Seeker tracking precision compensation method and system based on real-time feedback adjustment

Abstract

The invention relates to the technical field of seeker tracking precision compensation, in particular to a seeker tracking precision compensation method and system based on real-time feedback regulation, and the method comprises the steps: obtaining the real-time position deviation data of a seeker, generating a deviation signal, generating a compensation instruction through a dynamic compensation rule, and injecting the compensation instruction into a servo control system, and a real-time feedback module is used for monitoring an output state, extracting dynamic characteristic parameters, optimizing a compensation rule and correcting a motion track in real time. Through a real-time feedback and dynamic optimization mechanism, the tracking precision, the response speed and the dynamic adaptive capacity of the seeker under complex working conditions are remarkably improved, and the high-performance requirement is met.

Description

Technical Field

[0001] The present invention belongs to the technical field of seeker tracking accuracy compensation, and specifically relates to a seeker tracking accuracy compensation method and system based on real-time feedback regulation. Background Technique

[0002] With the continuous development of seeker tracking technology, high-precision and high-synchronization tracking control has become a key technical requirement in fields such as radar seekers and missile servo systems. However, in practical applications, due to factors such as friction, non-linear dynamic characteristics, and external disturbances, the accuracy and stability of the seeker tracking system are often difficult to reach the ideal level. Although existing technical solutions have solved some problems to a certain extent, there are still deficiencies.

[0003] For example, the patent with the publication number CN114578694B proposes an adaptive friction compensation control method based on the dynamic model of a dual-drive tracking platform and the LuGre friction model, which improves the tracking accuracy and synchronization accuracy through the derivation of an asymptotically stable control law. However, this solution has high requirements for the accuracy of the dynamic model, does not fully consider the impact of external real-time disturbances on system performance, and has limited adaptability to unknown or time-varying friction characteristics, restricting its applicability in complex environments.

[0004] In addition, the patent with the publication number CN108674634B provides a compensation method based on an experimentally identified friction model to improve the position tracking accuracy of the aircraft's active side stick system. However, this method mainly relies on static or quasi-static friction models, lacks the effective use of real-time feedback information, has insufficient adaptability to friction changes under high-frequency dynamic working conditions, and may lead to a decrease in tracking accuracy. The above problems indicate that existing seeker tracking accuracy compensation technologies still have obvious deficiencies in terms of real-time performance, dynamic adaptability, and anti-interference ability to external disturbances. Therefore, there is an urgent need for a seeker tracking accuracy compensation method and system based on real-time feedback regulation to improve the accuracy, stability, and adaptability of the system and meet the high-performance requirements under complex working conditions. Summary of the Invention

[0005] The present invention provides a seeker tracking accuracy compensation method and system based on real-time feedback regulation, and its main purpose is to improve the tracking accuracy and dynamic adaptability of the seeker under complex working conditions.

[0006] To achieve the above purpose, a seeker tracking accuracy compensation method based on real-time feedback regulation provided by the present invention includes: Obtain the real-time position deviation data during the movement of the seeker to obtain a deviation signal; Process the deviation signal according to a preset dynamic compensation rule to generate a compensation instruction, and inject the compensation instruction into the servo control system; Use a real-time feedback module to monitor the output state of the servo control system to obtain state response data; Extract features from the state response data to obtain dynamic characteristic parameters; Adjust the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameters to obtain an optimized compensation rule; Use the optimized compensation rule to perform real-time correction on the motion trajectory of the seeker to obtain a corrected tracking result.

[0007] Optionally, the processing the deviation signal according to a preset dynamic compensation rule to generate a compensation instruction includes: Collect real-time motion data of the seeker through a multi-channel sensor; Analyze the deviation between the real-time motion data and the target trajectory in combination with a preset dynamic compensation rule to generate a compensation instruction.

[0008] Optionally, the injecting the compensation instruction into the servo control system includes: Perform signal smoothing processing on the compensation instruction to obtain a smoothed instruction; Decompose the smoothed instruction into multiple sub-instructions and inject them into the corresponding execution units of the servo control system respectively.

[0009] Optionally, the using a real-time feedback module to monitor the output state of the servo control system includes: Start the real-time feedback module to obtain the real-time output signal of the servo control system; Perform filtering processing on the real-time output signal to obtain filtered state response data.

[0010] Optionally, the extracting features from the state response data to obtain dynamic characteristic parameters includes: Perform segmentation processing on the state response data to obtain time series segments; Construct a dynamic characteristic model according to the time series segments; Extract key parameters from the dynamic characteristic model to obtain dynamic characteristic parameters.

[0011] Optionally, before adjusting the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameters, the method further includes: Collect historical deviation data under various working conditions, classify and organize the historical deviation data to obtain a classified data set; Use the classified data set to perform offline training on the initial dynamic compensation rule to obtain a preliminarily optimized dynamic compensation rule; Verify the performance of the preliminary optimized dynamic compensation rule through simulation tests; If the performance does not meet the preset standard, adjust the training dataset and retrain until the performance requirements are met.

[0012] Optionally, the real-time correction of the motion trajectory of the seeker using the optimized compensation rule includes: Calculate the correction amount according to the optimized compensation rule; Superimpose the correction amount on the control input signal of the seeker to complete real-time correction.

[0013] To solve the above problems, the present invention also provides a seeker tracking accuracy compensation system based on real-time feedback regulation, and the system includes: A deviation acquisition module for acquiring real-time position deviation data during the movement of the seeker to obtain a deviation signal; A compensation generation module for processing the deviation signal according to a preset dynamic compensation rule to generate a compensation instruction and injecting the compensation instruction into the servo control system; A state monitoring module for monitoring the output state of the servo control system using a real-time feedback module to obtain state response data; A feature extraction module for extracting features from the state response data to obtain dynamic characteristic parameters; A rule optimization module for adjusting the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameters to obtain an optimized compensation rule; A trajectory correction module for performing real-time correction on the motion trajectory of the seeker using the optimized compensation rule to obtain a corrected tracking result.

[0014] In the embodiment of the present invention, by acquiring the real-time position deviation data of the seeker, generating a compensation instruction in combination with the dynamic compensation rule and injecting it into the servo control system, the response speed and accuracy of the system are improved. Using the real-time feedback module to monitor the state response data of the servo control system, extracting dynamic characteristic parameters and optimizing the compensation rule further enhances the dynamic adaptability of the system. Finally, using the optimized compensation rule to perform real-time correction on the motion trajectory of the seeker significantly improves the tracking accuracy and stability. Therefore, the seeker tracking accuracy compensation method and system based on real-time feedback regulation proposed by the present invention can effectively meet the high-performance requirements under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic flowchart of a seeker tracking accuracy compensation method based on real-time feedback regulation provided by an embodiment of the present invention; Figure 2Schematic flowchart of the dynamic compensation rule optimization process provided by an embodiment of the present invention; Figure 3 Functional block diagram of a seeker tracking accuracy compensation system based on real-time feedback regulation provided by an embodiment of the present invention. Detailed implementation manners

[0016] The present invention provides a seeker tracking accuracy compensation method and system based on real-time feedback regulation, aiming to significantly improve the tracking accuracy and dynamic adaptability of the seeker under complex working conditions through dynamic compensation rules and real-time feedback mechanisms. The following combines the attached Figure 1 to the attached Figure 3 to describe the detailed implementation manners of the present invention in detail.

[0017] First, the implementation process of a seeker tracking accuracy compensation method based on real-time feedback regulation is introduced. As Figure 1 shown, this method starts from obtaining real-time position deviation data during the movement of the seeker. Specifically, the deviation acquisition module collects real-time motion data through multi-channel sensors installed on the seeker, and these sensors include but are not limited to accelerometers, gyroscopes, and optical sensors. After the data collected by the sensors is preprocessed, the actual position information of the seeker is extracted and compared with the target trajectory to generate a deviation signal. The deviation signal is the core input data for subsequent compensation operations, and its accuracy directly affects the performance of the entire system.

[0018] Next, the deviation signal is processed according to preset dynamic compensation rules to generate a compensation instruction. This process is completed by the compensation generation module. The design of the dynamic compensation rules is based on a preliminary optimization model trained from historical data, and is adjusted online in combination with real-time collected motion data. For example, assuming the deviation signal is Δx(t), the compensation instruction u(t) can be calculated by the following formula: ; where , and are the proportional, integral, and differential coefficients respectively. The initial values of these parameters come from the offline training stage. By classifying and organizing historical deviation data under various working conditions and establishing a classification data set, machine learning algorithms are used to train the initial dynamic compensation rules, and finally a preliminary optimized dynamic compensation rule is formed. This rule will be further adjusted according to real-time feedback during actual application to ensure its adaptability.

[0019] The generated compensation command needs to be injected into the servo control system to achieve the correction of the seeker movement. To ensure the smoothness and execution efficiency of the compensation command, signal smoothing processing is required before injection. Specifically, the compensation generation module performs low-pass filtering on the compensation command to remove high-frequency noise and obtain a smooth command. Subsequently, the smooth command is decomposed into multiple sub-commands, which respectively correspond to different execution units of the servo control system, such as motor drivers or hydraulic actuators. Each sub-command is injected into the corresponding execution unit through an independent control channel, thereby achieving precise control of the seeker movement.

[0020] After the compensation command is injected into the servo control system, the status monitoring module activates the real-time feedback module to monitor the output status of the servo control system. The real-time feedback module collects the real-time output signals of the servo control system through high-precision sensors, such as motor speed, actuator displacement, etc. The collected signals usually contain certain noise, so filtering processing is required. Digital filtering algorithms, such as Kalman filtering or wavelet transform, are used for filtering to extract effective state response data. The state response data reflects the actual operating state of the servo control system under the action of the current compensation command and is an important basis for subsequent feature extraction and rule optimization.

[0021] After being processed by the feature extraction module, the state response data can obtain dynamic characteristic parameters. The process of feature extraction includes segmenting the state response data, dividing the continuous time series into several segments. Each segment of data is regarded as an independent time series segment for constructing a dynamic characteristic model. The dynamic characteristic model can adopt the ARMA (AutoRegressive Moving Average) model or other suitable mathematical modeling methods. By analyzing the parameters of the model, such as the order, coefficients, and residual distribution of the model, key parameters are extracted as dynamic characteristic parameters. These parameters can reflect the dynamic behavior characteristics of the servo control system under the current working conditions and provide a basis for subsequent optimization of the dynamic compensation rules.

[0022] After obtaining the dynamic characteristic parameters, the rule optimization module adjusts the parameter configuration of the dynamic compensation rules according to these parameters to obtain optimized compensation rules. The adjustment process includes recalculating the proportional, integral, and differential coefficients in the dynamic compensation rules. For example, if the dynamic characteristic parameters indicate that the response speed of the servo control system is slow, the proportional coefficient is appropriately increased to improve the response speed; if there is a large steady-state error in the system, the integral coefficient is increased to reduce the error; if the system shows oscillation phenomena, the differential coefficient is decreased to suppress the oscillation. The optimized compensation rules can better adapt to the current working conditions, thereby improving the overall performance of the system.

[0023] Finally, the trajectory correction module uses the optimized compensation rule to perform real-time correction on the motion trajectory of the seeker. Specifically, the correction amount Δu(t) is calculated according to the optimized compensation rule and superimposed on the control input signal of the seeker. The superimposed control signal acts on the seeker through the servo control system, making its motion trajectory gradually approach the target trajectory. The correction process is a closed-loop control process. By continuously iterating and optimizing the compensation rule and the correction amount, a high-precision tracking effect is finally achieved.

[0024] The specific implementation of the above method can be further illustrated in combination with the actual application scenario. For example, in a missile guidance system, the seeker needs to accurately track the target during high-speed flight. Due to the complex and changeable flight environment, traditional fixed compensation rules are difficult to meet the high-performance requirements. The compensation method based on real-time feedback regulation proposed by the present invention can adapt to different flight conditions by dynamically adjusting the compensation rule. For example, when the missile enters the atmosphere, due to the influence of air resistance and temperature changes, the motion characteristics of the seeker will change significantly. At this time, the real-time feedback module can quickly capture these changes and adjust the compensation rule through the feature extraction and rule optimization module to ensure that the seeker always maintains high-precision tracking performance.

[0025] In addition, the present invention also provides a seeker tracking accuracy compensation system based on real-time feedback regulation, and its functional modules are as Figure 3 shown. The system includes a deviation acquisition module, a compensation generation module, a state monitoring module, a feature extraction module, a rule optimization module, and a trajectory correction module. Each module communicates through a data bus to form a complete closed-loop control system. The deviation acquisition module is responsible for collecting real-time position deviation data, the compensation generation module generates compensation instructions, the state monitoring module monitors the output state of the servo control system, the feature extraction module extracts dynamic characteristic parameters, the rule optimization module adjusts the compensation rule, and the trajectory correction module completes the real-time correction of the motion trajectory. Each module works together to jointly achieve the dynamic compensation of the seeker tracking accuracy.

[0026] In summary, the present invention obtains the real-time position deviation data of the seeker, generates compensation instructions in combination with the dynamic compensation rule and injects them into the servo control system, improving the response speed and accuracy of the system. The real-time feedback module is used to monitor the state response data of the servo control system, extract dynamic characteristic parameters and optimize the compensation rule, further enhancing the dynamic adaptability of the system. Finally, the optimized compensation rule is used to perform real-time correction on the motion trajectory of the seeker, significantly improving the tracking accuracy and stability. Therefore, the seeker tracking accuracy compensation method and system based on real-time feedback regulation proposed by the present invention can effectively meet the high-performance requirements under complex working conditions.

Claims

1. A seeker tracking accuracy compensation method based on real-time feedback adjustment, characterized in that: The method comprises: Acquire the real-time position deviation data of the seeker during its movement and obtain a deviation signal; Processing the deviation signal according to a preset dynamic compensation rule, generating a compensation instruction, and injecting the compensation instruction into a servo control system; Using a real-time feedback module to monitor the output state of the servo control system to obtain state response data; Extracting features from the state response data to obtain dynamic characteristic parameters; Adjusting the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameter to obtain an optimized compensation rule; The optimized compensation rule is used to perform real-time correction on the motion trajectory of the seeker to obtain a corrected tracking result.

2. The method for compensation of tracking accuracy of a seeker based on real-time feedback adjustment according to claim 1, characterized in that: The step of processing the deviation signal according to a preset dynamic compensation rule to generate a compensation instruction includes: Collect real-time motion data of the seeker through multi-channel sensors; The deviation between the real-time motion data and the target trajectory is analyzed in combination with a preset dynamic compensation rule to generate a compensation instruction.

3. The seeker tracking accuracy compensation method based on real-time feedback adjustment as claimed in claim 1, characterized in that: The step of injecting the compensation instruction into the servo control system comprises: Performing signal smoothing processing on the compensation instruction to obtain a smoothed instruction; The smoothing instruction is decomposed into a plurality of sub-instructions, and the sub-instructions are respectively injected into corresponding execution units of the servo control system.

4. The seeker tracking accuracy compensation method based on real-time feedback adjustment as claimed in claim 1, characterized in that: The method of monitoring the output state of the servo control system by using a real-time feedback module includes: Start the real-time feedback module to obtain the real-time output signal of the servo control system; The real-time output signal is filtered to obtain filtered state response data.

5. The method for compensation of tracking accuracy of a seeker based on real-time feedback adjustment according to claim 1, characterized in that: The extracting features of the state response data to obtain dynamic characteristic parameters includes: Segmenting the state response data to obtain time series segments; constructing a dynamic characteristic model based on the time series fragments; Key parameters are extracted from the dynamic characteristic model to obtain dynamic characteristic parameters.

6. The method for compensation of tracking accuracy of a seeker based on real-time feedback adjustment according to claim 1, characterized in that: Before adjusting the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameter, the method further includes: Collecting historical deviation data under various working conditions, classifying and arranging the historical deviation data to obtain a classified data set; The initial dynamic compensation rule is trained offline using the classified data set to obtain a preliminary optimized dynamic compensation rule; Verifying the performance of the initially optimized dynamic compensation rule through simulation testing; If the performance does not meet the preset standard, the training data set is adjusted and retrained until the performance requirements are met.

7. The seeker tracking accuracy compensation method based on real-time feedback adjustment as claimed in claim 1, characterized in that: The method of using the optimized compensation rule to correct the motion trajectory of the seeker in real time includes: Calculating a correction amount according to the optimized compensation rule; The correction amount is superimposed on the control input signal of the seeker to complete the real-time correction.

8. A seeker tracking accuracy compensation system based on real-time feedback adjustment, characterized in that: The system comprises: The deviation acquisition module is used to acquire the real-time position deviation data of the seeker during its movement and obtain a deviation signal; A compensation generation module, used for processing the deviation signal according to a preset dynamic compensation rule, generating a compensation instruction, and injecting the compensation instruction into a servo control system; A state monitoring module, used to monitor the output state of the servo control system using a real-time feedback module to obtain state response data; A feature extraction module, used to extract features from the state response data to obtain dynamic characteristic parameters; A rule optimization module, used to adjust the parameter configuration of the dynamic compensation rule according to the dynamic characteristic parameters to obtain an optimized compensation rule; The trajectory correction module is used to use the optimized compensation rule to perform real-time correction on the motion trajectory of the seeker to obtain a corrected tracking result.

9. The seeker tracking accuracy compensation system based on real-time feedback adjustment as claimed in claim 8, characterized in that: The compensation generating module comprises a signal smoothing unit, which is used to perform signal smoothing processing on the compensation instruction to obtain a smoothed instruction.

10. The seeker tracking accuracy compensation system based on real-time feedback adjustment according to claim 8, characterized in that: The state monitoring module includes a filtering unit, which is used to filter the real-time output signal of the servo control system to obtain filtered state response data.

Images