A method for tracking signal compensation of shipboard defense

Abstract

The application relates to the technical field of electronic engineering, and discloses a tracking signal compensation method for shipborne defense, which comprises the following steps: S1, flying object identification, identifying the direction and shape of a flying object; S2, flying object confirmation, further confirming the identity of the flying object; S3, environment condition correction, using environment sensing technology to sense and monitor environment changes so as to more accurately correct sensor data; S4, interference and interference countermeasures, interfering with the flying object. And the flying object is prevented from interfering with detection, so that the detection precision is not reduced. Through the use of adaptive signal processing technology, environment sensing algorithm and temperature stabilization technology, automatic adjustment can be carried out according to different environments, different working conditions are adapted to, the performance of the system can be maintained under different temperature conditions, and the target flying object can be predicted for multiple times according to the harsh environment, so that the prediction precision is ensured.

Description

Technical Field

[0001] This invention relates to the field of electronic engineering technology, specifically to a method for compensating tracking signals in shipborne defense. Background Technology

[0002] With the development of the times and the process of globalization, ocean voyages are becoming increasingly important. Multinational corporations use ships to transport goods, and tourists use ships to continue their international travels. Therefore, the safe navigation of ships is very important. Due to the many unstable factors on the sea, in order to prevent ships from being damaged remotely, people generally install shipboard defense systems on ships. These systems identify flying objects and intercept dangers. In order to ensure successful defense, a tracking signal compensation system is usually installed. This system uses a Kalman filter to improve the tracking accuracy of targets, thus making the defense more secure.

[0003] However, in practical applications, the complex marine environment and adverse weather conditions can affect the visibility, stability, and accuracy of sensors. Furthermore, atmospheric refraction and scattering can influence electromagnetic wave propagation, thus impacting sensor performance. Atmospheric turbulence can cause signal distortion and fluctuations, affecting sensor resolution and accuracy. Consequently, ship tracking signals may be inaccurate, leading to delayed defense or failure to react in time to potential danger. Therefore, this paper proposes a tracking signal compensation method for shipborne defense to address these issues. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a tracking signal compensation method for shipborne defense, which solves the problem that existing technologies are affected by severe weather, resulting in inaccurate tracking signals and consequently, untimely defense or failure to respond to defenses when no danger has occurred.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a tracking signal compensation method for shipborne defense, comprising the following steps:

[0006] S1. Flying object identification: Identifying the location and shape of flying objects;

[0007] S2. Object Confirmation: Further identification of the object.

[0008] S3. Environmental condition correction: Utilizes environmental sensing technology to sense and monitor environmental changes in order to more accurately correct sensor data.

[0009] S4. Interference and countermeasures: Interfering with flying objects and preventing them from interfering with detection, thus ensuring that detection accuracy is not reduced;

[0010] S5. Motion prediction: Based on the target's current state, predict the target's future position.

[0011] S6. Continuous verification and testing: Conduct continuous verification and testing of the system to confirm the authenticity of the flying object information;

[0012] S7. The command is transmitted to the defense system, and the calculated signal compensation parameters are transmitted to the defense system to adjust the parameters of the defense system to ensure that the target can be accurately tracked and intercepted.

[0013] S8. Field verification and optimization: Collect actual defense data and optimize the sensor fusion algorithm based on the results to ensure that the defense system can still be used effectively under constantly changing conditions.

[0014] Preferably, step S1 includes radar detection and visual detection;

[0015] The radar detection involves using radar to confirm the location of the flying object;

[0016] The visual inspection confirms the approximate shape of the flying object by using an image recognition module.

[0017] Preferably, step S3 includes adaptive signal processing technology, environmental perception algorithm, and temperature stabilization technology;

[0018] The adaptive signal processing technology dynamically adjusts signal processing parameters according to real-time environmental conditions.

[0019] The environmental perception algorithm adjusts the sensor's operating parameters according to environmental changes to adapt to different working conditions;

[0020] The temperature stabilization technology ensures that the sensor can maintain the system's performance under different temperature conditions.

[0021] Preferably, step S4 includes electronic jamming and infrared and optical countermeasures;

[0022] The electronic jamming can emit electronic countermeasures signals to interfere with the radar and communication systems of flying objects;

[0023] The infrared and optical countermeasures employ strong light and lasers while releasing a large amount of heat to disorient the target flying object.

[0024] Preferably, the electronic interference includes frequency hopping and jamming frequency-modulated radar;

[0025] The frequency switching can make communication signals jump between different frequencies, making it difficult for the enemy to lock on and interfere with them;

[0026] The aforementioned frequency modulation jamming radar allows ships to interfere with the radar systems of target aircraft by adjusting the radar transmission frequency.

[0027] Preferably, step S5 includes an adaptive filtering algorithm, a motion model, and a target prediction algorithm;

[0028] The adaptive filtering algorithm can adjust and optimize sensor data in real time in dynamic environments, and can respond more flexibly to environmental changes and sensor errors.

[0029] The motion model and target prediction algorithm introduce a more complex and accurate target motion model, combined with an advanced target prediction algorithm, to more accurately estimate the future position and state of the target.

[0030] Preferably, step S5 further includes acquiring current state information, selecting motion model, updating and predicting state, time stepping, estimating and correcting error, and outputting prediction results;

[0031] The current status information acquisition refers to acquiring the current status information of the target;

[0032] The motion model selection process involves the system using a predefined motion model to describe the motion patterns of the target.

[0033] The state update and prediction, based on the current state information and the selected motion model, uses mathematical equations to update the target's state and predict its future position;

[0034] The time step is used to calculate the target's position at a future time point;

[0035] The error estimation and correction are used to correct the prediction and improve accuracy;

[0036] The output prediction result is the location information of the target at a future time point.

[0037] Preferably, step S6 includes field testing and simulation testing;

[0038] The field test can demonstrate multiple hits on the target flying object, thereby determining the true information of the target flying object;

[0039] The simulation test can detect the electromagnetic signal of the target flying object and compare it with the electromagnetic signal of a known flying object to determine the true information of the target flying object.

[0040] Preferably, step S8 includes target recognition and tracking, environmental perception and prediction, data processing and optimization, and adaptive system design;

[0041] The target recognition and tracking, deep learning and neural networks can be used to improve the accuracy and stability of the system in identifying targets;

[0042] The aforementioned environmental perception and prediction utilizes models such as recurrent neural networks (RNNs) or long short-term memory networks (LSTMs), enabling shipborne systems to better understand the dynamic changes in the environment.

[0043] The data processing and optimization mentioned above, deep learning can be used to optimize the processing and parsing of sensor data, which can improve the speed and accuracy of data processing and quickly and accurately extract target information;

[0044] The adaptive system design utilizes deep reinforcement learning, enabling the system to learn and adjust its operating methods to adapt to different environments and threats.

[0045] This invention provides a tracking signal compensation method for shipborne defense. It has the following beneficial effects:

[0046] 1. This invention utilizes adaptive signal processing technology, environmental perception algorithms, and temperature stabilization technology to automatically adjust to different environments and adapt to varying working conditions. This ensures that the sensor maintains system performance under different temperature conditions and enables multiple predictions of target flying objects in harsh environments, thereby guaranteeing prediction accuracy.

[0047] 2. By using target recognition and tracking, environmental perception and prediction, data processing and optimization, and adaptive system design, this invention can analyze and learn from the detected data and interception results. Through continuous learning, it can more accurately detect different flying objects and quickly formulate corresponding interception plans, ensuring detection accuracy while also providing high flexibility and reducing interception costs. Detailed Implementation

[0048] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the specification of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Example 1:

[0050] This invention provides a tracking signal compensation method for shipborne defense, comprising the following steps:

[0051] S1. Flying object identification: Identifying the location and shape of flying objects;

[0052] S2. Object Confirmation: Further identification of the object.

[0053] S3. Environmental condition correction: Utilizes environmental sensing technology to sense and monitor environmental changes in order to more accurately correct sensor data.

[0054] S4. Interference and countermeasures: Interfering with flying objects and preventing them from interfering with detection, thus ensuring that detection accuracy is not reduced;

[0055] S5. Motion prediction: Based on the target's current state, predict the target's future position.

[0056] S6. Continuous verification and testing: Conduct continuous verification and testing of the system to confirm the authenticity of the flying object information;

[0057] S7. The command is transmitted to the defense system, and the calculated signal compensation parameters are transmitted to the defense system to adjust the parameters of the defense system to ensure that the target can be accurately tracked and intercepted.

[0058] S8. Field verification and optimization: Collect actual defense data and optimize the sensor fusion algorithm based on the results to ensure that the defense system can still be used effectively under constantly changing conditions.

[0059] Specifically, when intercepting a target flying object, the system first performs basic position and shape identification to determine the interception direction and identifies potential intercepted objects and corresponding interception plans. Then, based on confirmation of the flying object's identity information, an appropriate interception plan is selected. The system then senses the environment around the ship and the flying object to avoid interception errors and applies electronic interference to deviate its flight trajectory, counteracting the interference to prevent errors in detection information. The system also predicts the flying object's trajectory, enabling early interception. By continuously verifying the flying object's identity information, its accuracy is ensured. When the flying object moves into the interception range, its data is transmitted to the defense system, allowing for interception. After interception, the system analyzes and learns from the process, enabling faster interception in similar situations in the future.

[0060] Step S1 includes radar detection and visual detection;

[0061] Radar detection, which uses radar to confirm the location of a flying object;

[0062] Visual inspection uses an image recognition module to confirm the approximate shape of the flying object.

[0063] Specifically, radar can detect distant targets and track their movement, thereby providing crucial early warning and target information. The image recognition module, using cameras, infrared cameras, etc., can provide rich image information for target detection, tracking, recognition, and scene understanding. This enables the system to identify the position and shape of target flying objects, allowing the defense system to develop defense plans against several possible flying objects.

[0064] Step S3 includes adaptive signal processing technology, environmental perception algorithm, and temperature stabilization technology.

[0065] Adaptive signal processing technology dynamically adjusts signal processing parameters based on real-time environmental conditions;

[0066] Environmental perception algorithms adjust the sensor's operating parameters according to environmental changes to adapt to different working conditions;

[0067] Temperature stabilization technology ensures that the sensor can maintain system performance under different temperature conditions.

[0068] Specifically, adaptive signal processing technology uses adaptive filtering algorithms to adjust and optimize sensor data in real time in dynamic environments to detect and counteract signal distortion caused by weather, electromagnetic interference, or other environmental factors. It can respond more flexibly to environmental changes and sensor errors. Environmental perception algorithms can monitor and analyze atmospheric conditions, ocean conditions, and electromagnetic environment in real time, and adjust the sensor's operating parameters according to environmental changes to adapt to different operating conditions. Temperature stabilization technology can address the impact of temperature changes on the performance of electronic components, enabling the sensor's cooling or heating system to maintain system performance under different temperature conditions, thereby increasing detection accuracy and ensuring that the interception success rate of the defense system is not affected.

[0069] Step S4 includes electronic jamming and infrared and optical countermeasures;

[0070] Electronic jamming can transmit electronic countermeasures signals to interfere with the radar and communication systems of aircraft.

[0071] Infrared and optical countermeasures are used, employing strong light and lasers while releasing a large amount of heat to disorient the target flying object.

[0072] Specifically, by using strong light and lasers and releasing a large amount of heat, the radar system of the target flying object will be damaged, causing it to deviate from the preset route and thus ensuring the safety of the ship's navigation.

[0073] Electronic jamming includes frequency hopping and jamming frequency-modulated radar;

[0074] Frequency hopping allows communication signals to jump between different frequencies, making it difficult for the enemy to lock onto and jam them;

[0075] Interfering with frequency-modulated radar: By adjusting the radar's transmission frequency, ships can interfere with the radar system of target aircraft.

[0076] Specifically, by using frequency hopping in conjunction with jamming frequency-modulated radar, the radar system of the target aircraft will be confused, making it impossible for the target aircraft to lock onto the ship. This will cause the target aircraft's flight path to deviate. When the deviation angle is large, there is no need to intercept it, thereby improving the ship's navigation safety and reducing the interception cost.

[0077] Step S5 includes an adaptive filtering algorithm, a motion model, and a target prediction algorithm.

[0078] Adaptive filtering algorithms can adjust and optimize sensor data in real time in dynamic environments, and can respond more flexibly to environmental changes and sensor errors.

[0079] Motion models and target prediction algorithms are introduced, with more complex and accurate target motion models combined with advanced target prediction algorithms to more accurately estimate the future position and state of the target.

[0080] Specifically, by analyzing data such as the surrounding environment, flight speed, and mass of the target flying object, the flight path can be predicted, and the target flying object can be intercepted in advance to ensure the safety of ship navigation.

[0081] Step S5 also includes current state information acquisition, motion model selection, state update and prediction, time stepping, error estimation and correction, and output of prediction results;

[0082] Current status information acquisition: Obtain the current status information of the target;

[0083] Motion model selection: The system uses a predefined motion model to describe the motion law of the target;

[0084] State update and prediction: Based on the current state information and the selected motion model, the system uses mathematical equations to update the target's state and predict its future position.

[0085] Time stepping calculates the target's position at a future point in time;

[0086] Error estimation and correction are used to refine predictions and improve accuracy.

[0087] Output the prediction results, which are the target's location information at a future time point.

[0088] Specifically, the system uses radar, infrared sensors, and other sensors to detect flying objects, analyzing their x, y, and z coordinates, velocity, and acceleration. Based on the target's flight characteristics, such as common motion models like uniform linear motion and accelerated linear motion, a suitable motion model is selected. The target's future position is then calculated using the motion model and current state information. Kalman filters or other error estimation techniques are employed to adapt the model to environmental changes, predict potential errors, correct predictions, and improve accuracy. Sensor orientation is adjusted, or signal compensation parameters are calculated to ensure the system can respond promptly when the target reaches the predicted position. The predicted future target position information is then transmitted to the defense system, adjusting its parameters for more precise interception.

[0089] Step S6 includes field testing and simulation testing;

[0090] Field tests can demonstrate multiple hits on the target aircraft, thereby determining the true information of the target aircraft.

[0091] Simulation testing can detect the electromagnetic signals of a target flying object and compare them with the electromagnetic signals of known flying objects to determine the true information of the target flying object.

[0092] Specifically, through field and simulation tests on flying targets, when multiple detections yield accurate information, the control and defense system intercepts the target. When the target's information is false, its true information is detected, and interception is initiated. This results in high interception accuracy, reduced cost, and enhanced security. If the target's true information is not detected and it has already entered the interception range, interception is performed based on previous information.

[0093] The S8 steps include target identification and tracking, environmental perception and prediction, data processing and optimization, and adaptive system design.

[0094] Target recognition and tracking: Deep learning and neural networks can be used to improve the accuracy and stability of the system in identifying targets.

[0095] Environmental perception and prediction, using models such as recurrent neural networks (RNN) or long short-term memory networks (LSTM), enable shipborne systems to better understand the dynamic changes in the environment.

[0096] Data processing and optimization: Deep learning can be used to optimize the processing and parsing of sensor data, improving the speed and accuracy of data processing and quickly and accurately extracting target information;

[0097] Adaptive system design, utilizing deep reinforcement learning, allows the system to learn and adjust its operating methods to adapt to different environments and threats.

[0098] Specifically, by employing deep learning models such as Convolutional Neural Networks (CNNs), features can be extracted from sensor data to identify and differentiate different types of targets. This can be used for target recognition and tracking, improving the system's accuracy and stability in target identification. Furthermore, by utilizing models such as Recurrent Neural Networks (RNNs) or Long Short-Term Memory Networks (LSTMs), the shipborne system can better understand the dynamic changes in the environment and optimize the processing and analysis of sensor data. This allows the defense system to learn and adjust its operating methods to adapt to different combat environments and threat patterns. Reinforcement learning enables the system to gain experience through interaction with the environment and make better decisions accordingly. Through continuous learning, it can more accurately detect different flying objects and quickly formulate corresponding interception plans, ensuring detection accuracy while increasing flexibility and reducing interception costs.

[0099] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for compensating tracking signals in shipborne defense, characterized in that, Includes the following steps: S1. Flying object identification: Identifying the location and shape of flying objects; S2. Object Confirmation: Further identification of the object. S3. Environmental condition correction: Using environmental sensing technology, sensing and monitoring environmental changes in order to more accurately correct sensor data. Step S3 includes adaptive signal processing technology, environmental sensing algorithm and temperature stabilization technology. The adaptive signal processing technology dynamically adjusts signal processing parameters according to real-time environmental conditions. The environmental perception algorithm adjusts the sensor's operating parameters according to environmental changes to adapt to different working conditions; The temperature stabilization technology ensures that the sensor can maintain the system's performance under different temperature conditions; S4. Interference and Interference Countermeasures: Interfere with flying objects and prevent flying objects from interfering with detection, so as not to reduce detection accuracy. S5. Motion prediction: Based on the target's current state, predict the target's future position. S6. Continuous verification and testing: Conduct continuous verification and testing of the system to confirm the authenticity of the flying object information; S7. The command is transmitted to the defense system, and the calculated signal compensation parameters are transmitted to the defense system to adjust the parameters of the defense system to ensure that the target can be accurately tracked and intercepted. S8. Field verification and optimization: Collect actual defense data and optimize the sensor fusion algorithm based on the results to ensure that the defense system can still be used effectively under constantly changing conditions. The S8 step includes target recognition and tracking, environmental perception and prediction, data processing and optimization, and adaptive system design; The target recognition and tracking, deep learning and neural networks can be used to improve the accuracy and stability of the system in identifying targets; The aforementioned environmental perception and prediction utilizes recurrent neural network (RNN) or long short-term memory (LSTM) models, enabling the shipborne system to better understand the dynamic changes in the environment. The data processing and optimization mentioned above can utilize deep learning to optimize the processing and parsing of sensor data, improve the speed and accuracy of data processing, and quickly and accurately extract target information. The adaptive system design utilizes deep reinforcement learning, enabling the system to learn and adjust its operating methods to adapt to different environments and threats.

2. The tracking signal compensation method for shipborne defense according to claim 1, characterized in that, Step S1 includes radar detection and visual detection; The radar detection involves using radar to confirm the location of the flying object; The visual inspection confirms the approximate shape of the flying object by using an image recognition module.

3. The tracking signal compensation method for shipborne defense according to claim 1, characterized in that, Step S4 includes electronic interference and infrared and optical countermeasures; The electronic jamming can emit electronic countermeasures signals to interfere with the radar and communication systems of flying objects; The infrared and optical countermeasures employ strong light and lasers while releasing a large amount of heat to disorient the target flying object.

4. The tracking signal compensation method for shipborne defense according to claim 3, characterized in that, The electronic interference includes frequency hopping and jamming of frequency-modulated radar; The frequency jump causes the communication signal to jump between different frequencies, making it difficult for the enemy to lock onto and interfere with it; The aforementioned frequency-modulated jamming radar, by adjusting the radar transmission frequency, interferes with the radar system of target flying objects.

5. The tracking signal compensation method for shipborne defense according to claim 1, characterized in that, Step S5 includes an adaptive filtering algorithm, a motion model, and a target prediction algorithm. The adaptive filtering algorithm can adjust and optimize sensor data in real time in dynamic environments, and respond more flexibly to environmental changes and sensor errors. The motion model and target prediction algorithm introduce a more complex and accurate target motion model, combined with an advanced target prediction algorithm, to more accurately estimate the future position and state of the target.

6. The tracking signal compensation method for shipborne defense according to claim 5, characterized in that, The S5 step also includes current state information acquisition, motion model selection, state update and prediction, time stepping, error estimation and correction, and output of prediction results; The current status information acquisition refers to acquiring the current status information of the target; The motion model selection process involves the system using a predefined motion model to describe the motion patterns of the target. The state update and prediction, based on the current state information and the selected motion model, uses mathematical equations to update the target's state and predict its future position; The time step is used to calculate the target's position at a future time point; The error estimation and correction are used to correct the prediction and improve accuracy; The output prediction result is the location information of the target at a future time point.

7. The tracking signal compensation method for shipborne defense according to claim 1, characterized in that, Step S6 includes field testing and simulation testing; The field test can demonstrate multiple hits on the target flying object, thereby determining the true information of the target flying object; The simulation test can detect the electromagnetic signal of the target flying object and compare it with the electromagnetic signal of a known flying object to determine the true information of the target flying object.