A method and device for suppressing clutter of isolated points of wind turbines of airborne radar

Abstract

The present invention relates to the field of signal processing technology, and provides a method and device for suppressing isolated point clutter of an airborne radar wind turbine. The present invention uses an edge detection operator to detect the range Doppler spectrum of the wind turbine clutter corresponding to the airborne radar, and obtains the range gate sample to be detected of the wind turbine clutter; determines the threshold value according to the noise estimation values ​​on both sides, compares the signal power of the range gate sample to be detected with the corresponding threshold value, and obtains at least one target range gate sample of the wind turbine clutter; suppresses the wind turbine clutter according to the target range gate sample; determines the residual clutter according to the target range gate sample, and performs space-time segmentation adaptive processing on the residual clutter to suppress the residual clutter. Among them, by means of edge detection and threshold value comparison, it is possible to effectively distinguish the wind turbine and the target echo in the space-time domain, and by processing the wind turbine clutter and the residual clutter separately, it is possible to suppress the wind turbine clutter while ensuring the integrity of the target signal.

Description

Technical Field

[0001] The invention relates to the technical field of signal processing, and in particular to a method and a device for suppressing isolated point clutter of an airborne radar wind turbine. Background Art

[0002] As a clean and renewable energy source, wind power generation has always received extensive attention in my country, and a large number of wind power generation equipment are deployed in the southeast coastal areas. Since airborne radars are usually in a downward detection state, when working over the wind farm area where wind power generation equipment is located, their radar receivers will receive a large number of wind field echoes.

[0003] As a special group of tall buildings with rotating parts, the wind field echo generated by wind farms will have a significant impact on airborne early warning radar equipment, mainly including: (1) reducing the probability of target detection; (2) increasing the probability of target false alarm; (3) increasing the non-uniformity of clutter; (4) the receiver is prone to saturation. The superposition of the above many influencing factors makes wind farm clutter one of the key technologies that urgently needs to be solved in the downward detection mission of airborne radar.

[0004] In view of this, overcoming the defects of the prior art is an urgent problem to be solved in the field of this technology. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide an airborne radar wind turbine isolated point clutter suppression method and device, the purpose of which is to use an edge detection operator to detect the range Doppler spectrum of wind turbine clutter, obtain its to-be-detected range gate sample, and effectively distinguish the wind turbine and the target echo in the space-time domain by comparing the signal power with the threshold value, and by processing the wind turbine clutter and the residual clutter separately, it is possible to suppress the wind turbine clutter while ensuring the integrity of the target signal, thereby solving the problem that the prior art cannot effectively suppress the wind turbine clutter and cannot ensure that the target signal is not damaged.

[0006] The present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides an airborne radar wind turbine isolated point clutter suppression method, comprising:

[0008] Using an edge detection operator to detect a range Doppler spectrum of wind turbine clutter corresponding to the airborne radar, and obtaining a range gate sample to be detected of the wind turbine clutter;

[0009] Determine the estimated values ​​of noise on both sides of the range gate sample to be detected, and determine the threshold value according to the estimated values ​​of noise on both sides; compare the signal power of the range gate sample to be detected with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter;

[0010] Wind turbine clutter is suppressed according to the target range gate samples; residual clutter is determined according to the target range gate samples, and the residual clutter is adaptively processed in space-time segmentation to suppress the residual clutter.

[0011] Further, suppressing wind turbine clutter according to the target range gate samples comprises:

[0012] Performing a short-time Fourier transform on the echo signal of the wind turbine clutter to obtain an average interval between two adjacent flashing moments in the periodic flashing signal; obtaining a corresponding rotation period and rotation speed of the wind turbine based on the average interval; determining a first flashing moment in the periodic flashing signal according to the rotation period, and obtaining an initial rotation speed phase based on the first flashing moment; using the rotation speed and the initial rotation speed phase as initial atomic parameters; and constructing a corresponding overcomplete dictionary atomic representation based on the initial atomic parameters;

[0013] According to the target range gate samples and the covariance distances between the multiple overcomplete dictionary atom representations, target atom parameters are determined; the corresponding overcomplete dictionary atom representations are updated using the target atom parameters to obtain target dictionary atom representations; according to the target dictionary atom representations, a target clutter suppression residual is obtained to suppress wind turbine clutter using the target clutter suppression residual.

[0014] Furthermore, the expression of the overcomplete dictionary atom representation is:

[0015]

[0016] in, For fast time, t m For slow time, is the complex amplitude of wind turbine clutter, is the space-time steering vector; t m =mTr, m is the number of slow time sampling, Tr is the pulse repetition period;

[0017] The complex amplitude of the wind turbine clutter is expressed as:

[0018]

[0019] Where, the number of azimuth sub-arrays is N, λ is the wavelength of the wind turbine clutter, j is a complex unit, α is the azimuth angle of the carrier relative to the X-axis, and R w is the wind turbine slant pitch, l n represents the length of the nth blade of the wind turbine, θ n (t) represents the initial phase angle of the nth blade, and the initial phase angle θ of the nth blade n (t) = θ 0 +2πf rot t,θ0 is the initial speed phase of the blade at time t, f rot is the blade speed at time t;

[0020] The expression of the space-time steering vector is:

[0021]

[0022] Among them, f sil represents the spatial frequency, represents the normalized Doppler frequency, represents the time-domain steering vector, S s (f sil ) represents the spatial steering vector, Express With S s (f sil ) of the Kronecker product;

[0023] The expression of the time domain steering vector is:

[0024]

[0025] Where fr is the pulse repetition frequency, V R is the carrier speed, the number of coherent processing pulses is K, For wind turbines Unit vector of direction;

[0026] The expression of the spatial steering vector is:

[0027]

[0028] Wherein, d is the array element spacing vector of the airborne radar.

[0029] Further, the determining target atom parameters according to the target range gate samples and the covariance distances between the multiple overcomplete dictionary atom representations; using the target atom parameters to update the corresponding overcomplete dictionary atom representation to obtain the target dictionary atom representation; and obtaining the target clutter suppression residual according to the target dictionary atom representation includes:

[0030] Taking the target range gate sample and the corresponding overcomplete dictionary atom representation as initial samples; constructing a training set, wherein the training set includes a plurality of initial samples;

[0031] Based on the target range gate sample in the initial sample, the first transposed value and the number of initial samples in the training set, a covariance distance matrix is ​​obtained; the product of the target range gate sample, the first transposed value and the covariance distance matrix is ​​determined as the test statistic of the initial sample; wherein the first transposed value is the transposed value of the target range gate sample;

[0032] Sorting the initial samples in the training set in ascending order of the test statistic, and determining the initial sample in the sorted training set whose test statistic is the median as the reference sample;

[0033] The training set is processed using the reference samples to determine the target clutter suppression residual.

[0034] Further, the using the reference sample to process the training set to determine the target clutter suppression residual includes:

[0035] For the overcomplete dictionary atomic representation of each initial sample in the training set, a corresponding training orthogonal projection operator is determined; the product of the target range gate sample and the corresponding training orthogonal projection operator is determined as the training orthogonal projection of the target range gate sample on its own sample space; the difference between the target range gate sample and the training orthogonal projection is determined as the training clutter suppression residual; and the Mahalanobis distance between the training clutter suppression residual and the reference sample is determined;

[0036] Determine the minimum value of all Mahalanobis distances corresponding to the training set; determine the initial atomic parameters corresponding to the minimum value as the target atomic parameters;

[0037] Based on the target atom parameter, construct a target dictionary atom representation; determine the product of the target dictionary atom representation and the second transposed value as an intermediate matrix; determine the product of the target dictionary atom representation, the inverse matrix of the intermediate matrix and the second transposed value as a target projection operator; wherein the second transposed value is the transposed value of the target dictionary atom representation;

[0038] The product of the target range gate sample and the corresponding target orthogonal projection operator is determined as the target orthogonal projection of the target range gate sample on its own sample space; and the difference between the target range gate sample and the target orthogonal projection is determined as the target clutter suppression residual corresponding to the target range gate sample.

[0039] Further, the determining the residual clutter according to the target range gate samples, and performing space-time segment adaptive processing on the residual clutter to suppress the residual clutter includes:

[0040] Determine the area except the target range gate sample in the range Doppler spectrum as the residual clutter area; divide the residual clutter area into a non-stationary clutter area and a stationary clutter area; wherein the distance distribution range of the non-stationary clutter area is between one times the carrier distance and five times the carrier distance, and the distance distribution range of the stationary clutter area is the area in the residual clutter area except the non-stationary clutter area;

[0041] Performing signal dimensionality reduction processing on the range Doppler unit in the non-stationary clutter area in the Doppler domain to obtain a space-time three-dimensional weight vector of the range Doppler unit; performing three-dimensional space-time adaptive processing on the non-stationary clutter and performing two-dimensional space-time adaptive processing on the stationary clutter to suppress the non-stationary clutter and the stationary clutter;

[0042] The expression of the space-time three-dimensional weight vector is: is the Doppler unit data to be detected after dimension reduction, is the training range Doppler unit data after dimension reduction, T k represents the Doppler domain dimension reduction matrix, L s is the number of training samples, is the space-time three-dimensional covariance matrix corresponding to the k-th range Doppler unit to be detected after dimensionality reduction, is the reduced-dimensional space-time steering vector of the kth Doppler channel, S k is the three-dimensional steering vector, S t Time domain steering vector, S a is the azimuth-dimensional steering vector, S e is the pitch-dimensional steering vector, f a is the azimuthal spatial frequency, f e is the pitch spatial frequency.

[0043] Further, the edge detection operator includes a first filter and a second filter;

[0044] The using of the edge detection operator to detect the range Doppler spectrum of the wind turbine clutter corresponding to the airborne radar to obtain the range gate sample to be detected of the wind turbine clutter comprises:

[0045] Using the first filter and the second filter to perform a convolution operation on the range Doppler spectrum, obtaining a first direction brightness difference approximation and a second direction brightness difference approximation; based on the first direction brightness difference approximation and the second direction brightness difference approximation, obtaining a gray value of each point in the range Doppler spectrum;

[0046] Obtaining a local maximum point of the grayscale value in the range Doppler spectrum through the first filter and the second filter, and determining the local maximum point as a preliminary range gate sample of the wind turbine clutter;

[0047] According to the azimuth width of the antenna beam of the airborne radar, the target azimuth angle corresponding to the azimuth width, the pitch angle corresponding to the azimuth width, and the moving speed of the carrier of the airborne radar, a main lobe clutter bandwidth corresponding to the airborne radar is obtained; according to the main lobe clutter bandwidth, a frequency gate threshold is obtained;

[0048] When the frequency gate occupied by the preliminary range gate sample is greater than the frequency gate threshold, the preliminary range gate sample is determined as the corresponding range gate sample to be detected.

[0049] Further, the determining of the noise estimation values ​​on both sides of the range gate sample to be detected, determining the threshold value according to the noise estimation values ​​on both sides; and comparing the signal power of the range gate sample to be detected with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter comprises:

[0050] According to the number of protection units, the number of reference units and the power at the main clutter of the range gate to be detected in the range Doppler spectrum, the two-side noise estimation value is obtained; wherein the two-side noise estimation value includes a first noise estimation value and a second noise estimation value;

[0051] Determine the minimum value of the first noise estimation value and the second noise estimation value as the target noise estimation value; determine the target warning coefficient according to the false alarm probability and the detection probability; determine the product of the target warning coefficient and the target noise estimation value as the corresponding threshold value;

[0052] When the signal power of the to-be-detected range gate sample is greater than the corresponding threshold value, the to-be-detected range gate sample is determined as a target range gate sample.

[0053] In a second aspect, the present invention further provides an airborne radar wind turbine isolated point clutter suppression device, which is used to implement the airborne radar wind turbine isolated point clutter suppression method described in the first aspect, wherein the airborne radar wind turbine isolated point clutter suppression device comprises a wind turbine edge detection module, a wind turbine position identification module, a wind turbine micro-motion parameter estimation and clutter suppression module, and a space-time adaptive segment processing module, wherein:

[0054] The wind turbine edge detection module is used to use an edge detection operator to detect the range Doppler spectrum of the wind turbine clutter corresponding to the airborne radar, and obtain the range gate samples to be detected of the wind turbine clutter.

[0055] The wind turbine position identification module is used to determine the noise estimation values ​​on both sides of the range gate sample to be detected, and determine the threshold value according to the noise estimation values ​​on both sides; and is also used to compare the signal power of the range gate sample to be detected with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter.

[0056] The wind turbine micro-motion parameter estimation and clutter suppression module is used to suppress wind turbine clutter according to the target range gate samples.

[0057] The space-time adaptive segment processing module is used to determine the residual clutter according to the target range gate samples, and perform space-time segment adaptive processing on the residual clutter to suppress the residual clutter.

[0058] In another optional embodiment, the airborne radar wind turbine isolated point clutter suppression device comprises:

[0059] At least one processor; and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to execute the airborne radar wind turbine isolated point clutter suppression method described in the first aspect.

[0060] In a third aspect, the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, which are executed by one or more processors to complete the airborne radar wind turbine isolated point clutter suppression method described in the first aspect.

[0061] In a fourth aspect, a chip is provided, comprising: a processor and an interface, for calling and running a computer program stored in a memory to execute the airborne radar wind turbine isolated point clutter suppression method as in the first aspect.

[0062] In a fifth aspect, a computer program product comprising instructions is provided. When the instructions are executed on a computer or a processor, the computer or the processor executes the airborne radar wind turbine isolated point clutter suppression method as described in the first to fourth aspects and any one of the above.

[0063] In a sixth aspect, an airborne radar wind turbine isolated point clutter suppression method system is provided, comprising an airborne radar wind turbine isolated point clutter suppression device as in the second aspect, and using the airborne radar wind turbine isolated point clutter suppression method as described in the first aspect to complete the interaction of the airborne radar wind turbine isolated point clutter suppression device of the second aspect.

[0064] Different from the prior art, the present invention has at least the following beneficial effects:

[0065] The present invention uses an edge detection operator to detect the range Doppler spectra of wind turbine clutter corresponding to the airborne radar, and obtains the range gate samples to be detected of the wind turbine clutter; determines the threshold value according to the noise estimation values ​​on both sides, compares the signal power of the range gate samples to be detected with the corresponding threshold value, and obtains at least one target range gate sample of the wind turbine clutter; suppresses the wind turbine clutter according to the target range gate sample; determines the residual clutter according to the target range gate sample, and performs space-time segmentation adaptive processing on the residual clutter to suppress the residual clutter. Among them, by means of edge detection and threshold value comparison, it is possible to effectively distinguish the wind turbine and the target echo in the space-time domain, and by processing the wind turbine clutter and the residual clutter separately, it is possible to suppress the wind turbine clutter while ensuring the integrity of the target signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0067] Figure 1 is a geometric configuration diagram of an airborne radar provided by an embodiment of the present invention;

[0068] Figure 2 It is a flow chart of a method for suppressing isolated point clutter of an airborne radar wind turbine provided by an embodiment of the present invention;

[0069] Figure 3 is a flow chart of step 10 provided in an embodiment of the present invention;

[0070] Figure 4 is a flow chart of step 20 provided in an embodiment of the present invention;

[0071] Figure 5 is a flow chart of step 30 provided in an embodiment of the present invention;

[0072] Figure 6It is a flow chart of another method for suppressing isolated point clutter of an airborne radar wind turbine provided by an embodiment of the present invention;

[0073] Figure 7 is a flowchart of step 302a provided by an embodiment of the present invention;

[0074] Figure 8 is a flowchart of step 3024 provided by an embodiment of the present invention;

[0075] Fig. 9 is another flowchart of step 30 provided in an embodiment of the present invention;

[0076] Fig.10 The present invention is a schematic diagram of the architecture of an airborne radar wind turbine isolated point clutter suppression device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0078] Unless the context requires otherwise, throughout the specification and claims, the term "including" is to be interpreted as open inclusion, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "examples", "specific examples" or "some examples" and the like are intended to indicate that specific features, structures, materials or characteristics associated with the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representation of the above terms does not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any appropriate manner, that is, although they may be carried in the embodiments or examples of the above terms due to reasons such as the order and position of appearance, it is not limited to that they can be carried in combination by one embodiment or example.

[0079] In the description of the present invention, it is necessary to understand that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0080] In the description of the present invention, the terms "first" and "second" are used only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, the meaning of "multiple" is two or more. In addition, for example, the same type of nouns may be described as two independent individuals by adding "A" and "B" at the end. In this case, the corresponding features defined as "A" and "B" are only used to distinguish the same type of individuals for description purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features.

[0081] When describing some embodiments, the expressions "coupling", "coupling" and "connection" and their derivatives may be used. For example, when describing some embodiments, the term "connection" may be used to indicate that two or more components are in direct physical or electrical contact with each other. For another example, when describing some embodiments, the term "coupling" may be used to indicate that two or more components are in direct physical or electrical contact. However, the terms "connection" or "coupling" may also refer to two or more components that are not in direct contact with each other, but still cooperate or interact with each other, such as "optical path coupling", "wireless connection", etc. The embodiments disclosed herein are not necessarily limited to the contents of the present invention.

[0082] In the description of the present invention, the expression "A and / or B" (where A and B are used to formally represent specific characteristic contents) will be involved, and the corresponding expressions include the following three combinations: only A, only B, and a combination of A and B.

[0083] As used herein, "about," "substantially," or "approximately" includes the stated value and an average value that is within an acceptable range of deviation from the particular value as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0084] Embodiment 1:

[0085] Wind turbine clutter mainly comes from the rotation and scattering effects of wind turbine blades. These clutter appear as isolated points or clumps in radar images, which may interfere with the radar's detection of real targets. The characteristics of wind turbine clutter include time-frequency domain and space-time domain features. The time-frequency domain features are manifested as the frequency and time changes of the clutter signal, while the space-time domain features reflect the distribution of the clutter in space and time.

[0086] Traditional ground radar clutter suppression methods such as Moving Target Indicator (MTI) and Moving Target Detection (MTD) use echo Doppler information to distinguish targets from clutter. However, wind turbine clutter has a wide symmetrical Doppler spectrum, so targets are easily indistinguishable. Space-Time Adaptive Processing (STAP) can distinguish targets from clutter in both spatial and temporal dimensions, and is widely used in airborne radar clutter suppression. However, wind turbine and target echoes are often difficult to distinguish in the spatial and temporal domains. At the same time, the STAP method often causes target signal loss while suppressing wind turbine clutter. In view of the micro-Doppler characteristics of wind turbine clutter, Karabayir et al. proposed a wind turbine clutter suppression method based on Clean. This method uses the micro-Doppler characteristics of wind turbines to reconstruct echo signals and suppress wind turbine clutter through subtraction operations. However, this method is only suitable for high signal-to-noise ratio situations. Naqvi et al. proposed a matching pursuit algorithm, which uses the echo model of the wind turbine to construct an over-complete dictionary and suppresses wind turbine clutter through repeated iterations. However, this method needs to generate an over-complete dictionary over a large range, so the more dictionary atoms there are, the greater the amount of computation.

[0087] In actual engineering, Figure 1 As shown in the figure, when the airborne radar is working downward, in addition to the inevitable near- and long-range non-stationary and non-uniform clutter, there may also be a clutter environment of isolated points in the wind farm, and the clutter non-uniformity increases significantly. The existence of wind farms will seriously affect the target detection performance of airborne early warning radars, and the existing clutter suppression methods cannot effectively suppress the clutter of isolated points in wind farms. Therefore, the detection of moving targets in the wind farm environment has become one of the core key technical problems that the current airborne radar needs to solve urgently.

[0088] In order to solve the above problems, Figure 2 As shown, an embodiment of the present invention provides an airborne radar wind turbine isolated point clutter suppression method, comprising:

[0089] Step 10: Use an edge detection operator to detect the range Doppler spectrum of the wind turbine clutter corresponding to the airborne radar to obtain the range gate samples to be detected of the wind turbine clutter.

[0090] The range Doppler spectrum is a data representation of wind turbine clutter of the airborne radar in a normal mode.

[0091] When the airborne radar works in a wind farm environment, the echoes it receives will be affected by the wind turbines, thus presenting specific features on the range Doppler spectrum. The embodiment of the present invention firstly detects the range gate samples to be detected of the wind turbine clutter from the range Doppler spectrum by edge detection.

[0092] Step 20: Determine the noise estimation values ​​on both sides of the range gate sample to be detected, and determine the threshold value according to the noise estimation values ​​on both sides; compare the signal power of the range gate sample to be detected with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter.

[0093] Based on the preliminary detected range gate samples to be detected, the noise on both sides of the isolated point being detected in the range Doppler spectrum is estimated, and the threshold value is obtained based on this. By comparing the signal power with the threshold value, the wind turbine and target echo can be effectively distinguished in the space-time domain to obtain the target range gate samples.

[0094] Step 30: suppress wind turbine clutter according to the target range gate samples; determine residual clutter according to the target range gate samples, and perform space-time segment adaptive processing on the residual clutter to suppress the residual clutter.

[0095] The present invention uses an edge detection operator to detect the range Doppler spectra of wind turbine clutter corresponding to the airborne radar, and obtains the range gate samples to be detected of the wind turbine clutter; determines the threshold value according to the noise estimation values ​​on both sides, compares the signal power of the range gate samples to be detected with the corresponding threshold value, and obtains at least one target range gate sample of the wind turbine clutter; suppresses the wind turbine clutter according to the target range gate sample; determines the residual clutter according to the target range gate sample, and performs space-time segmentation adaptive processing on the residual clutter to suppress the residual clutter. Among them, by means of edge detection and threshold value comparison, it is possible to effectively distinguish the wind turbine and the target echo in the space-time domain, and by processing the wind turbine clutter and the residual clutter separately, it is possible to suppress the wind turbine clutter while ensuring the integrity of the target signal.

[0096] The following is a specific description of the airborne radar wind turbine isolated point clutter suppression method according to an embodiment of the present invention:

[0097] In the embodiment of the present invention, the airborne radar array element spacing is set to d, the number of azimuth sub-arrays is N, the number of coherent processing pulses is K, the aircraft height is H, and the pulse repetition frequency is f. r , the range Doppler spectrum corresponding to a certain CPI is I.

[0098] In order to determine the range gate samples to be detected from the range Doppler spectrum, the edge detection operator includes a first filter and a second filter. In an optional embodiment, the first filter and the second filter are both a set of 3×3 filters, respectively F x and F y ,in,

[0099] like Figure 3 As shown, the step 10 includes:

[0100] Step 101: Use the first filter and the second filter to perform a convolution operation on the range Doppler spectrum to obtain an approximate brightness difference value in a first direction and an approximate brightness difference value in a second direction; based on the approximate brightness difference value in the first direction and the approximate brightness difference value in the second direction, obtain the grayscale value of each point in the range Doppler spectrum.

[0101] Using F x and F y By convolving the range Doppler spectrum I, the brightness difference approximation in the X-axis direction (i.e., the first direction) and the Y-axis direction (i.e., the second direction) can be obtained, and the formula is:

[0102] G x =F x *I

[0103] G y =F y *I

[0104] Among them, * represents the convolution operation, G x and G y Represents the image grayscale value of edge detection in the X-axis and Y-axis directions respectively. The grayscale value of each point in the image is:

[0105]

[0106] Step 102: obtaining local maximum points of grayscale values ​​in the range Doppler spectrum through the first filter and the second filter, and determining the local maximum points as preliminary range gate samples of the wind turbine clutter.

[0107] The edge detection operator returns the local maximum point of the edge detection, which is used as the initial range gate sample for the initial determination of the range gate where the wind turbine is located. Among them, n 0 To make a preliminary judgment on the number of wind turbines.

[0108] Step 103: Obtain a main lobe clutter bandwidth corresponding to the airborne radar according to the azimuth width of the antenna beam of the airborne radar, the target azimuth angle corresponding to the azimuth width, the pitch angle corresponding to the azimuth width, and the aircraft movement speed of the airborne radar; and obtain a frequency gate threshold according to the main lobe clutter bandwidth.

[0109] At the same time, the embodiment of the present invention takes into account that the wind turbine clutter has a significant widening phenomenon in the frequency gate, especially for wind turbines with relatively large rotation speeds. Therefore, in order to eliminate the interference caused by the widening phenomenon, the frequency gate threshold η is set 1 Among them, the frequency gate threshold η 1 It can be obtained from the main lobe clutter bandwidth. Assuming that the azimuth width of the antenna beam is Δθ, the corresponding main lobe clutter bandwidth is:

[0110]

[0111] Among them, θ 0 is the target azimuth, is the corresponding pitch angle, V R is the aircraft movement speed.

[0112] Step 104: When the frequency gate occupied by the preliminary range gate sample is greater than the frequency gate threshold, the preliminary range gate sample is determined as a corresponding range gate sample to be detected.

[0113] When the frequency gate occupied by wind turbine clutter is greater than the frequency gate threshold η 1 When , the range gate sample r to be detected of the wind turbine range gate position is confirmed.

[0114] To illustrate the process of determining the target range gate sample, Figure 4 As shown, the step 20 includes:

[0115] Step 201: Obtain the two-side noise estimation value according to the number of protection units, the number of reference units and the power at the main clutter of the range gate to be detected in the range Doppler spectrum; wherein the two-side noise estimation value includes a first noise estimation value and a second noise estimation value.

[0116] In order to further confirm the distance gate position of each wind turbine in the wind farm, the embodiment of the present invention adopts the constant false alarm detection method SO-CFAR to Further confirmation. Assume that the range gate to be detected is ri, and the number of protection units is n g =5, number of reference units n s =30, then the estimated value of the clutter noise power on both sides of the range gate ri and The expressions are:

[0117]

[0118]

[0119] Wherein, I(r) represents the power of the main clutter at the rth range gate to be detected in the range Doppler spectrum I.

[0120] Step 202: Determine the minimum value between the first noise estimation value and the second noise estimation value as the target noise estimation value; determine the target warning coefficient according to the false alarm probability and the detection probability; and determine the product of the target warning coefficient and the target noise estimation value as the corresponding threshold value.

[0121] The threshold value of SO-CFAR can be expressed as:

[0122]

[0123] When the false alarm probability P f =10 -6 , the probability of finding d =80%, α so =12.8dB.

[0124] Step 203: When the signal power of the to-be-detected range gate sample is greater than the corresponding threshold value, the to-be-detected range gate sample is determined as a target range gate sample.

[0125] Preliminary determination of wind turbine distance gate position Perform SO-CFAR detection again to confirm and finally obtain the target range gate sample where n 1 The number of wind turbines confirmed.

[0126] After confirming the target range gate sample, in order to explain the process of suppressing wind turbine clutter according to the target range gate sample, as shown in FIG. Figure 5 As shown, in step 30, suppressing wind turbine clutter according to the target range gate samples includes:

[0127] Step 301a: Perform a short-time Fourier transform on the echo signal of the wind turbine clutter to obtain the average interval between two adjacent flickering moments in the periodic flickering signal; obtain the corresponding rotation period and rotation speed of the wind turbine based on the average interval; determine the first flickering moment in the periodic flickering signal according to the rotation period, and obtain an initial rotation speed phase based on the first flickering moment; use the rotation speed and the initial rotation speed phase as initial atomic parameters; and construct a corresponding overcomplete dictionary atomic representation based on the initial atomic parameters.

[0128] The wind turbine clutter is generated by the airborne radar in the extended range mode.

[0129] like Figure 6 As shown in FIG. 1 , in the extended range mode, the echo signal is first subjected to a short-time Fourier transform, and the periodic flickering signal generated by the rotation of the wind turbine blades is obtained based on the transformation result; by analyzing the frequency and phase changes of these periodic flickering signals, the average interval between two adjacent flickering moments is estimated, thereby estimating the rotation period Tw and the rotation speed f of the wind turbine rot Since the rotation of wind turbine blades is periodic, the average interval between two adjacent flashing moments is a part of the wind turbine rotation cycle. Through multiple measurements and averaging, a more accurate rotation cycle can be obtained. The rotation speed is the reciprocal of the rotation cycle.

[0130] Based on the initial speed, the initial speed phase θ is obtained from the first flashing moment. 0 It should be noted that in order to meet the requirements of wind turbine parameter estimation, the beam dwell time in the extended range mode needs to be greater than the wind turbine rotation period T w .

[0131] The expression of the overcomplete dictionary atom representation is:

[0132]

[0133] in, For fast time, t m For slow time, is the complex amplitude of wind turbine clutter, is the space-time steering vector; t m =mTr, m is the number of slow time sampling, Tr is the pulse repetition period;

[0134] The complex amplitude of the wind turbine clutter is expressed as:

[0135]

[0136] Where, the number of azimuth sub-arrays is N, λ is the wavelength of the wind turbine clutter, j is a complex unit, α is the azimuth angle of the carrier relative to the X-axis, and R w is the wind turbine slant pitch, l n represents the length of the nth blade of the wind turbine, θ n (t) represents the initial phase angle of the nth blade, and the initial phase angle θ of the nth blade n (t) = θ 0 +2πf rot t,θ 0 is the initial speed phase of the blade at time t, f rot is the blade speed at time t;

[0137] The expression of the space-time steering vector is:

[0138]

[0139] Among them, f sil represents the spatial frequency, represents the normalized Doppler frequency, represents the time-domain steering vector, S s (f sil ) represents the spatial steering vector, Express With S s (f sil ) of the Kronecker product;

[0140] The expression of the time domain steering vector is:

[0141]

[0142] Where fr is the pulse repetition frequency, V R is the carrier speed, the number of coherent processing pulses is K, For wind turbines Unit vector of direction;

[0143] The expression of the spatial steering vector is:

[0144]

[0145] Wherein, d is the array element spacing vector of the airborne radar.

[0146] Step 302a: Determine target atom parameters according to the target range gate samples and the covariance distances between the multiple overcomplete dictionary atom representations; use the target atom parameters to update the corresponding overcomplete dictionary atom representation to obtain a target dictionary atom representation; obtain a target clutter suppression residual according to the target dictionary atom representation, so as to suppress wind turbine clutter using the target clutter suppression residual.

[0147] To illustrate the process of determining and using the target clutter suppression residual, Figure 7 As shown, step 302a includes:

[0148] Step 3021: taking the target range gate sample and the corresponding overcomplete dictionary atom representation as initial samples; constructing a training set, wherein the training set includes a plurality of initial samples.

[0149] Step 3022: Based on the target range gate sample in the initial sample, the first transposed value and the number of initial samples in the training set, a covariance distance matrix is ​​obtained; the product of the target range gate sample, the first transposed value and the covariance distance matrix is ​​determined as the test statistic of the initial sample; wherein the first transposed value is the transposed value of the target range gate sample.

[0150] The embodiment of the present invention takes into account the atomic parameter rotation period θ in the airborne radar extended range mode 0 and speed f rot There is an error in the estimation, and the initial dictionary atomic parameters are uniformly discretized to obtain {θ 0 +iΔθ,f rot +jΔf}(-M 1 ≤i≤M 1 ,-M 2 ≤j≤M 2 ), the discretized atomic step size is Δd{Δθ,Δf}, and the discretized atomic dictionary matrix D is

[0151] d i,j =d 0 +Δd{iΔθ,jΔf}(-M 1 ≤i≤M 1 ,-M 2 ≤j≤M 2 )

[0152] D=[d i,j ]

[0153] Among them, d 0 is θ 0 and f rot Constructed atoms.

[0154] Then, the optimal estimation of the initial atomic parameters is performed. In an optional embodiment, assuming that the training set consists of L initial samples, the test statistic corresponding to the lth initial sample can be expressed as

[0155]

[0156] Among them, R l Represents the covariance distance matrix of the training samples, which is usually estimated from the samples in the training set, that is,

[0157]

[0158] Step 3023: sort the initial samples in the training set in ascending order of the test statistic, and determine the initial samples in the sorted training set whose test statistic is the median as reference samples.

[0159] The training set X l According to T GIP (l) Sort the values ​​from small to large and select T GIP (l) The initial sample corresponding to the median is used as the reference sample X for subsequent non-uniform clutter data processing ref .

[0160] Step 3024: Process the training set using the reference samples to determine the target clutter suppression residual.

[0161] In order to illustrate the process of determining the target clutter suppression residual, Figure 8 As shown, the step 3024 includes:

[0162] Step 30241: for the overcomplete dictionary atomic representation of each initial sample in the training set, determine the corresponding training orthogonal projection operator; determine the product of the target range gate sample and the corresponding training orthogonal projection operator as the training orthogonal projection of the target range gate sample on its own sample space; determine the difference between the target range gate sample and the training orthogonal projection as the training clutter suppression residual; determine the Mahalanobis distance between the training clutter suppression residual and the reference sample.

[0163] After selecting the reference sample, the orthogonal projection operator corresponding to each dictionary atom is P i,j =d i,j (d i,j H d i,j ) - 1 d i,j H .

[0164] Step 30242: Determine the minimum value of all Mahalanobis distances corresponding to the training set; and determine the initial atomic parameters corresponding to the minimum value as the target atomic parameters.

[0165] The Mahalanobis distance represents the covariance distance of data, and the embodiment of the present invention uses it to calculate the similarity of two unknown sample sets.

[0166] Step 30243: Based on the target atom parameters, construct a target dictionary atom representation; determine the product of the target dictionary atom representation and the second transposed value as an intermediate matrix; determine the product of the target dictionary atom representation, the inverse matrix of the intermediate matrix and the second transposed value as a target projection operator; wherein the second transposed value is the transposed value of the target dictionary atom representation.

[0167] Step 30244: determine the product of the target range gate sample and the corresponding target orthogonal projection operator as the target orthogonal projection of the target range gate sample on its own sample space; determine the difference between the target range gate sample and the target orthogonal projection as the target clutter suppression residual corresponding to the target range gate sample.

[0168] In an optional embodiment, in the initial sample X l ,l∈r 1,2...n1Subtract the orthogonal projection on this space to obtain the residual after wind turbine clutter suppression: Calculate the reference sample X separately ref and residual after wind turbine clutter suppression The Mahalanobis distance between

[0169] The value ranges of i and j are the same as those of dictionary atomic parameters. MML The orthogonal projection operator P corresponding to the minimum value in (i,j) i,j The atomic parameters in are the optimal estimated parameters. and is the best estimate. and Constructing atoms Its corresponding orthogonal projection operator Therefore, the residual error of the range gate sample after wind turbine clutter suppression is

[0170] In order to illustrate the process of suppressing residual clutter, Fig. 9 As shown, in step 30, determining the residual clutter according to the target range gate samples, and performing space-time segment adaptive processing on the residual clutter to suppress the residual clutter includes:

[0171] Step 301b: Determine the area in the range Doppler spectrum except the target range gate sample as the residual clutter area; divide the residual clutter area into a non-stationary clutter area and a stationary clutter area; wherein the distance distribution range of the non-stationary clutter area is between one times the carrier distance and five times the carrier distance, and the distance distribution range of the stationary clutter area is the area in the residual clutter area except the non-stationary clutter area.

[0172] After suppressing the wind turbine clutter, the remaining clutter area can be divided into a non-stationary clutter area and a stationary clutter area. The distance distribution range of the non-stationary clutter area is The remaining area is the stationary clutter area.

[0173] Step 302b: performing signal dimensionality reduction processing on the range Doppler unit of the non-stationary clutter area in the Doppler domain to obtain a space-time three-dimensional weight vector of the range Doppler unit; performing three-dimensional space-time adaptive processing on the non-stationary clutter, and performing two-dimensional space-time adaptive processing on the stationary clutter to suppress the non-stationary clutter and the stationary clutter.

[0174] Space-time three-dimensional STAP processing is used for non-stationary clutter areas, and space-time two-dimensional STAP processing is used for other clutter areas. Since the system degree of freedom of space-time three-dimensional STAP processing is relatively high, the required number of training samples is usually difficult to meet, so the embodiment of the present invention performs dimensionality reduction processing on the echo in the Doppler domain.

[0175] The expression of the space-time three-dimensional weight vector is: is the Doppler unit data to be detected after dimension reduction, is the training range Doppler unit data after dimension reduction, T k represents the Doppler domain dimension reduction matrix, L s is the number of training samples, is the space-time three-dimensional covariance matrix corresponding to the k-th range Doppler unit to be detected after dimensionality reduction, is the reduced-dimensional space-time steering vector of the kth Doppler channel, S k is the three-dimensional steering vector, S t Time domain steering vector, S t =[1,e j2πk / K ,…,e j2π(K-1)k / K ] T , S a is the azimuth-dimensional steering vector, S e is the pitch-dimensional steering vector, f a is the azimuthal spatial frequency, f e is the pitch spatial frequency. The processed output signal is

[0176] The airborne radar wind turbine isolated point clutter suppression method of the embodiment of the present invention is a method for suppressing short-range clutter of an airborne radar in a complex terrain environment, comprising the following steps:

[0177] Step 1: For the range Doppler spectrum of the wind farm echo of the airborne radar, the edge detection operator is used to detect the edge of the wind turbine in the range Doppler spectrum. Step 2: The constant false alarm detection method is used to further determine the range gate where the wind turbine is located. Step 3: The optimal parameters of the initial phase and speed of the blades of the wind turbine clutter dictionary atoms are estimated, and the orthogonal projection matrix is ​​constructed using the updated dictionary atoms to suppress the wind turbine clutter. Step 4: The residual clutter of the airborne radar is processed by space-time adaptive segmentation.

[0178] The present invention utilizes the unique micro-Doppler characteristics of wind turbine echo signals to construct a wind turbine echo feature subspace, thereby being able to distinguish wind turbines, targets, clutter and noise; on the one hand, accurate positioning of wind turbines is achieved through image edge detection and constant false alarm detection; on the other hand, the Mahalanobis distance is used to estimate wind turbine dictionary atomic parameters, thereby ensuring the uniformity of samples after wind turbine clutter suppression, effectively improving the target detection performance of airborne radar in a wind turbine isolated point clutter environment, and having high engineering application value.

[0179] It should be noted that the methods not described in detail in the embodiments of the present invention are well known to those skilled in the art and can be implemented with reference to the prior art. They will not be expanded in the subsequent embodiments and should not be regarded as unclear aspects of the present invention.

[0180] Embodiment 2:

[0181] like Fig.10 , is a schematic diagram of the architecture of an airborne radar wind turbine isolated point clutter suppression device according to an embodiment of the present invention. The airborne radar wind turbine isolated point clutter suppression device according to this embodiment includes one or more processors 21 and a memory 22. Fig.10 A processor 21 is taken as an example.

[0182] The processor 21 and the memory 22 may be connected via a bus or other means. Fig.10 The example of connecting through bus is taken in the following.

[0183] The memory 22 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs and non-volatile computer executable programs, such as the airborne radar wind turbine isolated point clutter suppression method in this embodiment. The processor 21 executes the airborne radar wind turbine isolated point clutter suppression method by running the non-volatile software programs and instructions stored in the memory 22.

[0184] The memory 22 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 22 may optionally include a memory remotely arranged relative to the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0185] The program instructions / modules are stored in the memory 22, and when executed by the one or more processors 21, the airborne radar wind turbine isolated point clutter suppression method in the above embodiment is executed, for example, the above described Figure 2-Figure 9 The steps shown.

[0186] An embodiment of the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors, such as Fig.10 A processor 21 can enable the one or more processors to execute the airborne radar wind turbine isolated point clutter suppression method in a specific embodiment of the present invention, for example, to execute the above-described Figure 2-Figure 9 The steps shown can also be implemented Fig.10 The modules and units described above; or the airborne radar wind turbine isolated point clutter suppression method according to the specific embodiment of the present invention, for example, the above described Figure 2-Figure 9 The steps shown can also be implemented Fig.10 The various modules and units described.

[0187] It is worth noting that the information interaction, execution process, etc. between the modules and units within the above-mentioned devices and systems are based on the same concept as the processing method embodiment of the present invention. The specific contents can be found in the description of the method embodiment of the present invention and will not be repeated here.

[0188] A person skilled in the art may understand that all or part of the steps in the various methods of the embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0189] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for suppressing isolated point clutter of an airborne radar wind turbine, characterized in that: include: Using an edge detection operator to detect a range Doppler spectrum of wind turbine clutter corresponding to the airborne radar, and obtaining a range gate sample to be detected of the wind turbine clutter; Determine the estimated values ​​of noise on both sides of the range gate sample to be detected, and determine the threshold value according to the estimated values ​​of noise on both sides; compare the signal power of the range gate sample to be detected with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter; Suppress wind turbine clutter according to the target range gate samples; determine residual clutter according to the target range gate samples, and perform space-time segment adaptive processing on the residual clutter to suppress the residual clutter; Wherein, the edge detection operator includes a first filter and a second filter; The using of the edge detection operator to detect the range Doppler spectrum of the wind turbine clutter corresponding to the airborne radar to obtain the range gate sample to be detected of the wind turbine clutter comprises: Using the first filter and the second filter to perform a convolution operation on the range Doppler spectrum, obtaining a first direction brightness difference approximation and a second direction brightness difference approximation; based on the first direction brightness difference approximation and the second direction brightness difference approximation, obtaining a gray value of each point in the range Doppler spectrum; Obtaining a local maximum point of the grayscale value in the range Doppler spectrum through the first filter and the second filter, and determining the local maximum point as a preliminary range gate sample of the wind turbine clutter; According to the azimuth width of the antenna beam of the airborne radar, the target azimuth angle corresponding to the azimuth width, the pitch angle corresponding to the azimuth width, and the moving speed of the carrier of the airborne radar, a main lobe clutter bandwidth corresponding to the airborne radar is obtained; according to the main lobe clutter bandwidth, a frequency gate threshold is obtained; When the frequency gate occupied by the preliminary range gate sample is greater than the frequency gate threshold, the preliminary range gate sample is determined as the corresponding range gate sample to be detected.

2. The airborne radar wind turbine isolated point clutter suppression method according to claim 1, characterized in that: The suppressing wind turbine clutter according to the target range gate samples comprises: Performing a short-time Fourier transform on the echo signal of the wind turbine clutter to obtain an average interval between two adjacent flashing moments in the periodic flashing signal; obtaining a corresponding rotation period and rotation speed of the wind turbine based on the average interval; determining a first flashing moment in the periodic flashing signal according to the rotation period, and obtaining an initial rotation speed phase based on the first flashing moment; using the rotation speed and the initial rotation speed phase as initial atomic parameters; and constructing a corresponding overcomplete dictionary atomic representation based on the initial atomic parameters; According to the target range gate samples and the covariance distances between the multiple overcomplete dictionary atom representations, target atom parameters are determined; the corresponding overcomplete dictionary atom representations are updated using the target atom parameters to obtain target dictionary atom representations; according to the target dictionary atom representations, a target clutter suppression residual is obtained to suppress wind turbine clutter using the target clutter suppression residual.

3. The airborne radar wind turbine isolated point clutter suppression method according to claim 2, characterized in that: The expression of the overcomplete dictionary atom representation is: in, For fast time, t m For slow time, is the complex amplitude of wind turbine clutter, is the space-time steering vector; t m =mTr, m is the number of slow time sampling, Tr is the pulse repetition period; The complex amplitude of the wind turbine clutter is expressed as: Where, the number of azimuth sub-arrays is N, λ is the wavelength of the wind turbine clutter, j is a complex unit, α is the azimuth angle of the carrier relative to the X-axis, and R w is the wind turbine slant pitch, l n represents the length of the nth blade of the wind turbine, θ n (t) represents the initial phase angle of the nth blade, and the initial phase angle θ of the nth blade n (t) = θ0 + 2πf rot t, θ0 is the initial speed phase of the blade at time t, f rot is the blade speed at time t; The expression of the space-time steering vector is: Among them, f sil represents the spatial frequency, represents the normalized Doppler frequency, represents the time-domain steering vector, S s (f sil ) represents the spatial steering vector, Express With S s (f sil ) of the Kronecker product; The expression of the time domain steering vector is: Where fr is the pulse repetition frequency, V R is the carrier speed, the number of coherent processing pulses is K, For wind turbines Unit vector of direction; The expression of the spatial steering vector is: Wherein, d is the array element spacing vector of the airborne radar.

4. The airborne radar wind turbine isolated point clutter suppression method according to claim 2, characterized in that: Determining target atom parameters according to the target range gate samples and the covariance distances between the multiple overcomplete dictionary atom representations; using the target atom parameters to update the corresponding overcomplete dictionary atom representation to obtain the target dictionary atom representation; According to the target dictionary atomic representation, the target clutter suppression residual is obtained including: Taking the target range gate sample and the corresponding overcomplete dictionary atom representation as initial samples; constructing a training set, wherein the training set includes a plurality of initial samples; Based on the target range gate sample in the initial sample, the first transposed value and the number of initial samples in the training set, a covariance distance matrix is ​​obtained; the product of the target range gate sample, the first transposed value and the covariance distance matrix is ​​determined as the test statistic of the initial sample; wherein the first transposed value is the transposed value of the target range gate sample; Sorting the initial samples in the training set in ascending order of the test statistic, and determining the initial sample in the sorted training set whose test statistic is the median as the reference sample; The training set is processed using the reference samples to determine the target clutter suppression residual.

5. The airborne radar wind turbine isolated point clutter suppression method according to claim 4, characterized in that: The using the reference sample to process the training set to determine the target clutter suppression residual comprises: For the overcomplete dictionary atomic representation of each initial sample in the training set, a corresponding training orthogonal projection operator is determined; the product of the target range gate sample and the corresponding training orthogonal projection operator is determined as the training orthogonal projection of the target range gate sample on its own sample space; the difference between the target range gate sample and the training orthogonal projection is determined as the training clutter suppression residual; and the Mahalanobis distance between the training clutter suppression residual and the reference sample is determined; Determine the minimum value of all Mahalanobis distances corresponding to the training set; determine the initial atomic parameters corresponding to the minimum value as the target atomic parameters; Based on the target atom parameter, construct a target dictionary atom representation; determine the product of the target dictionary atom representation and the second transposed value as an intermediate matrix; determine the product of the target dictionary atom representation, the inverse matrix of the intermediate matrix and the second transposed value as a target projection operator; wherein the second transposed value is the transposed value of the target dictionary atom representation; The product of the target range gate sample and the corresponding target orthogonal projection operator is determined as the target orthogonal projection of the target range gate sample on its own sample space; and the difference between the target range gate sample and the target orthogonal projection is determined as the target clutter suppression residual corresponding to the target range gate sample.

6. The airborne radar wind turbine isolated point clutter suppression method according to claim 1, characterized in that: The determining of the residual clutter according to the target range gate samples and performing space-time segment adaptive processing on the residual clutter to suppress the residual clutter comprises: Determine the area except the target range gate sample in the range Doppler spectrum as the residual clutter area; divide the residual clutter area into a non-stationary clutter area and a stationary clutter area; wherein the distance distribution range of the non-stationary clutter area is between one times the carrier distance and five times the carrier distance, and the distance distribution range of the stationary clutter area is the area in the residual clutter area except the non-stationary clutter area; Performing signal dimensionality reduction processing on the range Doppler unit in the non-stationary clutter area in the Doppler domain to obtain a space-time three-dimensional weight vector of the range Doppler unit; performing three-dimensional space-time adaptive processing on the non-stationary clutter and performing two-dimensional space-time adaptive processing on the stationary clutter to suppress the non-stationary clutter and the stationary clutter; The expression of the space-time three-dimensional weight vector is: is the Doppler unit data to be detected after dimension reduction, is the training range Doppler unit data after dimension reduction, T k represents the Doppler domain dimension reduction matrix, L s is the number of training samples, is the space-time three-dimensional covariance matrix corresponding to the k-th range Doppler unit to be detected after dimensionality reduction, is the reduced-dimensional space-time steering vector of the kth Doppler channel, S k is the three-dimensional steering vector, S t Time domain steering vector, S t =[1,e j2πk / K ,…,e j2π(K-1)k / K ] T , S a is the azimuth-dimensional steering vector, S e is the pitch-dimensional steering vector, f a is the azimuthal spatial frequency, f e is the pitch spatial frequency.

7. The airborne radar wind turbine isolated point clutter suppression method according to claim 1, characterized in that: Determining the noise estimation values ​​on both sides of the range gate sample to be detected, and determining the threshold value according to the noise estimation values ​​on both sides; Comparing the signal power of the to-be-detected range gate sample with the corresponding threshold value to obtain at least one target range gate sample of the wind turbine clutter comprises: According to the number of protection units, the number of reference units and the power at the main clutter of the range gate to be detected in the range Doppler spectrum, the two-side noise estimation value is obtained; wherein the two-side noise estimation value includes a first noise estimation value and a second noise estimation value; Determine the minimum value of the first noise estimation value and the second noise estimation value as the target noise estimation value; determine the target warning coefficient according to the false alarm probability and the detection probability; determine the product of the target warning coefficient and the target noise estimation value as the corresponding threshold value; When the signal power of the to-be-detected range gate sample is greater than the corresponding threshold value, the to-be-detected range gate sample is determined as a target range gate sample.

8. An airborne radar wind turbine isolated point clutter suppression device, characterized in that: The airborne radar wind turbine isolated point clutter suppression device comprises at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions executable by the at least one processor, and after being executed by the processor, the instructions are used to implement the airborne radar wind turbine isolated point clutter suppression method according to any one of claims 1 to 7.

9. A non-volatile computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors to implement the airborne radar wind turbine isolated point clutter suppression method according to any one of claims 1-7.

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