Meteorological clutter suppression method and device and storage medium
By adaptively analyzing the distance Doppler spectrum of the radar signal, determining and suppressing meteorological clutter, solving the problem of high radar false alarm rate in cloudy and rainy weather, improving target detection performance and saving computing resources.
Patent Information
- Application Number
- CN202510062190.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-15
- Publication Date
- 2025-03-04
AI Technical Summary
Existing radar technology is difficult to effectively suppress meteorological clutter in cloudy and rainy weather, resulting in an increase in the probability of false alarms and a decrease in target detection performance.
By acquiring the distance Doppler spectrum of the radar signal, the clutter region is adaptively determined in the velocity dimension, and the clutter block is determined through quantization processing and gradient value analysis, and finally suppression is performed on the distance Doppler spectrum according to the characteristics of the clutter block.
Adaptive meteorological clutter suppression under cloudy and rainy weather conditions is achieved, the false alarm rate is reduced, the target detection performance of the radar is improved, and computing resources are saved.
Smart Images
Figure CN119556255A_ABST
Abstract
Description
Technical Field
[0001] The embodiments of the present application relate to the field of radar technology, and specifically to a method, device and storage medium for suppressing meteorological clutter. Background Art
[0002] In cloudy and rainy weather, clouds and rain will reflect and scatter the radar signals emitted by the radar, thereby generating meteorological clutter, which will interfere with the radar signal and significantly increase the false alarm probability of the radar, making it difficult for the radar to accurately distinguish between real targets and non-target objects, resulting in a decrease in the radar's target detection performance. Therefore, in order to improve the detection performance of the radar system and reduce the false alarm rate, an effective method is needed to suppress meteorological clutter.
[0003] At present, among the radar meteorological clutter suppression methods, MTD (Moving Target Detecting) uses Doppler filters to suppress clutter in the Doppler domain, which can suppress meteorological clutter, but its effectiveness depends on the mastery of prior knowledge of clutter and lacks adaptive ability. AMTD (Adaptive MTD) technology can adaptively obtain meteorological clutter characteristics and form corresponding Doppler filters to achieve meteorological clutter suppression, but the design of high-quality filters requires a lot of calculations, which consumes a lot of computing resources. Summary of the invention
[0004] In view of the above problems, the embodiments of the present application provide a meteorological clutter suppression method, device and storage medium, which can directly adaptively suppress the meteorological clutter of radar signals on the range Doppler spectrum without designing complex filters, thus saving computing resources.
[0005] According to one aspect of an embodiment of the present application, a method for suppressing meteorological clutter is provided, the method comprising: obtaining a range Doppler spectrum of a radar signal, the range Doppler spectrum having a distance dimension, a velocity dimension and a power dimension, wherein the distance dimension is a row dimension and the velocity dimension is a column dimension; determining a clutter region of the radar signal on the velocity dimension of the range Doppler spectrum according to a first variance between a power value of a middle column and power values of other columns, wherein the middle column corresponds to a maximum velocity value on the velocity dimension; quantizing all power values in the range Doppler spectrum to obtain a clutter quantization spectrum; determining a clutter block of the radar signal on the clutter quantization spectrum according to a gradient value between a quantization value of each column of the clutter region and a quantization value of a previous column; and suppressing clutter on the radar signal on the range Doppler spectrum according to a clutter bandwidth and a clutter center of the clutter block.
[0006] In an optional manner, determining the clutter area of the radar signal according to the first variance between the power value of the middle column and the power values of other columns in the velocity dimension of the range Doppler spectrum further includes: calculating the first variance between the power value of the middle column and the power values of other columns in sequence in the velocity dimension of the range Doppler spectrum to obtain the first variance corresponding to each other column; determining the clear area and the initial clutter area of the radar signal in the velocity dimension according to the first variance in the range Doppler spectrum; and determining the clutter area of the radar signal from the initial clutter area according to the second variance between the average power value of the clear area and each power value of the initial clutter area in the range Doppler spectrum.
[0007] In an optional manner, determining a clear area and an initial clutter area of a radar signal in a velocity dimension based on a first variance on a range Doppler spectrum further includes: in the velocity dimension of the range Doppler spectrum, determining a plurality of continuous columns whose first variances are all greater than a first preset variance threshold as the initial clutter area of the radar signal, and determining a middle column as the clear area of the radar signal.
[0008] In an optional manner, determining the clutter area of the radar signal from the initial clutter area according to the second variance between the average power value of the clear area and each power value of the initial clutter area on the range Doppler spectrum further includes: sequentially calculating the second variance between the average power value of the clear area and each power value of the initial clutter area; judging whether there is a second variance greater than a second preset variance threshold among the multiple second variances; and determining the initial clutter area as the clutter area on the range Doppler spectrum if there is a second variance greater than the second preset variance threshold among the multiple second variances.
[0009] In an optional manner, before successively calculating the second variance between the average power value of the clear area and each power value of the initial clutter area, the meteorological clutter suppression method also includes: determining a power value in the clear area that is greater than a preset power threshold as an abnormal power value; calculating the average value of the power value in the column where the abnormal power value is located; and after modifying the abnormal power value to the average value, calculating the average power value of the clear area.
[0010] In an optional manner, after all power values in the range Doppler spectrum are quantized to obtain a clutter quantization spectrum, the meteorological clutter suppression method further includes: establishing a sliding window matrix in the clutter quantization spectrum, the quantization value corresponding to the first row and first column of the sliding window matrix is the quantization value corresponding to the first row and first column of the clutter quantization spectrum, the number of columns of the sliding window matrix is less than the number of columns of the clutter quantization spectrum, and the number of columns and the number of rows of the sliding window matrix are both odd numbers; a step of eliminating clutter noise points: calculating the total number of quantization values in the sliding window matrix that is equal to a preset quantization value, and modifying the quantization value corresponding to the center position of the sliding window matrix whose total number is greater than a preset total number threshold to a preset quantization value; moving the sliding window matrix, and executing the step of eliminating clutter noise points until the entire clutter quantization spectrum is traversed.
[0011] In an optional manner, determining a clutter block of a radar signal according to a gradient value between each column of quantized values in a clutter region and a previous column of quantized values on a clutter quantized spectrum further includes: calculating a difference between each column of quantized values in a clutter region and a previous column of quantized values on the clutter quantized spectrum to obtain a plurality of gradient values in the clutter region, wherein the gradient value includes a first gradient value and a second gradient value, the absolute values of the first gradient value and the second gradient value are equal, the first gradient value is a positive number, and the second gradient value is a negative number; and determining, on each row of a distance dimension of a distance Doppler spectrum, a column where the first gradient value is located to a column where the second gradient value is located in the clutter region as a clutter block of the radar signal, wherein the column where the first gradient value is located is located to the left of the column where the second gradient value is located.
[0012] In an optional manner, obtaining the range Doppler spectrum of the radar signal further includes: obtaining a total range Doppler spectrum of the radar signal; and segmenting the total range Doppler spectrum in a range dimension of the range Doppler spectrum to obtain multiple range Doppler spectra.
[0013] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the meteorological clutter suppression method provided in the above embodiment.
[0014] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the meteorological clutter suppression method provided in the above embodiment is implemented.
[0015] The embodiment of the present application can determine the clutter area of the radar signal in the velocity dimension of the range Doppler spectrum by obtaining the range Doppler spectrum of the radar signal and the first variance between the power value of the middle column and the power value of other columns. Then, the clutter quantization spectrum is obtained by quantizing all power values in the range Doppler spectrum, so that the clutter block of the radar signal can be determined by the gradient value between the quantization value of each column of the clutter area and the quantization value of the previous column. Finally, the clutter of the radar signal is directly suppressed on the range Doppler spectrum by the clutter bandwidth and clutter center of the clutter block. Through the above method, there is no need to design a complex filter, and the characteristics of meteorological clutter can be directly extracted based on the range Doppler spectrum of the radar signal, and the meteorological clutter can be adaptively suppressed directly on the range Doppler spectrum based on the characteristics of the meteorological clutter, saving computing resources.
[0016] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:
[0018] Figure 1 A schematic diagram of a flow chart of a method for suppressing meteorological clutter provided in an embodiment of the present application is shown;
[0019] Figure 2 A schematic diagram of the range Doppler spectrum provided by an embodiment of the present application is shown;
[0020] FIG3( a ) shows a schematic diagram of a clutter quantization spectrum provided in an embodiment of the present application;
[0021] FIG3( b ) shows a schematic diagram of a clutter quantization spectrum gradient provided in an embodiment of the present application;
[0022] Figure 4 Shows Figure 1 Schematic diagram of the process after step 300;
[0023] FIG5(a) shows a schematic diagram of establishing a sliding window matrix in a clutter quantization spectrum provided in an embodiment of the present application;
[0024] FIG5( b ) shows a schematic diagram of a clutter quantization spectrum after sliding window provided in an embodiment of the present application;
[0025] FIG5( c ) shows a schematic diagram of a clutter quantization spectrum gradient provided by another embodiment of the present application;
[0026] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION
[0027] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.
[0028] At present, the main clutter suppression methods for radar include MTI (Moving Target Indication), MTD, AMTI (Adaptive MTI) and AMTD.
[0029] Among them, MTI uses signals of different pulses for cancellation, which can effectively suppress stationary clutter, but cannot suppress meteorological clutter; MTD directly uses Doppler filters to suppress clutter in the Doppler domain, which can suppress meteorological clutter, but its effectiveness depends on the mastery of prior knowledge of clutter and lacks adaptive ability; AMTI, based on MTI, adaptively learns clutter characteristics, moves the Doppler frequency of meteorological clutter to zero frequency, and then uses MTI technology to suppress clutter, but this method is only applicable to the case of a single clutter block; AMTD, based on MTD, adaptively obtains clutter characteristics and forms corresponding Doppler filters to achieve clutter suppression, but the design of high-quality filters requires a lot of calculations and consumes a lot of computing resources.
[0030] Based on this, the present application provides a clutter suppression method, which, according to the characteristics of meteorological clutter, directly based on the range Doppler spectrum of the radar signal, determines the clutter area of the radar signal in the velocity dimension by the power value of the middle column, quantizes the range Doppler spectrum, and determines the clutter block of the radar signal by the gradient value between the quantized values of each column in the clutter area, and finally suppresses the clutter of the radar signal by the characteristics of the clutter block. Through the above method, the characteristics of meteorological clutter can be adaptively extracted directly based on the range Doppler spectrum of the radar signal, and the meteorological clutter can be directly suppressed on the range Doppler spectrum based on the characteristics of the meteorological clutter, without the need to design a complex filter, saving computing resources.
[0031] Figure 1 A flow chart of a method for suppressing meteorological clutter provided in an embodiment of the present application is shown, and the method is executed by electronic devices such as a signal processor of a radar system, a drone countermeasure device, a computer or a server.
[0032] like Figure 1 As shown, the method comprises the following steps:
[0033] Step 100: Obtain a range Doppler spectrum of a radar signal, wherein the range Doppler spectrum has a range dimension, a velocity dimension, and a power dimension, wherein the range dimension is a row dimension, and the velocity dimension is a column dimension.
[0034] Specifically, within a coherence time, a radar signal is obtained, which can be recorded as X∈C L×K , where L represents the number of range gates, that is, the number of sampling points in a radar pulse, and K represents the number of pulses emitted by the radar within the coherence time. Then, by performing pulse compression on the range dimension of the radar signal X and performing fast Fourier transformation on the pulse dimension of the radar signal X, the total range Doppler spectrum P∈C of the radar signal X can be obtained. L×K .
[0035] In the total range Doppler spectrum P, the range Doppler spectrum has L rows of data in the distance dimension, and has K columns of data in the speed dimension. In either the distance dimension or the speed dimension, each data of the range Doppler spectrum has a corresponding distance value, speed value, and power value.
[0036] Since the characteristics of meteorological clutter are different in each distance segment, for example, within the distance of 1 to 50 meters, rain clutter has similar characteristics 1, and within the distance of 51 to 100 meters, rain clutter has similar characteristics 2. Therefore, the total range Doppler spectrum can be segmented in the distance dimension to obtain multiple range Doppler spectra. Each range Doppler spectrum is subsequently processed separately to remove meteorological clutter more accurately. Furthermore, since the total range Doppler spectrum has a large amount of data, after the total range Doppler spectrum is segmented in the distance dimension, the amount of data of each range Doppler spectrum obtained is small, which can make the calculation of each range Doppler spectrum simpler and faster, thereby improving the overall calculation efficiency.
[0037] Specifically, the total range Doppler spectrum can be evenly divided according to the number of rows in the range dimension. For example, each range Doppler spectrum can be set to include r l row data, that is, the total range Doppler spectrum is evenly divided into L / r i Range Doppler spectrum, each range Doppler spectrum can be recorded as The subscript i represents the i-th range Doppler spectrum. The obtained range Doppler spectrum P i In the example, the distance dimension corresponds to r l The speed dimension corresponds to K columns of data. It should be noted that when L cannot divide r l When the total range Doppler spectrum is divided into (L / r i +1) range Doppler spectrum P i , where the last row of the distance-Doppler spectrum is less than r l .
[0038] Taking rain clutter as an example, when the total range Doppler spectrum is P∈C 200×12 When the total range Doppler spectrum is divided into 40 range Doppler spectra in the distance dimension, according to the different clutter characteristics of rain clutter at different distances, each range Doppler spectrum has 5 rows of data in the distance dimension and 12 columns of data in the speed dimension. In this way, the total range Doppler spectrum is reasonably segmented according to the characteristics of clutter, so that the clutter characteristics of each range Doppler spectrum have good consistency in Doppler distribution, thereby determining more accurate clutter.
[0039] Assume that the first range Doppler spectrum is P1∈C 5×12 , we can get Figure 2The range Doppler power spectrum shown in the figure only shows part of the range Doppler power spectrum and does not constitute a limitation. Figure 2 As shown, the horizontal axis represents the speed dimension, and the vertical axis represents the distance dimension, wherein a speed of 0 to 5 indicates that the target is moving away, and a speed of 0 to -5 indicates that the target is approaching.
[0040] Step 200: In the velocity dimension of the range Doppler spectrum, determine the clutter region of the radar signal according to a first variance between the power value of the middle column and the power values of other columns, wherein the middle column corresponds to the maximum velocity value in the velocity dimension.
[0041] Since the intensity of meteorological clutter is usually stronger than the target signal, this will cause the clutter area in the range Doppler power spectrum to have a higher power value, thereby increasing the variance of the clutter area. In addition, changes in the Doppler shift will cause changes in the variance in the range Doppler power spectrum. In the embodiment of the present application, the middle column corresponds to the column with the largest speed value in the speed dimension. Since the speed of meteorological clutter, such as rain clutter, is relatively small, it is usually not distributed in areas with higher speeds. Therefore, the middle column is an area without clutter. Figure 2 As shown, the middle column may be the column corresponding to the speed value 5, or the column corresponding to the speed value (-5).
[0042] In the velocity dimension, the clutter region where clutter exists can be determined in the range Doppler spectrum according to the first variance between the power value of the middle column and the power values of other columns.
[0043] In some embodiments, step 200 includes the following steps:
[0044] Step 210: In the velocity dimension of the range Doppler spectrum, first variances between the power values of the middle column and the power values of other columns are calculated in sequence to obtain first variances corresponding to each other column.
[0045] For example, the variance between the power value of the middle column and the power value of the first column is calculated to obtain the first variance corresponding to the first column, the variance between the power value of the middle column and the power value of the second column is calculated to obtain the first variance corresponding to the second column... and so on, the first variance between the power value of the middle column and the power values of the first column, the second column, ..., the Kth column is calculated in sequence to obtain the first variances corresponding to the first column, the second column, ..., the Kth column except the middle column.
[0046] Step 220: Determine the clear area and the initial clutter area of the radar signal in the velocity dimension according to the first variance on the range Doppler spectrum.
[0047] Specifically, in the velocity dimension of the range Doppler spectrum, multiple consecutive columns whose first variances are all greater than a first preset variance threshold can be determined as initial clutter areas of the radar signal, and the middle columns can be determined as clear areas of the radar signal.
[0048] For example, assuming that the first preset variance threshold is 3dB, when the first variances corresponding to the 5th, 6th, 7th and 8th columns are all greater than 3dB, the 5th to 8th columns are determined as the initial clutter area of the radar signal; when the first variance corresponding to the 5th column is greater than 3dB, the first variance corresponding to the 6th column is less than 3dB, and the first variances corresponding to the 7th and 8th columns are greater than 3dB, the 7th and 8th columns are determined as the initial clutter area of the radar signal. In this way, when the radar signal has multiple clutters, multiple initial clutter areas of the radar signal can be determined in the range Doppler spectrum at the same time.
[0049] In the embodiment of the present application, since the middle column is located in the region without clutter in the range Doppler spectrum, the middle column is determined as a clear region of the radar signal, which can improve the accuracy of the initial clutter region. Figure 2 The two columns of data corresponding to the speed values 5 and / or (-5) shown are determined as clear areas. Of course, multiple consecutive columns with higher speeds, including the middle column, can also be determined as clear areas of the radar signal.
[0050] Step 230: Determine the clutter region of the radar signal from the initial clutter region based on a second variance between the average power value of the clear region and each power value of the initial clutter region on the range Doppler spectrum.
[0051] In the range Doppler spectrum, the power value of the initial clutter area may contain not only clutter but also the system noise floor power. In this case, the multiple initial clutter areas determined on the range Doppler spectrum may be areas without clutter. Subtracting the noise floor power from each power value of the initial clutter area can obtain a more accurate power value of the initial clutter area, thereby determining the clutter area of the radar signal from multiple initial clutter areas.
[0052] Since the clear area does not contain clutter, the average power value of the clear area can be used as the background noise power, and then the clutter area of the radar signal can be determined from multiple initial clutter areas through the second variance between the average power value of the clear area and each power value of the initial clutter area.
[0053] After step 210 to step 230, the clear area and the initial clutter area of the radar signal can be determined on the range Doppler spectrum. Then, the average power value of the clear area is used as the background noise power, and each power value in the clutter area is subtracted from the average power value in the clear area. A more accurate clutter area can be determined on the range Doppler spectrum, thereby improving the accuracy of clutter suppression.
[0054] In some embodiments, step 230 includes the following steps:
[0055] Step 231: sequentially calculating the second variance between the average power value of the clear area and each power value of the initial clutter area.
[0056] like Figure 2 As shown, when the clear area is the middle column, that is, the column corresponding to the speed value of 5, the average power value W of the clear area V for: When the speed value of the clear area is 5 and (-5) corresponding to the two columns, the average power value of the clear area is W V for:
[0057]
[0058] Calculate the average power W in the clear area V Then, calculate W V The second variance between each power value of the initial clutter area is obtained to obtain the second variance corresponding to each power value. Assuming that the two columns corresponding to the speed values 1 and 2 are the initial clutter area, the power value W can be calculated. 11 To W 20 The corresponding second variance S 11 To S 20 For example, W 11 The corresponding second variance S 11 For: S 11 =(W 11 -W V ) 2 .
[0059] In the process of calculating the background noise power, if the clear area contains a target point, since the power value of the target point is usually much higher than other power values in the clear area, this will cause the calculated average power value of the clear area to be much higher than the actual background noise power, resulting in the average power value not accurately reflecting the background noise power of the system. In this case, determining the abnormal power value (that is, the target point) in the clear area and calculating the average power value of the clear area after removing the abnormal power value can avoid the above problem.
[0060] Therefore, before calculating the second variance between the average power value of the clear area and each power value of the initial clutter area, the clear area is processed to remove the abnormal power values in the clear area to obtain a more accurate average power value of the clear area, and a more accurate clutter area can be obtained. Therefore, before step 231, the following steps are also included:
[0061] Step 231a: Determine the power value in the clear area that is greater than the preset power threshold as an abnormal power value.
[0062] Step 231b: Calculate the average value of the power value in the column where the abnormal power value is located.
[0063] Step 231c: After modifying the abnormal power value to the average value, calculate the average power value of the clear area.
[0064] like Figure 2 As shown, when the preset power threshold is 10dB, the clear area is the two columns corresponding to the speed values of 5 and (-5), and W4=20dB, W4 is determined as an abnormal power value. Then, the average power value of the column with the speed value of 5 where W4 is located is calculated. For example, the average value of W1, W2, W3, W4 and W5 can be directly calculated, or W4 can be eliminated first, and then the average value of W1, W2, W3 and W5 can be calculated. After that, W4 is modified to the average value, and the average power value W of the clear area is calculated after the modification. V .
[0065] Through step 231a to step 231c, the abnormal power values in the clear area can be eliminated, a more accurate average power value of the clear area can be calculated, and the calculation accuracy of the second variance can be improved, thereby obtaining a more accurate clutter area.
[0066] Step 232: Determine whether there is a second variance greater than a second preset variance threshold among the plurality of second variances.
[0067] Assuming that the second preset variance threshold is 5 dB, the S of the initial clutter area calculated in step 231 is determined to be 11 To S 20 Is there a second variance greater than 5dB in ?
[0068] Step 233: If there is a second variance greater than a second preset variance threshold among the plurality of second variances, the initial clutter region is determined as a clutter region on the range Doppler spectrum.
[0069] When S 11 To S 20 There is a second variance greater than 5dB in, for example, S 14 , S 15 and S 16 All greater than 5dB, or S 15 When S is greater than 5dB, it is considered that there is clutter in the initial clutter area and clutter suppression is required. Then the initial clutter area is determined as the clutter area of the radar signal. 11 To S 20 If there is no second variance greater than 5dB, it is considered that there is no clutter in the clutter area and no clutter suppression is required.
[0070] Through step 231 to step 233, the clutter area where clutter actually exists can be determined from the multiple initial clutter areas, so as to suppress clutter in the area where clutter suppression is really needed, thereby reducing false alarm events caused by system noise.
[0071] Step 300: quantize all power values in the range Doppler spectrum to obtain a clutter quantization spectrum.
[0072] After the clutter area is determined in the range Doppler spectrum, the power values greater than 0 in the entire range Doppler spectrum can be set to 1, and the power values less than 0 can be set to 0. In this way, the power values greater than 0 in the clutter area are also set to 1, and the power values less than 0 are also set to 0. Of course, the power values greater than 0 in the range Doppler spectrum can also be set to 2, and the power values less than 0 can be set to 0.
[0073] Through quantization, complex power values can be simplified into several discrete levels, which can reduce the complexity of the data and the amount of data processed.
[0074] Step 400: determining the clutter block of the radar signal according to the gradient value between each column of quantization values and the previous column of quantization values in the clutter area on the clutter quantization spectrum.
[0075] Specifically, the gradient value between each column of quantized values in the clutter area and the previous column of quantized values specifically refers to: the gradient value between the first column in the clutter area and the first column in the non-clutter area, the gradient value between the second column and the first column in the clutter area, the gradient value between the third column and the second column in the clutter area, the gradient value between the fourth column and the third column in the clutter area... Large changes in gradient values usually occur at the boundaries between the clutter area and the non-clutter area. Therefore, these boundaries can be accurately located through the above gradient values, and then the clutter blocks of the radar signal can be located in the clutter area.
[0076] In some embodiments, step 400 includes the following steps:
[0077] Step 410: Calculate the difference between each column of quantization values in the clutter area and the previous column of quantization values on the clutter quantization spectrum to obtain multiple gradient values in the clutter area, wherein the gradient value includes a first gradient value and a second gradient value, the absolute values of the first gradient value and the second gradient value are equal, the first gradient value is a positive number, and the second gradient value is a negative number;
[0078] For example, in the clutter quantization spectrum shown in Figure 3(a), the area indicated by the dotted box in the figure is the clutter area, that is, the 2nd to 6th columns are the clutter area, and the 1st and 7th columns are the non-clutter area. The differences between the 2nd column of the clutter area and the 1st column of the non-clutter area, between the 3rd column and the 2nd column, between the 4th column and the 3rd column, between the 5th column and the 4th column, and between the 6th column and the 5th column are calculated in sequence, and multiple gradient values shown in Figure 3(b) can be obtained.
[0079] Step 420: On each row of the distance dimension of the distance Doppler spectrum, determine a column from a first gradient value to a column from a second gradient value in the clutter region as a clutter block of the radar signal, wherein the column from the first gradient value to the left of the column from the second gradient value to the left of the column.
[0080] In this embodiment, the first gradient value may be 1, indicating the beginning of the clutter region, and the second gradient value may be -1, indicating the end of the clutter region. Therefore, the region between 1 and -1 is a region with clutter.
[0081] As shown in FIG3(b), for the first row, i.e., the row with a distance of 200, the column with a speed value of 3 where 1 is located and the column with a speed value of 5 where (-1) is located are determined as clutter block 1 of the radar signal; for the second row, i.e., the row with a distance of 300, the column with a speed value of 2 where 1 is located and the column with a speed value of 4 where (-1) is located are determined as clutter block 2 of the radar signal; for the third row, i.e., the row with a distance of 400, the column with a speed value of 3 where 1 is located and the column with a speed value of 5 where (-1) is located are determined as clutter block 3 of the radar signal; for the fourth row, i.e., the row with a distance of 500), the column with a speed value of 4 where 1 is located and the column with a speed value of 6 where (-1) is located are determined as clutter block 4 of the radar signal; for the fifth row, i.e., the row with a distance of 600, the column with a speed value of 3 where 1 is located and the column with a speed value of 5 where (-1) is located are determined as clutter block 5 of the radar signal.
[0082] By calculating the difference between the quantized values between consecutive columns in the clutter region, the distribution of clutter in the velocity dimension can be revealed, so that clutter blocks can be accurately identified on the range-Doppler spectrum.
[0083] Step 500: performing clutter suppression on the radar signal according to the clutter bandwidth and clutter center of the clutter block on the range Doppler spectrum.
[0084] The clutter bandwidth is the span of the clutter block in the velocity dimension, and the clutter center is the center of the clutter block in the velocity dimension.
[0085] As shown in Figure 3(b), the span of clutter block 1, clutter block 3 and clutter block 5 in the speed dimension is 3 columns, and the center in the speed dimension is the 4th column, that is, the clutter bandwidth of clutter block 1, clutter block 3 and clutter block 5 is 3, and the clutter center is the clutter frequency corresponding to speed 4. The span of clutter block 2 in the speed dimension is 3 columns, and the center in the speed dimension is the 3rd column, that is, the clutter bandwidth of clutter block 1 is 3, and the clutter center is the clutter frequency corresponding to speed 3. The span of clutter block 4 in the speed dimension is 3 columns, and the center in the speed dimension is the 5th column, that is, the clutter bandwidth of clutter block 4 is 3, and the clutter center is the clutter frequency corresponding to speed 5.
[0086] After determining the clutter bandwidth and the clutter center, the clutter block can be located on the range Doppler spectrum according to the clutter bandwidth and the clutter center, thereby suppressing the clutter block. Specifically, all power values in the clutter block can be modified to the average power value of the clear area, for example, to the average power value of the middle column.
[0087] The embodiment of the present application can determine the clutter area of the radar signal in the velocity dimension of the range Doppler spectrum by obtaining the range Doppler spectrum of the radar signal and the first variance between the power value of the middle column and the power value of other columns. Then, the clutter quantization spectrum is obtained by quantizing all power values in the range Doppler spectrum, so that the clutter block of the radar signal can be determined by the gradient value between the quantization value of each column of the clutter area and the quantization value of the previous column. Finally, the clutter of the radar signal is directly suppressed on the range Doppler spectrum by the clutter bandwidth and clutter center of the clutter block. Through the above method, there is no need to design a complex filter, and the characteristics of meteorological clutter can be directly extracted based on the range Doppler spectrum of the radar signal, and the meteorological clutter can be adaptively suppressed directly on the range Doppler spectrum based on the characteristics of the meteorological clutter, saving computing resources.
[0088] In order to improve the accuracy of the clutter block, the embodiment of the present application further processes the clutter quantization spectrum obtained in step 300 of the above embodiment, as follows: Figure 4 As shown, including:
[0089] Step 300a: Establish a sliding window matrix in the noise quantization spectrum, the quantization value corresponding to the first row and first column of the sliding window matrix is the quantization value corresponding to the first row and first column of the noise quantization spectrum, the number of columns of the sliding window matrix is less than the number of columns of the noise quantization spectrum, and the number of columns and rows of the sliding window matrix are both odd numbers.
[0090] As shown in FIG5( a ), a 3×3 sliding window matrix may be established in the clutter quantization spectrum. The sliding window matrix includes a total of 9 power values: 1, 0, 0, 1, 0, 1, 0, 1, and 1.
[0091] Step 300b of eliminating clutter noise: calculating the total number of quantization values in the sliding window matrix that is equal to the preset quantization value, and modifying the quantization value corresponding to the center position of the sliding window matrix whose total number is greater than the preset total number threshold to the preset quantization value;
[0092] The preset quantization value may be 1, and the preset total threshold may be 4. In this step, the total number of quantization values equal to 1 in the sliding window matrix is first calculated at the starting position, and then it is determined whether the total number is greater than 4. When the total number is greater than 4, the quantization value at the center position of the sliding window matrix, that is, the 2nd row and the 2nd column, is modified to 1; when the total number is less than or equal to 4, the quantization value at the center position of the sliding window matrix, that is, the 2nd row and the 2nd column, is modified to 0.
[0093] Step 300c: Move the sliding window matrix and execute step 300b of eliminating clutter noise until the entire clutter quantization spectrum is traversed.
[0094] Specifically, the sliding window matrix may be moved column by column and then row by row, or may be moved row by row and then column by column, and the step 300b of eliminating clutter noise is performed after each movement of the sliding window matrix, until the moving sliding window matrix traverses the entire clutter quantization spectrum and stops. After the sliding window matrix traverses the entire clutter quantization spectrum, the final clutter quantization spectrum as shown in FIG5(b) can be obtained.
[0095] After obtaining the final noise quantization spectrum, the gradient value is calculated again, and finally multiple gradient values as shown in Figure 5(c) can be obtained. As shown in Figure 5(c) on the right, after sliding the window, only the two rows with distances of 300 and 600 are finally determined to have noise blocks.
[0096] In the process of quantizing the clutter area, noise points may be introduced or target points may be misjudged as clutter points. Noise points or target points are often isolated or do not form a continuous area in the sliding window matrix. Therefore, through the above method, noise points and target points can be eliminated to obtain accurate clutter blocks.
[0097] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown, and the specific embodiment of the present application does not limit the specific implementation of the electronic device.
[0098] like Figure 6 As shown, the electronic device may include: a processor (processor) 602 and a memory (memory) 604.
[0099] The memory 604 is used to store a computer program 606. The memory 604 may include a high-speed RAM memory, or may also include a non-volatile memory, such as at least one disk memory. The computer program 606 may include computer executable instructions.
[0100] The processor 602 is used to execute the computer program 606 to implement the above-mentioned meteorological clutter suppression method embodiment.
[0101] The processor 602 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the electronic device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.
[0102] An embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned meteorological clutter suppression method embodiment is implemented.
[0103] An embodiment of the present application provides a computer program, which can be executed by a processor to implement the above-mentioned meteorological clutter suppression method embodiment.
[0104] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned meteorological clutter suppression method embodiment is implemented.
[0105] In several embodiments provided in the present application, if any function is implemented in the form of a software function module / unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, part or all of the technical solution of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, server or other electronic device) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (RandomAccess Memory, RAM), disk or optical disk and other media that can store computer program code.
[0106] The algorithm or display provided here is not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages can be utilized to realize the content of the present application described here, and the above description of specific languages is to disclose the best mode of implementation of the present application.
[0107] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be constructed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In the claims that list several devices, several units or modules in these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.
[0108] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for suppressing meteorological clutter, characterized in that: The meteorological clutter suppression method comprises: Acquire a range Doppler spectrum of the radar signal, wherein the range Doppler spectrum has a distance dimension, a velocity dimension, and a power dimension, wherein the distance dimension is a row dimension, and the velocity dimension is a column dimension; In the velocity dimension of the range Doppler spectrum, determining the clutter region of the radar signal according to a first variance between a power value of a middle column and power values of other columns, wherein the middle column corresponds to a maximum velocity value in the velocity dimension; Quantizing all power values in the range Doppler spectrum to obtain a clutter quantization spectrum; Determining the clutter block of the radar signal according to the gradient value between each column of quantization values and the previous column of quantization values in the clutter area on the clutter quantization spectrum; The radar signal is subjected to clutter suppression on the range Doppler spectrum according to the clutter bandwidth and the clutter center of the clutter block.
2. The method for suppressing meteorological clutter according to claim 1, characterized in that: The method further comprises: determining the clutter area of the radar signal according to a first variance between the power value of the middle column and the power values of other columns in the speed dimension of the range Doppler spectrum; In the velocity dimension of the range Doppler spectrum, first variances between the power values of the middle column and the power values of other columns are calculated in sequence to obtain a first variance corresponding to each of the other columns; Determining a clear area and an initial clutter area of the radar signal in the velocity dimension according to the first variance on the range Doppler spectrum; The clutter region of the radar signal is determined from the initial clutter region based on a second variance between an average power value of the clear region and each power value of the initial clutter region on the range-Doppler spectrum.
3. The method for suppressing meteorological clutter according to claim 2, characterized in that: The determining of the clear area and the initial clutter area of the radar signal in the velocity dimension according to the first variance on the range Doppler spectrum further includes: In the velocity dimension of the range Doppler spectrum, a plurality of continuous columns whose first variances are all greater than a first preset variance threshold are determined as initial clutter areas of the radar signal, and the middle column is determined as a clear area of the radar signal.
4. The method for suppressing meteorological clutter according to claim 2, characterized in that: The determining of the clutter region of the radar signal from the initial clutter region based on a second variance between an average power value of the clear region and each power value of the initial clutter region on the range Doppler spectrum further comprises: sequentially calculating a second variance between the average power value of the clear area and each power value of the initial clutter area; Determine whether there is a second variance greater than a second preset variance threshold among the plurality of second variances; If there is a second variance greater than the second preset variance threshold among the plurality of second variances, the initial clutter region is determined as the clutter region on the range Doppler spectrum.
5. The method for suppressing meteorological clutter according to claim 4, characterized in that: Before sequentially calculating the second variance between the average power value of the clear area and each power value of the initial clutter area, the meteorological clutter suppression method further includes: Determining a power value in the clear area that is greater than a preset power threshold as an abnormal power value; Calculate the average value of the power value in the column where the abnormal power value is located; After the abnormal power value is modified to the average value, the average power value of the clear area is calculated.
6. The method for suppressing meteorological clutter according to claim 1, characterized in that: After quantizing all power values in the range Doppler spectrum to obtain a clutter quantization spectrum, the meteorological clutter suppression method further includes: Establishing a sliding window matrix in the clutter quantization spectrum, the quantization value corresponding to the first row and the first column of the sliding window matrix is the quantization value corresponding to the first row and the first column of the clutter quantization spectrum, the number of columns of the sliding window matrix is less than the number of columns of the clutter quantization spectrum, and the number of columns and the number of rows of the sliding window matrix are both odd numbers; The step of eliminating clutter noise: calculating the total number of quantization values in the sliding window matrix equal to the preset quantization value, and modifying the quantization value corresponding to the center position of the sliding window matrix whose total number is greater than the preset total number threshold to the preset quantization value; The sliding window matrix is moved, and the step of eliminating clutter noise is performed until the entire clutter quantization spectrum is traversed.
7. The method for suppressing meteorological clutter according to claim 1, characterized in that: The method further comprises: determining the clutter block of the radar signal according to the gradient value between each column of quantization values of the clutter area and the previous column of quantization values on the clutter quantization spectrum; Calculating the difference between each column of quantization values of the clutter area and the previous column of quantization values on the clutter quantization spectrum to obtain a plurality of gradient values of the clutter area, wherein the gradient values include a first gradient value and a second gradient value, the first gradient value and the second gradient value have the same absolute value, the first gradient value is a positive number, and the second gradient value is a negative number; On each row of the range dimension of the range Doppler spectrum, a column where the first gradient value is located to a column where the second gradient value is located in the clutter area are determined as a clutter block of the radar signal, wherein the column where the first gradient value is located is located to the left of the column where the second gradient value is located.
8. The method for suppressing meteorological clutter according to claim 1, characterized in that: The step of obtaining the range Doppler spectrum of the radar signal further comprises: Acquire a total range Doppler spectrum of the radar signal; The total range Doppler spectrum is segmented in the range dimension of the range Doppler spectrum to obtain a plurality of the range Doppler spectra.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the meteorological clutter suppression method according to any one of claims 1 to 8.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the meteorological clutter suppression method according to any one of claims 1 to 8 is implemented.