Sonar efficiency calculation method for representing square array position detectability

Abstract

The invention relates to a sonar efficiency calculation method for representing the detectability of a square array position. The sonar efficiency calculation method comprises the following steps: 1, uniformly dividing a task sea area into a plurality of square array positions; 2, carrying out azimuth detection probability calculation on a single square array position, and identifying a detection probability value by using a colored tape; 3, normalizing the RGB value of the detection probability, equally dividing the color band used for identifying the numerical value of the detection probability into 11 sections, and uniformly representing the RGB value of each section of color gamut by using normalized specific numerical values S1, S2, S3,..., S11; 4, extracting the detection probability feature of a single square array position, and extracting a corresponding normalized RGB value to represent the detection probability of the whole single square array position; and 5, repeating the steps 2-4 until the detection probability characteristics of the square array position calculation area of the task sea area selected in the step 1 are completely extracted, forming a visual result representing the detection capability of the whole task sea area, and completing the representation of the detection capability of the task sea area. According to the invention, a visual representation result of the task sea area detection capability is formed.

Description

Technical Field

[0001] The present invention belongs to the technical field of sonar effectiveness analysis and calculation, and in particular relates to a sonar effectiveness calculation method for characterizing the detection capability of a square array. Background Art

[0002] Sonar is a core instrument for underwater surveillance, and its effectiveness in actual operation is typically measured by detection range and detection probability. Analyzing and calculating sonar effectiveness requires information about the ocean environment in which the sonar-carrying platform is currently located, as well as the acoustic characteristics of the target being monitored by the platform.

[0003] For carrier platforms such as ships and aircraft, compared with analyzing and calculating the sonar effectiveness of the current sea area, when they perform underwater surveillance tasks, knowing the quantitative evaluation distribution of sonar effectiveness at different locations in the mission sea area in advance is conducive to formulating surveillance action plans more efficiently.

[0004] Existing sonar effectiveness calculation methods primarily use the platform carrying the sonar as the center, calculating the detection range and detection probability at different azimuth angles, or using the platform's route as the trajectory to calculate the detection range and detection probability at different azimuth angles at multiple trajectory points. This calculation method is useful for characterizing the local, specific detection performance of a single sonar in a specific sea area. It is typically used to compare and select small- and medium-scale (hundreds of kilometers) application scenarios for different azimuth sonar effectiveness. However, due to the lack of overall feature extraction, calculation, and analysis of omnidirectional sonar effectiveness, it is not applicable to large-scale (thousands or tens of thousands of kilometers) mission areas with ranges dozens of times greater than the sonar detection range. Therefore, it is impossible to determine the optimal or worst-case square array sea area for the carrier platform based on existing sonar effectiveness calculation results. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the present invention proposes a sonar effectiveness calculation method for characterizing the detection capability of a square array.

[0006] The above-mentioned purpose of the present invention is achieved through the following technical solutions:

[0007] A sonar effectiveness calculation method for characterizing the detection capability of a square array comprises the following steps:

[0008] Step 1: Divide the mission sea area into square positions, evenly dividing the mission sea area into several square positions;

[0009] Step 2: Calculate the azimuth detection probability for a single square array position, and use color bands to mark the detection probability values.

[0010] Step 3: Normalize the detection probability RGB values. Divide the color band used to identify the detection probability value into 11 equal segments. The RGB values ​​of each segment are uniformly represented by the normalized specific values ​​S1, S2, S3, ..., S11.

[0011] Step 4: Extract the detection probability features of a single square array position, and extract the corresponding normalized RGB value to represent the detection probability of the entire single square array position;

[0012] Step 5. Repeat steps 2 to 4 until all the detection probability features of the square array calculation area of ​​the mission sea area selected in step 1 are extracted, forming a visualization result representing the detection capability of the entire mission sea area, and completing the characterization of the mission sea area detection capability.

[0013] Moreover, in step 1, the specific method of dividing the square array is as follows:

[0014] 1.1. Read the latitude and longitude of the origin of the upper left corner of the mission sea area, recorded as θ0.

[0015] 1.2, according to latitude 1′=1.85km, longitude Calculate the longitude and latitude of other points in the square array. The array size is 80km × 80km. The formula is as follows:

[0016]

[0017] Among them, θ n The longitude of the position point with the upper left corner as the first position and the origin spanning n positions to the right, The latitude of the position point with the upper left corner as the first position and the origin spanning m positions downward;

[0018] 1.3. Set the latitude and longitude of the lower right corner of the geographical scope of the mission sea area to θ. When θ n ≥θ, stop calculating the new position longitude to the right. When the latitude and longitude of the new position point are calculated downwards, the division and expansion of the square array position are completed, and a square array position calculation area is formed.

[0019] Moreover, in step 2, the carrier platform is set to be located at the center of a single square array position; the 360° full range is divided into 8 directions according to each direction of 45°; the detection probability distribution of the target is calculated for each direction based on the preset target characteristics. The detection probability of passive sonar is calculated using the formula SL-TL-(NL-DI+DT), and the detection probability of active sonar is calculated using the formula SL-2TL+TS-(NL-DI+DT), where SL represents the sound source level, TL represents the sound propagation loss, TS represents the target strength, NL represents the noise level, DI represents the directivity index, and DT represents the detection threshold.

[0020] Moreover, in step 4, the specific method of normalizing RGB value statistics is as follows:

[0021] 4.1、Read the RGB value of a single pixel, that is, p(n)={R n , G n , B n}, n ranges from 1 to N, where N is the total number of pixels;

[0022] 4.2. Compare the RGB value p(n) of a single pixel with the RGB value range of the color band to determine whether the RGB value p(n) of the pixel falls into one of the 11 segments S(m). The value range of m is 1 to 11, i.e., S1, S2, S3, ..., S11.

[0023] 4.3、Query the normalized RGB value corresponding to S(m), that is, S(m)={R m , G m , B m}, each time S(m) is queried, the statistical number T(m) of S(m) increases by 1;

[0024] 4.4 Repeat 4.4 to 4.3 until all pixel points with a single square array detection probability are traversed, and the final statistical quantity T(m) of each S(m) is obtained;

[0025] 4.5 The proportion of normalized RGB values ​​S(m) is calculated using T(m) / N.

[0026] The present invention has the following advantages and positive effects:

[0027] 1. Based on the traditional sonar effectiveness calculation method, this paper proposes a sonar effectiveness calculation method with square array positions as the basic unit. By extracting detection probability features, it forms a visual representation of the detection capability of the mission sea area. This can effectively support carrier platforms such as ships and aircraft to grasp the overall detection capabilities of different sea areas during the mission planning stage, and improve the usability and visualization level of warning detection auxiliary decision-making.

[0028] 2. Compared with existing sonar effectiveness calculation methods, the sonar effectiveness calculation method of the present invention is more applicable to mission sea areas with a large spatial scale (thousands or tens of thousands of kilometers), and the visualization representation is concise and intuitive. Through the flexible setting of feature extraction thresholds, a human-in-the-loop sonar effectiveness quantitative evaluation scheme is formed, which can support commanders with different personalities (radical, conservative) to easily obtain the sonar effectiveness quantitative evaluation distribution of the mission sea area in different mission scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a schematic diagram of a process for determining a square array position calculation area according to an embodiment of the present invention;

[0030] Figure 2 The color ribbon used to identify the numerical value of the detection probability in the embodiment of the present invention;

[0031] Figure 3 This is a schematic diagram of the detection probability calculation for a single square array position according to an embodiment of the present invention;

[0032] Figure 4 1 is a schematic diagram of the normalization of the color representation of the detection probability value according to an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of the proportion of normalized RGB values ​​in an embodiment of the present invention;

[0034] Figure 6 This is a schematic diagram of the detection probability feature extraction results of a single square array position in the present invention;

[0035] Figure 7 This is a schematic diagram showing the visualization of the overall detection capability of the mission sea area of ​​the present invention;

[0036] Figure 8 This is a diagram of the detection array planning software interface corresponding to the present invention. DETAILED DESCRIPTION

[0037] The structure of the present invention will be further described below with reference to the accompanying drawings and through examples. It should be noted that the present examples are descriptive rather than restrictive.

[0038] A sonar effectiveness calculation method to characterize the detection capability of a square array, see Figures 1-8 , the invention point is: comprising the following steps:

[0039] Step 1: Divide the mission sea area into square array positions: Use the mouse to select the geographical scope of the mission sea area on the thematic map, and then use the upper left corner of the geographical scope of the mission sea area as the origin to evenly divide the mission sea area into several square array positions with a size of 80km×80km. Among them, the thematic map is similar to the electronic nautical chart and has built-in latitude and longitude coordinates. If the geographical scope of the selected mission sea area cannot be divided into an integer number of square array positions, the software will automatically expand the edge of its geographical scope to an integer number of square array positions. The expansion method is to first fill in the geographical scope that is insufficient to form a complete square array position in the right area and then in the lower area to form a complete square array position, such as Figure 1 The size of the square array depends on the sonar's detection capability and typically does not exceed the maximum detection range centered on the sonar. The default size of the square array is 80 km x 80 km, but users can customize the size of the square array.

[0040] The specific method of dividing the square array is as follows:

[0041] (1) Read the latitude and longitude of the origin of the upper left corner of the mission sea area, recorded as θ0, The display format of longitude and latitude is xxx°xx.xxx′;

[0042] (2) According to latitude 1′=1.85km, longitude To calculate the latitude and longitude of other points in the square array, taking the default array size of 80km×80km as an example, the formula is as follows:

[0043]

[0044] Among them, θ n The longitude of the position point with the upper left corner as the first position and the origin spanning n positions to the right, The latitude of the position point that spans m positions downward from the origin with the upper left corner as the first position.

[0045] (3) Set the latitude and longitude of the lower right corner of the geographical scope of the mission sea area to θ, When θ n ≥θ, stop calculating the new position longitude to the right. When the latitude and longitude of the new position point are calculated downwards, the division and expansion of the square array position are completed, and a square array position calculation area is formed.

[0046] Step 2: Calculate the detection probability of a single square array position: Assume that the carrier platform is located at the center of a single square array position, and divide the 360° full range into 8 directions with each direction being 45°. Calculate the detection probability distribution of the target at each direction based on the preset target characteristics. The detection probability calculation of the passive sonar uses the formula SL-TL-

[0047] (NL-DI+DT), the detection probability of active sonar is calculated using the formula SL-2TL+TS-(NL-DI+DT), where SL represents the sound source level, TL represents the sound propagation loss, TS represents the target intensity, NL represents the noise level, DI represents the directivity index, and DT represents the detection threshold. The detection probability value (range 1.0 to 0.0) is marked with a color band, such as Figure 2 As mentioned above, the red part of the color band indicates a high detection probability, the blue part indicates a low detection probability, and the white part indicates a blind area, where the detection probability is null and can be regarded as a value of 0 in data statistics. Figure 3 shown.

[0048] Step 3: Normalize the detection probability RGB values: Divide the color band used to identify the detection probability value into 11 equal segments. The RGB values ​​of each segment are uniformly represented by a normalized specific value (S1, S2, S3, ..., S11), as shown in the following example: Figure 4 shown.

[0049] Step 4: Extract the detection probability features of a single square array. Take a single pixel as the basic unit and count Figure 2 The percentage of normalized RGB values ​​(S1, S2, S3, ..., S11) in the detection probability of a single square array position is shown. The statistical results are sorted from low to high, as shown in the figure. Figure 5 shown.

[0050] According to the detection probability feature extraction principle set by the detection array planning software (i.e. the functional software formed by this patent method), Figure 8 As shown, you can select the detection probability or quantity ratio. The two options are mutually exclusive. The range of each option is from Min to Max. Min represents the most conservative strategy, and Max represents the most aggressive strategy. Drag the slider to select a level from Min to Max (Min, 25%, 50%, 75%, Max. Drag the slider to automatically check the detection probability or quantity ratio selection box). Figure 4 (corresponding to the detection probability option), Figure 5 The corresponding normalized RGB values ​​(S1, S2, S3, ..., S11) (corresponding to the quantity ratio option) represent the detection probability of the entire single square array position, such as Figure 6 shown.

[0051] The specific method for normalizing RGB value statistics is as follows:

[0052] (1) Read the RGB value of a single pixel, that is, p(n) = {R n , G n , B n}, n ranges from 1 to N, where N is the total number of pixels;

[0053] (2) Compare the RGB value p(n) of a single pixel with the RGB value range of the color band to determine whether the RGB value p(n) of the pixel falls into a certain segment S(m) among the 11 segments. The value range of m is 1 to 11, i.e., S1, S2, S3, ..., S11.

[0054] (3) Query the normalized RGB value corresponding to S(m), that is, S(m) = {R m , G m , B m}, each time S(m) is queried, the statistical number T(m) of S(m) increases by 1;

[0055] (4) Repeat (1) to (3) until all pixel points of the detection probability of a single square array are traversed, and the final statistical number T(m) of each S(m) is obtained;

[0056] (5) The number ratio of normalized RGB values ​​S(m) is calculated using T(m) / N.

[0057] Step 5: Repeat steps 2 to 4 until all the detection probability features of the square array calculation area of ​​the mission sea area selected in step 1 are extracted to form a visualization result representing the detection capability of the entire mission sea area, thus completing the characterization of the mission sea area detection capability. Figure 7 shown.

[0058] Example:

[0059] The user opens the detection array planning software, clicks the "Array Recommendation" secondary menu in the decision support section, and uses the mouse to select a rectangular area within a specific sea area. The software then generates several equally divided rectangular array positions within the selected area, based on the preset sonar equipment type and parameters, following steps 1 through 5. The color of each position represents its detection capability. The positions in the red area are optimal for conducting surveillance and detection missions, and platforms equipped with the same type of sonar equipment can be deployed there. This feature provides users with a macro-level quantitative assessment of the detection capability distribution within the selected sea area, as well as optimal array position recommendations.

[0060] Users can click the "System Settings" button on the right side of the main interface, select "Formation Feature Extraction Principle," and select the extraction principle to use in the pop-up window. If you do not change the extraction principle, step 4 will be executed according to the previous setting.

[0061] The above embodiments further illustrate the purpose, technical solutions and advantages of the present invention in detail. It should be understood that the above embodiments are only preferred implementation plans of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made to the present invention within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A sonar effectiveness calculation method for characterizing the detection capability of a square array, characterized by: The following steps are involved: Step 1: Divide the mission sea area into square positions, evenly dividing the mission sea area into several square positions; Step 2: Calculate the azimuth detection probability for a single square array position, and use color bands to mark the detection probability values. Step 3: Normalize the detection probability RGB values. Divide the color band used to identify the detection probability value into 11 equal segments. The RGB values ​​of each segment are uniformly represented by the normalized specific values ​​S1, S2, S3, ..., S11. Step 4: Extract the detection probability features of a single square array position, and extract the corresponding normalized RGB value to represent the detection probability of the entire single square array position; Step 5. Repeat steps 2 to 4 until all the detection probability features of the square array calculation area of ​​the mission sea area selected in step 1 are extracted, forming a visualization result representing the detection capability of the entire mission sea area, and completing the characterization of the mission sea area detection capability.

2. The sonar effectiveness calculation method for characterizing the detection capability of a square array according to claim 1 is characterized by: In step 1, the specific method of dividing the square array is as follows: 1.

1. Read the latitude and longitude of the origin of the upper left corner of the mission sea area, recorded as θ0. 1.2, according to latitude 1′=1.85km, longitude Calculate the longitude and latitude of other points in the square array. The array size is 80km × 80km. The formula is as follows: Among them, θ n The longitude of the position point with the upper left corner as the first position and the origin spanning n positions to the right, The latitude of the position point with the upper left corner as the first position and the origin spanning m positions downward; 1.

3. Set the latitude and longitude of the lower right corner of the geographical scope of the mission sea area to θ. When θ n ≥θ, stop calculating the new position longitude to the right. When the latitude and longitude of the new position point are calculated downwards, the division and expansion of the square array position are completed, and a square array position calculation area is formed.

3. The sonar effectiveness calculation method for characterizing the detection capability of a square array according to claim 1 is characterized by: In step 2, the carrier platform is set to be located at the center of a single square array position; the 360° full range is divided into 8 directions according to each direction of 45°; the detection probability distribution of the target is calculated for each direction based on the preset target characteristics. The detection probability of passive sonar is calculated using the formula SL-TL-(NL-DI+DT), and the detection probability of active sonar is calculated using the formula SL-2TL+TS-(NL-DI+DT), where SL represents the sound source level, TL represents the sound propagation loss, TS represents the target strength, NL represents the noise level, DI represents the directivity index, and DT represents the detection threshold.

4. The sonar effectiveness calculation method for characterizing the detection capability of a square array according to claim 1 is characterized by: In step 4, the specific method for normalizing RGB value statistics is as follows: 4.1、Read the RGB value of a single pixel, that is, p(n)={R n , G n , B n }, n ranges from 1 to N, where N is the total number of pixels; 4.

2. Compare the RGB value p(n) of a single pixel with the RGB value range of the color band to determine whether the RGB value p(n) of the pixel falls into one of the 11 segments S(m). The value range of m is 1 to 11, i.e., S1, S2, S3, ..., S11. 4.3、Query the normalized RGB value corresponding to S(m), that is, S(m)={R m , G m , B m }, each time S(m) is queried, the statistical number T(m) of S(m) increases by 1; 4.4 Repeat 4.4 to 4.3 until all pixel points with a single square array detection probability are traversed, and the final statistical quantity T(m) of each S(m) is obtained; 4.5 The proportion of normalized RGB values ​​S(m) is calculated using T(m) / N.

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