CN102721967A - Method for discovering target in air based on disturbance type of wind field - Google Patents
Method for discovering target in air based on disturbance type of wind field Download PDFInfo
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Abstract
The invention relates to a method for discovering a target in air based on the disturbance type of a wind field. The method sequentially comprises the following steps: performing statistical modeling against a background atmosphere wind field of an air space with the need of important protection, and utilizing laser radar to scan in an uninterrupted manner to complete the real-time detection of the disturbing atmosphere wind field in the air space; judging whether the disturbance type of the wind field is of disturbance of the target wind field of the type of a trailing vortex disturbance field of an aircraft or the disturbance of the natural wind field; if the disturbance type is of the disturbance of the target wind field, determining that the moving target is discovered in the air space and the moving target is of the aircraft; and otherwise, determining that no aircraft target exists in the air space. According to the method disclosed by the invention, the detection of the disturbance of the atmosphere wind field is realized, the difficult problem of determining the disturbance of the atmosphere wind field is solved, and the large-range, long-distance and high-efficiency aircraft target fast discovery in the specific air space is achieved.
Description
Technical Field
The invention relates to the technical field of target detection, in particular to an aerial target discovery method based on wind field disturbance types.
Background
The target of the aerial airplane generates the disturbance information which can not be hidden, namely the disturbance of the wake vortex wind field, to the atmospheric wind field when moving, the disturbance intensity is about dozens of meters per second, the duration time is dozens of seconds or even hundreds of seconds, the longitudinal extension distance can reach more than ten kilometers, and the transverse diffusion diameter reaches more than one hundred meters. Because the wind field disturbance scale is far larger than that of the target body, and the detectability characteristic of the disturbance is also far stronger than that of the target body, compared with the direct scanning detection of the target body, the wind field disturbance detection method is more convenient and effective in detecting the wind field disturbance, and can more quickly find the target in a larger range. In addition, the laser radar can detect and acquire wind field disturbance information in a remote and high-precision manner by performing uninterrupted scanning on the atmospheric wind field in the airspace. At present, no technology exists for indirectly realizing the rapid discovery of the airplane target in the airspace by detecting the wind field disturbance in the airspace through laser.
Disclosure of Invention
The invention aims to provide an air target discovery method based on a wind field disturbance type, which can realize the quick detection of air aircraft targets with large range, long distance and high efficiency in a specific airspace.
In order to achieve the purpose, the invention adopts the following technical scheme: an air target discovery method based on a wind field disturbance type comprises the following steps in sequence:
(1) acquiring disturbance information of a wind field: carrying out statistical modeling aiming at a background atmospheric wind field of an airspace needing important protection, and finishing real-time detection of the disturbance atmospheric wind field in the airspace by utilizing the uninterrupted scanning of a laser radar;
(2) identifying the disturbance type of the wind field: judging whether the type of the wind field disturbance is a target wind field disturbance such as an aircraft tail vortex disturbance field or a natural wind field disturbance;
(3) detecting a found aerial target: if the disturbance is the disturbance of the target wind field, the moving target can be found in the airspace and is an airplane; otherwise, judging that no airplane target exists in the airspace.
According to the technical scheme, the method can obtain the wind field disturbance data distribution in the air through modeling of the aircraft wake vortex and processing of the laser anemometry radar data, and realize disturbance detection of the atmospheric wind field; by aiming at the characteristic analysis of the aircraft wake vortex, a corresponding criterion algorithm and criterion are established, the atmospheric wind field disturbance types are distinguished, whether the disturbance belongs to natural wind field disturbance or artificial disturbance is judged, and the difficulty in distinguishing the atmospheric wind field disturbance is solved; by processing detection parameters such as vortex structure characteristics of wind field disturbance, the aerial target is rapidly detected and found, and the problem of rapidly finding the large-range, long-distance and high-efficiency aircraft target in a specific airspace is solved.
Drawings
FIG. 1 is a schematic diagram showing the relationship between radial velocity and tangential velocity in a wake vortex laser transverse detection mode;
FIG. 2 is wake vortex echo Doppler spectrum simulation data of airbus A-340;
FIG. 3 is wake vortex echo Doppler spectrum simulation data for a B-2 aircraft;
FIG. 4 is a flow chart of wind field disturbance echo data preprocessing;
FIG. 5 is a flow chart of a wind field disturbance discrimination algorithm based on Doppler spectrum characteristics;
FIG. 6 is a diagram showing the coordinate relationship between radial velocity and tangential velocity.
Detailed Description
An air target discovery method based on a wind field disturbance type comprises the following steps in sequence:
(1) acquiring disturbance information of a wind field: carrying out statistical modeling aiming at a background atmospheric wind field of an airspace needing important protection, and finishing real-time detection of the disturbance atmospheric wind field in the airspace by utilizing the uninterrupted scanning of a laser radar;
(2) identifying the disturbance type of the wind field: distinguishing the type of wind field disturbance based on a wind field disturbance identification algorithm or a judgment criterion of Doppler spectrum characteristics, and judging whether the type of the wind field disturbance is target wind field disturbance such as an aircraft tail vortex disturbance field or natural wind field disturbance;
(3) detecting a found aerial target: if the disturbance is the disturbance of the target wind field, the moving target can be found in the airspace and is an airplane; otherwise, judging that no airplane target exists in the airspace
The present invention will be further described below.
In order to construct a wake vortex echo Doppler spectrum model, the Doppler velocity (radial velocity) distribution rule of the wake vortex can be determined. Here, the radial velocity distribution characteristics of the wake vortex in the laser transverse detection mode (RHI scanning mode) are analyzed in combination with a tangential velocity distribution model of the aircraft wake vortex.
In fig. 1, a target airplane flies in the forward direction along the X-axis, and a ground-based lidar scans a pair of wake vortexes generated by left and right wings of the airplane in flight in the YZ plane in a sector mode. Suppose the centers of the vortex cores of the left and right wake vortexes are O respectively1And O2And a radial distance from the laser radar of RO1And RO2The scanning elevation angle is alphaO1And alphaO2. If any point O on the right wing wake vortex is selected as a research object, the radial distance of the point O relative to the laser radar is ROThe scanning elevation angle is alphaOAnd the wake vortex has a tangential velocity V perpendicular to the radial direction of the vortex core at that pointT(r) its projection in the lidar scanning direction is the radial velocity V at that pointR(r, θ), where r represents the distance of the point O from the vortex core center O2Theta is the angle between the radial direction of the point on the wake vortex cross section and the positive direction of the Y axis. By analyzing the angle relation among various velocities in the graph, the tangential velocity V at the O point on the section of the wake vortexT(r) and radial velocity VRThe angle between (r) gamma can be expressed as
γ＝3π/2+αO-θ （1）
Thus, the radial velocity V of the wake vortex at any point OR(r) and tangential velocity VT(r) is
VR(r,θ)＝VT(r)cosγ
＝VT(r)cos(3π/2+αO-θ) （2）
＝VT(r)sin(αO-θ)
Based on Hallock-Burnham wake vortex tangential velocity model, radial velocity distribution on wake vortex transverse section can be obtained
Therefore, the same radial velocity V on the transverse section of the wake vortex can be reversely deducedREquation of the curve of (r, theta)
By solving the quadratic equation of one unit, the relation between r and theta can be obtained
Or
The above equations (5) and (6) are the equal radial velocity distribution curve equation of the wake vortex in the wake vortex disturbance field laser transverse detection mode, wherein the value range of theta is
Wherein k is 0,1,2, … n, and n is a positive integer.
In addition, at a point [ r ] on the wake vortex cross sectionc,αO-π/2-2kπ]At a radial velocity which will take a maximum value
At the same time, at the point [ r ] on the wake vortex sectionc,αO-3π/2-2kπ]At a radial velocity which is taken to a minimum
Because the Doppler spectrum is the result of the combined action of the target motion law and the target geometry, the constant radial velocity curve of the wake vortex can be completely regarded as a description of the radial velocity distribution characteristics of the wake vortex by the laser radar. Therefore, the wake vortex echo doppler spectrum can be constructed by the following method.
Calculating the radial velocity VRArea of circle segment enclosed by curve, i.e. radial velocity V > VRCan be expressed as
The equi-radial velocity distribution curve equations (5) and (6) based on the wake vortex can be slightly transformed into the following two formulas
And
in order to research the influence relationship of airplane model parameters, flight parameters and environment parameters on the wake vortex echo Doppler spectrum, the above equations (11) and (12) can be simplified through approximate processing. Analysis shows that r (V) in the formulaR) And swirl ring quantity gamma0And the radius r of the vortex corecAre closely related. But based on the formula Γ0Mg/ρ VsB and rcA comparison of 0.052sB reveals again that the vortex core radius rcSmall compared to the aircraft span B, and a swirl ring quantity Γ0Is greatly affected by the span B, so r can be approximately considered in the above formulacWhen the values are equal to 0, the equations (11) and (12) can be simplified to 0
Thus, the radial velocity V > VRCan be expressed as
In the formula, alphaOCan be regarded as a known constant, and the curved surface area A can be obtained by further integral operation
In addition, the combined radial velocity curve diagram of the wake vortex can show that the Doppler spectrum of the wake vortex echo can be expressed as follows
If the radial velocity resolution is assumed to be sufficiently small (i.e. the size of the interval Δ V between two adjacent radial velocities)R→ 0), the doppler spectrum of the wake vortex echo can be regarded as radial velocity V > VRDifferential of enclosed curved surface area A
The analysis formula (17) shows that the Doppler spectrum amplitude of the wake vortex echo is in inverse proportion to the third power of the radial velocity and is in inverse proportion to the vortex ring vector gamma0Is related to the square ofIs described. The larger the amount of eddy current ring, the larger the aircraft wake vortex will cause the laser echo to produce a significant doppler spectrum, i.e. Γ0The larger the velocity variance.
Based on radial velocity VRAnd Doppler shift Δ fDThe relation between Δ fD＝2VR/λ0Further, the Doppler frequency spectrum of the wake vortex echo can be obtained
In addition, in order to more intuitively reflect the dependency relationship between the wake vortex echo Doppler spectrum and airplane model parameters, flight parameters and environment parameters, the vortex ring quantity gamma is determined0Mg/ρ VsB and S ═ pi/4 are substituted in formula (17), and the doppler spectrum S (V) of the wake vortex echo is then obtainedR) Can also be expressed as another form
The environmental parameters rho and g are air density and gravity acceleration respectively, the model parameters M, B are the weight and the wingspan of the airplane respectively, the flight parameter V represents the speed of the airplane, and the relationship between the Doppler spectrum of the airplane wake vortex echo and the model parameters, the flight parameters and the environmental parameters is close to the Doppler spectrum of the airplane wake vortex echo obviously seen from the above formula.
In summary, the expressions (17), (18) and (19) are mathematical doppler spectrum models of the aircraft wake vortex echo under the laser transverse detection method, which are constructed based on theoretical analysis derivation in this section.
Based on the wake vortex echo Doppler spectrum mathematical models (17), (18) and (19) deduced and constructed based on the theory, the respective wake vortex echo Doppler spectra are simulated and drawn by taking airbus A-340 and B-2 under typical flight conditions as examples, as shown in FIGS. 2 and 3.
Fig. 2 and 3 show that, compared with atmospheric turbulence or high wind shear, the echo doppler spectrum of the aircraft wake vortex is mainly characterized by the following aspects:
1) symmetry: due to the high symmetry of the tangential velocity distribution of the wake vortex, the echo Doppler spectrum of the wake vortex has a symmetric characteristic (the positive Doppler velocity region and the negative Doppler velocity region are symmetrically distributed by taking zero velocity as the center). In contrast, sudden natural wind field disturbances such as turbulence or wind shear may cause the echo doppler spectrum distribution to be asymmetric due to the irregular distribution of the velocity.
2) Broadening property: if a wake vortex disturbance field condition with a certain scale is considered, the scattering of incident laser is mainly shown as the superposition effect of aerosol particles and atmospheric molecules at each point in a wake vortex cross section. Therefore, the echo Doppler spectrum of the Doppler laser has the characteristic of spectral broadening, and a plurality of broadened time-varying spectral lines are provided. The extended spectrum structure of the multispectral line is beneficial to detecting wake vortex echoes from a fixed clutter background. Furthermore, it was found by model analysis that the swirl ring quantity Γ0Larger aircraft wake vortexes result in a more pronounced doppler spectrum width produced by the laser echo.
3) Amplitude characteristics: wake vortex echo Doppler spectrum amplitude S (V)R) And radial velocity VR(Doppler shift Deltaf)D) Is inversely proportional to the swirl ring quantity gamma0Is proportional to the square of the plane and is influenced by the model parameters (weight M, span B), flight parameters (velocity V) and environmental parameters (air density ρ, gravitational acceleration g) of the aircraft. The amplitude digital characteristic is unique to the wake vortex echo Doppler spectrum, is caused by the tangential velocity distribution of the wake vortex, and is the most important characteristic for distinguishing the wake vortex from turbulence or wind shear and the like.
The invention adopts a wind field disturbance identification algorithm based on Doppler spectrum characteristics to distinguish the type of wind field disturbance, and the wind field disturbance identification algorithm based on Doppler spectrum characteristics mainly comprises the following three processes: preprocessing wind field disturbance echo data, extracting Doppler spectrum characteristics and identifying wind field disturbance types, as shown in FIG. 5.
(1) Preprocessing wind field disturbance echo data: in order to eliminate echo signal noise and extract more complete and real-time characteristic information, the original echo signal needs to be preprocessed first. Here, the preprocessing is to obtain a doppler spectrum point sequence waveform f ═ (f) by performing three processing steps, such as noise reduction processing, FFT processing, and normalization processing, on the wind field disturbance echo data0,f1,…,fN-1)。
(2) Doppler spectrum feature extraction: compared with sudden natural wind field disturbance such as turbulence, wind shear and the like, the Doppler spectrum of target wind field disturbance such as airplane wake vortex and the like mainly has symmetry characteristics, waveform entropy characteristics and amplitude digital characteristics. Therefore, the wind field disturbance doppler spectrum point train waveform obtained based on the echo data preprocessing is (f ═ f0,f1,…,fN-1) Symmetry characteristics (even margin R), waveform entropy characteristics (waveform entropy E) and amplitude digital characteristics (logarithmic margin L) of the Doppler spectrum can be extracted.
(3) Identifying disturbance types of a wind field: on the basis of wind field disturbance echo data preprocessing and Doppler spectrum feature extraction, the type attribute of the wind field disturbance Doppler spectrum can be judged from three aspects of symmetry features, waveform entropy features and amplitude digital features. If the three characteristics simultaneously satisfy the judgment condition, the Doppler spectrum belongs to the aircraft wake vortex, namely the detected and obtained wind field disturbance is the target wind field disturbance; on the contrary, the wind field disturbance is natural wind field disturbance such as turbulence, wind shear and the like.
As shown in fig. 4, in order to eliminate the influence of noise and dc component mixed in the echo signal during transmission and detection, the original echo signal needs to be preprocessed. The high-fidelity preprocessing technology is necessary preparation before feature extraction, so that extracted feature information is more complete and real-time, and the preprocessing technology plays an important role particularly in high-resolution radar detection such as laser radar. The wind field disturbance echo data preprocessing process comprises the following steps: noise reduction processing, FFT processing and normalization processing.
(1) And (3) noise reduction treatment: the signal-to-noise ratio of the laser radar atmosphere echo signal is low, so that echo information must be processed. The method adopts Empirical Mode Decomposition (EMD), and the EMD can effectively extract the trend of a data sequence and remove high-frequency noise in the data sequence, so that the signal-to-noise ratio can be improved and the interference of some thin clouds in the echo can be inhibited by adopting the EMD method for the laser radar echo signal.
(2) FFT processing: and performing Fast Fourier Transform (FFT) on the wind field echo signals in each group of distance units to obtain Doppler spectrums of the wind field echo signals, and superposing the Doppler spectrums of each distance unit to obtain the echo Doppler spectrum of the whole wind field.
(3) Normalization treatment: performing amplitude normalization processing on the Doppler spectrum to obtain a Doppler spectrum point sequence waveform f (f) with a zero frequency shift point as a center0,f1,…,fN-1). Wherein the first N/2 points of the Doppler spectrum point array are defined as a negative frequency region f-＝(f0,f1,…,fN/2-1) The last N/2 points of the point array are defined as positive frequency region f+＝(fN/2,fN/2+1，…,fN-1)。
For the doppler spectrum feature extraction, many factors should be considered for feature selection, and the following basic principles should be adhered to: firstly, the target information contained in the characteristics is as much as possible; secondly, the characteristics are independent or unrelated; thirdly, the dimension of the features should be as small and simple as possible. Therefore, the symmetry characteristic, the waveform entropy characteristic and the amplitude digital characteristic of the Doppler spectrum are mainly extracted by combining the characteristic of the wake vortex Doppler spectrum obtained by modeling analysis.
(1) The symmetry characteristic is as follows: because the Doppler spectrum of the aircraft wake vortex echo is an even function taking a zero frequency shift point (the radial velocity is zero) as a symmetry axis, the Doppler spectrum of natural wind field disturbance such as turbulence, wind shear and the like is asymmetric due to the irregularity of the Doppler spectrum. Thus, the symmetry of the Doppler spectrum distribution can be an important feature for distinguishing the wind field disturbance types.
Here, the even margin R is selected to describe the symmetry characteristic of the doppler spectrum distribution, and if the symmetry of the spectrum distribution is stronger, the value of the even margin R is smaller; conversely, the larger the value, and can be expressed as
In the formula (f)i(i-0, 1, …, N-1) is a doppler spectrum point sequence waveform.
Accordingly, the following wind field disturbance type judgment conditions can be set by combining the symmetry characteristics of Doppler spectrum distribution
Wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting a natural wind field disturbance. RthIs a constant decision threshold, the value of which is preset.
(2) Waveform entropy characteristics: the aircraft wake vortex echo Doppler spectrum has a plurality of broadened time-varying spectral lines and has the characteristic of broadening, and Doppler spectra disturbed by natural wind fields such as turbulence, wind shear and the like do not have the spread spectrum structure of the multispectral lines. Therefore, the wind field disturbance type can be distinguished by utilizing the spectrum spreading characteristic.
In view of the fact that entropy is often used in information theory to measure the centralized distribution degree of posterior probability distribution, if a wind field disturbance echo Doppler spectrum is regarded as a probability density function, the size of the entropy value can reflect the expansion degree of the Doppler spectrum, and the larger the entropy value is, the wider the Doppler spectrum is; conversely, the narrower the Doppler spectrum.
Wherein, the waveform entropy of the wind field disturbance echo Doppler spectrum can be defined as follows
In the formula, piIs a Doppler spectrum signal expressed by a probability density function and can be expressed as
Accordingly, the following wind field disturbance type judgment conditions can be set by combining the waveform entropy characteristics of the Doppler spectrum
Wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting a natural wind field disturbance. EthThe decision threshold is a constant decision threshold, the value of which is generally preset and can be determined by modeling simulation and an external field experiment in practical application.
(3) Amplitude numerical characteristics: the amplitude of the wake vortex echo doppler spectrum is inversely proportional to the third power of the radial velocity (doppler shift). The amplitude digital characteristic is unique to the wake vortex Doppler spectrum and is the most key characteristic for distinguishing the wake vortex from natural wind field disturbance such as turbulence or wind shear.
Here, to express the numerical characteristic (inverse third power relation) of Doppler spectrum magnitude, a logarithmic margin L is introduced, which can be expressed as
In the formula (f)iIs a signal of a positive frequency region of a Doppler spectrum, YiTo shift frequency fiThe corresponding radial velocity, C, is a constant and can be calculated from equations (26), (27), respectively.
Yi＝λ0fi/2 （26）
C＝ln(Γ0 2/8π) （27）
When the wind field disturbance echo Doppler spectrum amplitude has the more obvious third power inverse ratio characteristic, the more the logarithmic margin L value tends to be 0; on the contrary, if the doppler spectrum amplitude does not satisfy the feature of inverse third power, the value of the logarithmic margin L should be far from 0. Therefore, the logarithmic margin L can better describe the digital characteristic of the inverse third power of the Doppler spectrum amplitude.
Accordingly, the following wind field disturbance type judgment conditions can be set by combining the amplitude digital characteristics of the Doppler spectrum
Wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting a natural wind field disturbance. L isthIs a constant decision threshold, the value of which can be set directly by a doppler spectrum mathematical model.
Therefore, symmetry characteristics, waveform entropy characteristics and amplitude digital characteristics can be extracted from the wake vortex echo Doppler spectrum, and sudden natural wind field disturbance echo Doppler spectrums of atmospheric turbulence, high-altitude wind shear and the like do not have the characteristics.
The method can also distinguish the type of the wind field disturbance according to a judgment criterion, including a wind field disturbance judgment criterion based on vortex structure characteristics and a wind field disturbance judgment criterion based on a speed structure coefficient.
As shown in fig. 6, the wake vortex field disturbance generated when the airborne target such as an airplane moves is mainly composed of two cylindrical vortexes rotating in opposite directions, and the two cylindrical vortexes are two spiral rotating structures which are symmetrical to each other and have the same strength and opposite rotation directions when viewed from a rolling section. For such features of the vortex structure, the parameter of the vorticity H can be generally chosen for quantitative representation.
However, the laser detection of the disturbance of the wake vortex field is performed in a transverse detection mode, and the laser radar can only acquire the radial velocity V of atmospheric molecules or aerosol particles at each point of the wake vortex along the laser beamRAnd cannot directly acquire the tangential velocity V thereofT. Therefore, how to base on the radial velocity V at each point of the wake vortexRThe corresponding tangential velocity V is obtained by inversionTAnd by a tangential velocity VTAnd further calculating the vorticity H of the wake vortex, which is the key for extracting the vortex structure characteristics of the wake vortex. The invention calculates the vorticity H of the wake vortex by the following method.
In fig. 6, the Y axis in the rectangular coordinate system is the cross-sectional horizontal direction, the Z axis is the cross-sectional vertical direction, r in the polar coordinate system represents the distance between the wake vortex cross-sectional point and the vortex core center O, and θ is the included angle between the radial direction of the point and the negative direction of the Y axis. The continuity equation in the polar coordinate system (r, θ) is
And at any point (gamma, theta) in the cross sectionAndcan be approximately expressed as
And
where Δ r is the radial distance between two range gates, i denotes the number of range gates, and k denotes the number of elevation angles. Therefore, the formula (29) can be simplified to
To avoid aliasing, a filter parameter S (usually, S is 0.2-0.33) is introduced, and the formula (32) can be expressed as
Thus, the vorticity H in the polar coordinate system can be calculated by
In which at point (. gamma.,. theta.)
And
the calculation can be made with reference to the central finite element difference method of equation (30).
Therefore, the structural characteristics of natural wind field disturbance such as common high-altitude atmospheric wind field sudden change (such as discrete gust and high-altitude wind shear) are single, and the vortex structural characteristics specific to the tail vortex wind field disturbance of moving targets such as airplanes are not provided. The structural difference of the two types of wind field disturbance provides possibility for distinguishing the wind field disturbance types from the structural characteristic angle.
Therefore, based on the vortex structure characteristics, the following wind field disturbance judgment criterion can be set
Wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting a natural wind field disturbance. HthThe decision threshold is a constant decision threshold, the value of which is generally preset and can be determined by modeling simulation of aircraft wake vortexes and external field detection experiments in practical application.
The wind field disturbance types are distinguished through the vortex structure characteristics, so that the wind field disturbance can be judged to be target wind field disturbance such as airplane wake vortex or natural wind field disturbance such as atmospheric turbulence and high altitude wind shear simply, conveniently and quickly.
According to the designed wind field disturbance judgment criterion based on vortex structure characteristics, the type of wind field disturbance in the airspace can be judged, and therefore whether an airplane target exists in the airspace or not can be found. If the target wind field disturbance is the target wind field disturbance, the moving target can be considered to be found in the airspace and is an airplane; otherwise, it can be determined that no airplane target exists in the airspace.
The wind field disturbance decision criterion based on the velocity structure coefficient is presented below.
When the laser radar detects an atmospheric wind field, because the scattering of atmospheric suspended particles along the laser detection direction is mutually independent, and the output signal of the heterodyne optical receiver of the laser radar is in direct proportion to the scattering intensity, the photocurrent power spectrum generated by the scattered particles is the superposition of the single power spectrum generated by the single particles. Furthermore, because the doppler frequency is directly proportional to the scattering particle velocity vector projection, the spectral density can be seen as a function of velocity.
Based on the specific relationship between the square average of the integration of the spectral width of the photo-current and the velocity field of the wind, a structural coefficient of the velocity of the wind field can be introduced as follows
Wherein,
and V (r, t) is a radial wind speed value at the time r of t, and W (r, t) is a function representing the heterodyne efficiency of the laser radar and the power distribution in a detection beam and depends on the parameters of the laser radar only.
In view of the observation experiment of a large number of aircraft wake vortex wind field disturbances and natural wind field disturbances carried out abroad, the results show that the wind field disturbances taking the aircraft wake vortex as the main target are very similar to the natural wind field disturbances beginning with atmospheric turbulence and high altitude wind shear in certain parameters by comparing the characteristic parameters of the wind field disturbance scale, speed and the like, but other parameters are obviously different and change along with the flight path of the aircraft and the surrounding atmospheric conditions. In particular, the above-mentioned wind field structural coefficient can be used as an important quantitative decision criterion in an external field observation experiment to distinguish whether the observed wind field disturbance is a target wind field disturbance such as aircraft wake vortex or a natural wind field disturbance of atmospheric turbulence or high altitude wind shear.
If it is provided with
Representing the velocity structure coefficient of the background atmospheric wind field under calm weather conditions,
representing the speed structural coefficient of the disturbed atmospheric wind field acquired by the real-time detection of the laser radar, and making T represent the ratio of the two
Accordingly, the following wind field disturbance judgment criterion based on the speed structure coefficient can be set
Wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting a natural wind field disturbance. T isthThe constant judgment threshold value is a constant judgment threshold value, the value of the constant judgment threshold value is preset and is changed along with the specific conditions of detection places, distances, angles and background atmospheric disturbance, and the constant judgment threshold value can be determined by modeling simulation, external field detection experiments and background knowledge accumulation in practical application, and can be generally 102~103。
The existing experimental research shows that: if the sudden natural wind field disturbance grade under the condition of calm climate is selectedWhen expressed, the value is approximately 0.005m4/3/s2To 0.1m4/3/s2A range; and the speed structure coefficient of the wind field disturbance caused by the wake vortex of the aircraft after flying
The value range of (2 m)4/3/s2To 6m4/3/2The comparison between the two is two to three orders of magnitude different. Therefore, it is entirely possible to base the speed structure coefficientThe disturbance attribute of the wind field is distinguished simply, conveniently and quickly, and an important criterion is provided for detecting and finding low-in-air detectability targets.
According to the designed wind field disturbance judgment criterion based on the speed structure coefficient, the type of wind field disturbance in the airspace can be judged, and therefore whether the aircraft target exists in the airspace or not can be found.
Claims (9)
1. An air target discovery method based on a wind field disturbance type comprises the following steps in sequence:
(1) acquiring disturbance information of a wind field: carrying out statistical modeling aiming at a background atmospheric wind field of an airspace needing important protection, and finishing real-time detection of the disturbance atmospheric wind field in the airspace by utilizing the uninterrupted scanning of a laser radar;
(2) identifying the disturbance type of the wind field: judging whether the type of the wind field disturbance is a target wind field disturbance such as an aircraft tail vortex disturbance field or a natural wind field disturbance;
(3) detecting a found aerial target: if the disturbance is the disturbance of the target wind field, the moving target can be found in the airspace and is an airplane; otherwise, judging that no airplane target exists in the airspace.
2. The wind farm disturbance type-based aerial target discovery method according to claim 1, wherein: a Doppler spectrum mathematical model of the aircraft wake vortex echo is constructed in a laser transverse detection mode, and the formula is as follows:
based on radial velocity VRAnd Doppler shift Δ fDThe relation between Δ fD＝2VR/λ0And then furtherDoppler spectrum of wake vortex echo can be obtained
The eddy current ring volume is gamma0In formula (17) where Mg/ρ VsB and S ═ pi/4 are substituted, doppler spectrum S (V) of wake vortex echoR) Can also be expressed as
The environmental parameters ρ and g are air density and gravitational acceleration, the model parameters M, B are weight and wingspan of the aircraft, and the flight parameter V represents the speed of the aircraft.
3. The wind farm disturbance type-based aerial target discovery method according to claim 1, wherein: and distinguishing the type of the wind field disturbance based on a wind field disturbance identification algorithm or a judgment criterion of the Doppler spectrum characteristics.
4. The wind farm disturbance type-based aerial target discovery method according to claim 3, wherein: the wind field disturbance identification algorithm based on the Doppler spectrum characteristics comprises the following three steps: preprocessing wind field disturbance echo data, extracting Doppler spectrum characteristics and identifying wind field disturbance types.
5. The wind farm disturbance type-based aerial target discovery method according to claim 3, wherein: based on the vortex structure characteristics, the wind field disturbance judgment criterion is set as follows:
wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting disturbances of the natural wind field, HthIs a constant decision threshold.
6. The wind farm disturbance type-based aerial target discovery method according to claim 3, wherein: based on the speed structure coefficient, the wind field disturbance judgment criterion is set as follows:
wherein W represents the type of wind field disturbance, WtargetRepresenting disturbance of the target wind field, WnatureRepresenting disturbances of the natural wind field, TthIs a constant decision threshold.
7. The wind farm disturbance type-based aerial target discovery method according to claim 4, wherein: the wind field disturbance echo data preprocessing comprises three steps of noise reduction processing, FFT processing and normalization processing, wherein,
the noise reduction processing is to process the laser radar echo signal by adopting an EMD (empirical mode decomposition) method;
the FFT processing is that the wind field echo signals in each group of distance units are subjected to Fast Fourier Transform (FFT) to obtain Doppler spectrums of the wind field echo signals, and the Doppler spectrums of the distance units are superposed to obtain the echo Doppler spectrums of the whole wind field;
the normalization process is to perform amplitude normalization process on the Doppler spectrum to obtain a Doppler spectrum point sequence waveform f (f) with a zero frequency shift point as a center0,f1,…,fN-1) Wherein the first N/2 points of the Doppler spectrum point array are defined as a negative frequency region f-＝(f0,f1,…,fN/2-1) The last N/2 points of the point array are defined as positive frequency region f+＝(fN/2,fN/2+1，…,fN-1)。
8. The wind farm disturbance type-based aerial target discovery method according to claim 7, wherein: wind field disturbance Doppler spectrum point sequence waveform obtained based on wind field disturbance echo data preprocessing (f ═ f-0,f1,…,fN-1) And extracting the symmetry characteristic (even margin R), the waveform entropy characteristic (waveform entropy E) and the amplitude digital characteristic (logarithmic margin L) of the Doppler spectrum.
9. The wind farm disturbance type-based aerial target discovery method according to claim 8, wherein: if the symmetry characteristic, the waveform entropy characteristic and the amplitude digital characteristic simultaneously meet the judgment condition, the Doppler spectrum is determined to belong to the aircraft wake vortex, namely the detected and obtained wind field disturbance is the target wind field disturbance; otherwise, the wind field disturbance is the natural wind field disturbance.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104076350A (en) * | 2014-07-08 | 2014-10-01 | 西安电子科技大学 | Method for detecting floating targets on sea based on normalized Doppler spectrum |
| WO2014120296A3 (en) * | 2013-01-15 | 2014-10-23 | Raytheon Company | Ladar backtracking of wake turbulence trailing an airborne target for point-of-origin estimation and target classification |
| CN107782288A (en) * | 2017-09-22 | 2018-03-09 | 北京空间机电研究所 | The method of atmospheric perturbation formula optical monitoring aircraft based on background schlieren imaging |
| US9995277B2 (en) | 2014-07-31 | 2018-06-12 | General Electric Company | System and method for controlling the operation of wind turbines |
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| CN110118965A (en) * | 2019-04-01 | 2019-08-13 | 贵州航天电子科技有限公司 | A kind of radio is to lost motion target acquisition characteristic field trial device |
| JP2020008536A (en) * | 2018-07-12 | 2020-01-16 | 日本無線株式会社 | Target detection device and target detection program |
| CN110992399A (en) * | 2019-11-11 | 2020-04-10 | 北京空间机电研究所 | A high-precision target atmospheric disturbance detection method |
| CN111736172A (en) * | 2020-08-24 | 2020-10-02 | 中国人民解放军国防科技大学 | An aerial target detection method based on atmospheric disturbance coherent laser detection |
| CN113433555A (en) * | 2021-08-27 | 2021-09-24 | 中国人民解放军国防科技大学 | Laser heterodyne detection autonomous searching method for moving target in air |
| CN115372988A (en) * | 2022-10-18 | 2022-11-22 | 青岛镭测创芯科技有限公司 | Method, device and medium for identifying and positioning aircraft wake vortexes |
| CN116500580A (en) * | 2023-06-28 | 2023-07-28 | 中国民航大学 | Vortex core parameter calculation method and system based on Doppler radar detection |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101268384A (en) * | 2005-07-21 | 2008-09-17 | 空中客车德国有限公司 | Method and lidar system for measuring air turbulence on board an aircraft and also for airports and wind power plants |
| EP2212717A2 (en) * | 2007-10-09 | 2010-08-04 | Danmarks Tekniske Universitet | Coherent lidar system based on a semiconductor laser and amplifier |
-
2012
- 2012-06-21 CN CN2012102084411A patent/CN102721967A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101268384A (en) * | 2005-07-21 | 2008-09-17 | 空中客车德国有限公司 | Method and lidar system for measuring air turbulence on board an aircraft and also for airports and wind power plants |
| EP2212717A2 (en) * | 2007-10-09 | 2010-08-04 | Danmarks Tekniske Universitet | Coherent lidar system based on a semiconductor laser and amplifier |
Non-Patent Citations (2)
| Title |
|---|
| 吴永华,胡以华,戴定川,徐世龙,李今明: "基于1.5m多普勒激光雷达的飞机尾涡探测技术研究", 《光子学报》 * |
| 徐世龙，胡以华，吴永华: "基于多普勒谱特征的飞机尾涡识别", 《光电子·激光》 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014120296A3 (en) * | 2013-01-15 | 2014-10-23 | Raytheon Company | Ladar backtracking of wake turbulence trailing an airborne target for point-of-origin estimation and target classification |
| US8939081B1 (en) | 2013-01-15 | 2015-01-27 | Raytheon Company | Ladar backtracking of wake turbulence trailing an airborne target for point-of-origin estimation and target classification |
| CN104919335A (en) * | 2013-01-15 | 2015-09-16 | 雷斯昂公司 | Ladar backtracking of wake turbulence trailing an airborne target for point-of-origin estimation and target classification |
| CN104919335B (en) * | 2013-01-15 | 2016-11-16 | 雷斯昂公司 | For recalling the method and system of the track of aerial target |
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| CN110118965A (en) * | 2019-04-01 | 2019-08-13 | 贵州航天电子科技有限公司 | A kind of radio is to lost motion target acquisition characteristic field trial device |
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