Method and device for removing lightning contamination from meteor wind radar data

Abstract

This application relates to the field of space exploration technology, and in particular to a method and apparatus for removing lightning contamination from meteor wind radar data. The method includes: acquiring echo data from the receiver corresponding to the target meteor wind radar, and constructing an incoherent average amplitude sequence based on the echo data; constructing a ratio sequence based on the incoherent average amplitude sequence, and sequentially comparing the elements in the ratio sequence with a target threshold; when an element in the ratio sequence is greater than the target threshold, updating the incoherent average amplitude sequence and the ratio sequence using a target natural number division matrix, until the elements in the updated ratio sequence are less than the target threshold, thus obtaining an incoherent average amplitude sequence with lightning contamination removed. This application can quickly and efficiently remove lightning contamination from raw meteor wind radar echo data, achieving real-time removal of lightning contamination from raw meteor wind radar echo data with limited computing resources, thereby effectively improving the efficiency of meteor signal discrimination algorithms.

Description

Technical Field

[0001] This application relates to the field of space exploration technology, and in particular to a method and apparatus for removing lightning contamination from meteor wind radar data. Background Technology

[0002] The region of Earth's atmosphere above approximately 10 km is called the middle and upper atmosphere, which includes the upper troposphere, stratosphere, mesosphere, and thermosphere. Dramatic changes in the wind fields of the middle and upper atmosphere not only directly affect aerospace activities but also play a crucial role in radio communications. Therefore, the core objective of middle and upper atmosphere research is to reveal the key dynamic mechanisms within it and their impact on the space environment. This is of significant scientific value for deepening human understanding of global space environment changes and exploring the Sun-Earth relationship.

[0003] In related technologies, the mesopause (approximately 90 km high) is a transitional region between the neutral atmosphere and the thermosphere / ionosphere, carrying key dynamic and chemical processes and playing a crucial role in momentum, energy, and heat exchange. Common detection methods include sounding rockets, lidar, and radio radar. Among these, radio radar is an effective means of continuous observation of atmospheric wind fields in the mesopause region, especially meteor wind radar. Due to its simple system structure, stable operation, and independence from diurnal variations and weather conditions, it possesses all-weather continuous observation capabilities and is widely deployed globally to monitor dynamic processes such as wind fields, tides, gravity waves, and planetary waves in the middle and upper atmosphere. Its detection principle is based on the reflection of radar signals by meteor trails, and these echo signals contain information related to the atmospheric wind field in the mesopause. Therefore, by analyzing these echo signals, the atmospheric environment of the mesopause within the detection range can be deduced. A key point in the analysis of meteor events is to accurately identify valid meteor echoes and distinguish them from short-term noise signals.

[0004] However, in related technologies, atmospheric lightning interference, which frequently occurs in the raw data of meteor wind measurement radar receivers, is easily confused with real meteor signals, thereby reducing the efficiency of meteor signal discrimination algorithms. This makes it difficult to achieve real-time processing of the radar raw data under limited computing resources. How to quickly and efficiently remove these lightning contaminants from the raw data of meteor wind measurement radar is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a method and apparatus for removing lightning contamination from meteor wind measurement radar data, in order to solve the problems in related technologies, such as how frequent atmospheric lightning interference in the raw data of meteor wind measurement radar receivers is easily confused with real meteor signals, thereby reducing the efficiency of meteor signal discrimination algorithms and making it difficult to achieve real-time processing of radar raw data under limited computing resources, and how to quickly and efficiently remove these lightning contamination from the raw data of meteor wind measurement radar.

[0006] The first aspect of this application provides a method for removing lightning contamination from meteor wind radar data, comprising the following steps: acquiring echo data from a receiver corresponding to a target meteor wind radar, and constructing an incoherent average amplitude sequence based on the echo data; constructing a ratio sequence based on the incoherent average amplitude sequence, and sequentially comparing the elements in the ratio sequence with a target threshold; when the elements in the ratio sequence are greater than the target threshold, updating the incoherent average amplitude sequence and the ratio sequence through a target natural number division matrix, until the elements in the updated ratio sequence are less than the target threshold, thereby obtaining an incoherent average amplitude sequence with lightning contamination removed.

[0007] Optionally, in one embodiment of this application, constructing an incoherent average amplitude sequence based on the echo data includes: constructing an amplitude sequence corresponding to the receiver based on the echo data; and constructing the incoherent average amplitude sequence based on the amplitude sequence.

[0008] Optionally, in one embodiment of this application, constructing a ratio sequence based on the incoherent average amplitude sequence includes: collecting the ratios between adjacent elements in the incoherent average amplitude sequence; and constructing the ratio sequence based on the ratios.

[0009] Optionally, in one embodiment of this application, updating the incoherent average amplitude sequence and the ratio sequence by means of a natural number division matrix when the elements in the ratio sequence are greater than the target threshold includes: updating the corresponding elements in the incoherent average amplitude sequence by means of elements in the natural number division matrix when the ratio elements in the ratio sequence are greater than the target threshold, to obtain an updated incoherent average amplitude sequence; and updating the ratio sequence using the updated incoherent average amplitude sequence to obtain an updated ratio sequence.

[0010] Optionally, in one embodiment of this application, the update formula for the incoherent average amplitude sequence is:

[0011] A i+1 =(A i +A i+2 ) / n j =(A i +Ai+2 ) / (j+1)

[0012] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, and n... j Let each of the natural numbers be the j-th natural number in matrix n. j =j+1.

[0013] Optionally, in one embodiment of this application, the update formula for the ratio sequence is:

[0014] R i =A i+1 / A i

[0015] R i+1 =A i+2 / A i+1

[0016] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, R i R i+1 These are the i-th and (i+1)-th elements in the ratio sequence, respectively.

[0017] A second aspect of this application provides an apparatus for removing lightning contamination from meteor wind radar data, comprising: a first construction module for acquiring echo data from a receiver corresponding to a target meteor wind radar and constructing an incoherent average amplitude sequence based on the echo data; a second construction module for constructing a ratio sequence based on the incoherent average amplitude sequence and sequentially comparing the elements in the ratio sequence with a target threshold; and an update module for updating the incoherent average amplitude sequence and the ratio sequence by means of a target natural number division matrix when the elements in the ratio sequence are greater than the target threshold, until the elements in the updated ratio sequence are less than the target threshold, thereby obtaining an incoherent average amplitude sequence with lightning contamination removed.

[0018] Optionally, in one embodiment of this application, the first construction module includes: a first construction unit, configured to construct an amplitude sequence corresponding to the receiver based on the echo data; and a second construction unit, configured to construct the incoherent average amplitude sequence based on the amplitude sequence.

[0019] Optionally, in one embodiment of this application, the second construction module includes: a acquisition unit for acquiring the ratio between adjacent elements in the incoherent average amplitude sequence; and a third construction unit for constructing the ratio sequence based on the ratio.

[0020] Optionally, in one embodiment of this application, the updating module includes: a first updating unit, configured to update the corresponding element in the incoherent average amplitude sequence by means of the elements in the natural number division matrix when the ratio element in the ratio sequence is greater than the target threshold, to obtain an updated incoherent average amplitude sequence; and a second updating unit, configured to update the ratio sequence using the updated incoherent average amplitude sequence to obtain an updated ratio sequence.

[0021] Optionally, in one embodiment of this application, the update formula for the incoherent average amplitude sequence is:

[0022] A i+1 =(A i +A i+2 ) / n j =(A i +A i+2 ) / (j+1)

[0023] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, and n... j Let each of the natural numbers be the j-th natural number in matrix n. j =j+1.

[0024] Optionally, in one embodiment of this application, the update formula for the ratio sequence is:

[0025] R i =A i+1 / A i

[0026] R i+1 =A i+2 / A i+1

[0027] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, R i R i+1 These are the i-th and (i+1)-th elements in the ratio sequence, respectively.

[0028] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for removing lightning contamination from meteor wind radar data as described in the above embodiments.

[0029] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described above for removing lightning contamination from meteor wind measurement radar data.

[0030] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, is used to implement the method described above for removing lightning contamination from meteor wind measurement radar data.

[0031] This application embodiment can acquire echo data from a target meteor wind-measuring radar receiver to construct an incoherent average amplitude sequence, and then construct a ratio sequence. By comparing each element in the ratio sequence with a target threshold, the incoherent average amplitude sequence and the ratio sequence are updated to obtain an incoherent average amplitude sequence free of lightning contamination. Thus, by constructing an incoherent average amplitude sequence, redundant signals in the receiver echo data are removed, ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed from the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, ultimately obtaining an incoherent average amplitude sequence free of lightning contamination. Comparing this with the initial amplitude sequence, this application not only removes lightning contamination from the raw echo data of a meteor wind-measuring radar, but also does so in a very short time, with extremely high speed and efficiency. It can achieve real-time processing of raw radar echo data with limited computing resources, i.e., removing lightning contamination from the raw echo data of a meteor wind-measuring radar, thereby effectively improving the efficiency of meteor signal discrimination algorithms. This solves the problem in related technologies where frequent atmospheric lightning interference in the raw data of meteor wind measurement radar receivers is easily confused with real meteor signals, thereby reducing the efficiency of meteor signal identification algorithms and making it difficult to achieve real-time processing of radar raw data under limited computing resources. The solution addresses the problem of how to quickly and efficiently remove these lightning contaminants from the raw data of meteor wind measurement radar.

[0032] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0033] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0034] Figure 1 This is a flowchart illustrating a method for removing lightning contamination from meteor wind measurement radar data according to an embodiment of this application;

[0035] Figure 2 This is a flowchart illustrating a method for removing lightning contamination from raw data of a meteor wind-measuring radar according to an embodiment of this application.

[0036] Figure 3 This is a comparative result diagram of one embodiment of this application;

[0037] Figure 4 This is a schematic diagram of the device for removing lightning contamination from meteor wind radar data according to an embodiment of this application;

[0038] Figure 5 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application.

[0039] Figure label:

[0040] 10-A device for removing lightning contamination from meteor wind radar data: 100-First building block, 200-Second building block and 300-Update module; 501-Memory, 502-Processor and 503-Communication interface. Detailed Implementation

[0041] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0042] The following describes a method and apparatus for removing lightning contamination from meteor wind measurement radar data according to embodiments of this application, with reference to the accompanying drawings. In the related technologies mentioned in the background section, frequent atmospheric lightning interference in the raw data of meteor wind measurement radar receivers is easily confused with real meteor signals, thereby reducing the efficiency of meteor signal discrimination algorithms and making it difficult to achieve real-time processing of raw radar data with limited computing resources. To address the problem of how to quickly and efficiently remove this lightning contamination from the raw data of meteor wind measurement radar, this application provides a method for removing lightning contamination from meteor wind measurement radar data. In this method, echo data from a target meteor wind measurement radar receiver is acquired to construct an incoherent average amplitude sequence, followed by constructing a ratio sequence. Then, the incoherent average amplitude sequence and the ratio sequence are updated by comparing each element in the ratio sequence with a target threshold to obtain an incoherent average amplitude sequence with lightning contamination removed. This invention achieves the removal of redundant signals from receiver echo data by constructing an incoherent average amplitude sequence, ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed from the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, ultimately yielding an incoherent average amplitude sequence free of lightning contamination. Comparison with the initial amplitude sequence demonstrates that this application can not only remove lightning contamination from raw meteor wind radar echo data but also achieves this removal in a very short time, with extremely high speed and efficiency. It enables real-time processing of raw radar echo data with limited computing resources, effectively improving the efficiency of meteor signal discrimination algorithms. This solves the problem in related technologies where frequent atmospheric lightning interference in the raw data of meteor wind radar receivers is easily confused with real meteor signals, reducing the efficiency of meteor signal discrimination algorithms and making real-time processing of raw radar data difficult with limited computing resources. The invention addresses the challenge of quickly and efficiently removing lightning contamination from raw meteor wind radar data.

[0043] Specifically, Figure 1 This is a flowchart illustrating a method for removing lightning contamination from meteor wind measurement radar data, as provided in an embodiment of this application.

[0044] like Figure 1 As shown, the method for removing lightning contamination from meteor wind radar data includes the following steps:

[0045] In step S101, the echo data of the receiver corresponding to the target meteor wind radar is obtained, and an incoherent average amplitude sequence is constructed based on the echo data.

[0046] It is understandable that, in this context, a target meteor wind-measuring radar can be understood as a radar device that performs wind measurement by detecting and analyzing meteor trails and can remove lightning contamination from the echo data. The echo data from this meteor wind-measuring radar contains information related to the mesopause atmospheric wind field; by analyzing this echo data, the mesopause atmospheric environment within the detection range can be reconstructed.

[0047] However, the raw echo data from meteor wind radar receivers contains both meteor trail reflection signals and interference signals such as atmospheric scattering. Frequent atmospheric lightning interference signals are easily confused with actual meteor signals, reducing the efficiency of meteor signal identification algorithms and making real-time processing of raw radar data difficult with limited computing resources. Some studies have shown that in a single meteorological storm event, a raw echo data segment containing only six valid meteor records contained as many as 4000 lightning contamination events.

[0048] In some embodiments, this application can acquire echo data from the receiver corresponding to the target meteor wind measuring radar (here and in the following process, echo data refers to the raw echo data without any processing), and process these echo data to construct an incoherent average amplitude sequence to remove lightning contamination from the echo data.

[0049] In this context, incoherent averaging refers to a method that averages the amplitude of signals in the echo data without considering the phase relationship between signals in the original echo data from the receiver. Using this method, embodiments of this application can add and average the amplitudes of multiple signals with similar characteristics but potentially random phase differences in the echo data, thereby suppressing noise and random fluctuations to a certain extent and improving the stability and observability of signals in the echo data.

[0050] Optionally, in one embodiment of this application, constructing an incoherent average amplitude sequence based on echo data includes: constructing an amplitude sequence corresponding to the receiver based on the echo data; and constructing an incoherent average amplitude sequence based on the amplitude sequence.

[0051] As can be understood from the descriptions of other embodiments, incoherent averaging here refers to a method of averaging the amplitude of signals in the receiver echo data without considering the phase relationship between signals in the echo data.

[0052] In actual implementation, this application can first extract the amplitude of the signal in the echo data of each receiver of the target meteor wind measuring radar, construct the amplitude sequence corresponding to each receiver, and then process the amplitude sequence to construct an incoherent average amplitude sequence.

[0053] For example, this application can construct the corresponding amplitude sequence based on the raw echo data from all receivers of the target meteor wind measuring radar. Assuming the target meteor wind measuring radar has M receivers, the amplitude sequence corresponding to all receivers can be, but is not limited to, represented as: AMP1, AMP2, ..., AMP... k , ..., AMP M .

[0054] Among them, AMP k The amplitude sequence of the raw echo data of the k-th receiver (k∈[1,M]) can be represented, but is not limited to, as follows:

[0055]

[0056] in, For AMP k The i-th element (i∈[1,N]) in the AMP, where N is the AMP k The total number of elements in the set; and for any k∈[1,M], N is a constant.

[0057] Next, embodiments of this application can construct an incoherent average amplitude sequence based on the amplitude sequence of each receiver, and the final expression can be, but is not limited to, the following:

[0058] ICA = (AMP1 + AMP2 + ... + AMP) M ) / M=[A1,A2,…,A i ,…,A N ]

[0059]

[0060] Among them, A i Let i be the i-th element in ICA (i∈[1,N-1]).

[0061] Step S102: Construct a ratio sequence based on the incoherent average amplitude sequence, and compare the elements in the ratio sequence with the target threshold in turn.

[0062] In other embodiments, after constructing the incoherent average amplitude sequence, this application can construct a ratio sequence based on the incoherent average amplitude sequence in order to compare the elements in the ratio sequence with the target threshold, thereby helping to remove lightning contamination from the original echo data.

[0063] Here, the target threshold can be understood as a set numerical standard that can be used to determine whether the elements in the ratio sequence meet certain requirements. For example, the target threshold can be set to 2.73.

[0064] It should be noted that, given the different pulse repetition frequencies of different meteor wind measuring radars, the specific target threshold can be determined or adjusted by those skilled in the art based on the pulse repetition frequencies of different meteor wind measuring radars, combined with actual conditions or needs, and experiments. For example, an experiment can be conducted at a certain pulse repetition frequency of a certain meteor wind measuring radar, and the corresponding target threshold can be determined based on ensuring that the effect of removing lightning and decolorization reaches more than 90% or 95%. Once determined, it can be directly applied in the next practical application. Alternatively, it can be determined independently whether it is necessary to adjust or determine it each time. The embodiments in this application are only illustrative and do not constitute specific limitations.

[0065] Optionally, in one embodiment of this application, constructing a ratio sequence based on an incoherent average amplitude sequence includes: collecting the ratios between adjacent elements in the incoherent average amplitude sequence; and constructing a ratio sequence based on the ratios.

[0066] In some embodiments, when actually constructing the ratio sequence, this application determines the ratio sequence by the ratio between adjacent elements in the incoherent average amplitude sequence.

[0067] For example, suppose the incoherent average amplitude sequence is still:

[0068] ICA = (AMP1 + AMP2 + ... + AMP) M ) / M=[A1,A2,…,A i ,…,A M ]

[0069]

[0070] Among them, A i Let i be the i-th element in ICA (i∈[1,N-1]);

[0071] The ratio sequence can be, but is not limited to, represented as follows:

[0072]

[0073] Among them, R i Let i be the i-th element in the ratio sequence (i∈[1,N-1]), where the total number of elements in the ratio sequence is N-1.

[0074] Step S103: When the elements in the ratio sequence are greater than the target threshold, the incoherent average amplitude sequence and the ratio sequence are updated by dividing the target natural number by the matrix until the elements in the updated ratio sequence are less than the target threshold, so as to obtain the incoherent average amplitude sequence that has been removed from lightning contamination.

[0075] As one possible approach, embodiments of this application can update the incoherent average amplitude sequence and the ratio sequence by comparing the values ​​of elements in the ratio sequence with the target threshold, ultimately obtaining an incoherent average amplitude sequence that has been freed from lightning contamination.

[0076] Specifically, the embodiments of this application can gradually slide the ratio sequence, thereby realizing the comparison of each element in the ratio sequence with the target threshold. When any element is greater than the target threshold, the incoherent average amplitude sequence is updated by dividing the target natural number by the matrix. Then, the ratio sequence is updated by the updated incoherent average amplitude sequence until all elements in the updated ratio sequence are less than the target threshold. At this time, the incoherent average amplitude sequence is the incoherent average amplitude sequence after removing lightning pollution.

[0077] Here, the target natural number division matrix can be understood as a matrix constructed when updating the incoherent average amplitude sequence, where all elements are natural numbers. For example, n = [n1, n2, n3, n4, ..., n k ..., etc., where n1,n2,n3,n4,...,n j ... are all natural numbers, such as n = [n1, n2, n3, n4, ..., n j [,…] = [2,3,4,5,…,j+1,…] etc. It should be noted that the length of the matrix divided by all natural numbers can be determined or adjusted by those skilled in the art based on actual conditions or experiments. The embodiments in this application are only illustrative and do not impose specific limitations, but the natural numbers therein must be gradually increasing.

[0078] The process described in the embodiments of this application will be further explained below.

[0079] Optionally, in one embodiment of this application, when an element in the ratio sequence is greater than a target threshold, updating the incoherent average amplitude sequence and the ratio sequence using a natural number division matrix includes: updating the corresponding element in the incoherent average amplitude sequence by dividing the elements in the natural number division matrix when the ratio element in the ratio sequence is greater than the target threshold, obtaining an updated incoherent average amplitude sequence; and updating the ratio sequence using the updated incoherent average amplitude sequence, obtaining an updated ratio sequence. The update formula for the incoherent average amplitude sequence is:

[0080] A i+1 =(A i +A i+2 ) / n j =(A i +A i+2 ) / (j+1)

[0081] Among them, A i Ai+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, and n... j Let each of the natural numbers be the j-th natural number in matrix n. j =j+1.

[0082] The update formula for the ratio sequence is:

[0083] R i =A i+1 / A i

[0084] R i+1 =A i+2 / A i+1

[0085] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, R i R i+1 These are the i-th and (i+1)-th elements in the ratio sequence, respectively.

[0086] In other embodiments, when an element in the ratio sequence is greater than the target threshold, it is necessary to compare the incoherent average amplitude sequence and the ratio sequence using the target natural number division matrix. Specifically, during the update, this application can first update the corresponding elements in the incoherent average amplitude sequence using the elements in the natural number division matrix to obtain the updated incoherent average amplitude sequence, and then use the elements in the updated incoherent average amplitude sequence to update the corresponding elements in the ratio sequence to obtain the updated ratio sequence.

[0087] In this embodiment, when comparing the elements in the ratio sequence with the target threshold, the ratio sequence is gradually slid from beginning to end. That is, the comparison is carried out from the first element in the ratio sequence until the last element of the ratio sequence is compared. Only when none of the elements in the ratio sequence are greater than the target threshold can the incoherent average amplitude sequence corresponding to the ratio sequence be used as the incoherent average amplitude sequence for removing lightning contamination.

[0088] If there are still elements in the updated ratio sequence that are greater than the target threshold, then continue to update the corresponding elements in the incoherent average amplitude sequence by dividing the elements in the matrix by natural numbers, to obtain an updated incoherent average amplitude sequence. Then, continue to update the corresponding elements in the ratio sequence using the updated incoherent average amplitude sequence, to obtain an updated ratio sequence, until all elements in the updated ratio sequence are less than the target threshold.

[0089] For example, Figure 2 This is a flowchart illustrating a method for removing lightning contamination from raw data of a meteor wind-measuring radar according to an embodiment of this application, as follows: Figure 2 As shown:

[0090] Step S201: Construct an incoherent average amplitude sequence based on the raw echo data from all receivers of the target meteor wind measurement radar. This sequence can be represented, but is not limited to, as follows:

[0091] ICA = (AMP1 + AMP2 + ... + AMP) M ) / M=[A1,A2,…,A i ,…,A N ]

[0092]

[0093] Among them, A i Let i be the i-th element in ICA (i∈[1,N-1]);

[0094] Then, a ratio sequence is constructed based on this incoherent average amplitude sequence, which can be represented, but is not limited to, as follows:

[0095]

[0096] Among them, R i Let i be the i-th element in Ratio (i∈[1,N-1]), where the total number of elements in Ratio is N-1.

[0097] Step S202: Slide the ratio sequence from beginning to end to gradually compare each element in the ratio sequence;

[0098] Step S203, when there is an element R in the ratio sequence i When the threshold is R_Level (where i∈[1,N-1], R_Level is the target threshold), the elements n in matrix n are gradually divided by natural numbers. j (n j (∈n) Update the values ​​of corresponding elements in the incoherent average amplitude (ICA) sequence and the ratio sequence until R... i If R_Level ≤ R_Level (in this embodiment, R_Level = 2.73), continue to gradually slide the Ratio sequence until any R in the entire sequence is satisfied. i (where i∈[1,N-1]), we have R i ≤R_Level, the specific process can be, but is not limited to, represented as follows:

[0099] The i-th element R in the ratio sequence i (where i∈[1,N-1]) For example:

[0100] When R i If ≤R_Level, then slide to the next element R in the ratio sequence. i+1 ;

[0101] When R i When the R_Level is reached, let the matrix be n, where each natural number is divided by the others. Specifically:

[0102] n = [n1, n2, n3, n4, ..., n j [,…]=[2,3,4,5,…,j+1,…]

[0103] Where, n j Let j be the j-th natural number in n, specifically:

[0104] n j =j+1

[0105] The first update of the values ​​of corresponding elements in the incoherent average amplitude (ICA) sequence and the ratio sequence is as follows:

[0106] A i+1 =(A i +A i+2 ) / n1=(A i +A i+2 ) / 2

[0107] R i =A i+1 / A i

[0108] R i+1 =A i+2 / A i+1

[0109] For R after the first update i (Note that A is also present) i+1 and R i+1 (Also updated), if R is still available i If the value is >R_Level, then a second update will be performed, specifically as follows:

[0110] A i+1 =(A i +A i+2 ) / n2=(A i +A i+2 ) / 3

[0111] R i =A i+1 / A i

[0112] R i+1 =A i+2 / Ai+1

[0113] ...;

[0114] For R after the (j-1)th update i (Note that A is also present) i+1 and R i+1 (Also updated), if R is still available i If the value is greater than R_Level, then the j-th update will be performed, specifically as follows:

[0115] A i+1 =(A i +A i+2 ) / n j =(A i +A i+2 ) / (j+1)

[0116] R i =A i+1 / A i

[0117] R i+1 =A i+2 / A i+1

[0118] ...;

[0119] Until for the updated R i (Note that A is also present) i+1 and R i+1 Also updated), satisfying R i ≤R_Level, stop updating (in this embodiment, the same element is updated a maximum of 10 times, that is, the maximum value of j is 10. In actual application, j is determined by the specific number of updates. This embodiment is only for illustrative purposes and does not impose any specific restrictions).

[0120] Step S204, continue to gradually slide the updated ratio sequence R. i For subsequent elements, repeat the above steps until for any R in the updated entire ratio sequence i (where i∈[1,N-1]), we have R i ≤R_Level;

[0121] Step S205, using any R in the final entire ratio sequence i All have R i The incoherent average amplitude ICA sequence corresponding to the ratio sequence ≤R_Level is used as the incoherent average amplitude ICA sequence to remove lightning contamination;

[0122] Step S206: Compare the updated incoherent average amplitude ICA sequence with the original incoherent average amplitude ICA sequence. Figure 3 This is a comparative result diagram of one embodiment of this application, as shown below. Figure 3 As shown, the top two sub-figures on incoherent average amplitude (ICA) display one minute of raw radar data (left) and a valid meteor signal contained within it (right); the bottom two sub-figures correspond one-to-one with the top ones, showing the incoherent average amplitude (ICA) after removing lightning contamination. In these figures, the four rounded rectangles all indicate the same valid meteor signal. It can be seen that the embodiments of this application can effectively remove lightning contamination from the raw echo data of meteor wind radar, significantly improving the identification efficiency of valid meteor signals.

[0123] Additionally, this application embodiment also calculates the time required for the method of removing lightning contamination from meteor wind measurement radar data in this application embodiment, such as... Figure 3 As shown, Figure 3 The example in the example takes only 0.75 seconds to compute, which can effectively meet the efficiency requirements of popular wind-measuring radars for removing lightning contamination from raw echo data.

[0124] According to the method for removing lightning contamination from meteor wind radar data proposed in the embodiments of this application, the echo data of the target meteor wind radar receiver can be obtained to construct an incoherent average amplitude sequence, and then a ratio sequence can be constructed. The incoherent average amplitude sequence and the ratio sequence are updated by comparing the elements in the ratio sequence with the target threshold one by one, so as to obtain the incoherent average amplitude sequence with lightning contamination removed. This invention achieves the removal of redundant signals from receiver echo data by constructing an incoherent average amplitude sequence, ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed from the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, ultimately yielding an incoherent average amplitude sequence free of lightning contamination. Comparison with the initial amplitude sequence demonstrates that this application can not only remove lightning contamination from raw meteor wind radar echo data but also achieves this removal in a very short time, with extremely high speed and efficiency. It enables real-time processing of raw radar echo data with limited computing resources, effectively improving the efficiency of meteor signal discrimination algorithms. This solves the problem in related technologies where frequent atmospheric lightning interference in the raw data of meteor wind radar receivers is easily confused with real meteor signals, reducing the efficiency of meteor signal discrimination algorithms and making real-time processing of raw radar data difficult with limited computing resources. The invention addresses the challenge of quickly and efficiently removing lightning contamination from raw meteor wind radar data.

[0125] Next, with reference to the accompanying drawings, an apparatus for removing lightning contamination from meteor wind measurement radar data according to an embodiment of this application is described.

[0126] Figure 4 This is a schematic diagram of the device for removing lightning contamination from meteor wind radar data according to an embodiment of this application.

[0127] like Figure 4 As shown, the device 10 for removing lightning contamination from meteor wind radar data includes: a first building module 100, a second building module 200, and an update module 300.

[0128] The first construction module 100 is used to acquire the echo data of the receiver corresponding to the target meteor wind measurement radar, and construct an incoherent average amplitude sequence based on the echo data.

[0129] The second construction module 200 is used to construct a ratio sequence based on the incoherent average amplitude sequence, and sequentially compare the elements in the ratio sequence with the target threshold.

[0130] The update module 300 is used to update the incoherent average amplitude sequence and the ratio sequence by dividing the target natural number matrix when the elements in the ratio sequence are greater than the target threshold, until the elements in the updated ratio sequence are less than the target threshold, so as to obtain the incoherent average amplitude sequence that has been removed from lightning pollution.

[0131] Optionally, in one embodiment of this application, the first building module 100 includes: a first building unit and a second building unit.

[0132] One of the construction units is used to construct the amplitude sequence corresponding to the receiver based on the echo data.

[0133] The second building unit is used to construct an incoherent average amplitude sequence based on the amplitude sequence.

[0134] Optionally, in one embodiment of this application, the second construction module 200 includes: a data acquisition unit and a third construction unit.

[0135] The acquisition unit is used to acquire the ratio between adjacent elements in the incoherent average amplitude sequence.

[0136] The third building unit is used to construct a ratio sequence based on the ratio.

[0137] Optionally, in one embodiment of this application, the update module 300 includes: a first update unit and a second update unit.

[0138] The first update unit is used to update the corresponding element in the incoherent average amplitude sequence by dividing the elements in the matrix by natural numbers when the ratio element in the ratio sequence is greater than the target threshold, so as to obtain the updated incoherent average amplitude sequence.

[0139] The second update unit is used to update the ratio sequence using the updated incoherent average amplitude sequence to obtain the updated ratio sequence.

[0140] Optionally, in one embodiment of this application, the update formula for the incoherent average amplitude sequence is:

[0141] A i+1 =(A i +A i+2 ) / n j =(A i +A i+2 ) / (j+1)

[0142] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, and n... j Let each of the natural numbers be the j-th natural number in matrix n. j =j+1.

[0143] Optionally, in one embodiment of this application, the update formula for the ratio sequence is:

[0144] R i =A i+1 / A i

[0145] R i+1 =A i+2 / A i+1

[0146] Among them, A i A i+1 A i+2 These are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, respectively, R i R i+1 These are the i-th and (i+1)-th elements in the ratio sequence, respectively.

[0147] It should be noted that the foregoing explanation of the method embodiment for removing lightning contamination from meteor wind radar data also applies to the apparatus for removing lightning contamination from meteor wind radar data in this embodiment, and will not be repeated here.

[0148] According to the embodiments of this application, the apparatus for removing lightning contamination from meteor wind radar data can acquire echo data from the target meteor wind radar receiver to construct an incoherent average amplitude sequence, then construct a ratio sequence, and then update the incoherent average amplitude sequence and ratio sequence by comparing each element in the ratio sequence with the target threshold to obtain an incoherent average amplitude sequence with lightning contamination removed. This invention achieves the removal of redundant signals from receiver echo data by constructing an incoherent average amplitude sequence, ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed from the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, ultimately yielding an incoherent average amplitude sequence free of lightning contamination. Comparison with the initial amplitude sequence demonstrates that this application can not only remove lightning contamination from raw meteor wind radar echo data but also achieves this removal in a very short time, with extremely high speed and efficiency. It enables real-time processing of raw radar echo data with limited computing resources, effectively improving the efficiency of meteor signal discrimination algorithms. This solves the problem in related technologies where frequent atmospheric lightning interference in the raw data of meteor wind radar receivers is easily confused with real meteor signals, reducing the efficiency of meteor signal discrimination algorithms and making real-time processing of raw radar data difficult with limited computing resources. The invention addresses the challenge of quickly and efficiently removing lightning contamination from raw meteor wind radar data.

[0149] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0150] The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0151] When processor 502 executes the program, it implements the method for removing lightning contamination from meteor wind measurement radar data provided in the above embodiments.

[0152] Furthermore, electronic devices also include:

[0153] Communication interface 503 is used for communication between memory 501 and processor 502.

[0154] The memory 501 is used to store computer programs that can run on the processor 502.

[0155] The memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0156] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0157] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0158] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0159] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for removing lightning contamination from meteor wind measurement radar data.

[0160] This application also provides a computer program product, including a computer program that can run computer instructions. When the computer instructions are executed by a processor, they implement the method for removing lightning contamination from meteor wind measurement radar data provided in this application.

[0161] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0162] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0163] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0164] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0165] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0166] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0167] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0168] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for removing lightning contamination from meteor wind measurement radar data, characterized in that, Includes the following steps: Acquire the echo data of the receiver corresponding to the target meteor wind measurement radar, and construct an incoherent average amplitude sequence based on the echo data; A ratio sequence is constructed based on the incoherent average amplitude sequence, and the elements in the ratio sequence are compared with the target threshold in turn. When an element in the ratio sequence is greater than the target threshold, the incoherent average amplitude sequence and the ratio sequence are updated by dividing the target natural number by the matrix until the element in the updated ratio sequence is less than the target threshold, so as to obtain an incoherent average amplitude sequence that has been de-polluted by lightning. The update formula for the incoherent average amplitude sequence is as follows: in, , , These are the first in the incoherent average amplitude sequence. , , One element, A matrix that divides by natural numbers The first in 1 natural number .

2. The method according to claim 1, characterized in that, The step of constructing an incoherent average amplitude sequence based on the echo data includes: Construct the amplitude sequence corresponding to the receiver based on the echo data; The incoherent average amplitude sequence is constructed based on the amplitude sequence.

3. The method according to claim 1, characterized in that, The step of constructing a ratio sequence based on the incoherent average amplitude sequence includes: Collect the ratio between adjacent elements in the incoherent average amplitude sequence; Construct the ratio sequence based on the ratio values.

4. The method according to claim 1, characterized in that, When an element in the ratio sequence is greater than the target threshold, updating the incoherent average amplitude sequence and the ratio sequence using a natural number division matrix includes: When the ratio element in the ratio sequence is greater than the target threshold, the corresponding element in the incoherent average amplitude sequence is updated by the elements in the natural number division matrix to obtain the updated incoherent average amplitude sequence. The ratio sequence is updated using the updated incoherent average amplitude sequence to obtain the updated ratio sequence.

5. The method according to claim 1, characterized in that, The update formula for the ratio sequence is: in, , , These are the first in the incoherent average amplitude sequence. , No. , No. One element, , These are the first numbers in the ratio sequence. , No. Each element.

6. A device for removing lightning contamination from meteor wind measurement radar data, characterized in that, include: The first construction module is used to acquire the echo data of the receiver corresponding to the target meteor wind measurement radar, and construct an incoherent average amplitude sequence based on the echo data. The second construction module is used to construct a ratio sequence based on the incoherent average amplitude sequence, and sequentially compare the elements in the ratio sequence with the target threshold. An update module is used to update the incoherent average amplitude sequence and the ratio sequence by means of a target natural number division matrix when the elements in the ratio sequence are greater than the target threshold, until the elements in the updated ratio sequence are less than the target threshold, so as to obtain an incoherent average amplitude sequence that has been de-polluted by lightning. The update formula for the incoherent average amplitude sequence is as follows: in, , , These are the first in the incoherent average amplitude sequence. , , One element, A matrix that divides by natural numbers The first in 1 natural number .

7. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for removing lightning contamination from meteor wind radar data as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the method for removing lightning contamination from meteor wind radar data as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed, it is used to implement the method for removing lightning contamination from meteor wind radar data as described in any one of claims 1-5.

Images