Weather radar scatter noise filtering method

Abstract

The invention discloses a weather radar scatter noise filtering method, and belongs to the technical field of radar scatter noise filtering. Detection data detected by a weather radar are obtained; performing neighborhood proportional filtering and precipitation edge judgment on the detection data clockwise in a direction-by-direction manner to obtain a first judgment result; performing neighborhood proportional filtering and precipitation edge judgment on the detection data anticlockwise in a direction-by-direction manner to obtain a second judgment result; according to the first judgment result and the second judgment result, a third judgment result is obtained, and the third judgment result comprises a noise distance library and an effective echo distance library; according to the third judgment result, the echo value of the noise distance library is set as an invalid value, the problem that the precipitation echo edge judgment is incomplete during single-direction judgment is solved, the process is simple, calculation is convenient, no parameter is added on the basis of the filtering method, the method complexity is relatively low, the execution efficiency is high, and the method is suitable for popularization and application. And the method is easy to realize and apply in engineering.

Description

Technical Field

[0001] The present invention relates to the technical field of radar clutter noise filtering, and particularly relates to a method for filtering clutter noise of weather radar. Background Art

[0002] Radar is the abbreviation of Radio Detection and Ranging, that is, radio detection and ranging. It discovers and determines the position of spatial targets by using radio methods. It was initially applied in the military and gradually used in the meteorological field after World War II. With the development of technology, the detection ability of radar is getting higher and higher, and it has become an important means of weather detection. It is widely used in the observation of weather phenomena such as clouds, rain, snow, thunderstorms, and turbulence. Especially, it has important application value for the monitoring and forecasting of disaster weather.

[0003] According to different technical systems, meteorological radars are divided into pulse Doppler, dual polarization, and phased array radars. Doppler radar is a radar that uses the Doppler effect to measure the radial motion speed of meteorological targets on the radar beam. Dual polarization radar adds a vertical polarization channel on the basis of the original horizontal polarization channel of ordinary Doppler radar to obtain more meteorological information, such as physical quantities such as the geometric shape and particle phase state of meteorological targets. Phased array radar replaces the parabolic antenna of conventional radar with an array antenna and can flexibly and quickly control the beam movement through phased array technologies such as "electrical scanning" to obtain high spatio-temporal resolution observation data, and can better and more accurately detect rapidly changing weather systems, which is very useful for the analysis and early warning of severe convection processes. According to the wavelength of the emitted electromagnetic wave, the new generation of weather radars in China are mainly divided into S-band (10 cm), C-band (5 cm), X-band (3 cm) radars, etc. Among them, the S-band is mainly distributed in coastal areas with heavy and strong precipitation, the C-band is mainly deployed in the central region where convective weather occurs and is active frequently and the economy is relatively developed, and the X-band radar is used as a beneficial supplement to improve the accuracy of weather detection.

[0004] The radar emits electromagnetic waves in the form of pulses. When the electromagnetic wave pulses encounter various substances (raindrops, snowflakes, hail, and other non-meteorological targets), part of the energy is scattered by the target particles, and the other part is absorbed by the particles. The scattered energy part is received by the radar and converted into an image after being processed by the radar hardware and calculated by the software, and then displayed as a radar echo. The scattering of radar electromagnetic waves by meteorological targets is the basis for radar detection of the atmosphere.

[0005] At present, the basic data products of operational radars include echo intensity (also known as reflectivity), radial velocity, velocity spectrum width, etc. Among them, echo intensity reflects the size and concentration of target particles, radial velocity is the projection of the particle movement velocity in the beam direction, and velocity spectrum width reflects the deviation of the particle movement velocity. Based on the basic data products, other physical quantity products, automatic identification and tracking of severe weather, wind field inversion and other secondary products can be generated. The quality of the basic data products largely determines the quality of the secondary products. In order to accurately understand radar data and correctly identify and classify radar echoes, it is necessary to ensure the quality of the basic data products. Since the improvement of the quality of the basic data obtained by continuous hardware calibration is limited, non-meteorological echoes stored in the basic data need to be identified and removed using software algorithms.

[0006] There are mainly three types of non-meteorological echoes. One is point clutter caused by insects, birds, and other particles that return the electromagnetic wave power to the radar; the second is ground clutter returned when the radar beam hits ground buildings or mountains, etc., or sea clutter returned when the radar beam hits the sea under normal radar beam propagation conditions; the third is ground or sea clutter returned when the radar beam bends towards the ground under the condition of uneven atmospheric refractive index, and this kind of echo is called super-refraction echo.

[0007] It is very important to use certain clutter suppression techniques to recover available meteorological data from contaminated echo data. The amount of data that can be recovered and the reliability of the recovered data are closely related to the characteristics of the clutter itself and the clutter suppression methods used. Scattered noise echoes (also known as isolated echoes, speckle echoes) often appear in weather radar echo data, such as insect and aircraft echoes. These echoes mostly appear in the form of isolated points or thin lines, with weak echo reflectivity values, small echo areas, and are independent of other meteorological echoes. The reflectivity values of scattered noise vary widely and can cover a large range. The first type of non-meteorological echoes, improper post-processing of radar basic data quality control, etc. will all cause scattered noise in the echo diagram. The commonly used method for dealing with scattered noise at present is the "neighborhood ratio filtering method". As long as the proportion of the number of valid echo points in a certain neighborhood to the total number of the area is greater than a certain threshold, it is considered that this point is not scattered noise. However, this method will cause a large area loss of the edge information of meteorological echoes, seriously affecting the processing effect of meteorological data.

[0008] Therefore, in the application of the "neighborhood ratio filtering method", since the percentage of the number of valid echo bins at the edge of precipitation echoes is relatively small, it may be identified as noise and wrongly removed, resulting in a smaller scale of precipitation echoes, serious loss of echo edge information, and affecting the further application effect of echo data, such as precipitation estimation accuracy.

[0009] Although the "echo block area method" can solve the problem of information loss at the edge of precipitation echoes in the "neighborhood ratio filtering method", this method requires the division of the effective echo distance segment and the merging of echo blocks before noise identification, which increases the computational complexity compared to the "neighborhood ratio filtering method". In practical engineering applications, it will occupy more storage resources and cause problems with execution efficiency. In addition, this method has many preset parameters, and different parameter values will bring different results, which also increases the complexity of the noise filtering method to a certain extent. Summary of the Invention

[0010] The present invention provides a method for filtering scattered point noise of weather radar to solve the technical problems existing in the "neighborhood ratio filtering method" in the prior art, such as losing a lot of precipitation echo edge information while filtering noise, and the high complexity and large computational amount in the "echo block area method". It achieves the technical effects of avoiding the problem of incomplete precipitation echo edge judgment in one-way determination, with a simple process, convenient calculation, no additional parameters added on the basis of the filtering method, relatively low method complexity, high execution efficiency, and being easy to implement and apply in engineering.

[0011] The present invention provides a method for filtering scattered point noise of weather radar. The method for filtering scattered point noise of weather radar includes: Step 1: Obtain detection data detected by the weather radar; Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction by azimuth to obtain a first judgment result; Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a counterclockwise direction by azimuth to obtain a second judgment result; Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, where the third judgment result includes a noise distance library and an effective echo distance library; Step 5: Set the echo value of the noise distance library to an invalid value according to the third judgment result.

[0012] Preferably, in Step 2, performing neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction by azimuth to obtain a first judgment result specifically includes:

[0013] Perform filtering using Equation (1):

[0014]

[0015] where x is the first distance library, N b 、N g are the number of azimuths and the number of distance libraries of the fan-shaped window centered on x respectively, N x is the number of effective echoes in the fan-shaped window, and P x is the proportion of the number of effective echoes in the fan-shaped window.

[0016] Preferably, in the step 2, it further includes: obtaining a first set threshold; if P x is less than the first set threshold, and the echo values of the previous distance bin in the same radial direction adjacent to the first distance bin and the same distance bin in the previous radial direction adjacent to the first distance bin are both invalid echoes, then the first distance bin is noise and is replaced with an invalid value; if P x is less than the first set threshold, and any one of the echo values of the previous distance bin in the same radial direction adjacent to the first distance bin or the same distance bin in the previous radial direction adjacent to the first distance bin is a valid echo, then the first distance bin is a valid echo and is retained; if P x is greater than or equal to the first set threshold, then the first distance bin is a valid echo and is retained.

[0017] Preferably, in the step 3, the judgment method adopted is the same as the judgment method in the step 2.

[0018] Preferably, in the step 2, the first judgment result is saved.

[0019] Preferably, in the step 3, the second judgment result is saved.

[0020] Preferably, in the step 4, the distance bins that are simultaneously determined as noise in the first judgment result and the second judgment result are determined as noise echoes and are replaced with invalid values. If any one of the corresponding distance bins in the first judgment result and the second judgment result is a valid value, then it is a valid echo and needs to be retained.

[0021] One or more of the above technical solutions in the embodiments of the present invention have at least one or more of the following technical effects:

[0022] A method for filtering scattered point noise of weather radar provided by an embodiment of the present invention includes the following steps: Step 1: Obtain detection data detected by the weather radar; Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction for each azimuth to obtain a first judgment result; Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a counterclockwise direction for each azimuth to obtain a second judgment result; Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, where the third judgment result includes a noise distance bin and a valid echo distance bin; Step 5: According to the third judgment result, set the echo value of the noise distance bin to an invalid value, thereby solving the technical problems in the prior art that in the "neighborhood ratio filtering method", a large amount of precipitation echo edge information is lost while filtering noise, and in the "echo block area method", the complexity is high and the calculation amount is large. It achieves the effect of avoiding the problem of incomplete precipitation echo edge judgment in single-direction determination, and the process is simple, the calculation is convenient, no additional parameters are added on the basis of the filtering method, the method complexity is relatively low, the execution efficiency is high, and it is easy to implement and apply in engineering.

[0023] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are hereinafter specifically exemplified. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of a method for filtering scattered point noise of weather radar in an embodiment of the present invention;

[0025] Figure 2 It is the original echo diagram in an embodiment of the present invention;

[0026] Figure 3 It is the echo diagram after filtering by the "neighborhood ratio filtering method" in an embodiment of the present invention;

[0027] Figure 4 It is the echo diagram after clockwise processing for each azimuth in an embodiment of the present invention;

[0028] Figure 5 It is the echo diagram after counterclockwise processing for each azimuth in an embodiment of the present invention;

[0029] Figure 6 It is the echo diagram after comprehensive processing in an embodiment of the present invention;

[0030] Figure 7 It is the echo diagram of the echo identified as noise by filtering with the "neighborhood ratio filtering method";

[0031] Figure 8The echo map identified as noise after clockwise azimuth-by-azimuth processing in the embodiment of the present invention;

[0032] Figure 9 The echo map identified as noise after counterclockwise azimuth-by-azimuth processing in the embodiment of the present invention;

[0033] Figure 10 The echo map identified as noise after comprehensive processing in the embodiment of the present invention;

[0034] Figure 11 The schematic diagram of the fan-shaped window in the embodiment of the present invention. Detailed implementation manners

[0035] The embodiment of the present invention provides a method for filtering scattered point noise of weather radar, which is used to solve the technical problems existing in the "neighborhood ratio filtering method" in the prior art that a lot of precipitation echo edge information is lost while filtering noise, and the high complexity and large calculation amount existing in the "echo block area method".

[0036] The overall idea of the technical solution in the embodiment of the present invention is as follows:

[0037] A method for filtering scattered point noise of weather radar provided by the embodiment of the present invention includes: Step 1: Obtain detection data detected by the weather radar; Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction azimuth by azimuth to obtain a first judgment result; Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a counterclockwise direction azimuth by azimuth to obtain a second judgment result; Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, where the third judgment result includes a noise distance library and an effective echo distance library; Step 5: According to the third judgment result, set the echo value of the noise distance library to an invalid value, achieving the technical effect of avoiding the problem of incomplete precipitation echo edge judgment in single-direction determination, with a simple process, convenient calculation, no additional parameters added on the basis of the filtering method, relatively low method complexity, high execution efficiency, and easy implementation and application in engineering.

[0038] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Embodiment

[0040] Figure 1It is a flowchart of a method for filtering scattered point noise of weather radar in an embodiment of the present invention. As Figure 1 shown, the method includes:

[0041] Step 1: Obtain the detection data detected by the weather radar.

[0042] Specifically, in order to solve the problem of losing a lot of precipitation echo edge information while filtering noise in the "neighborhood ratio filtering method", and at the same time avoid the problems of high complexity and large amount of calculation in the "echo block area method". The present invention proposes a method for filtering scattered point noise of weather radar. When implementing, it is first necessary to obtain the detection data detected by the weather radar, that is, the echo data. The original reflectivity echo map is as Figure 2 shown, and at the same time, the effect of data processing using the "neighborhood ratio filtering method" and the noise echo map identified by it are as Figure 3 and Figure 7 shown.

[0043] Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction by azimuth to obtain a first judgment result.

[0044] Further, in the step 2, performing neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction by azimuth to obtain a first judgment result specifically includes:

[0045] Perform filtering using Equation (1):

[0046]

[0047] where x is the first range bin, N b 、N g are the number of azimuths and the number of range bins of the fan-shaped window centered on x respectively, N x is the number of valid echoes in the fan-shaped window, and P x is the proportion of the number of valid echoes in the fan-shaped window.

[0048] Further, in the step 2, it also includes: obtaining a first set threshold; if P x is less than the first set threshold, and at the same time, the echo values of the previous range bin in the same radial direction adjacent to the first range bin and the same range bin in the previous radial direction adjacent to the first range bin are both invalid echoes, then the first range bin is noise and is replaced with an invalid value; if P x is less than the first set threshold, and at the same time, any one of the echo values of the previous range bin in the same radial direction adjacent to the first range bin or the same range bin in the previous radial direction adjacent to the first range bin is a valid echo, then the first range bin is a valid echo and is retained; if P xIf it is greater than or equal to the first set threshold value, then the first distance bin is a valid echo, and it is retained.

[0049] Further, in step 2, the first judgment result is saved.

[0050] Specifically, after obtaining the detection data, next, neighborhood ratio filtering and precipitation edge judgment need to be performed in a clockwise direction for each azimuth. The specific judgment method is as follows: First, filtering is performed using equation (1):

[0051] where x represents a certain distance bin, N b and N g are respectively the number of azimuths and the number of distance bins of the fan-shaped window centered on x, N x represents the number of valid echoes in the window, and P x represents the proportion of the number of valid echoes in the window. As Figure 11 shown, it is a 5*5 (i.e., both the number of azimuths and the number of distance bins are 5) fan-shaped window centered on a certain distance bin (hollow circle). If P x is less than the given threshold value, and at the same time, the echo values of the previous distance bin in the same radial direction adjacent to this distance bin and the same distance bin in the previous radial direction adjacent to this distance bin are both invalid echoes, then this distance bin is noise and is replaced with an invalid value. If P x is less than the first set threshold value, and at the same time, any one of the echo values of the previous distance bin in the same radial direction adjacent to this distance bin or the same distance bin in the previous radial direction adjacent to this distance bin is a valid echo, then this distance bin is a valid echo and is retained. If P x is greater than or equal to the given threshold value, this distance bin is also a valid echo and is retained. The processing effect of filtering and precipitation edge judgment in a clockwise direction for each azimuth and the noise echo map identified are as Figure 4 and Figure 8 shown (where the number of azimuths N b =5, the number of distance bins N g =5, and the proportion of the number of valid echoes P x =0.75). The above is the judgment process carried out in a clockwise direction for each azimuth. Further, the first judgment result also needs to be saved.

[0052] Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a counterclockwise direction for each azimuth to obtain a second judgment result.

[0053] Further, in step 3, the judgment method adopted is the same as that in step 2.

[0054] Further, in step 3, the second judgment result is saved.

[0055] Specifically, the judgment process in the clockwise direction for each azimuth described above is equally applicable to the judgment in the counterclockwise direction for each azimuth. Therefore, after the judgment in the clockwise direction for each azimuth is completed and the judgment result is saved, on this basis, the same judgment process as above is carried out in the counterclockwise direction for each azimuth. After obtaining the second judgment result, the second judgment result is saved. The processing effect of filtering and precipitation edge judgment in the counterclockwise direction for each azimuth and the identified noise echo map are as Figure 5 shown Figure 9 in

[0056] Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, wherein the third judgment result includes a noise distance library and a valid echo distance library.

[0057] Step 5: Set the echo value of the noise distance library to an invalid value according to the third judgment result.

[0058] Further, in the step 4, if the distance library that is simultaneously determined to be noise in the corresponding distance libraries of the first judgment result and the second judgment result is determined to be a noise echo, it is replaced with an invalid value. If any one of the corresponding distance libraries in the first judgment result and the second judgment result is a valid value, it is a valid echo and needs to be retained.

[0059] Specifically, after obtaining the first judgment result and the second judgment result, it is necessary to comprehensively judge the judgment results of the clockwise and counterclockwise methods and obtain a third judgment result. Specifically: the distance library that is simultaneously determined to be noise in the corresponding distance libraries of the first judgment result and the second judgment result is finally determined to be a noise echo and is replaced with an invalid value. Otherwise, if any one of the corresponding distance libraries is a valid value, the echo of this distance library is a valid echo and is retained. The processing effect of the comprehensive judgment of counterclockwise and clockwise and the identified noise echo map are as Figure 6 shown Figure 10 in

[0060] Although the "neighborhood ratio filtering method" can filter out scattered point noise, this method will filter out the precipitation edge echo while filtering the scattered points, which brings information loss to the further application of the echo data and affects the accuracy of echo judgment or calculation. Therefore, the present invention adds the judgment of the precipitation echo edge on the basis of the filtering method, retains the echo value that is identified as noise by the filtering method but is simultaneously the precipitation edge, and avoids the problem of incomplete judgment of the precipitation echo edge in the single-direction judgment by designing a comprehensive judgment strategy in the clockwise and counterclockwise directions. This method has a simpler process and more convenient calculation compared with the "echo block area method", does not add any parameters on the basis of the filtering method, has a relatively low method complexity, high execution efficiency, and is easy to implement and apply in engineering.

[0061] Further, in this embodiment, it is possible to first calculate in the clockwise direction for each azimuth, then calculate in the counterclockwise direction and make a comprehensive determination, or first calculate in the counterclockwise direction for each azimuth, and then calculate in the clockwise direction for each azimuth and make a comprehensive determination; this embodiment can be applied not only in radars with different technical systems and different frequency bands, but also in different radar scanning modes, such as volume scanning, elevation sector scanning, etc.; further, for the determination of the edge of precipitation echoes, the number of adjacent range bins of the determination range bin can be increased, for example, increasing the previous range bin in the same radial direction to the previous two or more, and increasing the same range bin in the previous radial direction adjacent to the range bin to the previous two or more radials; in the clockwise and counterclockwise comprehensive noise point determination method designed in this embodiment, it can be jointly applied with the "neighborhood ratio filtering method", or can also be used in combination with other relevant filtering methods to solve the problem of excessive edge filtering.

[0062] One or more of the above technical solutions in the embodiments of the present invention have at least one or more of the following technical effects:

[0063] A method for filtering scattered point noise of a weather radar provided by an embodiment of the present invention includes: Step 1: Obtain detection data detected by the weather radar; Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in the clockwise direction for each azimuth to obtain a first judgment result; Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in the counterclockwise direction for each azimuth to obtain a second judgment result; Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, where the third judgment result includes noise range bins and effective echo range bins; Step 5: According to the third judgment result, set the echo value of the noise range bin to an invalid value, thereby solving the technical problems in the prior art that in the "neighborhood ratio filtering method", a lot of precipitation echo edge information is lost while filtering noise, and in the "echo block area method", the complexity is high and the calculation amount is large, achieving the technical effects of avoiding the problem of incomplete precipitation echo edge judgment in single-direction determination, with a simple process, convenient calculation, no additional parameters added on the basis of the filtering method, relatively low method complexity, high execution efficiency, and being easy to implement and apply in engineering.

[0064] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0065] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A method for filtering scattered point noise of weather radar, characterized in that The weather radar scatter noise filtering method includes the following steps: Step 1: Obtain the detection data detected by the weather radar; Step 2: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction for each azimuth to obtain a first judgment result; Step 3: Perform neighborhood ratio filtering and precipitation edge judgment on the detection data in a counterclockwise direction for each azimuth to obtain a second judgment result; Step 4: Obtain a third judgment result according to the first judgment result and the second judgment result, wherein the third judgment result includes a noise distance bin and an effective echo distance bin; Step 5: According to the third judgment result, set the echo value of the noise distance bin to an invalid value.

2. The weather radar scatter noise filtering method according to claim 1, characterized in that In step 2, performing neighborhood ratio filtering and precipitation edge judgment on the detection data in a clockwise direction for each azimuth to obtain a first judgment result specifically includes: Using formula (1) for filtering: where x is the first distance library, N b , N g are respectively the number of azimuths and the number of distance libraries of the fan-shaped window centered on x, N x is the number of valid echoes of the fan-shaped window, P x is the proportion of the number of valid echoes in the fan-shaped window.

3. The weather radar scatter noise filtering method according to claim 2, characterized in that, In step 2, it further includes: Obtaining a first set threshold; If P x is less than the first set threshold, and the echo values of the previous distance bin in the same radial direction adjacent to the first distance bin and the same distance bin in the previous radial direction adjacent to the first distance bin are both invalid echoes, then the first distance bin is noise and is replaced with an invalid value; If P x is less than the first set threshold, and when any one of the echo values of the previous range bin in the same radial direction adjacent to the first range bin or the range bin in the same radial direction adjacent to the previous radial direction of the first range bin is a valid echo, then the first range bin is a valid echo and is retained; If P x is greater than or equal to the first set threshold, the first distance library is an effective echo and is retained.

4. The weather radar scatter noise filtering method according to claim 3, characterized in that In step 3, the judgment method used is the same as that in step 2.

5. The weather radar scatter noise filtering method according to claim 1, characterized in that In step 2, the first judgment result is saved.

6. The weather radar scatter noise filtering method according to claim 1, characterized in that, In step 3, the second judgment result is saved.

7. The weather radar scatter noise filtering method according to claim 4, characterized in that In step 4, if the distance bins that are simultaneously determined to be noise in the first judgment result and the second judgment result are determined to be noise echoes, they are replaced with invalid values. If any one of the corresponding distance bins in the first judgment result and the second judgment result is a valid value, it is an effective echo and needs to be retained.

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