Quality analysis method and system for very-low-frequency mechanical antenna communication signal

Abstract

The invention belongs to the technical field of electrical digital data processing, and particularly relates to a very low frequency mechanical antenna communication signal quality analysis method and system, and the method comprises the steps: determining a driving current data sequence and a screening component of each time in the IMF extraction process of each layer corresponding to the driving current data sequence; determining an energy convergence index, waveform complexity and a resonance ripple residual factor of a current screening component in the current layer IMF extraction process; determining an optimized screening stop threshold value of a current screening component in the current layer IMF extraction process; and obtaining a main inertia mode component, obtaining an instantaneous frequency curve, and evaluating the signal quality according to an area difference between the instantaneous frequency curve and an ideal frequency curve of the driving instruction signal. According to the method, the energy characteristics and waveform characteristics of the screening component are analyzed, the screening stop threshold is self-adapted, the defect of a fixed screening stop threshold is overcome, high-frequency noise is filtered out, and the accuracy and robustness of communication signal quality analysis are improved.

Description

Technical Field

[0001] This invention relates to the field of electrical digital data processing technology. More specifically, this invention relates to a method and system for quality analysis of very low frequency mechanical antenna communication signals. Background Technology

[0002] Very low frequency (VLF) communication technology, with its strong penetration capabilities in media such as seawater and soil, has become a core technology in fields such as geological exploration and underground mine rescue. Unlike traditional electric antennas that use large antenna arrays to transmit electromagnetic waves, mechanical antennas, as a new type of VLF transmitting device, operate by driving a rotating magnet to physically cut magnetic field lines and generate VLF electromagnetic signals. This mechanism allows mechanical antennas to maintain extremely low operating frequencies while significantly reducing antenna size, achieving portability and low power consumption. In the efficient operating system of a mechanical antenna, the power amplifier not only bears the heavy responsibility of converting weak modulation command signals into high-voltage, high-current signals, but also needs to overcome the nonlinear characteristics of the mechanical load. Through precise control of the drive current waveform, it forces the drive motor to perform complex variable-speed movements to achieve signal modulation. Therefore, the quality of the drive current output by the power amplifier directly determines the accuracy of the mechanical movement and the quality of the final transmitted signal.

[0003] However, mechanical systems inherently possess a significant physical inertia. When a communication system switches frequencies according to modulation commands, although the power amplifier can quickly respond to changes in the electrical signal, the mechanical rotor it drives is limited by its enormous rotational inertia and damping. It cannot keep up with the instantaneous frequency changes of the drive current, resulting in a lag process from the current motion frequency to the target motion frequency, known as inertial lag. This physical lag effect is directly fed back to the output circuit of the power amplifier through electromagnetic coupling, causing the drive current to exhibit obvious frequency tailing, elongated transition region, and phase ambiguity in the time and frequency domain. In severe cases, this can prevent the demodulation algorithm at the receiving end from correctly identifying symbol boundaries, leading to a sharp increase in the bit error rate and a significant reduction in the effective communication distance. To address this issue, precise analysis of the quality of the drive current data is required. The Hilbert-Huang Transform (HHT), a powerful mathematical tool for processing nonlinear and non-stationary signals, has been increasingly used for the analysis of such transient signals. Through its core empirical mode decomposition algorithm, the non-stationary drive current signal can be decomposed into several intrinsic mode functions (IMFs), thereby extracting the instantaneous frequency curve. This is one of the most effective technical paths for quantifying the inertial hysteresis characteristics of mechanical antennas.

[0004] When using the empirical mode decomposition algorithm in the existing HHT algorithm to screen drive current data to extract the IMF representing inertial characteristics, a fixed screening stop threshold is usually used. However, this approach ignores the complex electromagnetic characteristics of the power amplifier under actual operating conditions. At the moment of frequency switching when driving a high-inertia load, the power amplifier is often in a high-load transient adjustment phase. Its output drive current not only contains the effective low-frequency component representing the mechanical inertial trend, but also inevitably mixes in high-frequency noise caused by the power amplifier's own switching ripple, harmonic distortion, and current loop regulation. Under fixed screening criteria, over-screening or under-screening can easily occur. Over-screening will cause the low-frequency amplitude modulation feature representing inertial lag to be excessively smoothed, resulting in a distorted signal that cannot accurately reflect physical inertia. Under-screening, on the other hand, will cause high-frequency noise introduced by the power amplifier to remain in the IMF component, interfering with the subsequent extraction of instantaneous frequency. Therefore, based on the fixed screening stop threshold, it will be impossible to remove high-frequency noise, resulting in the final calculated instantaneous frequency curve being full of spikes. This will cause the calculated inertial lag to be seriously overestimated, leading to misjudgment of signal quality. Summary of the Invention

[0005] To address the technical problem that the existing empirical mode decomposition algorithm in the HHT algorithm easily misjudges high-frequency noise interference as signal components when screening drive current data, resulting in incomplete screening or over-screening, and thus failing to accurately extract the main inertial mode components, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for quality analysis of very low frequency (VLF) mechanical antenna communication signals, comprising: acquiring drive current data and a synchronized drive command signal; performing preprocessing to determine the drive current data sequence and the corresponding sieving component for each step in the IMF extraction process of each layer; determining the energy convergence index of the current sieving component in the current layer IMF extraction process based on the energy difference between the current sieving component and the previous sieving component in the current layer IMF extraction process; and determining the energy convergence index of the current layer IMF extraction process based on the ratio between the absolute value of the second-order difference of the current sieving component and the total energy of the current sieving component in the current layer IMF extraction process. During the process, the waveform complexity of the current screening component is determined, and combined with the waveform complexity and energy convergence index, the resonant ripple residual factor of the current screening component in the current layer IMF extraction process is determined; the optimized screening stop threshold of the current screening component in the current layer IMF extraction process is determined based on the resonant ripple residual factor; the optimized screening stop threshold is used to perform empirical mode decomposition screening on the drive current data sequence to obtain the main inertial mode component, the HHT transform is performed on the main inertial mode component to obtain the instantaneous frequency curve, and the signal quality is evaluated based on the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal.

[0007] This invention highlights the convergence characteristics of the true signal components by calculating the energy convergence index and utilizing the energy differences between the sieving components. It analyzes the local second-order difference and waveform morphology of high-frequency noise by calculating waveform complexity, achieving accurate identification of high-frequency noise. By combining waveform complexity and the energy convergence index to calculate the resonant ripple residual factor, it adaptively corrects the benchmark sieving stop threshold, enhancing the anti-interference capability of the empirical mode decomposition algorithm in complex backgrounds. Furthermore, by generating the principal inertial mode components based on the optimized sieving stop threshold and performing HHT transformation and area difference evaluation, it achieves the assessment of the communication signal quality of very low frequency mechanical antennas, accurately identifying frequency deviations caused by mechanical vibration and improving the accuracy and robustness of the analysis.

[0008] Preferably, the acquisition of drive current data and synchronous drive command signal includes: acquiring drive current data of the mechanical antenna in working state using the current monitoring port of the power amplifier; and recording drive command signal within the same time period corresponding to the drive current data using the host computer control system.

[0009] Preferably, the energy convergence exponent satisfies the expression: In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. This represents the total number of sampling times in the drive current data sequence. and The first The first layer of IMF extraction process Second and third The secondary screening components are in The value at time, when hour, For the drive current data sequence in The value of the moment. To prevent constants with a denominator of zero.

[0010] This invention constructs a positive correlation function relationship based on the squared numerical difference between screening components at several time points, thereby achieving the evaluation of the energy convergence index. This squared difference term reflects the degree of energy convergence between screening components, resulting in the screening components corresponding to the real signal having a smaller energy convergence index, while the screening components affected by high-frequency noise have a larger energy convergence index. This provides a reliable convergence characteristic basis for the calculation of the resonant ripple residual factor.

[0011] Preferably, the waveform complexity satisfies the expression: In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components This represents the total number of sampling times in the drive current data sequence. , and The first The first layer of IMF extraction process The fraction of the second sieve was in the first The, the The and the first The value at each moment. For the first The first layer of IMF extraction process The total energy of the secondary screening components, and satisfying .

[0012] This invention achieves waveform complexity assessment by constructing a positive correlation function relationship between the ratio of the second-order difference absolute value and the total energy. The second-order difference absolute value term reflects the curvature change of the screening component, which makes the screening component affected by high-frequency resonance ripple noise calculate a larger waveform complexity, while the screening component corresponding to the real signal maintains a lower waveform complexity, thereby effectively distinguishing the real signal from the high-frequency resonance ripple noise.

[0013] Preferably, the resonant ripple residual factor satisfies the expression: In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Resonance ripple residual factor of secondary sieved components For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. It is a natural exponential function.

[0014] This invention achieves the evaluation of the resonant ripple residual factor by constructing a composite function containing a waveform complexity positive correlation term and an energy convergence exponent term. The waveform complexity term enhances the residual weight of the high-frequency resonant ripple noise region, while the energy convergence exponent term suppresses the residual contribution of the signal region. This results in the sieve component affected by high-frequency resonant ripple noise obtaining a larger resonant ripple residual factor, while the sieve component corresponding to the real signal maintains a lower resonant ripple residual factor, thereby effectively distinguishing resonant ripple interference from the real signal.

[0015] Preferably, the optimized screening stop threshold satisfies the expression: In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The optimized screening stop threshold for the next screening component. The preset basic screening stop threshold, For the first The first layer of IMF extraction process The resonant ripple residual factor of the secondary sieving component, ln is a natural logarithm function with base e. This is the threshold shrinkage strength coefficient.

[0016] This invention achieves adaptive screening stop threshold by dynamically adjusting the basic screening stop threshold using the resonant ripple residual factor as an exponential decay term. In areas with strong resonant ripple interference, the threshold is automatically lowered to enhance screening, while in areas with obvious signal characteristics, a higher threshold is maintained to preserve the true response, thus ensuring the accuracy of acquiring the main inertial mode components.

[0017] Preferably, the method for obtaining the principal inertial mode component is as follows: calculate the Pearson correlation coefficient between each IMF obtained by empirical mode decomposition of the driving current data sequence and the driving current data sequence, and select the IMF with the largest Pearson correlation coefficient as the principal inertial mode component.

[0018] Preferably, the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal satisfies the expression: In the formula, The area difference between the instantaneous frequency curve of the dominant inertial mode component and the ideal frequency curve of the drive command signal. and These are the start and end times of the drive current data sequence, respectively. The instantaneous frequency curve of the dominant inertial mode component is in The value of the moment. The ideal frequency curve for the drive command signal is in The value of the moment. This represents the sampling time interval.

[0019] Preferably, the evaluation of signal quality includes: responding to a situation where the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal is greater than a preset signal quality alarm threshold, indicating that the communication signal quality is unqualified, and triggering an alarm prompt.

[0020] Secondly, the present invention provides a quality analysis system for very low frequency mechanical antenna communication signals, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned method for quality analysis of very low frequency mechanical antenna communication signals is implemented.

[0021] By adopting the above technical solution, a computer program is generated from the quality analysis method of a very low frequency mechanical antenna communication signal, and stored in a memory for loading and execution by a processor. Terminal devices are then manufactured based on the memory and processor for convenient use.

[0022] The beneficial effects of this invention are as follows: This invention solves the technical problem of traditional empirical mode decomposition algorithms in existing HHT algorithms easily misidentifying high-frequency noise as signal components in very low frequency mechanical antenna environments, leading to distortion of quality analysis, by introducing an adaptive screening stop threshold correction mechanism.

[0023] This invention establishes an intrinsic mapping relationship between the energy convergence index and the convergence of the real signal by analyzing the energy differences between the sieved components. On this basis, it further integrates waveform complexity and tightly couples the index reflecting energy changes with the index reflecting waveform curvature changes, thereby realizing the identification of high-frequency resonant ripples.

[0024] This invention calculates a resonant ripple residual factor matching the true characteristics of each sieving component. By adaptively correcting the baseline sieving stop threshold using this residual factor, it achieves an accurate match between the sieving stop threshold and the true characteristics of the component. For sieving components affected by high-frequency noise, the threshold is automatically lowered to prevent incomplete sieving. For sieving components corresponding to the true signal, the threshold is maintained to ensure complete preservation. Ultimately, this invention improves the accuracy and anti-interference capability of very low frequency mechanical antenna communication signal processing, enhances the robustness of quality analysis, and enables timely and accurate identification of frequency deviations, providing a solid technical guarantee for antenna performance optimization and improved communication reliability. Attached Figure Description

[0025] Figure 1This is a flowchart illustrating a method for quality analysis of very low frequency mechanical antenna communication signals according to the present invention; Figure 2 The graph shows a comparison of the instantaneous frequency extraction effects of existing technologies using a fixed screening stop threshold and the optimized screening stop threshold used in this invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0028] This invention discloses a method for quality analysis of very low frequency mechanical antenna communication signals, referring to... Figure 1 This includes steps S001 to S005, specifically: S001: Acquire drive current data and synchronous drive command signals, perform preprocessing, and determine the drive current data sequence and the corresponding screening components for each IMF extraction process.

[0029] Specifically, in operation, the mechanical antenna acquires drive current data through the current monitoring port of the power amplifier, and records drive command signals within the same time period corresponding to the drive current data using the host computer control system. The drive current data is divided into a data sequence to obtain a drive current data sequence. Empirical mode decomposition (EMD) is performed on the drive current data sequence to obtain the screening components for each layer of IMF extraction in the drive current data sequence. In this embodiment, the acquisition frequency of the drive current data is set to 10Hz, and the length of the drive current data sequence is set to 10000. In other embodiments, the implementer can set the acquisition frequency and the length of the drive current data sequence according to the actual implementation situation.

[0030] S002: Based on the energy difference between the current screening component and the previous screening component during the current layer IMF extraction process, determine the energy convergence index of the current screening component during the current layer IMF extraction process.

[0031] It should be noted that when using Empirical Mode Decomposition (EMD) to process drive current data sequences, traditional fixed sieving stopping criteria are ill-suited to the complex operating conditions of mechanical antennas and high-frequency noise interference. This leads to an inability to accurately determine the convergence state of mode components, potentially resulting in over-sieving or under-sieving of the extracted IMF components, affecting the accuracy of subsequent assessments of communication signal inertial hysteresis. Based on the sieving theory of EMD, as sieving iterations proceed, non-stationary fluctuations in the signal are gradually smoothed, and the differences in waveform and energy between components obtained from adjacent sieving iterations gradually decrease and tend to stabilize. Therefore, this invention combines the energy difference between the current sieving component and its previous sieving component during the current layer IMF extraction process to determine the energy convergence index of the current sieving component during the current layer IMF extraction process. This index characterizes the degree of convergence of the current sieving component in the energy dimension during the current layer IMF extraction process.

[0032] Specifically, the energy convergence exponent satisfies the expression: ; In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. This represents the total number of sampling times in the drive current data sequence. and The first The first layer of IMF extraction process Second and third The secondary screening components are in The value at time, when hour, For the drive current data sequence in The value of the moment. To prevent the denominator from being zero, in this embodiment, the constant for preventing the denominator from being zero is set to 0.001. In other embodiments, implementers can set it according to the actual implementation situation.

[0033] In the formula, It is the first The first layer of IMF extraction process Second and third The energy differences of the secondary screening components were normalized. The cumulative number The first layer of IMF extraction process Second and third The square of the numerical difference of the second sieved component at all times reflects the... The first layer of IMF extraction process The magnitude of the change in the waveform of the drive current data sequence caused by the second screening operation; the smaller this value, the more significant the change. The first layer of IMF extraction process Second and third The smaller the relative energy difference between the fractions in the second sieve, the better the energy distribution. The first layer of IMF extraction process The more stable the secondary screening becomes, the more stable the tertiary screening becomes. The first layer of IMF extraction process The smaller the energy convergence index of the secondary sieving component, the better.

[0034] S003: Based on the ratio between the absolute value of the second difference of the current screening component and the total energy of the current screening component during the current layer IMF extraction process, determine the waveform complexity of the current screening component during the current layer IMF extraction process. Combine the waveform complexity and the energy convergence index to determine the resonant ripple residual factor of the current screening component during the current layer IMF extraction process.

[0035] It should be noted that because very low frequency (VLF) mechanical antennas are prone to mechanical resonance lock-in during frequency keying modulation, the driving current signal contains relatively stable high-frequency resonance ripple. This high-frequency resonance ripple noise changes only slightly during the continuous sieving iterations of empirical mode decomposition (EMF), resulting in low energy differences between adjacent sieving components. Relying solely on energy convergence characteristics for judgment can easily misjudge spurious stable states containing significant high-frequency resonance ripple noise as true convergence, leading to distortion of the extracted mode components. According to the time-domain smoothness theory in signal processing, the second-order difference amplitude of a signal is proportional to the square of its frequency. Effective VLF inertial components exhibit smooth waveforms and small second-order differences, while high-frequency resonance ripple exhibits rough waveforms and significant second-order differences. Therefore, this invention determines the waveform complexity and resonance ripple residual factor of the current sieving component during the current layer IMF extraction process to characterize the risk of high-frequency resonance ripple noise residue implied in the current sieving component while exhibiting an energy convergence trend during the current layer IMF extraction process.

[0036] Specifically, the waveform complexity satisfies the expression: ; In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components This represents the total number of sampling times in the drive current data sequence. , and The first The first layer of IMF extraction process The fraction of the second sieve was in the first The, the The and the first The value at each moment. For the first The first layer of IMF extraction process The total energy of the secondary screening components, and satisfying .

[0037] In the formula, Used for the first The first layer of IMF extraction process The absolute value of the second difference of the secondary screening component is normalized. Reflects the first The first layer of IMF extraction process The geometric roughness of the waveform of the second sieved component; the larger the value, the better. The first layer of IMF extraction process The larger the absolute value of the second difference of the second sieve component, the more it indicates that the second sieve component is larger. The first layer of IMF extraction process The more complex the waveform of the second sieve component, the more complex the second sieve component. The first layer of IMF extraction process The greater the waveform complexity of the secondary screening component, the better.

[0038] Specifically, the resonant ripple residual factor satisfies the expression: ; In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Resonance ripple residual factor of secondary sieved components For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. It is a natural exponential function.

[0039] In the formula, The larger the value, the more likely it is to be the first. The first layer of IMF extraction process The more high-frequency resonant ripple noise remains in the second sieve component, the more it indicates that the second sieve component... The first layer of IMF extraction process The greater the likelihood of high-frequency resonant ripple in the second sieve component, the higher the probability of high-frequency resonant ripple in the third sieve component. The first layer of IMF extraction process The larger the residual factor of the resonance ripple in the secondary sieve component, the greater the residual factor. The larger the value, the more likely it is to be the first. The first layer of IMF extraction process The less stable the subsequent screening, the more likely it is that the second screening... The first layer of IMF extraction process The more likely the secondary screening component is to be affected by high-frequency noise, the more likely the secondary screening component is to be affected by high-frequency noise. The first layer of IMF extraction process The larger the residual factor of the resonance ripple in the secondary sieve component, the greater the residual factor.

[0040] S004: Determine the optimized screening stop threshold of the current screening component during the current layer IMF extraction process based on the resonance ripple residual factor.

[0041] It should be noted that after obtaining the resonant ripple residual factor of the current screening component in the current layer IMF extraction process, this invention will calculate the optimized screening stop threshold of the current screening component in the current layer IMF extraction process based on the resonant ripple residual factor. Traditional empirical mode decomposition often uses a fixed screening stop threshold when processing the driving current data sequence. This invention, however, uses the resonant ripple residual factor to calculate the optimized screening stop threshold of the current screening component in the current layer IMF extraction process, so that empirical mode decomposition can obtain a more accurate IMF.

[0042] Specifically, the optimized screening stopping threshold satisfies the expression: ; In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The optimized screening stop threshold for the next screening component. The preset basic screening stop threshold, For the first The first layer of IMF extraction process The resonant ripple residual factor of the secondary sieving component, ln is a natural logarithm function with base e. The threshold shrinkage strength coefficient is set to 2 in this embodiment. In other embodiments, the implementer can set it according to the actual implementation situation. For example, when the mechanical antenna is in a complex operating condition and the resonance ripple interference is severe, resulting in strict requirements for the extraction accuracy of the main inertial mode component, the threshold shrinkage strength coefficient can be appropriately increased to enhance the shrinkage force of the screening stop threshold and ensure the complete removal of high-frequency noise in the pseudo-steady state. When the real-time requirements for signal quality analysis are high or the resonance interference is weak, the threshold shrinkage strength coefficient can be appropriately decreased to reduce the number of screening iterations and improve the computational efficiency of the algorithm.

[0043] In the formula, The larger the value, the more likely it is to be the first. The first layer of IMF extraction process The more likely the secondary screening component is to be affected by high-frequency noise, the more likely the secondary screening component is to be affected by high-frequency noise. The first layer of IMF extraction process The smaller the optimized screening stop threshold of the secondary screening component, the more effectively high-frequency noise can be eliminated.

[0044] S005: The driving current data sequence is subjected to empirical mode decomposition and screening using the optimized screening stop threshold to obtain the main inertial mode component. The main inertial mode component is subjected to HHT transformation to obtain the instantaneous frequency curve, and the signal quality is evaluated based on the area difference between the instantaneous frequency curve and the ideal frequency curve of the driving command signal.

[0045] Specifically, the signal quality is evaluated, including: Based on the optimized screening stop threshold, empirical mode decomposition is used to perform empirical mode decomposition on the drive current data sequence to obtain several IMFs; The Pearson correlation coefficients of each IMF obtained by empirical mode decomposition of the drive current data sequence and the drive current data sequence are calculated, and the IMF with the largest Pearson correlation coefficient is selected as the principal inertial mode component. The instantaneous frequency curve is obtained by performing HHT transform on the principal inertial mode components; the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal is calculated, and the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal satisfies the expression: ; In the formula, The area difference between the instantaneous frequency curve of the dominant inertial mode component and the ideal frequency curve of the drive command signal. and These are the start and end times of the drive current data sequence, respectively. The instantaneous frequency curve of the dominant inertial mode component is in The value of the moment. The ideal frequency curve for the drive command signal is in The value of the moment. The sampling time interval; If the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal exceeds the preset signal quality alarm threshold, the communication signal quality is deemed unqualified, triggering an alarm.

[0046] like Figure 2 As shown in the figure, the graph compares the instantaneous frequency extraction effects of very low frequency (VLF) mechanical antenna communication signals when using a fixed screening stop threshold in existing technology and when using an optimized screening stop threshold in this invention. The ideal drive command frequency curve in the figure serves as a standard reference. The curve corresponding to the existing technology exhibits severe amplitude oscillations and dense clutter interference at the step of frequency switching. This indicates that the fixed screening stop threshold cannot effectively remove high-frequency resonant ripples, resulting in severely distorted extracted frequency curves that fail to accurately reflect the motion inertia of the mechanical antenna. Conversely, the curve corresponding to this invention exhibits significant smoothness. This curve closely tracks the mechanical inertia trend while completely eliminating high-frequency spikes, confirming that this invention, by introducing a resonant ripple residual factor, can adaptively adjust the screening strategy, strengthening screening to filter out high-frequency noise when interference is strong. This effectively avoids over-screening or under-screening, ensuring the accuracy and reliability of communication signal quality assessment.

[0047] This invention also discloses a quality analysis system for very low frequency (VLF) mechanical antenna communication signals, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a VLF mechanical antenna communication signal quality analysis method according to the present invention.

[0048] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

Claims

1. A method of quality analysis of a very low frequency mechanical antenna communication signal, characterized by, include: Acquire drive current data and synchronous drive command signals, perform preprocessing, and determine the drive current data sequence and the corresponding screening components for each IMF extraction process. Based on the energy difference between the current screening component and the previous screening component during the current layer IMF extraction process, determine the energy convergence index of the current screening component during the current layer IMF extraction process; Based on the ratio between the absolute value of the second difference of the current screening component and the total energy of the current screening component during the current layer IMF extraction process, the waveform complexity of the current screening component during the current layer IMF extraction process is determined. Combining the waveform complexity and the energy convergence index, the resonant ripple residual factor of the current screening component during the current layer IMF extraction process is determined. The optimized screening stop threshold for the current screening component during the current layer IMF extraction process is determined based on the resonant ripple residual factor. The optimized screening stop threshold is used to perform empirical mode decomposition screening on the drive current data sequence to obtain the main inertial mode component. The main inertial mode component is then subjected to HHT transformation to obtain the instantaneous frequency curve. The signal quality is evaluated based on the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal.

2. The method of claim 1, wherein, The acquisition of drive current data and synchronous drive command signals includes: acquiring drive current data of the mechanical antenna in operation using the current monitoring port of the power amplifier; and recording drive command signals within the same time period corresponding to the drive current data using the host computer control system.

3. The method of claim 1, wherein the method further comprises: The energy convergence exponent satisfies the expression: ； In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. This represents the total number of sampling times in the drive current data sequence. and The first The first layer of IMF extraction process Second and third The secondary screening components are in The value at time, when hour, For the drive current data sequence in The value of the moment. To prevent constants with a denominator of zero.

4. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The waveform complexity satisfies the expression: ； In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components This represents the total number of sampling times in the drive current data sequence. , and The first The first layer of IMF extraction process The fraction of the second sieve was in the... The, the The and the first The value at each moment. For the first The first layer of IMF extraction process The total energy of the secondary screening components, and satisfying .

5. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The resonant ripple residual factor satisfies the expression: ； In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process Resonance ripple residual factor of secondary sieved components For the first The first layer of IMF extraction process Waveform complexity of the secondary sieved components For the first The first layer of IMF extraction process The energy convergence index of the secondary sieving component. It is a natural exponential function.

6. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The optimized screening stop threshold satisfies the expression: ； In the formula, The sequence number extracted from the current layer IMF. This is the sequence number of the current screening step during the current layer IMF extraction process. For the first The first layer of IMF extraction process The optimized screening stop threshold for the next screening component. The preset basic screening stop threshold, For the first The first layer of IMF extraction process The resonant ripple residual factor of the secondary sieving component, ln is a natural logarithm function with base e. This is the threshold shrinkage strength coefficient.

7. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The method for obtaining the principal inertial mode component is as follows: calculate the Pearson correlation coefficient between each IMF obtained by empirical mode decomposition of the driving current data sequence and the driving current data sequence, and select the IMF with the largest Pearson correlation coefficient as the principal inertial mode component.

8. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal satisfies the expression: ； In the formula, The area difference between the instantaneous frequency curve of the dominant inertial mode component and the ideal frequency curve of the drive command signal. and These are the start and end times of the drive current data sequence, respectively. The instantaneous frequency curve of the dominant inertial mode component is in The value of the moment. The ideal frequency curve for the drive command signal is in The value of the moment. This represents the sampling time interval.

9. The method for quality analysis of very low frequency mechanical antenna communication signals according to claim 1, characterized in that, The evaluation of signal quality includes: in response to the area difference between the instantaneous frequency curve and the ideal frequency curve of the drive command signal being greater than a preset signal quality alarm threshold, the communication signal quality is deemed unqualified, and an alarm is triggered.

10. A quality analysis system for very low frequency mechanical antenna communication signals, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement a method for quality analysis of very low frequency mechanical antenna communication signals according to any one of claims 1-9.

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