Method and device for eliminating lightning pollution from meteor wind-finding radar data

Abstract

The invention relates to the technical field of space exploration, in particular to a method and device for eliminating lightning pollution from meteor wind-finding radar data, and the method comprises the steps: obtaining echo data of a receiver corresponding to a target meteor wind-finding radar, and constructing an incoherent average amplitude sequence according to the echo data; constructing a ratio sequence according to the incoherent average amplitude sequence, and sequentially comparing elements in the ratio sequence with a target threshold value; and when the elements in the ratio sequence are greater than a target threshold value, updating the incoherent average amplitude sequence and the ratio sequence through the target natural number mean division matrix until the elements in the updated ratio sequence are smaller than the target threshold value so as to obtain the incoherent average amplitude sequence without lightning pollution. According to the method, the lightning pollution can be quickly and efficiently eliminated from the meteor wind-finding radar original echo data, and the lightning pollution can be eliminated from the meteor wind-finding radar original echo data in real time under limited computing resources, so that the efficiency of a meteor signal discrimination algorithm is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of space detection technology, and in particular to a method and device for removing lightning pollution from meteor wind radar data. Background Art

[0002] The region of Earth's atmosphere above approximately 10 km is called the middle and upper atmosphere, encompassing the upper troposphere, stratosphere, mesosphere, and thermosphere. Dramatic changes in wind fields in the middle and upper atmosphere not only directly impact aerospace activities but also play a significant role in radio communications. Therefore, a core goal of research in the middle and upper atmosphere is to uncover key dynamical mechanisms and their impact on the space environment. This has significant scientific value for deepening our understanding of global space environmental changes and exploring the relationship between the Sun and the Earth.

[0003] In related technologies, the mesopause (approximately 90 km altitude) is the transition region between the neutral atmosphere and the thermosphere / ionosphere in the middle and upper atmosphere. It hosts key dynamic and chemical processes and plays a vital role in the exchange of momentum, energy, and heat. Common detection methods include sounding rockets, lidar, and radio radar. Radio radar is an effective means of continuously observing atmospheric wind fields in the mesopause region. Meteor wind radar, in particular, is widely deployed worldwide to monitor dynamic processes such as wind fields, tides, gravity waves, and planetary waves in the middle and upper atmosphere due to its simple system structure, stable operation, and unrestricted by diurnal variations and weather conditions. It offers all-weather continuous observation capabilities. Its detection principle is based on the reflection of radar signals from meteor wakes. This echo signal contains information related to the atmospheric wind field at the mesopause. Therefore, by analyzing these echo signals, the atmospheric environment at the mesopause within the detection range can be inferred. A key point in analyzing meteor events is the accurate identification of valid meteor echoes and their distinction from short-term noise signals.

[0004] However, in the related art, in the raw data of the meteor wind measurement radar receiver, the frequent atmospheric lightning interference can easily be confused with the real meteor signal, thereby reducing the efficiency of the meteor signal identification algorithm, making it difficult to achieve real-time processing of the radar raw data under limited computing resources. How to quickly and efficiently remove these lightning pollution from the raw data of the meteor wind measurement radar needs to be solved urgently. Summary of the Invention

[0005] The present application provides a method and apparatus for removing lightning contamination from meteor wind radar data to address the related art problem that, in the raw data of a meteor wind radar receiver, atmospheric lightning interference frequently appears and is easily confused with real meteor signals, thereby reducing the efficiency of the meteor signal identification algorithm and making it difficult to achieve real-time processing of the radar raw data with limited computing resources. The method and apparatus also address the problem of how to quickly and efficiently remove this lightning contamination from the raw data of a meteor wind radar.

[0006] A first aspect embodiment of the present application provides a method for removing lightning contamination from meteor wind radar data, comprising the following steps: obtaining echo data of 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 an element in the ratio sequence is greater than the target threshold, updating the incoherent average amplitude sequence and the ratio sequence through a target natural number averaging matrix until the element in the updated ratio sequence is less than the target threshold, so as to obtain an incoherent average amplitude sequence from which lightning contamination has been removed.

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

[0008] Optionally, in one embodiment of the present application, constructing a ratio sequence based on the incoherent average amplitude sequence includes: collecting 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 the present application, when the element in the ratio sequence is greater than the target threshold, the incoherent average amplitude sequence and the ratio sequence are updated through a natural number averaging matrix, including: when a ratio element in the ratio sequence is greater than the target threshold, updating the corresponding element in the incoherent average amplitude sequence through the element in the natural number averaging matrix to obtain an updated incoherent average amplitude sequence; and using the updated incoherent average amplitude sequence to update the ratio sequence to obtain an updated ratio sequence.

[0010] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, n j is the jth natural number in the natural number matrix n, n j =j+1.

[0013] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, R i 、R i+1 are the i-th and i+1-th elements in the ratio sequence respectively.

[0017] A second aspect of the present 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; an update module for updating the incoherent average amplitude sequence and the ratio sequence using a target natural number mean division matrix when an element in the ratio sequence is greater than the target threshold, until the element in the updated ratio sequence is less than the target threshold, so as to obtain an incoherent average amplitude sequence from which lightning contamination has been removed.

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

[0019] Optionally, in one embodiment of the present application, the second construction module includes: an acquisition unit, configured to acquire ratios between adjacent elements in the incoherent average amplitude sequence; and a third construction unit, configured to construct the ratio sequence according to the ratios.

[0020] Optionally, in one embodiment of the present application, the updating module includes: a first updating unit, used to update the corresponding element in the incoherent average amplitude sequence by the element in the natural number mean 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, used to update the ratio sequence using the updated incoherent average amplitude sequence, to obtain an updated ratio sequence.

[0021] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, n j is the jth natural number in the natural number matrix n, n j =j+1.

[0024] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, R i 、R i+1 are the i-th and i+1-th elements in the ratio sequence respectively.

[0028] A third aspect of the present application provides an electronic device, comprising: 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 embodiment.

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

[0030] A fifth aspect of the present application provides a computer program product, including a computer program. When the computer program is executed, it is used to implement the above method for removing lightning pollution from meteor wind radar data.

[0031] The embodiment of the present application can obtain the echo data of the target wind radar receiver to construct an incoherent average amplitude sequence, and then construct a ratio sequence, and then update the incoherent average amplitude sequence and the ratio sequence by comparing the elements in the ratio sequence with the target threshold one by one, to obtain an incoherent average amplitude sequence that has been removed from the lightning contamination. Thus, it is achieved by constructing an incoherent average amplitude sequence to remove the redundant signals in the receiver echo data, thereby 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, and finally an incoherent average amplitude sequence that has been removed from the lightning contamination is obtained. For comparison with the original amplitude sequence, the present application can not only remove lightning contamination from the original echo data of the meteor wind radar, but also remove it in an extremely short time, with extremely high speed and efficiency. It can realize real-time processing of the radar original echo data under limited computing resources, that is, remove lightning contamination from the original echo data of the meteor wind radar, thereby effectively improving the efficiency of the meteor signal discrimination algorithm. This solves the problem in related technologies that frequent atmospheric lightning interference in the raw data of meteor wind measurement radar receivers can easily be 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 with limited computing resources. The problem also arises as to how to quickly and efficiently remove these lightning contamination issues from the raw data of meteor wind measurement radars.

[0032] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0034] Figure 1 A flowchart of a method for removing lightning contamination from meteor wind radar data provided according to an embodiment of the present application;

[0035] Figure 2 A flowchart of a method for removing lightning contamination from raw data of a meteor wind radar according to one embodiment of the present application;

[0036] Figure 3 This is a schematic diagram of the comparison results of an embodiment of the present application;

[0037] Figure 4 A schematic diagram of the structure of an apparatus for removing lightning contamination from meteor wind radar data according to an embodiment of the present application;

[0038] Figure 5 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application.

[0039] Reference numerals:

[0040] 10-Device for removing lightning contamination from meteor wind radar data: 100-first building module, 200-second building module and 300-update module; 501-memory, 502-processor and 503-communication interface. DETAILED DESCRIPTION

[0041] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0042] The following describes a method and apparatus for removing lightning contamination from meteor wind radar data according to an embodiment of the present application with reference to the accompanying drawings. In view of the related art mentioned in the above background art, in the raw data of the meteor wind radar receiver, the frequently occurring atmospheric lightning interference is easily confused with the real meteor signal, thereby reducing the efficiency of the meteor signal identification algorithm, resulting in difficulty in achieving real-time processing of the radar raw data under limited computing resources. The problem of how to quickly and efficiently remove these lightning contaminations from the raw data of the meteor wind radar is addressed. The present application provides a method for removing lightning contamination from meteor wind radar data. In this method, 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 is constructed. The incoherent average amplitude sequence and the ratio sequence are then updated by comparing the elements in the ratio sequence with the target threshold one by one, thereby obtaining an incoherent average amplitude sequence from which lightning contamination has been removed. Thus, it is achieved that by constructing an incoherent average amplitude sequence, redundant signals in the receiver echo data are eliminated, thereby ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed by the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, and finally an incoherent average amplitude sequence with lightning contamination eliminated is obtained. For comparative study with the original amplitude sequence, the present application can not only eliminate lightning contamination from the original echo data of the meteor wind measurement radar, but also eliminate it in an extremely short time, with extremely high speed and efficiency. It can realize real-time processing of the radar original echo data under limited computing resources, that is, eliminate lightning contamination from the original echo data of the meteor wind measurement radar, thereby effectively improving the efficiency of the meteor signal identification algorithm. Thus, it solves the problem in the related art that in the raw data of the meteor wind measurement radar receiver, the frequent atmospheric lightning interference is easily confused with the real meteor signal, thereby reducing the efficiency of the meteor signal identification algorithm, making it difficult to realize real-time processing of the radar raw data under limited computing resources, and how to quickly and efficiently eliminate these lightning contaminations from the raw data of the meteor wind measurement radar.

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

[0044] like Figure 1 As shown in FIG, the method for removing lightning pollution 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 measurement radar is obtained, and an incoherent average amplitude sequence is constructed according to the echo data.

[0046] It's understood that the target meteor wind radar here refers to a radar device that detects and analyzes meteor trails to measure winds and removes lightning contamination from its echo data. The echo data from the meteor wind radar contains information related to the mesotope wind field. By analyzing this echo data, the atmospheric environment at the mesotope within the detection range can be inferred.

[0047] However, the raw echo data from meteor wind radar receivers contains both reflections from meteor trails and interference signals such as atmospheric scattering. Frequent atmospheric lightning interference signals can easily confuse actual meteor signals, reducing the efficiency of meteor signal identification algorithms and making real-time processing of radar raw data difficult with limited computing resources. Some studies have shown that within a single meteor storm event, a single segment of raw echo data containing only six valid meteor records contained approximately 4,000 instances of lightning contamination.

[0048] In some embodiments, the present application can obtain the echo data of the receiver corresponding to the target meteor wind measurement radar (the echo data here and in subsequent processes refer to the original echo data without any processing), and process these echo data to construct an incoherent average amplitude sequence for eliminating lightning contamination in the echo data.

[0049] Incoherent averaging, as used herein, refers to a method that averages only the amplitudes of the signals in the echo data, without considering the phase relationships between the signals in the receiver's original echo data. This method allows embodiments of the present application to add and average the amplitudes of multiple signals in the echo data that have similar characteristics but may have random phase differences. This can, to a certain extent, suppress noise and random fluctuations, improving the stability and observability of the signals in the echo data.

[0050] Optionally, in one embodiment of the present application, constructing a non-coherent average amplitude sequence according to the echo data includes: constructing an amplitude sequence corresponding to the receiver according to the echo data; and constructing a non-coherent average amplitude sequence according to the amplitude sequence.

[0051] It can be understood based on the relevant descriptions of other embodiments that the non-coherent averaging here refers to a method of averaging only the amplitudes of the signals in the receiver echo data without considering the phase relationship between the signals in the echo data.

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

[0053] For example, the present application can construct the corresponding amplitude sequence based on the original echo data of all receivers of the target meteor wind measurement radar. Assuming that the target meteor wind measurement radar has a total of M receivers, the amplitude sequences corresponding to all receivers can be expressed as, but not limited to: AMP1, AMP2, ..., AMP k ,…,AMP M .

[0054] Among them, AMP k The amplitude sequence representing the original echo data of the kth receiver (k∈[1,M]) among all receivers can be represented as follows, but is not limited to:

[0055]

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

[0057] Next, the embodiment of the present application can construct a non-coherent average amplitude sequence based on the amplitude sequence of each receiver. The final expression can be, but is not limited to, expressed as follows:

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

[0059]

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

[0061] Step S102 : constructing a ratio sequence according to the incoherent average amplitude sequence, and sequentially comparing elements in the ratio sequence with a target threshold.

[0062] In other embodiments, after constructing the incoherent average amplitude sequence, the present application can construct a ratio sequence based on the incoherent average amplitude sequence to compare the elements in the ratio sequence with the target threshold to help eliminate lightning contamination in the original echo data.

[0063] The target threshold here can be understood as a set numerical standard, which 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 that different meteor wind radars have different pulse repetition frequencies, the specific target threshold can be determined or adjusted by professionals in this field based on the pulse repetition frequencies of different meteor wind radars, in combination with actual conditions or actual needs and experiments. For example, when conducting experiments at a certain pulse repetition frequency of a certain meteor wind radar, the corresponding target threshold can be determined on the basis of ensuring that the lightning decontamination effect reaches more than 90% or more than 95%. After the determination is made, the actual implementation can be directly carried out next time, or the user can independently determine whether adjustment or determination is required each time. The embodiments of this application are for illustrative purposes only and are not specifically limited.

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

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

[0067] For example, assume that 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 is the i-th element in ICA (i∈[1,N-1]);

[0071] Then the ratio sequence can be expressed as follows but is not limited to:

[0072]

[0073] Among them, R i is 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 an element in the ratio sequence is greater than a target threshold, the incoherent average amplitude sequence and the ratio sequence are updated by using the target natural number averaging 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 eliminates lightning pollution.

[0075] As a possible implementation method, the embodiment of the present application can update the incoherent average amplitude sequence and the ratio sequence by comparing the size of the elements in the ratio sequence with the target threshold, and finally obtain the incoherent average amplitude sequence that eliminates lightning pollution.

[0076] Specifically, the embodiment of the present 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 the target natural number average division matrix, and 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 that eliminates lightning pollution.

[0077] The target natural number averaging matrix can be understood as a matrix constructed when updating the incoherent average amplitude sequence, and all elements in the matrix 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 natural number average division matrix can be determined or adjusted by professionals in this field based on actual conditions or experiments. The embodiments of this application are only for illustrative purposes and are not specifically limited. However, the natural numbers therein need to be gradually increasing.

[0078] Next, the process in the embodiments of the present application will be further explained.

[0079] Optionally, in one embodiment of the present application, when an element in the ratio sequence is greater than a target threshold, the incoherent average amplitude sequence and the ratio sequence are updated using a natural number average division matrix, including: when a ratio element in the ratio sequence is greater than the target threshold, updating the corresponding element in the incoherent average amplitude sequence using the element in the natural number average division matrix to obtain an updated incoherent average amplitude sequence; and using the updated incoherent average amplitude sequence to update the ratio sequence to obtain an updated ratio sequence. The updating 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, n j is the jth natural number in the natural number matrix n, n j =j+1.

[0082] The update formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, R i 、R i+1 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 a target threshold, the incoherent average amplitude sequence and the ratio sequence need to be compared using a target natural number averaging matrix. During the specific update, the present application can first update the corresponding elements in the incoherent average amplitude sequence using the elements in the natural number averaging matrix to obtain an 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 an updated ratio sequence.

[0087] Among them, when comparing the elements in the ratio sequence with the target threshold, the embodiment of the present application gradually slides the ratio sequence from the beginning to the end, that is, traverses and compares from the first element in the ratio sequence until the last element of the ratio sequence is compared. When all the elements in the ratio sequence are compared and none of them is greater than the target threshold, the incoherent average amplitude sequence corresponding to the ratio sequence at this time can be used as the incoherent average amplitude sequence for eliminating lightning pollution.

[0088] If there are still elements in the updated ratio sequence that are greater than the target threshold, the elements in the natural number mean division matrix are used to continue updating the corresponding elements in the incoherent average amplitude sequence to obtain an updated incoherent average amplitude sequence. The updated incoherent average amplitude sequence is then used to continue updating the corresponding elements in the ratio 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 flow chart of a method for removing lightning pollution from raw data of a meteor wind radar according to an embodiment of the present application. Figure 2 As shown:

[0090] Step S201: constructing an incoherent average amplitude sequence based on the original echo data of all receivers of the target meteor wind radar, which can be expressed as follows but is not limited to:

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

[0092]

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

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

[0095]

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

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

[0098] Step S203: When there is an element R in the ratio sequence i >R_Level (where i∈[1,N-1], R_Level is the target threshold), gradually divide the element n in the matrix n by the natural number j (n j ∈n) Update the values ​​of the corresponding elements in the incoherent average amplitude ICA sequence and the ratio sequence until R i ≤R_Level (in the embodiment of the present application, R_Level=2.73), continue to slide the ratio sequence step by step until any R in the entire sequence i (where i∈[1,N-1]), both have R i ≤R_Level, the specific process can be but not limited to the following:

[0099] Take the i-th element R in the ratio sequence i (where i∈[1,N-1]) is taken as an example:

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

[0101] When R i When >R_Level, let the natural number mean division matrix be n, specifically:

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

[0103] Among them, n j is the jth natural number in n, specifically:

[0104] n j =j+1

[0105] The first update is to update the values ​​of the corresponding elements in the incoherent average amplitude ICA sequence and the ratio sequence, specifically:

[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 i+1 and R i+1 has also been updated), if there is still R i >R_Level, then the second update is performed, specifically:

[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-1th update i (Note that A i+1 and R i+1 has also been updated), if there is still R i >R_Level, then the jth update is performed, specifically:

[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 the updated R i (Note that A i+1 and R i+1 is also updated), satisfying R i ≤R_Level, stop updating (in the embodiment of the present application, the same element is updated up to 10 times, that is, the maximum value of j is 10. In actual application, j is determined by the specific number of updates. In the embodiment of the present application, it is only for illustrative purposes and is not specifically limited);

[0120] Step S204, continue to gradually slide the updated ratio sequence R i Repeat the above steps for the following elements until any R in the updated ratio sequence is i (where i∈[1,N-1]), both have R i ≤R_Level;

[0121] Step S205: take any R in the final ratio sequence i Both 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 for removing lightning pollution;

[0122] Step S206: Compare the updated incoherent average amplitude ICA sequence with the initial incoherent average amplitude ICA sequence. Figure 3 This is a schematic diagram of the comparison results of an embodiment of the present application, as shown in FIG. Figure 3 As shown, the two upper sub-graphs about incoherent average amplitude (ICA) show one minute of radar raw data (left) and a valid meteor signal contained therein (right); the two lower sub-graphs correspond one to the upper ones, and are sub-graphs of incoherent average amplitude (ICA) after removing lightning contamination. Among them, the four rounded rectangular boxes in the figure all indicate the same valid meteor signal. It can be seen that the embodiment of the present application can effectively remove lightning contamination in the raw echo data of the meteor wind measurement radar, greatly improving the efficiency of identifying valid meteor signals.

[0123] Additionally, the embodiment of the present application also calculates the time taken for the method of removing lightning pollution from meteor wind radar data in the embodiment of the present application, such as Figure 3 As shown, Figure 3 The computation time of the embodiment in the embodiment is only 0.75 seconds, which can effectively meet the efficiency requirements of popular wind measurement radars for removing lightning pollution from raw echo data.

[0124] According to the method for removing lightning contamination from meteor wind radar data proposed in an embodiment of the present 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 is constructed. The incoherent average amplitude sequence and the ratio sequence are then updated by comparing the elements in the ratio sequence with the target threshold one by one, thereby obtaining an incoherent average amplitude sequence that has been removed from the lightning contamination. Thus, it is achieved that by constructing an incoherent average amplitude sequence, redundant signals in the receiver echo data are eliminated, thereby ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed by the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, and finally an incoherent average amplitude sequence with lightning contamination eliminated is obtained. For comparative study with the original amplitude sequence, the present application can not only eliminate lightning contamination from the original echo data of the meteor wind measurement radar, but also eliminate it in an extremely short time, with extremely high speed and efficiency. It can realize real-time processing of the radar original echo data under limited computing resources, that is, eliminate lightning contamination from the original echo data of the meteor wind measurement radar, thereby effectively improving the efficiency of the meteor signal identification algorithm. Thus, it solves the problem in the related art that in the raw data of the meteor wind measurement radar receiver, the frequent atmospheric lightning interference is easily confused with the real meteor signal, thereby reducing the efficiency of the meteor signal identification algorithm, making it difficult to realize real-time processing of the radar raw data under limited computing resources, and how to quickly and efficiently eliminate these lightning contaminations from the raw data of the meteor wind measurement radar.

[0125] Next, a device for removing lightning contamination from meteor wind radar data according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0126] Figure 4 Schematic diagram of the structure of the device for removing lightning contamination from meteor wind radar data according to an embodiment of the present application.

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

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

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

[0130] The updating module 300 is used to update the incoherent average amplitude sequence and the ratio sequence by using the target natural number averaging matrix when an element in the ratio sequence is greater than a target threshold, until the element in the updated ratio sequence is less than the target threshold, so as to obtain the incoherent average amplitude sequence that eliminates lightning pollution.

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

[0132] Among them, a construction unit is used to construct an amplitude sequence corresponding to the receiver according to the echo data.

[0133] The second constructing unit is configured to construct an incoherent average amplitude sequence according to the amplitude sequence.

[0134] Optionally, in one embodiment of the present application, the second building module 200 includes: a collection unit and a third building unit.

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

[0136] The third construction unit is used to construct a ratio sequence according to the ratio.

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

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

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

[0140] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, n j is the jth natural number in the natural number matrix n, n j =j+1.

[0143] Optionally, in one embodiment of the present application, the updating formula of 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 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, R i 、R i+1 are the i-th and i+1-th elements in the ratio sequence respectively.

[0147] It should be noted that the above explanation of the embodiment of the method for removing lightning pollution from meteor wind radar data is also applicable to the device for removing lightning pollution from meteor wind radar data in this embodiment, and will not be repeated here.

[0148] According to the device for removing lightning contamination from meteor wind radar data proposed in an embodiment of the present 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 is constructed. The incoherent average amplitude sequence and the ratio sequence are then updated by comparing the elements in the ratio sequence with the target threshold one by one, thereby obtaining an incoherent average amplitude sequence that has been removed from the lightning contamination. Thus, it is achieved that by constructing an incoherent average amplitude sequence, redundant signals in the receiver echo data are eliminated, thereby ensuring the accuracy of the data foundation. By sequentially comparing the elements in the ratio sequence constructed by the incoherent average amplitude sequence with the target threshold, the incoherent average amplitude sequence can be updated, and finally an incoherent average amplitude sequence with lightning contamination eliminated is obtained. For comparative study with the original amplitude sequence, the present application can not only eliminate lightning contamination from the original echo data of the meteor wind measurement radar, but also eliminate it in an extremely short time, with extremely high speed and efficiency. It can realize real-time processing of the radar original echo data under limited computing resources, that is, eliminate lightning contamination from the original echo data of the meteor wind measurement radar, thereby effectively improving the efficiency of the meteor signal identification algorithm. Thus, it solves the problem in the related art that in the raw data of the meteor wind measurement radar receiver, the frequent atmospheric lightning interference is easily confused with the real meteor signal, thereby reducing the efficiency of the meteor signal identification algorithm, making it difficult to realize real-time processing of the radar raw data under limited computing resources, and how to quickly and efficiently eliminate these lightning contaminations from the raw data of the meteor wind measurement radar.

[0149] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0150] Memory 501 , processor 502 , and computer programs stored in the memory 501 and executable on the processor 502 .

[0151] When the processor 502 executes the program, the method for removing lightning pollution from meteor wind radar data provided in the above embodiment is implemented.

[0152] Furthermore, the electronic device further includes:

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

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

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

[0156] If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, 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, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0158] The 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 the present application.

[0159] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for removing lightning contamination from meteor wind radar data as described above is implemented.

[0160] An embodiment of the present application also provides a computer program product, including a computer program, which can run computer instructions. When the computer instructions are executed by a processor, the method for removing lightning contamination from meteor wind radar data provided by the embodiment of the present application is implemented.

[0161] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

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

[0163] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0164] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the 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 (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program 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 the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0165] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0166] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

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

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

Claims

1. A method for removing lightning contamination from meteor wind radar data, characterized in that: The following steps are involved: Acquiring echo data from a receiver corresponding to a target meteor wind measurement radar, and constructing an incoherent average amplitude sequence based on the echo data; constructing a ratio sequence according to the incoherent average amplitude sequence, and sequentially comparing elements in the ratio sequence with a target threshold; 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 using a target natural number averaging 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 eliminates lightning pollution.

2. The method according to claim 1, characterized in that The constructing of a non-coherent average amplitude sequence according to the echo data comprises: constructing an amplitude sequence corresponding to the receiver according to the echo data; The incoherent average amplitude sequence is constructed according to the amplitude sequence.

3. The method according to claim 1, characterized in that The step of constructing a ratio sequence according to the incoherent average amplitude sequence comprises: collecting ratios between adjacent elements in the incoherent average amplitude sequence; The ratio sequence is constructed based on the ratios.

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

5. The method according to claim 1, wherein The updating formula of the incoherent average amplitude sequence is: A i+1 =(A i +A i+2 ) / n j =(A i +A i+2 ) / (j+1) Among them, A i 、A i+1 、A i+2 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, n j is the jth natural number in the natural number matrix n, n j =j+1.

6. The method according to claim 1, characterized in that The updating formula of the ratio sequence is: R i =A i+1 / A i R i+1 =A i+2 / A i+1 Among them, A i 、A i+1 、A i+2 are the i-th, i+1-th, and i+2-th elements in the incoherent average amplitude sequence, R i 、R i+1 are the i-th and i+1-th elements in the ratio sequence respectively.

7. A method for removing lightning contamination from meteor wind radar data, characterized in that: The following steps are involved: The first construction module is used to obtain echo data of a receiver corresponding to the target meteor wind measurement radar, and to construct an incoherent average amplitude sequence according to the echo data; a second building module, configured to build a ratio sequence according to the incoherent average amplitude sequence, and sequentially compare elements in the ratio sequence with a target threshold; An updating module is configured to update the incoherent average amplitude sequence and the ratio sequence by using a target natural number averaging matrix when an element in the ratio sequence is greater than the target threshold, until the element in the updated ratio sequence is less than the target threshold, so as to obtain an incoherent average amplitude sequence that eliminates lightning pollution.

8. An electronic device, characterized in that: include: 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 according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for removing lightning pollution from meteor wind radar data according to any one of claims 1 to 6.

10. 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 pollution from meteor wind radar data according to any one of claims 1 to 6.

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