Inertial navigation underwater path tracking method and system for complex marine environments

Abstract

The application discloses an inertial navigation underwater path tracking method and system for complex marine environment and relates to the technical field of inertial navigation.The method comprises the following steps: monitoring during AUV navigation, underwater tracking position correction, underwater path tracking stability analysis and underwater path tracking stability change analysis.The application monitors the IMU acceleration change in the INS and the DVL wave speed quality fluctuation, respectively carries out IMU acceleration change analysis and DVL wave speed quality fluctuation analysis, then adopts the underwater tracking position correction scheme based on the analysis results of the two kinds, simultaneously carries out underwater path position reliability analysis, judges whether the path stability correction measure is adopted through the stability of the AUV underwater path position tracking, and then determines whether the path correction adjustment is executed, so that the accuracy of the underwater path tracking position is improved, and the problem of reduced underwater path tracking position accuracy in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of inertial navigation technology, and in particular to an inertial navigation underwater path tracking method and system for complex marine environments. Background Technology

[0002] To achieve a technical means for autonomous underwater vehicles (AUVs) to maintain a precise navigation path in complex marine environments, existing technologies have designed a method for underwater path tracking using inertial navigation technology. This method specifically includes path tracking, inertial navigation, adaptation to complex marine environments, fusion algorithms and intelligent control, and error compensation and adaptive correction. The goal of this method is to enable underwater vehicles to navigate with high precision and stability along a preset path even in the absence of GPS (Global Positioning System), under strong interference, and in complex flow fields, thus ensuring mission success.

[0003] Path tracking is used to control underwater vehicles to move along a preset path or target trajectory, minimizing deviations. In tasks such as search and rescue, marine exploration, and deploying underwater sensors, precise control of the vehicle along a specific route is required. Inertial navigation, on the other hand, utilizes an internal inertial measurement unit (IMU). The system uses a combination of inertial navigation units (accelerometers and gyroscopes) to estimate position, velocity, and attitude, providing continuous navigation capability even underwater without GPS signals. Its complex marine environment adaptation feature addresses complex environmental factors such as current disturbances, ocean turbulence, and irregular terrain, enabling robust path correction and enhancing the stability and accuracy of the navigation system in real, harsh marine environments. Fusion algorithms and intelligent control integrate inertial navigation data with other sensors (such as sonar and multibeam sonar), applying advanced control algorithms (such as sliding mode control, model predictive control, and deep learning-assisted control) to improve path tracking performance, reduce drift errors in the inertial navigation system, and enhance overall tracking accuracy and robustness. Error compensation and adaptive correction dynamically correct path deviations caused by ocean currents, equipment errors, etc., maintaining the reliability of navigation data and enabling long-duration, long-distance underwater missions.

[0004] For example, the Chinese invention patent application CN118189947A discloses an inertial Doppler integrated navigation error suppression method and system in water tracking mode, which includes: the inertial Doppler integrated navigation system completing initial alignment; under normal circumstances, the Doppler operates in bottom tracking mode, and the integrated navigation system operates in normal integrated navigation state, i.e., the integrated navigation model in bottom tracking mode, and the integrated navigation model in bottom tracking mode is constructed through the state space model and observations; if the Doppler cannot perform bottom tracking, the integrated navigation system switches to the integrated navigation model in water tracking mode, and the integrated navigation model in water tracking mode is constructed through the state space model and observations; if the Doppler can perform bottom tracking, the system switches back to the integrated navigation model in bottom tracking mode.

[0005] For example, Chinese invention patent CN106017467B discloses an inertial / underwater acoustic integrated navigation method based on multiple underwater transponders, including: underwater transponder deployment and position calibration; calculating the absolute position information of the AUV using a distance-transformation position algorithm; using the inertial navigation system INS / DVL in the AUV and the calculated absolute position information of the AUV to perform a position integrated navigation algorithm to correct its dead reckoning error; deploying a subsequent underwater transponder, using the distance combined output between the AUV and the current underwater transponder to estimate the position of the subsequent underwater transponder, and then performing distance integrated navigation between the AUV and the subsequent underwater transponder, and repeating the above process.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] In complex marine environments, relying solely on inertial navigation systems (INS) leads to rapid error accumulation. Therefore, existing technologies generally employ a multi-source information fusion approach combined with external correction to combat the influence of external factors. To address the impact of ocean currents and swells on INS, Doppler velocity logs (DVLs) are introduced to measure the relative velocity of the seabed or water body to correct accumulated INS errors. However, during the correction process, modern inertial navigation systems widely adopt adaptive weight adjustment mechanisms. But due to the lack of reliability modeling for multi-source information, filter weights may be improperly set, affecting the correction effect. Many systems simply adjust based on the current data characteristics of a single sensor (such as residuals) without comprehensively considering multi-dimensional information such as sensor health status, redundancy, and consistency. For example, a decrease in DVL beam quality or a drastic change in IMU acceleration are often not incorporated into the weight adjustment logic, leading to a decrease in the accuracy of INS and DVL data fusion, and consequently, a decrease in the accuracy of inertial navigation, resulting in reduced underwater path tracking and positioning accuracy. Summary of the Invention

[0008] To address the technical problem of reduced accuracy in underwater path tracking in existing technologies, this invention provides an inertial navigation underwater path tracking method and system for complex marine environments. The technical solution is as follows:

[0009] On the one hand, an underwater path tracking method for inertial navigation in complex marine environments is provided. This method includes: during AUV navigation, real-time monitoring of IMU acceleration changes and DVL wave velocity-mass fluctuations within a set underwater navigation tracking period; performing IMU acceleration change analysis to reflect the amplitude of IMU acceleration changes, and DVL wave velocity-mass fluctuation analysis to characterize the DVL wave velocity-mass fluctuations; and making a dual determination based on the results of the IMU acceleration change analysis and the DVL wave velocity-mass fluctuation analysis to decide on the appropriate underwater tracking position correction scheme to correct the AUV's trajectory. The study analyzes the underwater path deviation of the UV and performs an underwater path position reliability analysis to reflect the reliability of the AUV's underwater path position. The results of the reliability analysis over a set time period determine the stability of the AUV's underwater path position tracking, thus determining whether path stability correction measures should be implemented to reduce the degree of underwater path position drift. Furthermore, the study analyzes the stability changes in underwater path position tracking stability based on the stability of the AUV's underwater path position accuracy over adjacent set time periods, thereby determining whether path correction adjustments should be implemented to improve the compatibility between the underwater path correction frequency and the stability of underwater path position tracking.

[0010] On the other hand, an inertial navigation underwater path tracking system for complex marine environments is provided. This system includes: an AUV navigation monitoring module, an underwater tracking position correction module, an underwater path tracking stability analysis module, and an underwater path tracking stability change analysis module. The AUV navigation monitoring module monitors the IMU acceleration changes and DVL wave velocity-mass fluctuations in the INS within a set underwater navigation tracking period during AUV navigation. It performs IMU acceleration change analysis (reflecting the amplitude of IMU acceleration changes) and DVL wave velocity-mass fluctuation analysis (characterizing DVL wave velocity-mass fluctuations), respectively. The underwater tracking position correction module performs dual analysis based on the results of the IMU acceleration change analysis and the DVL wave velocity-mass fluctuation analysis. The system determines the appropriate underwater tracking position correction scheme to correct the AUV's underwater path deviation, and performs an underwater path position reliability analysis to reflect the reliability of the AUV's underwater path position. The underwater path tracking stability analysis module determines the stability of the AUV's underwater path position tracking based on the results of the reliability analysis over a set time period, and decides whether to implement path stability correction measures to reduce the degree of underwater path position drift. The underwater path tracking stability change analysis module analyzes the stability changes of the AUV's underwater path position accuracy over adjacent set time periods, and determines whether to implement path correction adjustments to improve the compatibility between the underwater path correction frequency and the underwater path position tracking stability.

[0011] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0012] 1. During AUV navigation, real-time monitoring of IMU acceleration changes and DVL wave velocity-mass fluctuations in the INS ensures continuous monitoring of the underwater tracking position data source. IMU acceleration change analysis reflects the amplitude of IMU acceleration fluctuations, and DVL wave velocity-mass fluctuation analysis characterizes the DVL wave velocity-mass fluctuations. This allows for more accurate data quantification based on the corresponding fluctuations, providing a more intuitive understanding of the stability of the underwater tracking position data source. Then, based on the results of both IMU acceleration change analysis and DVL wave velocity-mass fluctuation analysis, a dual assessment is made to determine the appropriate underwater tracking position correction scheme to correct the AUV's underwater path deviation, thereby improving the accuracy of the AUV's underwater path navigation. Simultaneously, underwater path position reliability analysis is performed, reflecting not only... The reliability of the AUV's underwater path position provides a clearer indication of its current credibility. Then, by analyzing the credibility of the underwater path position over a set time period, the stability of the AUV's underwater path position tracking is determined. This allows for a decision on whether to implement path stability correction measures to reduce underwater path position drift, thereby improving the accuracy of the current underwater path tracking position. Finally, by analyzing the stability of the AUV's underwater path position accuracy over adjacent set time periods, the stability of underwater path position tracking is analyzed to determine whether to implement path correction adjustments to improve the compatibility between the underwater path correction frequency and the underwater path position tracking stability. This further improves the accuracy of the AUV's underwater path position and helps solve the problem of reduced underwater path tracking accuracy caused by the decreased accuracy of INS and DVL data fusion in existing technologies.

[0013] 2. After the IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis are completed, the DVL wave velocity quality analysis coefficients and the quantized values ​​of IMU acceleration changes are compared with the corresponding navigation tracking judgment thresholds. This enables synchronous analysis of data sources for each underwater tracking position, which not only improves the efficiency of underwater tracking position determination but also helps improve the reliability of underwater tracking positions. Then, based on the DVL wave velocity quality analysis coefficients, DVL wave velocity quality judgment thresholds, and the quantized values ​​and judgment thresholds of IMU acceleration changes, separate judgments are made. This helps to further refine the analysis of the accuracy of underwater path tracking positions and facilitates subsequent automated decision-making. Specifically, four judgment results are included, and corresponding underwater tracking position correction schemes are adopted to achieve automated correction of underwater tracking positions. At the same time, underwater path position credibility analysis is performed, which provides a more intuitive feedback on the credibility of the current underwater path position, thereby helping the AUV to have a clearer understanding of the current navigation position.

[0014] 3. After analyzing the reliability of the underwater path position for a preset number of underwater navigation tracking cycles, the corresponding underwater path position reliability scores are statistically analyzed and linearly fitted to obtain the corresponding underwater path tracking stability coefficient. This more accurately reflects the fluctuation of underwater path position stability, allowing for timely corrective measures. The underwater path tracking stability coefficient is then compared with the underwater path tracking stability judgment threshold, achieving automated classification of the underwater path tracking stability fluctuation amplitude. If the underwater path tracking stability coefficient is less than the underwater path tracking stability judgment threshold, the monitoring continues for the next underwater navigation tracking cycle, monitoring the DVL wave velocity quality and the IMU acceleration changes in the INS, ensuring accurate monitoring of the DVL wave velocity quality and IMU acceleration changes in the INS. If the underwater path tracking stability coefficient is not maintained, a secondary warning is issued to the operator's interface, and the current underwater path tracking stability coefficient is fed back to the operator's interface to promptly remind the operator of the reliability of the current underwater tracking position, providing the operator with a data basis for driving judgment. At the same time, the stability path correction amplitude influence factor is obtained, thereby realizing accurate control of the underwater path correction frequency based on the stability gap that needs to be corrected reflected by the underwater path tracking stability coefficient. Finally, the preset correction amplitude is compensated based on the stability path correction amplitude influence factor to obtain the corresponding optimized correction amplitude, realizing precise correction of the path correction frequency. By optimizing the correction amplitude to correct the path correction frequency of the AUV, the accuracy of the path tracking position of the AUV during underwater navigation is improved. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the inertial navigation underwater path tracking method for complex marine environments provided in an embodiment of the present invention.

[0017] Figure 2 This is a flowchart illustrating the underwater tracking position correction scheme provided in an embodiment of the present invention.

[0018] Figure 3 This is a flowchart illustrating the process of determining and implementing path stability correction measures according to an embodiment of the present invention;

[0019] Figure 4 This is a schematic diagram of the structure of an inertial navigation underwater path tracking system for complex marine environments provided in an embodiment of the present invention. Detailed Implementation

[0020] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0021] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0022] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0023] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0024] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0025] This invention provides an inertial navigation underwater path tracking method for complex marine environments. For example... Figure 1 The illustrated embodiment of the present invention provides a flowchart of an inertial navigation underwater path tracking method for complex marine environments. The processing flow of this method may include the following steps:

[0026] AUV navigation monitoring: During AUV navigation, the changes in IMU acceleration and DVL wave velocity-mass fluctuations in the INS are monitored in real time within the set underwater navigation tracking cycle. IMU acceleration change analysis is performed to reflect the amplitude of IMU acceleration change fluctuations, and DVL wave velocity-mass fluctuation analysis is performed to characterize the DVL wave velocity-mass fluctuations.

[0027] Underwater tracking position correction: Based on the results of IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis, a dual judgment is made to determine the underwater tracking position correction scheme to correct the AUV's deviation in the underwater path. At the same time, an underwater path position reliability analysis is performed to reflect the reliability of the AUV's underwater path position.

[0028] Underwater path tracking stability analysis: The stability of AUV underwater path position tracking is determined by analyzing the reliability of underwater path position over a set time period, so as to determine whether path stability correction measures should be taken to reduce the degree of underwater path position drift.

[0029] Underwater path tracking stability change analysis: Based on the stability of the underwater path position accuracy of AUVs in adjacent set time periods, the stability change of underwater path position tracking is analyzed to determine whether to perform path correction adjustment to improve the compatibility between underwater path correction frequency and underwater path position tracking stability.

[0030] In this embodiment, dual judgment is made through IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis, avoiding misjudgment caused by a single sensor anomaly and improving the accuracy of path correction decisions. Simultaneously, when abnormal fluctuations in IMU and DVL data are detected, corresponding path correction schemes can be implemented in a timely manner, helping to reduce position drift of the AUV during long-term underwater navigation. Furthermore, by analyzing the reliability of the path position within a set time period, the reliability of the AUV's path results can be quantified, providing a more reliable basis for subsequent path correction and improving the robustness of the overall navigation system. By analyzing the stability trend of path position tracking, the path correction frequency can be adaptively adjusted to avoid over-correction (increased energy consumption) or under-correction (increased drift), thus balancing navigation accuracy and energy efficiency, and ultimately ensuring the accuracy of path tracking position for the AUV during underwater navigation.

[0031] As a further embodiment, the specific process of IMU acceleration change analysis is as follows:

[0032] F1 assigns a number to the underwater navigation tracking cycle and acquires the IMU acceleration change monitoring parameters in real time within the underwater navigation tracking cycle. The IMU acceleration change monitoring parameters include the acceleration change rate and acceleration variance.

[0033] It should be added that the raw acceleration values ​​(ax, ay, az) of each time point in the underwater navigation tracking cycle are read from the IMU's raw data (usually via UART, CAN, Ethernet, or SDK). The raw acceleration values ​​of each time point are numerically differentiated and averaged to obtain the corresponding acceleration change rate of each axis. The acceleration variance is obtained by averaging the raw acceleration values ​​of each time point within a sliding time window (such as 100ms or 1s) to obtain the acceleration variance of each axis.

[0034] F2 calculates the deviation between the rate of change of acceleration and the rate of change of acceleration in the previous underwater navigation tracking cycle to obtain the corresponding rate of change of acceleration offset value.

[0035] Specifically, the acceleration change rate is subtracted from the acceleration change rate in the previous underwater navigation tracking cycle, then the ratio is calculated with the acceleration change rate, and finally the absolute value is calculated to obtain the acceleration change rate offset value.

[0036] F3 quantifies the difference ratio between the pre-extracted acceleration variance reference value and the acceleration variance to obtain the corresponding acceleration variance change ratio.

[0037] Specifically, the acceleration variance is calculated by ratioing the acceleration variance to the acceleration variance reference value, and the acceleration variance reference value is preset by professional technicians.

[0038] F4 extracts the pre-stored IMU acceleration change reference weights, which include acceleration rate of change weights and acceleration variance weights.

[0039] It should be added that the IMU acceleration change reference weights are extracted from a preset database. The preset database stores an IMU acceleration change mapping set in advance. The obtained IMU acceleration change monitoring parameters are input into the IMU acceleration change mapping set to output the corresponding IMU acceleration change reference weights, namely the acceleration change rate weight and the acceleration variance weight, which respectively represent the degree of influence of the acceleration change rate and acceleration variance on the quantized value of IMU acceleration change. The IMU acceleration change mapping set is trained based on IMU acceleration change training data. The IMU acceleration change training data includes IMU acceleration change monitoring parameters in historical time periods and IMU acceleration change reference weights set by professional technicians based on empirical rules. The sum of the acceleration change rate weight and the acceleration variance weight is 1.

[0040] F5 aggregates the acceleration change quantization value by weighting the acceleration change rate offset value and the acceleration variance change ratio through the IMU acceleration change reference weight. The IMU acceleration change quantization value is used to quantify the magnitude of the IMU acceleration change.

[0041] The specific expression for the quantized value of IMU acceleration change is as follows:

[0042] ;

[0043] In the formula, t represents the number of the underwater navigation tracking cycle, t=1,2,...,T, and T represents the total number of underwater navigation tracking cycles, Δa tLet Δa represent the rate of change of acceleration during the t-th underwater navigation tracking cycle. t-1 Δa represents the rate of change of acceleration during the (t-1)th underwater navigation tracking cycle (at t=1, Δa) t-1 (for the set initial rate of change of acceleration), a v0 This represents the reference value for the variance of acceleration, a. vt Let τ represent the acceleration variance in the t-th underwater navigation tracking cycle, α represent the acceleration rate of change weight, β represent the acceleration variance weight, and τ represent the acceleration variance weight. t This represents the quantized value of the IMU acceleration change during the t-th underwater navigation tracking cycle.

[0044] In this embodiment, the algorithm combines IMU acceleration change monitoring parameters, acceleration variance reference value, and IMU acceleration change reference weight to comprehensively analyze and obtain the corresponding IMU acceleration change quantization value. In the formula, as the difference between the acceleration change rate and the acceleration change rate in the previous underwater navigation tracking cycle increases, the corresponding acceleration change rate offset value increases, and the IMU acceleration change quantization value also increases. This indicates that the greater the fluctuation amplitude of the IMU acceleration change, the more drastic the acceleration may be. Similarly, when the acceleration variance is greater than the acceleration variance reference value, the corresponding acceleration variance change ratio is larger, indicating that the IMU acceleration... The more drastic the change, the larger the corresponding quantized value of the IMU acceleration change. Meanwhile, the acceleration change rate describes the instantaneous amplitude of the acceleration change, while the acceleration variance describes the overall fluctuation intensity of the acceleration. Both measure whether the acceleration changes drastically. If an acceleration sequence fluctuates drastically and continuously, its acceleration change rate will usually be large, and its acceleration variance will also be large. Through the above analysis, the amplitude of IMU acceleration changes is quantified more accurately, thus more accurately reflecting whether a drastic change in acceleration has occurred. This allows for timely coordination of the importance of the source data for underwater path tracking positions, ensuring the reliability of the underwater path tracking data.

[0045] As a further embodiment, the specific process of DVL wave velocity quality fluctuation analysis is as follows:

[0046] J1 acquires DVL wave velocity quality monitoring parameters in real time during the underwater navigation tracking cycle. The DVL wave velocity quality monitoring parameters include echo intensity, echo-signal correlation, and SNR. The echo-signal correlation represents the correlation between the echo and the local signal.

[0047] Specifically, the echo intensity is provided in the raw beam data message (Raw Beam Data / Bottom Track Data), with each beam outputting a separate intensity value. The echo-signal correlation is the correlation parameter output by the DVL, typically found in the bottom tracking or water tracking data packet for each beam. The SNR is output directly from the DVL.

[0048] J2 queries pre-stored DVL wave velocity quality analysis factors, which include echo intensity analysis factors, echo-signal correlation analysis factors, and SNR analysis factors.

[0049] It should be added that the DVL wave speed quality analysis factors are obtained by querying the DVL wave speed quality dataset stored in the preset database. The DVL wave speed quality monitoring parameters are input into the DVL wave speed quality dataset, and the corresponding DVL wave speed quality analysis factors are output, namely echo intensity analysis factor, echo-signal correlation analysis factor, and SNR analysis factor. These represent the degree of influence of echo intensity, echo-signal correlation, and SNR on the DVL wave speed quality analysis coefficients, respectively. The DVL wave speed quality dataset is a dataset that fits the mapping relationship between the DVL wave speed quality monitoring parameters and the DVL wave speed quality analysis factors. It is trained using DVL wave speed quality training data, which includes DVL wave speed quality monitoring parameters from historical time periods and DVL wave speed quality analysis factors set by professional technicians according to empirical rules. The sum of the echo intensity analysis factor, echo-signal correlation analysis factor, and SNR analysis factor is 1.

[0050] J3 quantifies the echo intensity by comparing it with the echo intensity in the previous underwater navigation tracking cycle, thus obtaining the percentage change in echo intensity. Specifically, the percentage change in echo intensity is obtained by calculating the ratio of the echo intensity to the echo intensity in the previous underwater navigation tracking cycle.

[0051] J4, after normalizing the SNR data, performs weighted operations on the echo intensity variation ratio, echo-signal correlation and SNR based on the DVL wave velocity quality analysis factor, and then couples them to obtain the DVL wave velocity quality analysis coefficient. The DVL wave velocity quality analysis coefficient is used to quantify the fluctuation of DVL wave velocity quality.

[0052] The specific limiting expressions for the DVL wave velocity quality analysis coefficients are as follows:

[0053] ;

[0054] In the formula, Y represents the DVL wave velocity quality analysis coefficient, X1 represents the echo intensity, X2 represents the echo-signal correlation, X3 represents the SNR, and X... L θ1 represents the echo intensity during the previous underwater navigation tracking cycle, θ2 represents the echo-signal correlation analysis factor, and θ3 represents the SNR analysis factor.

[0055] In this embodiment, the algorithm combines DVL wave velocity quality monitoring parameters and DVL wave velocity quality analysis factors to obtain the corresponding DVL wave velocity quality analysis coefficient. In the formula, as the echo intensity is greater than the echo intensity in the previous underwater navigation tracking cycle, the corresponding echo intensity change percentage is larger, indicating higher echo quality and a smaller corresponding DVL wave velocity quality analysis coefficient. Conversely, as the echo-signal correlation and SNR increase, the echo quality fluctuation is lower, and the corresponding DVL wave velocity quality analysis coefficient is larger. Higher echo intensity usually corresponds to a higher SNR (provided the noise level is not high). While high echo intensity does not necessarily equate to high echo-signal correlation (if the waveform is distorted, the echo-signal correlation may be lower), high SNR is usually accompanied by high echo-signal correlation (low noise, signal closer to the original). At low SNR, even if the echo intensity is high, it may be masked by noise, leading to a decrease in echo-signal correlation. Based on the above analysis, a more accurate quantification of the fluctuation of DVL wave velocity quality was achieved, and a joint judgment was made by combining the change amplitude of IMU acceleration, thereby ensuring the reliability of the data used to determine the underwater tracking position and improving the credibility of the underwater tracking position.

[0056] like Figure 2 The diagram shows a flowchart of the underwater tracking position correction scheme provided in this embodiment of the invention. The specific logic is as follows: The DVL wave velocity quality analysis coefficient and the IMU acceleration change quantization value are compared with the corresponding navigation tracking judgment thresholds. If the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, the underwater tracking position correction scheme adopted is to continue monitoring the DVL wave velocity quality and the IMU acceleration change in the INS for the next underwater navigation tracking cycle, while simultaneously performing an underwater path position reliability analysis. If the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is executed. The correction scheme is an IMU acceleration correction scheme, while simultaneously performing an underwater path position reliability analysis. If the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is the DVL wave velocity quality correction scheme, and an underwater path position reliability analysis is performed. If the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is to immediately issue a first-level warning to the vehicle pilot's operating interface, while simultaneously performing an underwater path position reliability analysis. Through the above process, not only is the accuracy of underwater path correction improved, but the reliability of the inertial navigation system is also enhanced.

[0057] Furthermore, a dual assessment is made based on the results of IMU acceleration change analysis and DVL wave velocity-mass fluctuation analysis to determine the appropriate underwater tracking position correction scheme. The specific steps are as follows:

[0058] The DVL wave velocity quality analysis coefficients and IMU acceleration change quantization values ​​are compared with the corresponding set navigation tracking judgment thresholds, which include four categories. The navigation tracking judgment thresholds include the DVL wave velocity quality judgment threshold and the IMU acceleration change judgment threshold.

[0059] It should be noted that the DVL wave velocity quality judgment threshold and the IMU acceleration change judgment threshold are obtained from a preset database. The DVL wave velocity quality monitoring parameters within the historical time period are substituted into the specific constraint expression of the DVL wave velocity quality analysis coefficient to obtain a dataset of DVL wave velocity quality analysis coefficients. The average value of the dataset is then calculated to obtain the DVL wave velocity quality judgment threshold. Similarly, the IMU acceleration change monitoring parameters within the historical time period are substituted into the specific expression of the IMU acceleration change quantization value to obtain a dataset of IMU acceleration change quantization values. The average value of the dataset is then calculated to obtain the corresponding IMU acceleration change judgment threshold.

[0060] In the first case, if the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, the underwater tracking position correction scheme adopted is to continue monitoring the DVL wave velocity quality and the IMU acceleration change in the INS for the next underwater navigation tracking cycle, and at the same time perform underwater path position reliability analysis.

[0061] In the second case, if the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is the IMU acceleration correction scheme to correct the impact of IMU acceleration change on the underwater path tracking position, and at the same time, the underwater path position reliability analysis is performed.

[0062] In the third case, if the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is the DVL wave velocity quality correction scheme to correct the impact of DVL wave velocity quality fluctuations on the underwater path tracking position, and an underwater path position reliability analysis is performed.

[0063] In the fourth scenario, if the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, the underwater tracking position correction scheme adopted is to immediately issue a Level 1 warning to the vehicle pilot's operating interface and simultaneously perform an underwater path position reliability analysis. The Level 1 warning is used to provide feedback on the urgency of the current underwater path tracking position deviation, and the urgency represented by the Level 1, Level 2, and Level 3 warnings decreases progressively.

[0064] In this embodiment, by comparing the DVL wave velocity quality analysis coefficients and the IMU acceleration change quantization values ​​with preset thresholds, not only is accurate identification of different anomaly sources achieved, but misjudgments caused by fluctuations from a single sensor are also avoided, improving the accuracy and robustness of underwater path correction. For different combinations of DVL or IMU anomalies, either the IMU acceleration correction scheme or the DVL wave velocity quality correction scheme is executed, achieving directional correction, which helps reduce underwater path tracking deviation and improves the positioning accuracy of the vehicle. Furthermore, by combining underwater path position reliability analysis under each judgment condition, the accuracy of the corrected path can be dynamically evaluated, ensuring that the corrected result is not only numerically reasonable but also verifiable, thereby improving the overall reliability of the navigation system.

[0065] It should be noted that the specific details of the IMU acceleration correction scheme are as follows:

[0066] The difference between the quantized value of IMU acceleration change and the IMU acceleration change judgment threshold is calculated to obtain the corresponding IMU acceleration difference. The IMU acceleration difference is compared with the preset IMU acceleration difference boundary value. If the IMU acceleration difference is greater than the IMU acceleration difference boundary value, a prompt to determine the AUV position by referring to the DVL data source is triggered. Otherwise, the process noise covariance matrix influence is obtained by projecting the IMU acceleration difference into the preset process noise covariance matrix projection sequence, and the process noise covariance matrix influence is input to the filter to correct the process noise covariance matrix.

[0067] It should be explained that the corresponding IMU acceleration difference is obtained by subtracting the quantized value of the IMU acceleration change from the IMU acceleration change judgment threshold. Furthermore, the IMU acceleration difference boundary value is obtained from a preset database and is preset by professional technicians based on historical data and empirical rules.

[0068] It should be added that the influence of the process noise covariance matrix is ​​obtained from the process noise covariance matrix projection sequence in the preset database. The process noise covariance matrix projection sequence is used to reflect the mapping relationship between the IMU acceleration difference and the influence of the process noise covariance matrix. The process noise covariance matrix projection sequence is obtained by training the process noise covariance matrix training data. The process noise covariance matrix training data includes the IMU acceleration difference based on historical data of historical time periods, as well as the influence of the process noise covariance matrix set by professional technicians based on empirical rules.

[0069] In this embodiment, by comparing the IMU acceleration difference with the corresponding difference threshold, two different strategies—relying on the DVL reference or the filter matrix correction—can be automatically selected based on the degree of anomaly, improving the flexibility and intelligence of path correction. Simultaneously, when the IMU acceleration deviation is too large, a timely prompt from the reference DVL data source is triggered to prevent the spread of accumulated errors when the IMU operates alone. When the deviation is small, the process noise covariance matrix projection is used to correct and optimize the filter, which helps suppress small drifts and ensures the stability and accuracy of the positioning results. Furthermore, in cases of excessive IMU acceleration deviation, the reference DVL data source can be actively guided to make corrections, thereby preventing the overall navigation system from failing due to IMU inaccuracy and improving the overall reliability of AUV path tracking.

[0070] It should be noted that the specific details of the DVL wave velocity quality correction scheme are as follows:

[0071] The difference between the DVL wave velocity quality analysis coefficients and the DVL wave velocity quality judgment threshold is calculated to obtain the corresponding DVL wave velocity quality difference. The DVL wave velocity quality difference is compared with the preset DVL wave velocity quality difference boundary value. If the DVL wave velocity quality difference is greater than the DVL wave velocity quality difference boundary value, a prompt to determine the AUV location by referring to the INS data source is triggered. Otherwise, the influence of the observation noise covariance matrix is ​​obtained by matching the DVL wave velocity quality difference in the preset observation noise covariance matrix projection sequence, and the influence of the observation noise covariance matrix is ​​input to the filter to correct the observation noise covariance matrix.

[0072] It should be explained that the DVL wave velocity quality analysis coefficient is subtracted from the DVL wave velocity quality judgment threshold to obtain the corresponding DVL wave velocity quality difference. Furthermore, the DVL wave velocity quality difference boundary value is obtained from a preset database and is preset by professional technicians based on historical data and empirical rules.

[0073] It should be added that the influence of the observation noise covariance matrix is ​​obtained from the observation noise covariance matrix projection sequence in the preset database. The observation noise covariance matrix projection sequence is used to reflect the mapping relationship between the DVL wave velocity quality difference and the influence of the observation noise covariance matrix. The observation noise covariance matrix projection sequence is obtained by training the observation noise covariance matrix training data. The observation noise covariance matrix training data includes the DVL wave velocity quality difference based on historical data of historical time periods, as well as the influence of the observation noise covariance matrix set by professional technicians based on empirical rules.

[0074] In this embodiment, during DVL velocity quality correction, the difference between the DVL velocity quality difference threshold and the threshold value is used to determine whether the INS data source needs to be referenced. When the DVL fluctuation does not exceed the limit, the DVL velocity quality difference is matched with the observation noise covariance matrix projection sequence to correct the observation model, thereby improving the stability and robustness of the filter under DVL abnormal conditions. Based on the corresponding judgment result, the DVL velocity quality correction scheme is dynamically selected to be executed, or a warning prompt of the corresponding warning level is triggered, which is beneficial to improving the adaptability and processing efficiency of path correction under different abnormal conditions.

[0075] Furthermore, the specific steps for the underwater path location reliability analysis are as follows:

[0076] Step 1: Based on the DVL wave velocity quality analysis coefficient and the DVL wave velocity quality judgment threshold, obtain the DVL wave velocity quality offset value, which reflects the degree of deviation of the DVL wave velocity quality analysis coefficient relative to the DVL wave velocity quality judgment threshold; and based on the IMU acceleration change quantization value and the IMU acceleration change judgment threshold, obtain the IMU acceleration change offset value, which reflects the degree of deviation of the IMU acceleration change quantization value relative to the IMU acceleration change judgment threshold.

[0077] It should be added that the DVL wave velocity quality offset value represents the result of the ratio of the DVL wave velocity quality judgment threshold to the DVL wave velocity quality analysis coefficient after subtraction, and the IMU acceleration offset value represents the result of the ratio of the IMU acceleration change quantization value to the IMU acceleration change judgment threshold after subtraction, and the IMU acceleration change judgment threshold.

[0078] Step 2: After weighting the DVL wave velocity quality offset value and the IMU acceleration offset value using preset confidence impact parameters, the underwater path position confidence score is obtained by aggregation. The confidence impact parameters include the DVL wave velocity quality impact parameter and the IMU acceleration impact parameter. The underwater path position confidence score is used to reflect the reliability of the underwater path tracking position in the current underwater navigation tracking cycle.

[0079] Specifically, the reliability impact parameters are extracted from a preset database and pre-set by professional technicians based on the reliability of the DVL and INS data sources. The sum of the DVL wave velocity quality impact parameters and the IMU acceleration impact parameters is 1.

[0080] In this embodiment, by calculating the DVL wave velocity mass offset value and the IMU acceleration offset value, the deviation of each navigation data from its quality judgment threshold can be more accurately characterized, providing a quantifiable basis for subsequent underwater path position reliability assessment. At the same time, a preset reliability influence parameter is introduced to perform weighted fusion of the DVL and IMU offset values, which fully considers the contribution of the two types of sensors to navigation accuracy under different operating conditions, thereby generating a more objective and comprehensive path position reliability score. Furthermore, the aggregated path position reliability score can reflect the path tracking stability and reliability of the current navigation cycle in real time, which helps to dynamically adjust the navigation strategy and improve the practicality and adaptability of the underwater navigation system.

[0081] like Figure 3 The diagram shown is a flowchart illustrating the process of determining and implementing path stability correction measures according to an embodiment of the present invention. The specific logic is as follows: Underwater path position confidence scores for a preset number of underwater navigation tracking cycles are obtained and subjected to fluctuation quantization processing to obtain the corresponding underwater path tracking stability coefficient. This coefficient is then compared with an underwater path tracking stability judgment threshold. If the underwater path tracking stability coefficient is less than the threshold, the DVL wave velocity quality and IMU acceleration changes in the INS are monitored in the next underwater navigation tracking cycle. If the underwater path tracking stability coefficient is not less than the threshold, then... The underwater vehicle (AUV) pilot's interface issues a level-two warning and feeds back the current underwater path tracking stability coefficient. Simultaneously, a stability path correction amplitude influence factor is obtained by mapping the difference between the underwater path tracking stability coefficient and the critical value for underwater path tracking stability judgment. Based on this influence factor, a compensation calculation is performed on the preset correction amplitude to obtain the corresponding optimized correction amplitude. The path correction frequency of the AUV is then corrected using this optimized correction amplitude. Through this process, not only is the AUV's path correction adaptive capability improved, but the stability of the inertial navigation system's continuous positioning in complex marine environments is also ensured.

[0082] Furthermore, the specific procedure for determining whether to take path stability correction measures is as follows:

[0083] First, the underwater path position confidence score of a preset number of underwater navigation tracking cycles is obtained and fluctuation quantification is performed to obtain the corresponding underwater path tracking stability coefficient. The time length corresponding to the preset number of underwater navigation tracking cycles is the set time period.

[0084] It should be explained that the underwater path tracking stability coefficient is represented by the variance of the underwater path position confidence score over a preset number of underwater navigation tracking cycles.

[0085] Next, the underwater path tracking stability coefficient is compared with the set underwater path tracking stability judgment threshold; the underwater path tracking stability judgment threshold is preset by professional technicians and stored in a preset database.

[0086] If the underwater path tracking stability coefficient is less than the critical value for judging underwater path tracking stability, then continue to monitor the DVL wave velocity quality and the IMU acceleration changes in the INS during the next underwater navigation tracking cycle.

[0087] If the underwater path tracking stability coefficient is not less than the underwater path tracking stability judgment threshold, a level two warning is issued to the underwater vehicle operator's interface, and the current underwater path tracking stability coefficient is fed back to the operator's interface. Simultaneously, based on the difference between the underwater path tracking stability coefficient and the underwater path tracking stability judgment threshold, a stability path correction amplitude influence factor is obtained, reflecting the degree of stability difference to be corrected based on the underwater path tracking stability coefficient. The preset correction amplitude is then compensated based on the stability path correction amplitude influence factor to obtain the corresponding optimized correction amplitude. The path correction frequency of the AUV is corrected using the optimized correction amplitude. The compensation operation involves multiplying the stability path correction amplitude influence factor with the preset correction amplitude. The preset correction amplitude is pre-set by technical personnel and stored in a preset database, which can be directly retrieved during use. Next, the optimized correction amplitude is multiplied with the AUV's path correction frequency, and path correction is performed based on the path correction frequency corresponding to the product result.

[0088] It should be added that the difference between the underwater path tracking stability coefficient and the critical value for judging underwater path tracking stability is called the tracking stability difference. The tracking stability difference is input into the preset tracking stability mapping table for querying to obtain the corresponding stability path correction amplitude influence factor. The tracking stability mapping table is used to fit the mapping relationship between the tracking stability difference and the stability path correction amplitude influence factor. The tracking stability mapping table is trained based on tracking stability training data, which includes the tracking stability difference for historical time periods and the stability path correction amplitude influence factor set by professional technicians based on empirical rules.

[0089] In this embodiment, the stability coefficient is obtained by linearly fitting the path reliability scores of multiple underwater navigation tracking cycles within a preset time period. This dynamically measures the volatility of path tracking from a trend perspective, exhibiting higher robustness and accuracy compared to traditional single-point judgment methods. Simultaneously, by comparing the path tracking stability coefficient with a set threshold, the system automatically determines whether to trigger stability warnings and path correction compensation, constructing an intelligent judgment and dynamic response mechanism. This enhances the system's sensitivity to path anomalies and the timeliness of intervention. When the stability coefficient does not meet the threshold requirements, the system automatically triggers a secondary warning and feeds real-time data back to the operating interface, helping the driver to gain a more comprehensive understanding of the current navigation status and improving the targeting and effectiveness of manual decision-making intervention. Furthermore, by adjusting the path correction frequency based on the optimized correction amplitude results, the system can flexibly adjust the correction behavior rhythm according to the current environment and system state, improving the system's continuous positioning stability in complex or highly volatile underwater environments.

[0090] Furthermore, the specific process for determining whether to perform path correction adjustment is as follows:

[0091] The first step is to obtain the underwater path tracking stability coefficient for the next preset number of underwater navigation tracking cycles, and then quantify it proportionally with the underwater path tracking stability coefficient for the previous set time period to obtain the underwater path tracking stability change rate. In other words, the underwater path tracking stability coefficient is calculated by taking the ratio of the underwater path tracking stability coefficient to the underwater path tracking stability coefficient for the previous set time period to obtain the underwater path tracking stability change rate.

[0092] The second step is to compare the rate of change of underwater path tracking stability with the preset stability change judgment value:

[0093] If the rate of change in underwater path tracking stability exceeds the corresponding stability change judgment value, a level three warning is issued to the underwater vehicle operator's interface, and the current rate of change in underwater path tracking stability is fed back to the operator's interface. Simultaneously, a stability change path correction amplitude influence factor is obtained based on the difference between the rate of change in underwater path tracking stability and the corresponding stability change judgment value, reflecting the degree of underwater path tracking stability fluctuation that needs correction. The preset correction amplitude is then compensated based on this stability change path correction amplitude influence factor to obtain the corresponding adjustment correction amplitude. The path correction frequency of the AUV is corrected by adjusting the correction amplitude. Specifically, the compensation operation involves multiplying the stability change path correction amplitude influence factor by the preset correction amplitude, and then multiplying the adjustment correction amplitude by the AUV's path correction frequency. Path correction is then performed based on the path correction frequency corresponding to the product result.

[0094] It should be added that the difference between the underwater path tracking stability change rate and the stability change judgment quantity is called the tracking stability change difference. The tracking stability change difference is input into the preset tracking stability change mapping table for querying to obtain the corresponding stability change path correction amplitude influence factor. The tracking stability change mapping table is used to fit the mapping relationship between the tracking stability change difference and the stability change path correction amplitude influence factor. The tracking stability mapping table is trained based on tracking stability change training data. The tracking stability change training data includes the tracking stability change difference for historical time periods and the stability change path correction amplitude influence factor set by professional technicians based on empirical rules.

[0095] If the rate of change of underwater path tracking stability is not greater than the corresponding stability change judgment value, then continue to monitor the DVL wave velocity quality and the IMU acceleration change in the INS during the next underwater navigation tracking cycle.

[0096] In this embodiment, by acquiring the underwater path tracking stability coefficients for two consecutive preset time periods and performing proportional quantification, a "path stability change rate" index is constructed. This index judges the system state evolution trend from the perspective of change trend, which has a more dynamic perception capability compared to the single stability threshold judgment method. When the path tracking stability change rate exceeds the set judgment amount, the system automatically triggers a level three warning and feeds back the change rate to the operator interface in real time. This helps the operator quickly identify system operation fluctuations and take control measures. At the same time, by mapping the difference between the change rate and the judgment amount to the "stability change path correction amplitude influence factor", the original correction amplitude is dynamically compensated, resulting in a more accurate adjustment correction amplitude. This is beneficial to suppress path jitter or drift caused by over-correction or correction lag. The path correction frequency is adjusted in real time according to the adjusted correction amplitude, enabling the AUV to respond quickly when stability fluctuates continuously and avoid over-correction when stability recovers, demonstrating a higher adaptive path control capability.

[0097] Figure 4 This is a schematic diagram of the structure of an inertial navigation underwater path tracking system for complex marine environments provided in an embodiment of the present invention. (Refer to...) Figure 4 The system includes an AUV navigation monitoring module, an underwater tracking position correction module, an underwater path tracking stability analysis module, and an underwater path tracking stability change analysis module.

[0098] Among them, the AUV navigation monitoring module is used to monitor the changes in IMU acceleration and DVL wave velocity and mass fluctuation in the INS in real time during the AUV navigation process. It performs IMU acceleration change analysis to reflect the amplitude of IMU acceleration change fluctuation and DVL wave velocity and mass fluctuation analysis to characterize the DVL wave velocity and mass fluctuation.

[0099] The underwater tracking position correction module is used to make a dual judgment based on the results of IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis, so as to decide on the underwater tracking position correction scheme to correct the AUV's deviation in the underwater path, and at the same time perform underwater path position reliability analysis to reflect the reliability of the AUV's underwater path position.

[0100] The underwater path tracking stability analysis module is used to determine the stability of AUV underwater path position tracking by analyzing the reliability of underwater path position over a set time period, so as to determine whether to take path stability correction measures to reduce the degree of underwater path position drift.

[0101] The underwater path tracking stability change analysis module is used to analyze the stability changes of underwater path position tracking based on the stability of the underwater path position accuracy of AUVs in adjacent set time periods, thereby determining whether to perform path correction adjustment to improve the compatibility between underwater path correction frequency and underwater path position tracking stability.

[0102] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0103] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0104] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0105] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0106] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0107] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0108] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0109] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0110] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0111] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0112] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An inertial navigation underwater path tracking method for complex marine environments, characterized in that, The specific steps are as follows: During AUV navigation, the changes in IMU acceleration and DVL wave velocity and mass fluctuations in the INS are monitored in real time within the set underwater navigation tracking cycle. IMU acceleration change analysis is used to reflect the amplitude of IMU acceleration change fluctuations, and DVL wave velocity and mass fluctuation analysis is used to characterize the DVL wave velocity and mass fluctuations. The underwater tracking position correction scheme is determined by a dual assessment based on the results of IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis to correct the AUV's deviation in the underwater path. At the same time, an underwater path position reliability analysis is performed to reflect the reliability of the AUV's underwater path position. The stability of AUV underwater path position tracking is determined by analyzing the reliability of underwater path position over a set time period, so as to determine whether path stability correction measures should be taken to reduce the degree of underwater path position drift. Based on the stability of the underwater path position accuracy of the AUV in adjacent set time periods, an analysis of the stability changes in underwater path position tracking is conducted to determine whether to perform path correction adjustment to improve the compatibility between the underwater path correction frequency and the stability of underwater path position tracking.

2. The inertial navigation underwater path tracking method for complex marine environments according to claim 1, characterized in that, The specific process of the IMU acceleration change analysis is as follows: The underwater navigation tracking cycle is numbered and the IMU acceleration change monitoring parameters within the underwater navigation tracking cycle are acquired in real time. The IMU acceleration change monitoring parameters include the acceleration change rate and the acceleration variance. The deviation between the rate of change of acceleration and the rate of change of acceleration in the previous underwater navigation tracking cycle is calculated to obtain the corresponding rate of change of acceleration offset value. The difference ratio between the pre-extracted acceleration variance reference value and the acceleration variance is quantified to obtain the corresponding acceleration variance change ratio; Extract the pre-stored IMU acceleration change reference weights, which include acceleration change rate weights and acceleration variance weights; The acceleration change rate offset and acceleration variance change ratio are weighted and aggregated using IMU acceleration change reference weights to obtain the IMU acceleration change quantization value, which is used to quantify the magnitude of IMU acceleration change.

3. The inertial navigation underwater path tracking method for complex marine environments according to claim 1, characterized in that, The specific process of the DVL wave velocity quality fluctuation analysis is as follows: The DVL wave velocity quality monitoring parameters are acquired in real time during the underwater navigation tracking cycle. The DVL wave velocity quality monitoring parameters include echo intensity, echo-signal correlation, and SNR. The echo-signal correlation represents the correlation between the echo and the local signal. Query the pre-stored DVL wave velocity quality analysis factors, which include echo intensity analysis factors, echo-signal correlation analysis factors, and SNR analysis factors; The echo intensity is quantified by comparing its proportion with the echo intensity in the previous underwater navigation tracking cycle to obtain the proportion of echo intensity change. After normalizing the SNR, the DVL wave velocity quality analysis coefficients are obtained by weighting the echo intensity variation ratio, echo-signal correlation, and SNR based on the DVL wave velocity quality analysis factor. These coefficients are used to quantify the fluctuation of DVL wave velocity quality.

4. The inertial navigation underwater path tracking method for complex marine environments according to claim 3, characterized in that, The underwater tracking position correction scheme is determined by a dual assessment based on the results of IMU acceleration change analysis and DVL wave velocity-mass fluctuation analysis. The specific steps are as follows: The DVL wave velocity quality analysis coefficient and the IMU acceleration change quantization value are compared with the corresponding set navigation tracking judgment thresholds, which include the DVL wave velocity quality judgment threshold and the IMU acceleration change judgment threshold. If the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, the underwater tracking position correction scheme adopted is to continue monitoring the DVL wave velocity quality and the IMU acceleration change in the INS for the next underwater navigation tracking cycle, and at the same time perform underwater path position reliability analysis. If the DVL wave velocity quality analysis coefficient is greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is the IMU acceleration correction scheme to correct the impact of IMU acceleration change on the underwater path tracking position, and at the same time, the underwater path position reliability analysis is performed. If the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is less than the IMU acceleration change judgment threshold, then the underwater tracking position correction scheme is the DVL wave velocity quality correction scheme to correct the impact of DVL wave velocity quality fluctuations on the underwater path tracking position, and an underwater path position reliability analysis is performed. If the DVL wave velocity quality analysis coefficient is not greater than the DVL wave velocity quality judgment threshold and the IMU acceleration change quantization value is not less than the IMU acceleration change judgment threshold, the underwater tracking position correction scheme adopted is to immediately issue a first-level warning to the vehicle pilot's operating interface and at the same time conduct an underwater path position reliability analysis. The first-level warning is used to provide feedback on the urgency of the current underwater path tracking position deviation, and the urgency of the first-level warning, second-level warning and third-level warning decreases progressively.

5. The inertial navigation underwater path tracking method for complex marine environments according to claim 4, characterized in that, The specific details of the IMU acceleration correction scheme are as follows: The difference between the quantized value of IMU acceleration change and the IMU acceleration change judgment threshold is calculated to obtain the corresponding IMU acceleration difference. The IMU acceleration difference is compared with the preset IMU acceleration difference boundary value. If the IMU acceleration difference is greater than the IMU acceleration difference boundary value, a prompt to determine the AUV position by referring to the DVL data source is triggered. Otherwise, the process noise covariance matrix influence is obtained by projecting the IMU acceleration difference into the preset process noise covariance matrix projection sequence, and the process noise covariance matrix influence is input to the filter to correct the process noise covariance matrix.

6. The inertial navigation underwater path tracking method for complex marine environments according to claim 4, characterized in that, The specific details of the DVL wave velocity quality correction scheme are as follows: The difference between the DVL wave velocity quality analysis coefficients and the DVL wave velocity quality judgment threshold is calculated to obtain the corresponding DVL wave velocity quality difference. The DVL wave velocity quality difference is compared with the preset DVL wave velocity quality difference boundary value. If the DVL wave velocity quality difference is greater than the DVL wave velocity quality difference boundary value, a prompt to determine the AUV location by referring to the INS data source is triggered. Otherwise, the influence of the observation noise covariance matrix is ​​obtained by matching the DVL wave velocity quality difference in the preset observation noise covariance matrix projection sequence, and the influence of the observation noise covariance matrix is ​​input to the filter to correct the observation noise covariance matrix.

7. The inertial navigation underwater path tracking method for complex marine environments according to claim 4, characterized in that, The specific steps for the underwater path location reliability analysis are as follows: Based on the DVL wave velocity quality analysis coefficient and the DVL wave velocity quality judgment threshold, the DVL wave velocity quality offset value, which reflects the degree of deviation of the DVL wave velocity quality analysis coefficient relative to the DVL wave velocity quality judgment threshold, is obtained; and based on the IMU acceleration change quantization value and the IMU acceleration change judgment threshold, the IMU acceleration change quantization value, which reflects the degree of deviation of the IMU acceleration change quantization value relative to the IMU acceleration change judgment threshold, is obtained. The underwater path position reliability score is obtained by weighting the DVL wave velocity quality offset value and the IMU acceleration offset value through preset reliability influence parameters and then aggregating them. The reliability influence parameters include the DVL wave velocity quality influence parameter and the IMU acceleration influence parameter. The underwater path position reliability score is used to reflect the reliability of the underwater path tracking position in the current underwater navigation tracking cycle.

8. The inertial navigation underwater path tracking method for complex marine environments according to claim 1, characterized in that, The specific procedure for determining whether to take path stability correction measures is as follows: The underwater path position confidence score of a preset number of underwater navigation tracking cycles is obtained and fluctuation quantization is performed to obtain the corresponding underwater path tracking stability coefficient. The time length corresponding to the preset number of underwater navigation tracking cycles is a set time period. The underwater path tracking stability coefficient is compared with the set critical value for judging underwater path tracking stability: If the underwater path tracking stability coefficient is less than the underwater path tracking stability judgment threshold, then continue to monitor the DVL wave velocity quality and the IMU acceleration change in the INS during the next underwater navigation tracking cycle. If the underwater path tracking stability coefficient is not less than the underwater path tracking stability judgment threshold, a level two warning is issued to the underwater vehicle pilot's operating interface, and the current underwater path tracking stability coefficient is fed back to the underwater vehicle pilot's operating interface. At the same time, based on the difference between the underwater path tracking stability coefficient and the underwater path tracking stability judgment threshold, a stability path correction amplitude influence factor is obtained, which reflects the degree of stability difference that needs to be corrected based on the underwater path tracking stability coefficient. Based on the stability path correction amplitude influence factor, a compensation calculation is performed on the preset correction amplitude to obtain the corresponding optimized correction amplitude. The path correction frequency of the AUV is corrected by optimizing the correction amplitude.

9. The inertial navigation underwater path tracking method for complex marine environments according to claim 1, characterized in that, The specific process for determining whether to perform path correction adjustment is as follows: Obtain the underwater path tracking stability coefficient for the next preset number of underwater navigation tracking cycles, and proportionally quantize it with the underwater path tracking stability coefficient for the previous set time period to obtain the underwater path tracking stability change rate. The rate of change of underwater path tracking stability is compared with the preset stability change judgment value: If the rate of change of underwater path tracking stability is greater than the corresponding stability change judgment value, a level 3 warning is issued to the underwater vehicle operator's interface, and the current rate of change of underwater path tracking stability is fed back to the underwater vehicle operator's interface. At the same time, based on the difference between the rate of change of underwater path tracking stability and the corresponding stability change judgment value, a stability change path correction amplitude influence factor is obtained, which reflects the degree of underwater path tracking stability fluctuation that needs to be corrected based on the rate of change of underwater path tracking stability. Based on the stability change path correction amplitude influence factor, a compensation calculation is performed on the preset correction amplitude to obtain the corresponding adjustment correction amplitude. The path correction frequency of the AUV is corrected by adjusting the correction amplitude. If the rate of change of underwater path tracking stability is not greater than the corresponding stability change judgment value, then continue to monitor the DVL wave velocity quality and the IMU acceleration change in the INS during the next underwater navigation tracking cycle.

10. An inertial navigation underwater path tracking system for complex marine environments, characterized in that, It includes an AUV navigation monitoring module, an underwater tracking position correction module, an underwater path tracking stability analysis module, and an underwater path tracking stability change analysis module; The AUV navigation monitoring module is used to monitor the changes in IMU acceleration and DVL wave velocity and mass fluctuation in the INS in real time during the AUV navigation process. It performs IMU acceleration change analysis to reflect the amplitude of IMU acceleration change fluctuation and DVL wave velocity and mass fluctuation analysis to characterize the DVL wave velocity and mass fluctuation. The underwater tracking position correction module is used to make dual judgments based on the results of IMU acceleration change analysis and DVL wave velocity quality fluctuation analysis, thereby deciding on the underwater tracking position correction scheme to correct the AUV's deviation in the underwater path, and at the same time performing underwater path position reliability analysis to reflect the reliability of the AUV's underwater path position. The underwater path tracking stability analysis module is used to determine the stability of AUV underwater path position tracking by analyzing the reliability of underwater path position over a set time period, so as to determine whether to take path stability correction measures to reduce the degree of underwater path position drift. The underwater path tracking stability change analysis module is used to analyze the stability change of underwater path position tracking based on the stability of the underwater path position accuracy of AUV in adjacent set time periods, so as to determine whether to perform path correction adjustment to improve the compatibility between underwater path correction frequency and underwater path position tracking stability.

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