A method, medium and apparatus for automatically adjusting an STC curve

Abstract

The application provides a method, medium and device for automatically adjusting an STC curve, and the method comprises the following steps: S1, setting the STC curve to a default theoretical value when the system is initialized; S2, saving and recording the amplitudes of original correlation peaks of a sum channel in a fixed format in units of distance during the system operation; S3, when the number of original correlation peak amplitudes corresponding to a distance exceeds a threshold value and the recorded value meets a double-peak distribution, starting to analyze and calculate the STC curve value corresponding to the distance, and saving and immediately taking effect when the STC curve value of the distance is less than the theoretical value. The application supports the device to automatically set the STC curve according to the actual use environment, improves the parameter accuracy, and reduces the labor participation cost.

Description

Technical Field

[0001] This invention relates to the field of secondary radar technology, and more specifically, to a method, medium, and apparatus for automatically adjusting the STC curve. Background Technology

[0002] The STC (Sensitivity Time Control) curve is a technique used by secondary radar receivers to suppress the amplitude of echo signals based on distance. A larger STC curve indicates a stronger signal at close range, while a smaller STC curve indicates a weaker signal at greater distances. To ensure the receiver functions correctly at all distances, filters out false targets, and accurately displays the detected target, STC curve parameters generally need to be configured within the equipment.

[0003] The parameters of the STC curve need to be manually set according to the equipment's operating environment. Manual setting generally uses empirical values ​​or values ​​calculated from accumulated field data. The problem with empirical values ​​is that they are difficult to match with the equipment environment, while the problem with calculated values ​​is that the data is incomplete, the calculation is inaccurate, and the cost of manual intervention is high. Summary of the Invention

[0004] The present invention aims to provide a method, medium, and apparatus for automatically adjusting STC curves, so as to improve the accuracy of STC curve parameters and reduce the cost of manual intervention.

[0005] The present invention provides a method for automatically adjusting the STC curve, comprising the following steps:

[0006] S1: During system initialization, the STC curve is set to the default theoretical value;

[0007] S2: During system operation, the amplitude of the original related peaks of the channel is saved and recorded in a fixed format, with distance as the unit;

[0008] S3: When the number of original correlation peak amplitudes corresponding to a certain distance exceeds the threshold and the recorded value satisfies the bimodal distribution, start analyzing and calculating the STC curve value corresponding to that distance. When the STC curve value of that distance is less than the theoretical value, save and take effect immediately.

[0009] Furthermore, the horizontal axis of the STC curve represents distance, and the vertical axis represents the amplitude of the original correlation peak of the channel; the default theoretical value calculation formula is:

[0010] y = Pyd + M - (93 + 20 * lgD)

[0011] Where y is the vertical axis of the STC curve, D is the horizontal axis of the STC curve, representing the distance between the transmitter and the receiver, Pyd is the power of the receiver, and M is a fixed offset value.

[0012] Furthermore, the fixed offset value M is used to ensure that the value of y is non-negative; the condition for the fixed offset value M is as follows:

[0013] M≥93+20lgDmax-Pyd

[0014] Where Dmax is the system's maximum power value.

[0015] Furthermore, the fixed format refers to storing the amplitude value of each original correlation peak corresponding to a unit distance using three bytes: the first two bytes are used to record the number of times, and the last byte is used to record the amplitude value.

[0016] Furthermore, the bimodal distribution refers to the fact that the range of values ​​[0, M] of the original correlation peak amplitude of a certain distance and the corresponding number of records constitutes a one-dimensional space, and the distribution of the number of records in the value space of 0 to M presents a pattern of two peaks.

[0017] Furthermore, the method for determining a bimodal distribution is:

[0018] The number of records in the range [0, M] is averaged and smoothed with a window size of 3, and it is determined whether it is a bimodal structure. If a bimodal structure is not obtained after several iterations, the determination fails. The bimodal structure refers to a value at a certain point that is greater than the previous point and greater than the next point.

[0019] Furthermore, the analysis and calculation process of the STC curve value adopts the K-Means algorithm, with K set to 2. The peak values ​​of the bimodal structure are used as two initial cluster centers for automatic clustering. Finally, the average of the two cluster centers is taken as the STC curve value of that distance.

[0020] The present invention also provides a computer terminal storage medium storing computer terminal executable instructions, which are used to execute the above-described method for automatically adjusting the STC curve.

[0021] The present invention also provides a computing device, comprising:

[0022] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described method for automatically adjusting the STC curve.

[0023] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0024] This invention supports the device to automatically set the STC curve according to the actual usage environment, which improves parameter accuracy and reduces the cost of manual intervention. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a method for automatically adjusting the STC curve in an embodiment of the present invention.

[0027] Figure 2 This is a flowchart illustrating the determination of the bimodal distribution pattern in Example 1 of this invention.

[0028] Figure 3 This is a flowchart illustrating the processing of STC curve values ​​in Example 2 of this invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0030] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0031] Example

[0032] like Figure 1 As shown in the figure, this embodiment proposes a method for automatically adjusting the STC curve, including the following steps:

[0033] S1: During system initialization, the STC curve is set to the default theoretical value; where the horizontal axis of the STC curve represents distance (in km), and the vertical axis represents the amplitude of the original correlation peak of the channel (in dB); the formula for calculating the default theoretical value is:

[0034] y = Pyd + M - (93 + 20 * lgD)

[0035] Where y is the vertical axis of the STC curve, D is the horizontal axis of the STC curve, representing the distance between the transmitter and receiver (in km), Pyd is the receiver power, and M is a fixed offset value. The fixed offset value M is used to ensure that the value of y is non-negative; the condition for the fixed offset value M is as follows:

[0036] M≥93+20lgDmax-Pyd

[0037] Where Dmax is the system's maximum power value.

[0038] S2: During system operation, the amplitude of the original correlation peak of the channel is saved and recorded in a fixed format in units of distance; wherein, the fixed format means that the value of the amplitude of each original correlation peak of the channel corresponding to a unit distance is saved using three bytes, the first two bytes are used to record the number of times, and the last byte is used to record the amplitude value, with the unit being 0.25dB.

[0039] S3: When the number of original correlation peak amplitudes corresponding to a certain distance exceeds the threshold and the recorded value satisfies the bimodal distribution, start analyzing and calculating the STC curve value corresponding to that distance. When the STC curve value of that distance is less than the theoretical value, save and take effect immediately.

[0040] The bimodal distribution refers to the fact that the range of values ​​[0, M] of the original correlation peak amplitude of a certain distance and the corresponding number of records constitutes a one-dimensional space. In the value space of 0 to M, the distribution of the number of records presents a pattern of two peaks.

[0041] Furthermore, the method for determining a bimodal distribution is as follows: the number of records in the range [0, M] is averaged and smoothed with a window size of 3, and it is determined whether it is a bimodal structure; if a bimodal structure is not obtained after several iterations (e.g., 1000 times), the determination fails. The bimodal structure refers to a value at a certain point that is greater than the previous point and greater than the next point.

[0042] Example 1:

[0043] To simplify the analysis process, in this example, we assume that the unit of M is 1 dB, and the analysis object is the amplitude of the original correlation peak of the channel at a distance of D km.

[0044] Figure 2 The procedure for determining a bimodal distribution pattern is shown, including:

[0045] Step 101: Initialize the array Array (array size M, values ​​are the number of times the original correlation peak amplitude of the channel occurs) and the iteration value N;

[0046] Step 102: Determine whether the array of peak amplitudes related to the original channel satisfies the bimodal structure. The judgment criteria are to traverse the array Array and find two m values ​​that meet the conditions Array[m]>Array[m-1] and Array[m]>Array[m+1] and save and output them. Otherwise, proceed to step 103.

[0047] Step 103: Perform mean smoothing on the Array array with a window size of 3 and determine whether the number of iterations is less than N. If it is, proceed to step 102 for iteration processing; otherwise, fail the iteration count.

[0048] Example 2:

[0049] Figure 3 The processing flow for STC curve values ​​is shown, including:

[0050] Step 201: When the number of records exceeds 10,000, start the process of determining the bimodal distribution pattern in Example 1. If successful, proceed to step 202.

[0051] Step 202: The two peaks of the bimodal structure are calculated and obtained as the two initial cluster centers of the K-Means algorithm and iterated. The calculation is stopped when the centroid does not change or the number of iterations exceeds 1000.

[0052] Step 203: Take the average value of the two centroids and compare it with the theoretical value of the STC curve of distance D. If the average value is less than the theoretical value, update the STC curve value to the average value and turn on the flag. Otherwise, ignore the average value.

[0053] Furthermore, in some embodiments, a computer terminal storage medium is proposed, storing computer terminal executable instructions for performing the method of automatically adjusting the STC curve as described in the preceding embodiments. Examples of computer storage media include magnetic storage media (e.g., floppy disks, hard disks, etc.), optical recording media (e.g., CD-ROMs, DVDs, etc.), or memory such as memory cards, ROMs, or RAMs. The computer storage medium may also be distributed across a network-connected computer system, for example, as an application store.

[0054] Furthermore, in some embodiments, a computing device is proposed, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for automatically adjusting the STC curve as described in the foregoing embodiments. Examples of computing devices include PCs, tablet computers, smartphones, or PDAs.

[0055] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for automatically adjusting the STC curve, characterized in that, Includes the following steps: S1: During system initialization, the STC curve is set to the default theoretical value; S2: During system operation, the amplitude of the original related peaks of the channel is saved and recorded in a fixed format, with distance as the unit; S3: When the number of peak amplitudes corresponding to a certain distance and the original correlation peak amplitude of the channel exceeds the threshold and the recorded value satisfies the bimodal distribution, start analyzing and calculating the STC curve value corresponding to that distance. When the STC curve value of that distance is less than the theoretical value, save and take effect immediately. The bimodal distribution means that the range of values ​​[0,M] of the peak amplitude of the original correlation peak amplitude of the channel corresponding to a certain distance and the corresponding number of records constitute a one-dimensional space. In the value space of 0~M, the distribution of the number of records shows a two-peak pattern. The method for determining a bimodal distribution is as follows: the number of records in the range [0, M] is taken with a window size of 3 and the mean is smoothed to determine whether it is a bimodal structure; if a bimodal structure is not obtained after several iterations, the determination fails. The bimodal structure refers to a value at a certain point that is greater than the previous point and greater than the next point. The analysis and calculation process of the STC curve value adopts the K-Means algorithm, with K set to 2. The peak values ​​of the bimodal structure are used as two initial cluster centers for automatic clustering. Finally, the average of the two cluster centers is taken as the STC curve value of that distance.

2. The method for automatically adjusting the STC curve according to claim 1, characterized in that, The horizontal axis of the STC curve represents distance, and the vertical axis represents the amplitude of the original correlation peak of the channel; the default theoretical value calculation formula is: y = Pyd + M - (93 + 20 * lgD) Where y is the vertical axis of the STC curve, D is the horizontal axis of the STC curve, representing the distance between the transmitter and the receiver, Pyd is the power of the receiver, and M is a fixed offset value.

3. The method for automatically adjusting the STC curve according to claim 2, characterized in that, The fixed offset value M is used to ensure that the value of y is non-negative; the condition for the fixed offset value M is as follows: M≥93+20lgDmax-Pyd Where Dmax is the system's maximum power value.

4. The method for automatically adjusting the STC curve according to claim 1, characterized in that, The fixed format refers to storing the amplitude value of each original correlation peak corresponding to a unit distance using three bytes: the first two bytes are used to record the number of times, and the last byte is used to record the amplitude value.

5. A computer terminal storage medium storing computer terminal executable instructions, characterized in that, The computer terminal can execute instructions for performing the method of automatically adjusting the STC curve as described in any one of claims 1-4.

6. A computing device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for automatically adjusting the STC curve as described in any one of claims 1-4.

Images