Echo detection algorithm under strong reverberation

Abstract

The application relates to the technical field of sonar echo detection, and discloses a strong reverberation echo detection algorithm, which comprises a sonar data receiving module, a sonar data calculation processing module, a sonar data digitization display module and a sonar data saving module, the sonar data saving module comprises a sonar database, the sonar database comprises an echo database and a clutter database, the sonar data calculation processing module comprises a first processing program and a secondary processing program, and the echo detection algorithm extracts the sonar echo data features in the sonar database when starting for the first time. The strong reverberation echo detection algorithm can obtain more accurate structures of the sonar echo data when the sonar echo data is calculated and analyzed by adopting the echo detection and comparison from the clutter database, the accuracy of sonar detection is improved, and the analysis error is reduced.

Description

Technical Field

[0001] This invention relates to the field of sonar echo detection technology, specifically an echo detection algorithm under strong reverberation. Background Technology

[0002] In underwater geological exploration and disaster search and rescue, active sonar is often used to search for target areas. The echoes transmitted back by the target are used to analyze and detect the terrain and landforms of the target area, which greatly improves the efficiency and accuracy of the search. Therefore, sonar equipment, as well as related analysis equipment and detection algorithms, are needed to detect and analyze the data of the echoes transmitted back from the ground.

[0003] When monitoring echo data, the terrain elevation of the target location and the presence of objects or special terrain features on the ground are usually observed by the speed and position of the echo displayed on the sonar image. This requires professional detection algorithms for analysis and calculation to obtain accurate sonar echo data.

[0004] However, in actual use, the existing algorithms of the above-mentioned equipment often produce a lot of chaotic waves in the echo in certain areas due to geological reasons or interference from enemy personnel, which affects the accuracy of the sonar echo data and reduces the effectiveness of sonar. In view of this, we propose an echo detection algorithm under strong reverberation. Summary of the Invention

[0005] The purpose of this invention is to provide an echo detection algorithm under strong reverberation to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an echo detection algorithm under strong reverberation, comprising a sonar data receiving module, a sonar data calculation and processing module, a sonar data digitization display module, and a sonar data storage module. The sonar data storage module includes a sonar database, which includes an echo database and a clutter database. The sonar data calculation and processing module includes a primary processing program and a secondary processing program. The primary processing program includes the following specific steps:

[0007] S1. Construct a signal interference clutter identification model using the polarization characteristics of dual-polarization sonar to identify and mark ground clutter and suspected signal interference clutter mixed with ground clutter.

[0008] S2. Separate and preserve suspected signal interference clutter from data echoes;

[0009] S21. Save the data echo format and data characteristics to facilitate subsequent digital processing and graphical display;

[0010] S422. Save suspected signal interference clutter for easy comparison of subsequent data echoes and further identification.

[0011] S3. Extract the features of the data echo and compare them with signal interference clutter. Analyze the data echo information features in the suspected signal interference clutter, and extract the data echo information features into the echo detection data for merging and saving to the sonar database.

[0012] Preferably, the sonar data calculation and processing module includes a secondary processing program comprising the following specific steps:

[0013] S1. Extract the echo transmitted by the sonar;

[0014] S2. Remove suspected signal interference clutter and data echoes;

[0015] S21. Cache the data echo format and data characteristics of this data;

[0016] S22. Buffer suspected signal interference clutter;

[0017] S3. Extract the features of the cached data echo, the past clutter features in the clutter database, and the data echo features respectively, and compare and analyze them with the suspected signal interference clutter in S21.

[0018] S4. Further strip away the suspected signal interference clutter in S3;

[0019] S5. Upload the data echo obtained in S4 to the echo database for saving and overwriting;

[0020] S6. Upload the signal interference clutter obtained in S4 to the database for storage and overwriting.

[0021] Preferably, the echo detection algorithm extracts sonar echo data features from the sonar database upon initial power-on, takes a 3×3 area from the surrounding background information centered on the point to be detected, sets the sonar echo data features accordingly within this area, and adds spatial features, temporal features, and motion features to the features within this area based on the information of the echo data features.

[0022] Preferably, step S21 includes a caching step before saving the data echo format and data features, so as to facilitate the subsequent merging and saving of supplementary data echo features after echo comparison, thereby improving the comprehensiveness and accuracy of echo data features.

[0023] Preferably, in step S3, after the echo comparison is completed, the obtained clutter feature data is uploaded to the clutter database for storage, which facilitates the extraction and comparison of clutter feature data in subsequent sonar detection processes.

[0024] Preferably, the sonar data receiving module is equipped with multiple sets of filters to filter out common external noise and other common interference waves, thereby improving the analysis and calculation accuracy and efficiency of the echo detection algorithm.

[0025] Preferably, the sonar data digitization display module extracts cached data echo features from the echo database, analyzes them, and then converts them into graphics in a digital form to form a sonar image, which is convenient for people to view and query.

[0026] Preferably, the echo comparison method adopts a dual-view collaborative training method, which identifies and marks key nodes of clutter features, and analyzes and compares them by overlaying and covering data entered later, so as to quickly and accurately identify clutter features.

[0027] Preferably, the output value of the sonar echo detection algorithm needs to be analyzed and compared by the first processing program of the sonar data calculation and processing module and N secondary processing programs before output, where N is 3-10.

[0028] Compared with existing technologies, this invention provides an echo detection algorithm under strong reverberation, which has the following characteristics:

[0029] Beneficial effects:

[0030] 1. This strong reverberation echo detection algorithm, by employing echo detection and comparison with clutter databases, enables sonar echo data to obtain a more accurate structure during calculation and analysis, thereby improving the accuracy of sonar detection and reducing analysis errors.

[0031] 2. This echo detection algorithm under strong reverberation greatly improves the accuracy of echo detection data by employing a secondary processing procedure of the sonar data calculation and processing module that is repeated multiple times.

[0032] 3. This strong reverberation echo detection algorithm temporarily buffers the data echo behind the glass and then stitches and saves the buffered data echo after subsequent echo comparison, making the acquisition and storage of data echo more three-dimensional and accurate. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the echo detection algorithm module of the present invention;

[0034] Figure 2 This is a schematic diagram of the echo data processing flow of the present invention. Detailed Implementation

[0035] like Figure 1-2As shown, the present invention provides a technical solution: an echo detection algorithm under strong reverberation, including a sonar data receiving module, a sonar data calculation and processing module, a sonar data digitization display module, and a sonar data storage module. The sonar data storage module includes a sonar database, which includes an echo database and a clutter database. The sonar data calculation and processing module includes a primary processing program and a secondary processing program. The primary processing program includes the following specific steps:

[0036] S1. Construct a signal interference clutter identification model using the polarization characteristics of dual-polarization sonar to identify and mark ground clutter and suspected signal interference clutter mixed with ground clutter.

[0037] S2. Separate and preserve suspected signal interference clutter from data echoes;

[0038] S21. Save the data echo format and data characteristics to facilitate subsequent digital processing and graphical display;

[0039] S422. Save suspected signal interference clutter for easy comparison of subsequent data echoes and further identification.

[0040] S3. Extract the features of the data echo and compare them with signal interference clutter. Analyze the data echo information features in the suspected signal interference clutter, and extract the data echo information features into the echo detection data for merging and saving to the sonar database.

[0041] In an embodiment of the present invention, the sonar data calculation and processing module includes a secondary processing procedure comprising the following specific steps:

[0042] S1. Extract the echo transmitted by the sonar;

[0043] S2. Remove suspected signal interference clutter and data echoes;

[0044] S21. Cache the data echo format and data characteristics of this data;

[0045] S22. Buffer suspected signal interference clutter;

[0046] S3. Extract the features of the cached data echo, the past clutter features in the clutter database, and the data echo features respectively, and compare and analyze them with the suspected signal interference clutter in S21.

[0047] S4. Further strip away the suspected signal interference clutter in S3;

[0048] S5. Upload the data echo obtained in S4 to the echo database for saving and overwriting;

[0049] S6. Upload the signal interference clutter obtained in S4 to the database for storage and overwriting.

[0050] In an embodiment of the present invention, the echo detection algorithm extracts sonar echo data features from the sonar database upon initial power-on. A 3×3 area is selected from the surrounding background information, centered on the detection point. The sonar echo data features are then set within this area, and spatial, temporal, and motion features are added to the features within this area based on the echo data feature information. In S21 of the initial processing procedure of the sonar data calculation and processing module, a caching step is performed before saving the data echo format and data features to facilitate the subsequent merging and saving of supplementary echo features after echo comparison, thereby improving the comprehensiveness and accuracy of the echo data features. In S3 of the initial processing procedure of the sonar data calculation and processing module, after echo comparison is completed, the obtained clutter feature data is uploaded to the clutter database for storage, facilitating the extraction of clutter feature data during subsequent sonar detection processes. The sonar data receiving module is equipped with multiple filters to filter out common external noise and other common interference waves, improving the accuracy and efficiency of the echo detection algorithm. The sonar data digitization display module extracts cached echo features from the echo database, analyzes them, and then converts them into graphics in digital form, forming a sonar image for easy viewing and querying. The echo comparison method adopts a dual-view collaborative training approach, identifying and marking key nodes of clutter features, and using a post-entry data overlay method for analysis and comparison to quickly and accurately identify clutter features. The output value of the sonar echo detection algorithm requires an initial processing program from the sonar data calculation and processing module and N secondary processing programs for analysis and comparison before output, where N is a value of 3-10, thereby greatly improving the accuracy of the echo detection data.

[0051] The present invention has been described in detail above. However, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, any modifications or improvements that do not depart from the spirit of the present invention are within the scope of protection of the present invention.

Claims

1. An echo detection algorithm under strong reverberation, comprising a sonar data receiving module, a sonar data calculation and processing module, a sonar data digitization display module, and a sonar data storage module, wherein the sonar data storage module includes a sonar database, the sonar database including an echo database and a clutter database, characterized in that: The sonar data calculation and processing module includes a primary processing program and a secondary processing program. The primary processing program includes the following specific steps: S1. Construct a signal interference clutter identification model using the polarization characteristics of dual-polarization sonar to identify and mark ground clutter and suspected signal interference clutter mixed with ground clutter. S2. Separate and preserve suspected signal interference clutter from data echoes; S21. Save the data echo format and data characteristics to facilitate subsequent digital processing and graphical display; S422. Save suspected signal interference clutter for easy comparison of subsequent data echoes and further identification. S3. Extract the features of the data echo and compare them with signal interference clutter. Analyze the data echo information features in the suspected signal interference clutter, and extract the data echo information features into the echo detection data for merging and saving to the sonar database. The secondary processing procedure includes the following specific steps: S1. Extract the echo transmitted by the sonar; S2. Remove suspected signal interference clutter and data echoes; S21. Cache the data echo format and data characteristics of this data; S22. Buffer suspected signal interference clutter; S3. Extract the features of the cached data echo, the past clutter features in the clutter database, and the data echo features respectively, and compare and analyze them with the suspected signal interference clutter in S21. S4. Further strip away the suspected signal interference clutter in S3; S5. Upload the data echo obtained in S4 to the echo database for saving and overwriting; S6. Upload the signal interference clutter obtained in S4 to the database for storage and overwriting; The echo detection algorithm extracts sonar echo data features from the sonar database upon initial power-on. It takes a 3×3 area from the surrounding background information with the point to be detected as the center, sets the sonar echo data features in this area accordingly, and adds spatial features, temporal features, and motion features to the features in this area based on the information of the echo data features.

2. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: The step of caching in S21 before saving the data echo format and data features is to facilitate the subsequent merging and saving of supplementary features of the data echo after echo comparison, thereby improving the comprehensiveness and accuracy of the echo data features.

3. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: In step S3, after the echo comparison is completed, the clutter feature data obtained is uploaded to the clutter database for storage, which facilitates the extraction and comparison of clutter feature data in subsequent sonar detection processes.

4. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: The sonar data receiving module is equipped with multiple sets of filters to filter out common external noise and other common interference waves, thereby improving the analysis and calculation accuracy and efficiency of the echo detection algorithm.

5. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: The sonar data digitization display module extracts cached data echo features from the echo database, analyzes them, and then converts them into graphics in a digital form, thereby forming a sonar image for easy viewing and querying.

6. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: The echo comparison method adopts a dual-view collaborative training approach. By identifying and marking key nodes of clutter features, and simultaneously using a post-entry data overlay method for analysis and comparison, clutter features can be identified quickly and accurately.

7. The echo detection algorithm under strong reverberation according to claim 1, characterized in that: The output value of the sonar echo detection algorithm needs to be analyzed and compared by the first processing program of the sonar data calculation and processing module and N secondary processing programs before it is output, where N is 3-10.

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