. item; It is the control domain coupling mapping function, representing the dynamic induction mapping relationship caused by angular velocity, corresponding to the coarse compensation branch. item; It is the error domain coupling mapping function, which represents the comprehensive mapping relationship between error and non-ideal factors, corresponding to the fine compensation branch. item.

[0038] Thirdly, at the structural parameter constraint level, the structural sensitivity function maps the changes in the number of turns and radius of the cancellation coil to the deviation of the compensation magnetic field distribution uniformity index. During optimization, it is necessary to ensure that the values ​​of the number of turns and radius of the cancellation coil are within an interval that makes the structural sensitivity function value less than a preset threshold, thereby ensuring that the manufacturing tolerances of the structural parameters do not lead to severe distortion of the compensation magnetic field. Define the structural sensitivity function: , In the formula To compensate for the uniformity index of magnetic field distribution, To offset the number of coil turns, To compensate for the coil radius, For structural sensitivity.

[0039] Fourth, at the dynamic response constraint level, the time constants of the coarse compensation branch and the fine compensation branch must satisfy their respective first-order dynamic differential equation constraints. At the same time, the total equivalent time constant of the system is constrained by the bandwidth limitation of the current source, the delay of the control algorithm and the delay of data transmission. When optimizing the solution, it is necessary to ensure that the combination of time constants in the design variables does not exceed the physical realizable range of the system.

[0040] Constraints of first-order dynamic differential equations: , In the formula: The time constant of the coarse compensation branch is usually small to ensure fast response; The time constant of the fine compensation branch is usually large to ensure high accuracy.

[0041] It should be noted that the constraints of the first-order dynamic differential equation do not contradict the coarse compensation current calculation formula and the fine compensation current calculation formula. The coarse compensation current calculation formula is as follows: , Formula for calculating precise compensation current: , During each control cycle in flight, the control unit directly uses the coarse compensation current calculation formula and the fine compensation current calculation formula to calculate the target value.

[0042] The first-order dynamic differential equation constraint ensures that the actual output current of the constant current drive unit cannot instantly jump to the target value, but rather gradually approaches the target value exponentially from the current value. The speed of this approximation process is determined by the time constants of the coarse compensation branch and the fine compensation branch. Therefore, in the system optimization design phase before flight operations, the first-order dynamic differential equation constraint participates in solving the optimal parameter combination of the system under the constraints of the electromechanical coupling constraint model.

[0043] Based on the constraints of the electromechanical coupling constraint model described above, the objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The objective function is: , in, The dynamic motion noise is equal to the product of the attitude modulation term and the state weight function, plus the angular velocity induced term and the higher-order disturbance term. Specifically, the attitude modulation term is converted into a structural domain coupling mapping function, the angular velocity induced term into a control domain coupling mapping function, and the system integrated error field into an error domain coupling mapping function. The state weight function automatically switches values ​​as flight conditions change.

[0044] This represents the compensating magnetic field generated by the cancellation coil. In the electromechanical coupling constraint model, the compensating magnetic field is composed of the superposition of a coarse compensating magnetic field and a fine compensating magnetic field.

[0045] This represents the residual motion noise after coarse compensation.

[0046] This represents the attitude angle vector of the given receiving coil. and angular velocity vector Under these conditions, the statistical average of the squared residual noise is taken for all possible flight state samples.

[0047] The objective function operates on design variables, namely the number and radius of the compensation coil, attitude compensation coefficient, angular velocity compensation coefficient, error compensation gain, and the time constants of the coarse and fine compensation branches. The optimization algorithm changes the objective function value by adjusting the values ​​of the design variables. The objective function value provides feedback to guide the search direction, and the two iterate repeatedly until convergence to the optimal solution. The quality of the design variables is entirely judged by the level of the objective function value; the objective function value is the sole evaluation criterion throughout the entire optimization process.

[0048] The optimization algorithm can be a sequential quadratic programming algorithm, a hierarchical optimization algorithm, or a genetic algorithm, etc., and there are no restrictions here.

[0049] For example, using a sequential quadratic programming algorithm for iterative solution: In each iteration, the objective function is approximated as a quadratic function at the current iteration point, and the constraints are approximated as linear constraints to construct a quadratic programming subproblem. Solving the subproblem yields the search direction. A one-dimensional line search is performed along the search direction to determine the optimal step size, and then the design variables are updated. The new design variables are substituted into the electromechanical coupling constraint model for feasibility verification. The above process is repeated until the gradient norm of the objective function, the change in design variables, and the amount of constraint violation are all less than the preset tolerance, at which point the algorithm is determined to have converged to the optimal solution.

[0050] Configure the structural parameters of the cancellation coil according to the optimal combination of system parameters, and initialize the control unit according to the initial values ​​of attitude compensation coefficient, angular velocity compensation coefficient and error compensation gain. Configure the time constant of the constant current drive unit using the time constant of the coarse compensation branch and the time constant of the fine compensation branch.

[0051] In one embodiment, the state weight function is a quantitative coefficient characterizing the contribution of each noise generation mechanism to the total motion noise under different flight conditions. In three typical flight conditions—stable cruise, airflow disturbance, and maneuvering flight—the relative contribution ratio of the attitude modulation term to the total motion noise is different. By assigning different values ​​to the state weight function, the same noise model can automatically adjust the superposition ratio of each noise component under different conditions, thereby achieving adaptive matching to the actual noise composition.

[0052] Before flight operations, based on historical attitude angle and angular velocity data collected from one or more complete flight tests, a state weighting function is obtained through condition classification and statistical analysis. In one example, the process includes: Historical data acquisition: Attitude angle and angular velocity data are continuously acquired throughout the entire flight cycle via the inertial measurement unit. The sampling frequency should be no less than twice the main frequency component of the receiving coil's motion noise to ensure that high-frequency details of attitude changes can be captured. The real-time attitude angle and real-time angular velocity of the receiving coil at each sampling moment are recorded to form a complete attitude-time series.

[0053] The continuously acquired attitude angle and angular velocity time series are arranged in chronological order. A short-time sliding window method is used to calculate the local statistical characteristics at each moment, including the root mean square value of the attitude angle, the root mean square value of the angular velocity, and the power spectral density distribution characteristics of the angular velocity within the window.

[0054] Based on the aforementioned local statistical characteristics, the operating condition type is labeled for each moment according to a preset operating condition discrimination criterion. Specifically, the discrimination rules are as follows: when the root mean square value of angular velocity exceeds a preset high-speed threshold and the root mean square value of attitude angle exceeds a preset large-angle threshold, it is labeled as a maneuvering flight segment; when the root mean square value of angular velocity exceeds a preset disturbance threshold but does not exceed a high-speed threshold, and the proportion of low-frequency components in the power spectral density exceeds a preset ratio, it is labeled as an airflow disturbance segment; when the root mean square value of angular velocity does not exceed a preset disturbance threshold and the root mean square value of attitude angle does not exceed a preset small-angle threshold, it is labeled as a stable cruise segment. Continuous samples of the same type of operating condition are merged into a single segment to obtain a set of time segments corresponding to each operating condition.

[0055] Statistical calculations were performed on the three types of labeled operating condition samples: the statistical variance of attitude angles, the statistical variance of angular velocity, and the probability distribution functions and power spectral density distributions of the two variances were calculated for each type of operating condition. Statistical variance is a core indicator for measuring the dispersion of attitude changes, reflecting the severity of noise generation under that operating condition. The statistical variance of attitude angles is equal to the sum of the squares of the differences between the attitude angles at all sampling times and the mean attitude angles, divided by the total number of sampling points. The mean attitude angle is equal to the algebraic sum of the attitude angles at all sampling times, divided by the total number of sampling points; the statistical variance of angular velocity is equal to the sum of the squares of the differences between the angular velocities at all sampling times and the mean angular velocity, divided by the total number of sampling points.

[0056] The state weighting function is assigned a value based on the contribution of the attitude modulation term to the total motion noise under different operating conditions. The attitude modulation term arises from the change in the geomagnetic field projection component caused by the change in the normal direction of the receiving coil. During the maneuvering flight phase, the attitude angle of the receiving coil deflects significantly, making the attitude modulation term the main source of low-frequency, high-amplitude motion noise. During the stable cruise phase, the attitude angle change is minimal, and the contribution of the attitude modulation term is extremely low. Therefore, the state weighting function needs to quantitatively reflect the significant differences in the contribution of the attitude modulation term under different operating conditions.

[0057] In one example, the calculation method can be: The statistical variance of attitude angles is used as an estimate of the contribution magnitude of the attitude modulation term, and the statistical variance of angular velocity is used as a reference benchmark to calculate the relative contribution ratio of the attitude modulation term under the corresponding operating condition. Specifically, the relative contribution ratio of the attitude modulation term is equal to the statistical variance of attitude angles divided by the sum of the statistical variances of attitude angles and angular velocity. This ratio is the value of the state weight function corresponding to the attitude modulation term under the corresponding operating condition.

[0058] In one embodiment, during flight, the control unit performs closed-loop adaptive parameter adjustment, constructing a closed-loop negative feedback control loop aimed at minimizing the residual motion noise after coarse compensation. A recursive least squares algorithm is used to update the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain in real time. The adaptive learning rate is dynamically adjusted based on the parameter sensitivity of the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain under the current flight conditions. The formula for real-time updating the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain using the recursive least squares algorithm is as follows: The attitude compensation coefficients are updated as follows: , in, This represents the attitude compensation coefficient for the next moment. The attitude compensation coefficient at the current moment. The attitude compensation coefficients are adaptive learning rates. The residual motion noise after coarse compensation at the current moment. The attitude angle at the current moment; The update method for the angular velocity compensation coefficient is as follows: , in, This is the angular velocity compensation coefficient for the next moment. The angular velocity compensation coefficient at the current moment. The adaptive learning rate is the angular velocity compensation coefficient. The angular velocity at the current moment; The error compensation gain is updated as follows: , in, The error compensation gain for the next time step. This is the error compensation gain at the current moment. For error compensation gain adaptive learning rate, This represents the residual motion noise after coarse compensation at the previous moment.

[0059] Here, parameter sensitivity is used to represent the different sensitivity characteristics of attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain to the mean square value (system performance) of the residual motion noise after coarse compensation under different flight conditions. Parameter sensitivity is defined as the partial derivative of the mean square value of the residual motion noise after coarse compensation with respect to a certain control parameter. When the sensitivity of a parameter is high, it means that the parameter value must be precise. Even a small deviation in the parameter value will significantly worsen the mean square value of the residual motion noise after coarse compensation. When the sensitivity of a parameter is low, it means that the mean square value of the residual motion noise after coarse compensation does not change much within a certain range.

[0060] For example, during maneuvering flight, the attitude angle amplitude reaches several degrees or even tens of degrees, and the attitude modulation term becomes the dominant source of motion noise. At this point, even a small change in the attitude compensation coefficient will significantly alter the effectiveness of the coarse compensation magnetic field in canceling attitude modulation noise; therefore, the attitude compensation coefficient has the highest parameter sensitivity to system performance. The angular velocity compensation coefficient has the next highest parameter sensitivity because the angular velocity-induced term still contributes to some extent under this condition, but less so than the attitude modulation term. The error compensation gain has the lowest parameter sensitivity because the coarse compensation branch already undertakes the majority of the cancellation task, and the fine compensation branch only plays a secondary correction role.

[0061] During the airflow disturbance phase: angular velocity increases significantly, and the angular velocity-induced term becomes the main source of motion noise. At this point, the angular velocity compensation coefficient has the highest sensitivity, followed by the attitude compensation coefficient, and the error compensation gain has the lowest sensitivity.

[0062] During the stable cruise phase: both attitude angle and angular velocity are at low levels, and the amplitudes of all three types of noise components are small. At this time, the parameter sensitivity of the three control parameters is significantly reduced, but the relative parameter sensitivity of the error compensation gain is slightly higher than the other two, because the output of the coarse compensation branch is small under this condition, and the fine compensation branch undertakes the main residual correction task.

[0063] In one example, during the maneuvering flight phase, the attitude compensation coefficient has the highest parameter sensitivity and its adaptive learning rate is at its maximum value, while the angular velocity compensation coefficient has a medium adaptive learning rate and the error compensation gain has a minimum adaptive learning rate. During the airflow disturbance phase, the angular velocity compensation coefficient has the highest parameter sensitivity and its adaptive learning rate is at its maximum value, while the attitude compensation coefficient has a medium adaptive learning rate and the error compensation gain has a minimum adaptive learning rate. During the stable cruise phase, the parameter sensitivity of all three types of parameters decreases, and all three adaptive learning rates are small. Among them, the relative parameter sensitivity of the error compensation gain is slightly higher than that of the other two, and its adaptive learning rate is slightly higher than that of the attitude compensation coefficient and the angular velocity compensation coefficient. During stable operation under a certain working condition, as the compensation coefficient gradually approaches the optimal value, the corresponding adaptive learning rate adopts a decay strategy to gradually reduce from an initial large value to a smaller value, achieving a smooth transition from rapid convergence to fine-tuning.

[0064] The system evaluates the compensation effect online by calculating the signal-to-noise ratio and noise suppression ratio before and after compensation in real time; when an abnormal decrease in the compensation effect is detected, the system automatically triggers the abnormal handling mechanism. The anomaly handling mechanism includes: pausing adaptive parameter adjustment and restoring to the initial optimal parameters; the control unit immediately stops the parameter update process of the recursive least squares algorithm and restores the current attitude compensation coefficient, angular velocity compensation coefficient and error compensation gain to the system's optimal parameter combination initialized before the flight operation.

[0065] The operating condition is re-identified to determine if an extreme flight condition has occurred. The control unit re-reads the real-time attitude angle and real-time angular velocity of the receiving coil at the current moment and compares them with the operating condition identification threshold library to determine whether the current flight state belongs to one of the three typical operating conditions: stable cruise segment, airflow disturbance segment, or maneuvering flight segment.

[0066] If the current operating condition identification result exceeds the discrimination threshold range of the three typical operating conditions in the operating condition identification threshold library, that is, the attitude angle amplitude or angular velocity amplitude exceeds the preset maximum threshold, it is determined to be an extreme flight condition. At this time, the system does not execute the subsequent fault diagnosis process, maintains the initial optimal parameters, and waits for the flight state to recover to the typical operating condition range before restarting the adaptive adjustment process.

[0067] If the current operating condition is still within the range of the three typical operating conditions, but the compensation effect still drops abnormally, it is determined that the system may have a hardware or software fault, and the next step of the fault diagnosis process will be initiated.

[0068] Perform fault diagnosis on the inertial measurement unit and receiving coil signals; if the fault is eliminated, restart the adaptive parameter adjustment process.

[0069] See Figure 3 As shown, based on the above-described active noise suppression system for airborne electromagnetic receiving sensors, this application also provides a method for active noise suppression of airborne electromagnetic receiving sensors, comprising: S101, before flight operations, under the constraints of the electromechanical coupling constraint model, solve for the optimal combination of system parameters, and configure the structural parameters of the cancellation coil, the initial values ​​of the attitude compensation coefficient, the initial values ​​of the angular velocity compensation coefficient and the initial values ​​of the error compensation gain of the control system, and the time constant of the constant current drive unit according to the optimal combination of system parameters. S102, during flight, the motion state information of the receiving coil's real-time attitude angle and real-time angular velocity is obtained in real time through the inertial measurement unit; S103, calculate the coarse compensation current based on the real-time attitude angle and real-time angular velocity of the receiving coil, and perform coarse compensation; S104, Calculate the residual motion noise after coarse compensation; S105, calculate the product of the error compensation gain and the residual motion noise after coarse compensation to obtain the fine compensation current; S106 combines the coarse compensation current and the fine compensation current to obtain the final compensation current, which is used to drive the cancellation coil to generate a compensation magnetic field.

[0070] In one embodiment, in the electromechanical coupling constraint model, the attitude change of the receiving coil during flight is regarded as a multi-degree-of-freedom random disturbance process. Based on the collected historical motion data, statistical analysis is performed to divide the flight state into three typical operating conditions: stable cruise, airflow disturbance, and maneuvering flight, and corresponding state weight functions are established for each. The state weight function is used to quantitatively characterize the degree of influence of different operating conditions on the contribution of motion noise, and its value is determined based on the statistical variance of attitude angles and angular velocity.

[0071] Under the constraints of the electromechanical coupling model, the optimization objective is to minimize the mean square value of the residual motion noise after coarse compensation. A sequential quadratic programming algorithm or a hierarchical optimization algorithm is used for iterative solution to obtain the optimal parameter combination of the system. The optimal parameter combination includes the structural parameters of the cancellation coil (number of turns and radius), the initial attitude compensation coefficient, initial angular velocity compensation coefficient, and initial error compensation gain of the control unit, as well as the time constants of the coarse compensation branch and the fine compensation branch in the constant current drive unit.

[0072] The system initialization configuration is completed based on the optimal combination of system parameters obtained from the solution: the optimal number of turns and radius of the cancellation coil are fixed as hardware design parameters for the fabrication of the cancellation coil; the time constants of the optimal coarse compensation branch and fine compensation branch are configured into the secondary compensation current source of the constant current drive unit to limit the dynamic response characteristics of the constant current drive unit; the optimal initial attitude compensation coefficient, the optimal initial angular velocity compensation coefficient, and the optimal initial error compensation gain are written into the control unit as the starting point for closed-loop adaptive adjustment; a condition identification threshold library containing three types of typical flight condition discrimination thresholds and corresponding state weight function values ​​is established and stored in the control unit.

[0073] During flight, the inertial measurement unit (IMU) mounted on the receiver coil frame collects the motion state information of the receiver coil in real time at a fixed sampling frequency, including three-axis attitude angles (roll, pitch, and yaw) and three-axis angular velocities. At the beginning of each control cycle, the IMU outputs the real-time attitude angles and real-time angular velocities of the receiver coil to the control unit.

[0074] In one example, after receiving real-time attitude angle and angular velocity data from the receiving coil, the control unit first calculates the combined amplitude of the attitude angle and the combined amplitude of the angular velocity, and compares them with the three typical flight condition discrimination thresholds stored in the condition identification threshold library. When the combined amplitude of the attitude angle exceeds the preset large angle threshold and the combined amplitude of the angular velocity exceeds the preset high speed threshold, it is determined to be a maneuvering flight segment; when the combined amplitude of the attitude angle does not exceed the preset large angle threshold but the combined amplitude of the angular velocity exceeds the preset disturbance threshold, it is determined to be an airflow disturbance segment; when the combined amplitude of the attitude angle does not exceed the preset small angle threshold and the combined amplitude of the angular velocity does not exceed the preset disturbance threshold, it is determined to be a stable cruise segment.

[0075] The control unit calculates the target value of the coarse compensation current based on the real-time attitude angle and angular velocity data of the receiving coil. The coarse compensation current equals the attitude compensation coefficient multiplied by the real-time receiving coil attitude angle, plus the angular velocity compensation coefficient multiplied by the real-time receiving coil angular velocity. This calculation is a non-differential, non-iterative algebraic operation, completed instantaneously within each control cycle to ensure real-time performance. The control unit converts the calculated target value of the coarse compensation current into an analog voltage signal via a digital-to-analog converter and outputs it to the coarse compensation branch of the constant current drive unit, driving the cancellation coil to generate a coarse compensation magnetic field. The coarse compensation magnetic field feeds forward to cancel the main motion noise components generated by the receiving coil due to changes in the geomagnetic field projection component and the dynamic rotating magnetic flux change rate.

[0076] The control unit calculates the fine compensation current according to the formula: the fine compensation current equals the error compensation gain multiplied by the residual motion noise after coarse compensation. The control unit converts the target value of the fine compensation current into an analog voltage signal via a digital-to-analog converter and outputs it to the fine compensation branch of the constant current drive unit. This drives the cancellation coil to generate a fine compensation magnetic field, which slightly corrects the residual error component after coarse compensation. The residual motion noise after coarse compensation is an actual measured value, originating from the induced signal of the receiving coil, rather than a theoretically calculated value.

[0077] During the compensation process, the control unit takes minimizing the residual motion noise after coarse compensation as the objective function and uses a recursive least squares algorithm to update the attitude compensation coefficient, angular velocity compensation coefficient and error compensation gain in real time.

[0078] The attitude compensation coefficient is updated as follows: the attitude compensation coefficient at the next moment is equal to the attitude compensation coefficient at the current moment plus the attitude compensation coefficient, the adaptive learning rate multiplied by the residual motion noise after coarse compensation at the current moment, and then multiplied by the attitude angle at the current moment.

[0079] The update method for the angular velocity compensation coefficient is as follows: the angular velocity compensation coefficient at the next moment is equal to the angular velocity compensation coefficient at the current moment plus the angular velocity compensation coefficient, the adaptive learning rate multiplied by the residual motion noise after coarse compensation at the current moment, and then multiplied by the angular velocity at the current moment.

[0080] The error compensation gain is updated as follows: the error compensation gain at the next time step is equal to the error compensation gain at the current time step plus the error compensation gain adaptive learning rate multiplied by the residual motion noise after coarse compensation at the current time step, and then multiplied by the residual motion noise after coarse compensation at the previous time step.

[0081] The values ​​of the three adaptive learning rates are dynamically adjusted based on the current flight condition type and parameter sensitivity analysis results. Specifically: during maneuvering flight, the attitude compensation coefficient has the highest parameter sensitivity, so its adaptive learning rate is set to the maximum value; the angular velocity compensation coefficient has a medium adaptive learning rate; and the error compensation gain has the minimum adaptive learning rate. During airflow disturbance, the angular velocity compensation coefficient has the highest parameter sensitivity, so its adaptive learning rate is set to the maximum value; the attitude compensation coefficient has a medium adaptive learning rate; and the error compensation gain has the minimum adaptive learning rate. During stable cruise, the parameter sensitivity of all three types of parameters decreases, and all three learning rates are set to smaller values, with the error compensation gain's adaptive learning rate being slightly higher than the other two. When the flight condition identification result changes, the three adaptive learning rates switch synchronously and gradually decay to a smaller value after the flight condition stabilizes.

[0082] During the compensation process, the control unit calculates the signal-to-noise ratio and noise suppression ratio of the signal before and after compensation in real time, and evaluates the compensation effect online. When an abnormal decrease in the compensation effect is detected, the system automatically triggers the abnormal handling mechanism: first, it suspends the adaptive parameter adjustment and restores the three compensation coefficients to the optimal parameter combination initialized before the flight operation; second, it re-identifies the operating conditions to determine whether extreme flight conditions exceeding the range of the three typical operating conditions have occurred. If it is an extreme operating condition, it maintains the initial parameter operation and waits for the flight state to recover; if it is not an extreme operating condition, it performs fault diagnosis on the inertial measurement unit and the receiving coil signal; after the fault is cleared, it restarts the adaptive parameter adjustment process.

[0083] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An active noise suppression system for an airborne electromagnetic receiving sensor, characterized in that, include: A receiving coil is used to receive electromagnetic response signals generated by underground targets. A cancellation coil is used to generate a compensation magnetic field to actively cancel the motion noise generated by the receiving coil due to attitude changes. The receiving coil and the cancellation coil are mounted on the same carrier structure in a coaxial and coplanar arrangement, with their centers coinciding and their normal directions being consistent. The cancellation coil is arranged around the receiving coil. An inertial measurement unit is used to acquire the motion state information of the receiving coil in real time; The signal processing unit is used to obtain the real-time attitude angle and real-time angular velocity of the receiving coil through attitude calculation based on the motion state information. The control unit is used to calculate the compensation current value based on the real-time attitude angle and real-time angular velocity of the receiving coil. The constant current drive unit outputs a compensation current to drive the canceling coil to generate a compensation magnetic field.

2. The active noise suppression system for an aviation electromagnetic receiving sensor according to claim 1, characterized in that, The constant current drive unit adopts a two-stage compensation current source structure that combines coarse compensation and fine compensation, including a coarse compensation branch and a fine compensation branch. The output currents of the two branches are superimposed to drive the cancellation coil to generate a compensation magnetic field.

3. The active noise suppression system for an aviation electromagnetic receiving sensor according to claim 2, characterized in that, The coarse compensation current provided by the coarse compensation branch is equal to the attitude compensation coefficient multiplied by the real-time attitude angle of the receiving coil, plus the angular velocity compensation coefficient multiplied by the real-time angular velocity of the receiving coil. The fine compensation current provided by the fine compensation branch is equal to the error compensation gain multiplied by the residual motion noise after coarse compensation.

4. The active noise suppression system for an aviation electromagnetic receiving sensor according to claim 3, characterized in that, Under the constraints of the electromechanical coupling constraint model, the optimal combination of system parameters is designed, and the structural parameters of the cancellation coil, the time constant of the constant current drive unit, and the control parameters of the initialization control unit are configured according to the optimal combination of system parameters. The control parameters include the initial values ​​of the attitude compensation coefficient, the initial values ​​of the angular velocity compensation coefficient, and the initial values ​​of the error compensation gain. The design process includes: The objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The design variables are the structural parameters of the cancellation coil, the attitude compensation coefficient, the angular velocity compensation coefficient and the error compensation gain, and the time constant of the constant current drive unit, while satisfying the constraints of the electromechanical coupling constraint model. An optimization algorithm is used to iteratively solve the objective function until it converges to the minimum value, thus obtaining the optimal combination of system parameters.

5. The active noise suppression system for an aviation electromagnetic receiving sensor according to claim 4, characterized in that, The electromechanical coupling constraint model includes: The dynamic motion noise is defined as the sum of an attitude modulation term, an angular velocity induced term, and a higher-order perturbation term, wherein the attitude modulation term is adjusted according to a state weight function; The superposition of dynamic motion noise, the compensation magnetic field generated by the cancellation coil, and the residual motion noise after coarse compensation satisfies the system's magnetic field balance relationship. The values ​​of the number of turns and the radius of the cancellation coil are located within the range that makes the structural sensitivity function value less than a preset threshold; The time constant of the constant current drive unit satisfies the constraints of the first-order dynamic differential equation.

6. The active noise suppression system for an aviation electromagnetic receiving sensor according to claim 3, characterized in that, During flight, the control unit compares the real-time collected attitude angle and angular velocity data with the operating condition identification threshold database to determine the current flight operating condition; Based on the sensitivity of the parameters of attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain under the current flight conditions, an adaptive learning rate is selected. With the goal of minimizing the residual motion noise after coarse compensation, a recursive least squares algorithm is used to update the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain in real time according to the selected adaptive learning rate.

7. A method for actively suppressing motion noise of an airborne electromagnetic receiving sensor, employing the active motion noise suppression system for an airborne electromagnetic receiving sensor as described in any one of claims 1-6, characterized in that, include: Before flight operations, under the constraints of the electromechanical coupling constraint model, the optimal combination of system parameters is solved. Based on the optimal combination of system parameters, the structural parameters of the cancellation coil, the initial values ​​of the attitude compensation coefficient of the control unit, the initial values ​​of the angular velocity compensation coefficient and the initial values ​​of the error compensation gain, and the time constant of the constant current drive unit are configured. During flight, the real-time attitude angle and real-time angular velocity of the receiving coil are obtained through the inertial measurement unit; The coarse compensation current is calculated based on the real-time attitude angle and real-time angular velocity of the receiving coil, and coarse compensation is performed. Calculate the residual motion noise after coarse compensation; The fine compensation current is obtained by multiplying the error compensation gain by the residual motion noise after coarse compensation. The coarse compensation current and the fine compensation current are superimposed to obtain the final compensation current, which is used to drive the cancellation coil to generate a compensation magnetic field.

8. The method for actively suppressing motion noise of an airborne electromagnetic receiving sensor according to claim 7, characterized in that, Under the constraints of the electromechanical coupling constraint model, the optimal parameter combination of the system is solved, including: The objective function is to minimize the mean square value of the residual motion noise after coarse compensation. The design variables are the structural parameters of the cancellation coil, the attitude compensation coefficient, the angular velocity compensation coefficient and the error compensation gain, and the time constant of the constant current drive unit, while satisfying the constraints of the electromechanical coupling constraint model. An optimization algorithm is used to iteratively solve the objective function until it converges to the minimum value, thus obtaining the optimal combination of system parameters.

9. The method for actively suppressing motion noise of an airborne electromagnetic receiving sensor according to claim 7, characterized in that, During flight, attitude angle and angular velocity data are collected in real time and compared with the operating condition identification threshold library to determine the current flight operating condition; Based on the sensitivity of the parameters of attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain under the current flight conditions, an adaptive learning rate is selected. With the goal of minimizing the residual motion noise after coarse compensation, a recursive least squares algorithm is used to update the attitude compensation coefficient, angular velocity compensation coefficient, and error compensation gain in real time according to the selected adaptive learning rate.

10. The method for actively suppressing motion noise of an airborne electromagnetic receiving sensor according to claim 9, characterized in that, The recursive least squares algorithm is used to update the attitude compensation coefficients, angular velocity compensation coefficients, and error compensation gain in real time based on the selected adaptive learning rate, including: The attitude compensation coefficients are updated as follows: ， in, This represents the attitude compensation coefficient for the next moment. The attitude compensation coefficient at the current moment. The attitude compensation coefficients are adaptive learning rates. The residual motion noise after coarse compensation at the current moment. The attitude angle at the current moment; The update method for the angular velocity compensation coefficient is as follows: ， in, This is the angular velocity compensation coefficient for the next moment. The angular velocity compensation coefficient at the current moment. The adaptive learning rate is the angular velocity compensation coefficient. The angular velocity at the current moment; The error compensation gain is updated as follows: ， in, The error compensation gain for the next time step. This is the error compensation gain at the current moment. For error compensation gain adaptive learning rate, This represents the residual motion noise after coarse compensation at the previous moment.

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