A radar-ultraviolet cooperative detection method and system for extremely low RCS targets

Abstract

The application belongs to the technical field of radar and ultraviolet cooperative detection, and discloses a radar and ultraviolet cooperative detection system for extremely low RCS targets, which is composed of one radar, multiple ultraviolet detectors and a core processor, wherein the radar emits electromagnetic wave signals to space in an active manner, the ultraviolet detectors monitor ultraviolet radiation of targets in a passive manner, and the core processor processes the detected data and realizes cooperative detection of the radar and the ultraviolet system.The application effectively combines the advantages of traditional radar and ultraviolet detection, can make the detection system work effectively in various scenes, combines various target characteristic information detected by the radar and the ultraviolet detector to realize feature fusion judgment, and realizes effective detection of extremely low RCS targets; only when the extremely low RCS target is detected, the corresponding ultraviolet detector is started, so that fast identification and accurate detection of the extremely low RCS target can be realized; in a multi-target combat scene, the extremely low RCS target is effectively identified, so that the combat target is more reasonably planned, and the threat brought by the extremely low RCS target is greatly reduced.

Description

Technical Field

[0001] This invention belongs to the field of radar ultraviolet cooperative detection technology, and particularly relates to a radar ultraviolet cooperative detection method and system for targets with extremely low RCS. Background Technology

[0002] RCS (Radar Cross Section) is a physical quantity that measures the intensity of the echo generated by a target under radar wave illumination, and it is the most critical concept in radar stealth technology. It is the imaginary area of ​​the target, represented by the projected area of ​​an isotropic equivalent reflector, which has the same echo power as the defined target per unit solid angle in the receiving direction. With the rapid development of new stealth technologies and materials for aircraft, traditional detection technologies face numerous difficulties in detecting targets with extremely low RCS. Existing conventional detection methods include radar detection and infrared detection. For radar detection technology, multipath interference can significantly affect radar signals, impacting target detection and tracking. The radar signals reflected back by targets with extremely low RCS are very weak, requiring advanced signal processing technologies for effective noise reduction, enhancement, tracking, and identification. However, existing signal processing systems often cannot effectively meet the requirements for detecting extremely low RCS targets. Due to the extremely high technical requirements for detecting extremely low RCS targets, the design and manufacturing costs of radar systems are also very high, making their widespread application difficult in certain situations. For infrared detection technology, infrared radiation is greatly affected by ambient temperature, resulting in strong background radiation. Excessively low or high ambient temperatures can also affect detection effectiveness or generate false alarms. Furthermore, infrared detection is susceptible to interference from enemy inertial guided missiles, electro-optical jamming devices, and other malicious attacks. Therefore, current conventional detection methods are insufficient for effectively detecting targets with extremely low RCS (Radar Cross Section). Thus, to improve the combat effectiveness and survivability of military aircraft, and to achieve the principle of "a skillful attacker makes the enemy unaware of his defenses; a skillful defender makes the enemy unaware of his attacks," there is an urgent need to explore unconventional detection technologies for targets with extremely low RCS.

[0003] Ultraviolet (UV) detection systems operating in the "solar blind zone" have extremely low UV radiation from the sky background, resulting in a clean detection environment that avoids the strongest natural light sources. Furthermore, their passive operation can create favorable stealth conditions in specific scenarios. In addition, aircraft typically emit exhaust plumes, radiating strong UV energy into space and effectively countering conventional jamming methods such as electromagnetic and infrared interference. Therefore, the advantages of radar and UV detection systems can be effectively combined to achieve effective detection of targets with extremely low RCS (Radar Cross Section), reducing the false negative rate and the threat posed by such targets.

[0004] Currently, for the detection of targets with extremely low RCS, existing aircraft detection methods mainly consist of radar and infrared detection, or a combination of the two. The basic principle of radar detection is to use the interaction between electromagnetic waves and objects to achieve target detection and positioning. It emits radar signals to the surrounding area and then detects the received reflected signals to determine the position, distance, speed, and other information of the surrounding targets. Infrared detection works passively, detecting the infrared energy emitted by objects in the environment to find targets.

[0005] Based on the above analysis, the problems and shortcomings of the existing technology are as follows:

[0006] (1) When detecting targets with extremely low RCS, multipath interference can have a significant impact on radar signals, affecting the detection and tracking of targets. The radar signals reflected back by targets with extremely low RCS are very weak, requiring high-end signal processing technology for effective noise reduction, enhancement, tracking and identification. However, existing signal processing systems often cannot effectively meet the requirements for detecting targets with extremely low RCS. Due to the very high requirements for the detection technology of targets with extremely low RCS, the design and manufacturing costs of radar systems are also very high, which makes it difficult to widely apply them in certain situations.

[0007] (2) For infrared detection technology, infrared radiation is greatly affected by ambient temperature, resulting in strong background radiation. Also, excessively low or high ambient temperatures can affect the detection effect or produce false detection signals. In addition, infrared detection is susceptible to interference from enemy inertial guided missiles, photoelectric jamming devices, etc. Summary of the Invention

[0008] To address the problems existing in the prior art, this invention provides a radar-ultraviolet cooperative detection method and system for targets with extremely low RCS.

[0009] This invention is implemented as follows: a radar-ultraviolet cooperative detection system for extremely low RCS targets. The radar-ultraviolet cooperative detection system for extremely low RCS targets consists of one radar, multiple ultraviolet detectors, and a core processor. The radar actively transmits electromagnetic wave signals into space, the ultraviolet detectors passively monitor the ultraviolet radiation of the target, and the core processor processes the detected data to achieve cooperative detection by the radar and the ultraviolet system.

[0010] Another object of the present invention is to provide a radar ultraviolet cooperative detection method for extremely low RCS targets using a radar ultraviolet cooperative detection system for implementing the aforementioned extremely low RCS targets, the method comprising:

[0011] Step one: The airborne radar performs long-range conventional detection missions;

[0012] Step 2: When a target appears in the radar detection area, calculate the radar cross section of the target and determine whether it is an extremely low RCS target. If it is determined to be a non-extremely low RCS target, the radar will perform conventional target detection and proceed to Step 3. If it is determined to be an extremely low RCS target, proceed to Steps 4 to 7.

[0013] Step 3: The radar acquires multiple important features of M targets, and combines digital signal processing technology to extract and classify the target features, compare them with information in the database, determine the type of each of the M targets, and then proceed to step 7.

[0014] Step four: The collaborative detection system activates tracking mode for N targets with extremely low RCS, extracting and predicting the targets' motion characteristics in real time, such as distance. position( θ i Important information such as distances to n (1≤n≤N) targets out of N targets with extremely low RCS can be extracted. When the target's location information is combined, an ultraviolet detector capable of covering n incoming targets is activated to prepare for ultraviolet identification.

[0015] Step 5: In the ultraviolet identification process, the ultraviolet images detected by the ultraviolet detector need to be processed in real time and the targets need to be initially classified.

[0016] Step 6: Estimate the approximate size of the incoming target. Combine the preliminary classification results from Step 5 with the approximate target size information obtained in Step 6 to perform a final classification of the n extremely low RCS targets. Compare the classification with the ultraviolet information in the database to determine the type of incoming target.

[0017] Step 7: If the target is identified as an aircraft, the cooperative detection system will issue an alarm; if it is identified as a non-aircraft target, the cooperative detection system will abandon tracking the target.

[0018] Furthermore, in step one, when the fighter jet performs a combat mission, the onboard radar first performs a long-range conventional detection mission, with a maximum achievable detection range. Where E t G represents the energy of the received signal. t G represents the axial power gain of the transmitting antenna. r Let λ represent the axial gain of the receiving antenna, σ represent the wavelength, and σ represent the radar cross-section of the target. t 2 F represents the pattern propagation factor along the launch path. r 2 T represents the pattern propagation factor along the receiving path, k represents the Boltzmann constant, and T represents the pattern propagation factor along the receiving path. s This indicates the system noise temperature, in Kelvin (K), or Delvin (D). x(n) represents the pulse energy ratio, and L represents the radio frequency loss, which is the product of multiple loss factors.

[0019] Furthermore, in step two, when a target appears within the radar detection area, the radar cross section of the target is calculated. Where P in σ represents the target's echo power, R represents the distance between the radar and the target, and P represents the radar's transmitted pulse power. If σ ≥ -20dBsm, it is judged as a non-extremely low RCS target; if σ < -20dBsm, it is judged as an extremely low RCS target.

[0020] Furthermore, in step three, the radar calculates the range of M non-extremely low RCS targets. Where c represents the speed of light, f bav The average value of the frequency offset is represented by μ, which represents the modulation slope. Important motion characteristics of the target, including azimuth angle, include the azimuth angle. Pitch angle θ i acceleration a i (i = 1, 2, ..., M), and other features include RCS, target shape, and target height.

[0021] Furthermore, step five includes:

[0022] (1) Use the method of finding the maximum correlation to register the scene of neighboring frames;

[0023] (2) Find the region with a large distance between corresponding pixels between two frames as the candidate region of the target;

[0024] (3) Use the average gray level of the inter-frame difference image as the adaptive threshold for segmentation. For each pixel, compare its gray level with the threshold value. If it is greater than the threshold value, the pixel is considered to belong to the target; otherwise, the pixel is considered to belong to the background. Divide the image into target region and background region.

[0025] (4) In the inter-frame difference image after threshold segmentation, the target imaging area is compressed, and the relationship between the average gray value of the candidate target area in the inter-frame difference image and the overall average gray value of the image, as well as its shape features, are used to screen out effective candidate targets.

[0026] (5) Perform feature extraction on the selected targets, use different feature extraction algorithms (such as SIFT, HOG, etc.) to extract the corresponding feature vectors of the targets in each frame of ultraviolet image, and ensure that the dimensions and sizes of these feature vectors are the same;

[0027] (6) The feature vectors of each frame of ultraviolet image are weighted to obtain the feature fusion vector, which is then normalized. Commonly used machine learning algorithms such as SVM are used to perform preliminary classification of the target.

[0028] Furthermore, in step six, the target imaging size (length l) in the ultraviolet image detected by the ultraviolet detector... i Width w i (1≤i≤n)) and focal length f, combined with the distance from the target's motion information. Based on similar triangles, we can estimate the approximate size of the incoming target:

[0029]

[0030]

[0031] Among them, L i W is the estimated length of target i. i The estimated value of the target width i.

[0032] Another object of the present invention is to provide a computer device including a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the radar-ultraviolet cooperative detection method for extremely low RCS targets.

[0033] Another object of the present invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the radar-ultraviolet cooperative detection method for targets with extremely low RCS.

[0034] Another objective of this invention is to provide an information data processing terminal for implementing a radar-ultraviolet cooperative detection system for extremely low RCS targets.

[0035] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions protected by this invention are analyzed from the following aspects:

[0036] First, addressing the technical problems existing in the prior art and the difficulty in solving them, this paper closely analyzes, in conjunction with the technical solution to be protected by this invention and the results and data obtained during the research and development process, how the technical solution of this invention solves the technical problems, and the inventive technical effects brought about by solving these problems. The specific description is as follows:

[0037] (1) This invention effectively combines the advantages of traditional radar and ultraviolet detection, enabling the detection system to work effectively in various scenarios. It also combines the feature fusion judgment of multiple target feature information detected by radar and ultraviolet detection to achieve effective detection of targets with extremely low RCS.

[0038] (2) The present invention has made reasonable optimizations to the radar and ultraviolet cooperative detection system, that is, the corresponding ultraviolet detector is turned on only when a target with extremely low RCS is detected, which minimizes the amount of data that the cooperative detection system needs to process, improves the system's computing efficiency, reduces the system's power consumption, and enables rapid identification and accurate detection of targets with extremely low RCS.

[0039] (3) In multi-target combat scenarios, this invention can more rationally plan combat targets by effectively identifying targets with extremely low RCS, thereby greatly reducing the threat posed by targets with extremely low RCS.

[0040] Secondly, as supporting evidence of the inventiveness of this invention, it is also reflected in the following important aspects:

[0041] (1) The rapid development of new stealth technologies and materials for aircraft has placed higher demands on current detection systems. Achieving accurate detection of targets with extremely low RCS is a problem that has been hoped to be solved. The radar-ultraviolet cooperative detection method and system for targets with extremely low RCS proposed in this invention can effectively detect targets with extremely low RCS and can work flexibly in various scenarios, which can greatly reduce the threat posed by targets with extremely low RCS. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of a radar-ultraviolet cooperative detection system for extremely low RCS targets provided in an embodiment of the present invention;

[0043] Figure 2 This is a basic flowchart of the radar-ultraviolet cooperative detection system for extremely low RCS targets provided in this embodiment of the invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0045] I. Explanatory and Illustrative Embodiments. To enable those skilled in the art to fully understand how the present invention is specifically implemented, this section provides an explanatory and illustrative description of the embodiments described in the claims.

[0046] The radar-ultraviolet cooperative detection system for extremely low RCS targets provided in this embodiment of the invention is as follows: Figure 1As shown, this system consists of one radar, multiple ultraviolet detectors (each with a different field of view, which can be selected as needed), and a core processor, enabling global coverage and achieving omnidirectional, blind-spot-free detection. The radar actively transmits electromagnetic signals into space, the ultraviolet detectors passively monitor the ultraviolet radiation of targets, and the core processor processes the detected data and enables coordinated detection by the radar and ultraviolet systems.

[0047] The basic operating method of the radar-ultraviolet cooperative detection system for extremely low RCS targets provided in this embodiment of the invention is as follows: Figure 2 As shown, it includes:

[0048] Step one: The airborne radar performs long-range conventional detection missions;

[0049] Step 2: When a target appears in the radar detection area, calculate the radar cross section of the target and determine whether it is an extremely low RCS target. If it is determined to be a non-extremely low RCS target, the radar will perform conventional target detection and proceed to Step 3. If it is determined to be an extremely low RCS target, proceed to Steps 4 to 7. In addition, assume that among the targets appearing at this time, there are M non-extremely low RCS targets and N extremely low RCS targets.

[0050] Step 3: The radar calculates the distances of M non-extremely low RCS targets and obtains important motion characteristics such as the azimuth and acceleration of these targets. Then, it combines various other features and digital signal processing techniques to extract the features of the targets. Finally, the M non-extremely low RCS targets are classified and compared with the information in the database to determine the type of each of the M targets. Then, proceed to step 7.

[0051] Step four: The collaborative detection system activates tracking mode for N targets with extremely low RCS, extracting and predicting the targets' motion characteristics in real time, such as distance. position( θ i Important information such as distances to n (1≤n≤N) targets out of N targets with extremely low RCS can be extracted. When the target's location information is combined, an ultraviolet detector capable of covering n incoming targets is activated to prepare for ultraviolet identification.

[0052] Step 5: In the ultraviolet identification process, the ultraviolet images detected by the ultraviolet detector need to be processed in real time and the targets need to be initially classified.

[0053] Step 6: Estimate the approximate size of the incoming target. Combine the preliminary classification results from Step 5 with the approximate target size information obtained in Step 6 to perform a final classification of the n extremely low RCS targets. Compare the classification with the ultraviolet information in the database to determine the type of incoming target.

[0054] Step 7: If the target is identified as an aircraft, the cooperative detection system will issue an alarm; if it is identified as a non-aircraft target, the cooperative detection system will abandon tracking the target.

[0055] In the first step provided by this embodiment of the invention, when a fighter jet performs a combat mission, the airborne radar first performs a long-range conventional detection mission, achieving a maximum detection range of... Where E t G represents the energy of the received signal. t G represents the axial power gain of the transmitting antenna. r Let λ represent the axial gain of the receiving antenna, σ represent the wavelength, and σ represent the radar cross-section of the target. t 2 F represents the pattern propagation factor along the launch path. r 2 T represents the pattern propagation factor along the receiving path, k represents the Boltzmann constant, and T represents the pattern propagation factor along the receiving path. s This indicates the system noise temperature, in Kelvin (K), or Delvin (D). x (n) represents the pulse energy ratio, and L represents the radio frequency loss, which is the product of multiple loss factors.

[0056] Step two of this embodiment of the invention involves calculating the radar cross-section of a target when it appears within the radar detection area. Where P in σ represents the target's echo power, R represents the distance between the radar and the target, and P represents the radar's transmitted pulse power. If σ ≥ -20dBsm, it is judged as a non-extremely low RCS target; if σ < -20dBsm, it is judged as an extremely low RCS target.

[0057] Step three in this embodiment of the invention involves the radar calculating the range of M non-extremely low RCS targets. Where c represents the speed of light, f bav The average value of the frequency offset is represented by μ, which represents the modulation slope. Important motion characteristics of the target, including azimuth angle, include the azimuth angle. Pitch angle θ i acceleration a i (i = 1, 2, ..., M), other features include RCS, target shape and target height, etc.

[0058] Step five provided in this embodiment of the invention includes:

[0059] (1) The method of finding the maximum correlation is used to register the scene of the neighboring frame, so that the motion of the background is basically canceled out, and it can be assumed that only the target is making a large motion in the field of view.

[0060] (2) Find the region with a large distance between corresponding pixels between two frames as the candidate region of the target;

[0061] (3) The average gray level of the inter-frame difference image is used as the adaptive threshold for segmentation. For each pixel, its gray level is compared with the threshold value. If it is greater than the threshold value, the pixel is considered to belong to the target; otherwise, the pixel is considered to belong to the background. Thus, the image is divided into target region and background region.

[0062] (4) In order to improve the accuracy and completeness of target region extraction, in the inter-frame difference image after threshold segmentation, it is necessary to ensure that the inner side of each boundary is adjacent to the whole area formed by the target motion. The target imaging area needs to be compressed, and the relationship between the average gray value of the candidate target area in the inter-frame difference image and the overall average gray value of the image, as well as its shape features, are used to screen out effective candidate targets.

[0063] (5) Perform feature extraction on the selected targets. Use different feature extraction algorithms (such as SIFT, HOG, etc.) to extract the corresponding feature vectors of the targets in each frame of ultraviolet image, and ensure that the dimensions and sizes of these feature vectors are the same.

[0064] (6) The feature vectors of each frame of ultraviolet image are weighted to obtain the feature fusion vector, which is then normalized. Commonly used machine learning algorithms such as SVM are used to perform preliminary classification of the target.

[0065] Step six of this embodiment of the invention provides that the target imaging size (length l) in the ultraviolet image detected by the ultraviolet detector is... i Width w i (1≤i≤n)) and focal length f, combined with the distance from the target's motion information. Based on similar triangles, we can estimate the approximate size of the incoming target:

[0066]

[0067]

[0068] Among them, L i W is the estimated length of target i. i The estimated value of the target width i.

[0069] II. Application Examples. To demonstrate the inventiveness and technical value of the technical solution of this invention, this section provides application examples of the technical solution of the claims on specific products or related technologies.

[0070] The radar-ultraviolet cooperative detection system for extremely low RCS targets provided in the application embodiment of the present invention is applied to a computer device, the computer device including a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, the processor performs the steps of the radar-ultraviolet cooperative detection system for extremely low RCS targets.

[0071] The radar-ultraviolet cooperative detection system for extremely low RCS targets provided in the application embodiment of the present invention is applied to an information data processing terminal, which is used to implement the radar-ultraviolet cooperative detection system for extremely low RCS targets.

[0072] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0073] III. Evidence of the Relevant Effects of the Embodiments. The embodiments of the present invention have achieved some positive effects during research and development or use, and indeed possess significant advantages compared to existing technologies. The following description, in conjunction with data, charts, and other materials from the experimental process, illustrates these advantages.

[0074] This invention takes a three-sided phased array airborne radar as an example to construct a radar and ultraviolet cooperative detection system, and describes the characteristics of the cooperative detection system of this invention.

[0075] (1) If the radar detects few targets, when it encounters a non-extremely low RCS target, the radar will automatically identify the target; when it encounters an extremely low RCS target, the cooperative detection system will activate the ultraviolet detector in the corresponding azimuth based on the target data detected by the radar, and wait for secondary identification and confirmation of the incoming target, thereby achieving accurate detection of extremely low RCS targets and further reducing the false detection rate.

[0076] By activating only a small number of ultraviolet detectors when extremely low RCS targets are detected, the amount of data that the collaborative detection system needs to process is minimized, improving the system's computational efficiency. This enables rapid identification and accurate detection of extremely low RCS targets, giving pilots more time to handle crises.

[0077] (2) If the radar detects a large number of targets, and assume that the radar can track N targets. T One goal and N E Multiple targets are engaged in combat simultaneously (generally N) T >N E If this is the case, multiple targets can be locked in among targets with non-extremely low RCS, and the number of targets N that need to be engaged can be preliminarily determined. E There are several targets, and preparations for engagement are being made. If a target with extremely low RCS exists, it will be marked first. When it enters the ultraviolet detection range, the system will perform secondary identification and reconfirm the final N target for engagement. E One goal.

[0078] The cooperative detection system can minimize the threat posed by targets with extremely low RCS and ensure the safety of our fighter jets to the greatest extent possible.

[0079] Application Scenarios

[0080] (1) During the attack

[0081] (i) When our aircraft launch a surprise attack, in order to avoid being identified by the enemy's electromagnetic detection system in the vicinity of the enemy, it can only use the ultraviolet detection system to achieve a better stealth effect and create more favorable conditions for the surprise attack.

[0082] (ii) When our aircraft is detected by the enemy, the enemy will generally use conventional jamming methods such as electromagnetic or infrared interference to hinder our attack. However, the ultraviolet detection system in this invention can still detect and lock onto enemy targets even under complex environmental interference.

[0083] (2) When defending

[0084] When our aircraft are locked on and attacked, we can also conduct electromagnetic and infrared jamming against the enemy. At this time, our cooperative detection system is not affected by the jamming and can still monitor the enemy's aircraft movements with high precision, and take evasive or even countermeasure actions according to the battle situation.

[0085] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A radar-ultraviolet cooperative detection system for targets with extremely low RCS, characterized in that, The radar-ultraviolet cooperative detection system for extremely low RCS targets consists of one radar, multiple ultraviolet detectors, and a core processor. The radar actively transmits electromagnetic wave signals into space, the ultraviolet detectors passively monitor the ultraviolet radiation of the target, and the core processor processes the detected data and realizes cooperative detection between the radar and the ultraviolet system. A method for radar-ultraviolet cooperative detection of extremely low RCS targets using a radar-ultraviolet cooperative detection system, the method specifically comprising: Step one: The airborne radar performs long-range conventional detection missions; Step 2: When a target appears in the radar detection area, calculate the radar cross section of the target and determine whether it is an extremely low RCS target. If it is determined to be a non-extremely low RCS target, the radar will perform conventional target detection and proceed to Step 3. If it is determined to be an extremely low RCS target, proceed to Steps 4 to 7. Step 3: The radar calculates the distances of M non-extremely low RCS targets, extracts and classifies the target features, compares them with information in the database, determines the type of each of the M targets, and then proceeds to step 7. Step four: The collaborative detection system activates tracking mode for N extremely low RCS targets, extracting and predicting the target motion characteristics in real time, including range. ,position( , Important information, including If N targets with extremely low RCS are extracted, then... Distance to each target hour, Then, by combining the target's location information, a system capable of covering incoming attacks can be activated. An ultraviolet detector is set up to perform ultraviolet identification on several targets. Represents the speed of light. This represents the average value of the frequency offset. Indicates the modulation slope. Indicates azimuth. Indicates the pitch angle; Step 5: In the ultraviolet identification process, the ultraviolet images detected by the ultraviolet detector need to be processed in real time and the targets need to be initially classified. Step Six: Estimate the approximate size of the incoming target. Combine the preliminary classification results from Step Five with the approximate target size information obtained in Step Six to... The targets with extremely low RCS are classified and compared with the ultraviolet information in the database to determine the type of incoming target. Step 7: If the target is identified as an aircraft, the cooperative detection system will issue an alarm; if it is identified as a non-aircraft target, the cooperative detection system will abandon tracking the target.

2. The radar-ultraviolet cooperative detection system for extremely low RCS targets according to claim 1, in step one, when the fighter jet performs a combat mission, the airborne radar first performs a long-range conventional detection mission, achieving a maximum detection range... ,in Indicates the energy of the received signal. This indicates the axial power gain of the transmitting antenna. This indicates the axial gain of the receiving antenna. Indicates wavelength. This represents the radar cross-section of the target. Indicates the pattern propagation factor along the launch path. Indicates the pattern propagation factor along the receiving path. Represents the Boltzmann constant. This indicates the system noise temperature, in Kelvin (K). Indicates the pulse energy ratio. This represents radio frequency loss, which is the product of multiple loss factors.

3. In the radar-ultraviolet cooperative detection system for extremely low RCS targets according to claim 1, in step two, when a target appears within the radar detection area, the radar cross section of the target is calculated. ,in Indicates the target's echo power. Indicates the distance between the radar and the target. This indicates the power of the pulse transmitted by the radar. If so, it is judged to be a non-extremely low RCS target; if If it is, then it is judged to be a target with extremely low RCS; among which This represents radio frequency loss, which is the product of multiple loss factors. This indicates the axial power gain of the transmitting antenna. This indicates the axial gain of the receiving antenna. Indicates wavelength.

4. In the radar-ultraviolet cooperative detection system for extremely low RCS targets according to claim 1, in step three, the radar calculates the range of M non-extremely low RCS targets. ,in , Represents the speed of light. This represents the average value of the frequency offset. Indicating modulation slope, target azimuth, and acceleration, key motion characteristics include azimuth angle. Pitch angle acceleration Other features include RCS, target shape, and target height.

5. The radar-ultraviolet cooperative detection system for extremely low RCS targets according to claim 1, step five includes: (1) Use the method of finding the maximum correlation to register the scene of neighboring frames; (2) Find the region with a large distance between corresponding pixels between two frames as the candidate region of the target; (3) Use the average gray level of the inter-frame difference image as the adaptive threshold for segmentation. For each pixel, compare its gray level with the adaptive threshold value. If it is greater than the threshold value, the pixel is considered to belong to the target; otherwise, the pixel is considered to belong to the background. Divide the image into target region and background region. (4) In the inter-frame difference image after threshold segmentation, the target imaging area is compressed, and the relationship between the average gray value of the candidate target area in the inter-frame difference image and the overall average gray value of the image and its shape features are used to screen out effective candidate targets. (5) Perform feature extraction on the selected targets, use different feature extraction algorithms to extract the corresponding feature vectors of the targets in each frame of ultraviolet image, and ensure that the dimension and size of these feature vectors are the same. The feature extraction algorithms include SIFT and HOG. (6) The feature vectors of each frame of ultraviolet image are weighted to obtain the feature fusion vector, which is then normalized and the target is initially classified using the SVM algorithm.

6. The radar-ultraviolet cooperative detection system for extremely low RCS targets according to claim 1, in step six, the target imaging length in the ultraviolet image detected by the ultraviolet detector... ,Width and focal length , Combined with the distance from the target's motion information Based on similar triangles, we can estimate the approximate size of the incoming target, and thus: ， ； ， ； in, For the goal Long estimate, For the goal The estimated width.

7. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of a radar-ultraviolet cooperative detection method for extremely low RCS targets applied to a radar-ultraviolet cooperative detection system for extremely low RCS targets as described in any one of claims 1-6.

8. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the radar-ultraviolet cooperative detection method for extremely low RCS targets according to any one of claims 1-6.

9. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the radar ultraviolet cooperative detection system for extremely low RCS targets as described in claim 1.

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