CN109307860B - Foil cloud identification method based on micro-motion characteristics - Google Patents
Foil cloud identification method based on micro-motion characteristics Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/415—Identification of targets based on measurements of movement associated with the target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/414—Discriminating targets with respect to background clutter
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Abstract
The invention discloses a foil cloud identification method based on micro-motion characteristics, and relates to the technical field of radar systems. The foil strip micro-motion characteristic analysis method and the foil strip micro-motion characteristic analysis system have the advantages that the distance image sequence, the time-frequency graph and the distance-instantaneous Doppler image sequence are respectively adopted for micro-motion characteristic analysis, the video graph is added on the basis of existing one-dimensional distance image identification and two-dimensional distance-Doppler identification, foil strip cloud echo signals are researched in a three-dimensional characteristic space, foil strip scattering characteristics are reviewed from a wider visual angle, extraction of foil strip scattering characteristics is facilitated, and extraction of micro-time, micro-distance and micro-Doppler characteristics of micro-motion of foil strips is facilitated. The method can be applied to engineering, and foil cloud can be identified no matter the detection target is naval vessels, cities, aircraft carriers and military places.
Description
Technical Field
The application relates to the technical field of radar systems, in particular to a foil cloud identification method based on micro-motion characteristics.
Background
The existing main foil strip identification methods comprise: distance-Doppler domain two-dimensional joint identification, guidance of multi-mode composite search, Doppler identification, wavelet analysis, MTI/MTD and polarization identification. The identification method is as follows:
a) and (3) distance-Doppler domain two-dimensional joint identification, namely transmitting a coherent pulse train and performing Doppler analysis by using the coherence of echo signals. One of the most common methods is to transmit coherent LFM pulse trains, which has the advantage of high-resolution nuclear doppler resolution, and usually, the coherent LFM pulse trains are accumulated by passing the pulse-compressed target echoes directly through an FFT filter bank to implement matched filtering of echoes of different doppler frequencies.
b) Guidance of multi-mode compound search: the method is characterized in that in the whole attack process, multiple modes of different electromagnetic waves are adopted and connected in series or in parallel, optimal target data information is comprehensively obtained according to a plurality of sensors, and a guidance task is jointly completed. They are roughly classified into three categories, photoelectric composite, optical wave composite, and electric wave composite. The method has the advantages that the method can identify the camouflage and the deception of the target, can effectively resist the interference of the foil strips and the false target, but also has the problems of high overall complexity, high design cost, poor technical maturity and the like of the system.
c) Doppler identification: the method is realized by adopting an FFT or FIR filter bank based on the Doppler frequency difference caused by the foil strip cloud echo and the speed difference of a target relative to a detector. The amount of doppler shift due to such motion echoes may occur in some filters in the narrow band filter bank, and the detection threshold of each filter may be selected according to the intensity of the noise and foil cloud echoes contained in the filter. This makes it possible to protect the target signal, which may be present in other filters, from interference by the foil strip echoes. The method has the defects of complex algorithm, large calculation amount and inflexibility.
d) Wavelet analysis: the method is that the mixed echo signal containing foil clutter is preprocessed, then multi-scale decomposition is carried out by utilizing wavelet change, the wavelet coefficient on each scale is denoised, namely the wavelet coefficient belonging to noise is removed as much as possible, the part belonging to a target signal is enhanced, finally the signal is reconstructed by wavelet inverse transformation and is changed into a denoised signal, the target and the foil clutter are separated as much as possible, the target echo signal is reserved, and the foil interference signal is inhibited.
e) MTI/MTD: the processing basis of this method is that the amplitude and phase of the echo obtained by repeatedly measuring a fixed target are the same. Thus, the stationary target echoes will cancel completely when one continuous pulse is subtracted from another, while the moving target echoes will not cancel completely, producing a doppler residual. Conventional MTI radars typically use a delay line canceller to implement a high pass filter to eliminate fixed targets; compared with the MTI radar of a modern point, the corresponding function is realized by adopting a digital method. Generally, echo pulses of foil strip clouds with unequal amplitude, high shielding strength, compound interference and the like are reduced so as to destroy the working effect of the radar MTI.
f) Polarization identification: and receiving the scattered echo containing the actual geometrical structure information of the target by adopting a certain receiving and transmitting polarization mode, further extracting the characteristics of an echo signal, and fully exploiting the difference of polarization state information between the fake target foil strip and the target echo, thereby inhibiting the foil strip echo information to the maximum extent, improving the signal-to-noise ratio and obtaining the ideal target identification effect. Such methods stay in the theoretical stage and have a great gap from use.
In general, the foil strip identification method described above is not suitable for use in proximity detector height measurement scenarios for two reasons.
On one hand, due to the difference of detection targets, methods such as Doppler identification, range-Doppler domain two-dimensional joint identification and the like are no longer effective in a short-range detector height measurement scene. For example, distance-doppler domain two-dimensional joint identification is an effective method for identifying a foil cloud and a ship target in a ship end guidance scene, and realizes the distinction of a dot target such as a ship and a foil two-dimensional extended planar target by using the distribution difference of an echo signal of the ship target and a foil cloud reflection echo on a time-frequency domain, the principle of which is shown in fig. 1, fig. 1 is that the doppler extension of a foil is obviously larger than that of the ship as can be seen from a distance-doppler two-dimensional image of actual measurement data of a certain ship and a foil cluster, the energy distribution of the distance-doppler two-dimensional image of the foil is relatively uniform, and the time-frequency unit area occupied by the two-dimensional image is relatively large; the energy of the two-dimensional image of the ship target is mainly concentrated on a plurality of strong scattering points, and the time-frequency unit area occupied by the two-dimensional image is small.
However, in the short-range detector height measurement scene, the detection targets are cities, aircraft carriers and military places, and the echoes of the detection targets have similar time-frequency domain two-dimensional expansion characteristics with foil strip cloud echo signals. In this scenario, the distance-doppler domain two-dimensional joint identification of the foil strip cloud presents difficulties. For another example, in a scene of hitting an aerial target, the doppler recognition method is a main means for recognizing a foil cloud, and realizes the distinction of a target echo and a foil cloud echo signal by using a doppler filter bank through the difference of the speed of the target and the foil cloud, and the principle is shown in fig. 2, and fig. 2 is a foil interference resistance test result based on doppler recognition. a) The original data time domain waveform of 33 moments for a certain foil strip interference resisting test cannot distinguish a target echo from a foil strip echo. b) For the Doppler domain processing result, the target echo and the foil strip echo fall in different Doppler frequency bands. The reason is that the foil strips must move slowly to keep longer air-leaving time, while the moving speed of air targets such as airplanes and missiles is fast, and the difference of Doppler frequency shift between the two is obvious. However, in the short-range detector height measurement scenario, the doppler identification method is no longer effective because the detected object and the foil cloud have little difference in velocity.
On the other hand, technologies effective on radar, such as polarization angle identification and multi-domain joint identification, are transplanted to a short-range detector height measurement scene, and are constrained by a plurality of engineering boundary conditions. Taking polarization angle identification as an example, a fully polarized antenna, a multi-channel microwave front end and expanded signal processing capability need to be added in engineering implementation. However, the resources that can be invoked by proximity detectors are limited compared to large radar systems, and there is little possibility of implementation under existing engineering boundary conditions.
In summary, the foil cloud formed by the foil bomb has the physical characteristics of large bandwidth, high density and strong reflection, so that the false alarm rate and the false alarm rate of the short-range detector are easily increased in a height measurement scene, and the existing foil cloud identification method is not applicable.
Disclosure of Invention
In order to overcome the defects and shortcomings in the prior art, the foil cloud identification method based on the micro-motion characteristics is provided, the distance image sequence, the time-frequency image and the distance-instantaneous Doppler image sequence are respectively adopted for micro-motion characteristic analysis, a video image is added on the basis of the existing one-dimensional distance image identification and two-dimensional distance-Doppler identification, a foil cloud echo signal is researched in a three-dimensional characteristic space, the foil scattering characteristics are reviewed from a wider visual angle, the extraction of the foil scattering characteristics is facilitated, and the extraction of the micro-time, micro-distance and micro-Doppler characteristics of the micro-motion of the foil is facilitated. The method can be applied to engineering, and foil cloud can be identified no matter the detection target is naval vessels, cities, aircraft carriers and military places.
In order to solve the problems existing in the prior art, the method is realized by the following technical scheme:
a foil strip cloud identification method based on micro-motion characteristics is characterized by comprising the following steps: carrying out translation compensation on the output target dynamic echo data, and obtaining a range profile sequence after the translation compensation; respectively processing the range profile sequence subjected to the translational compensation by a range profile, a time-frequency graph and a range Doppler image to obtain a foil strip state; and contrasting and drawing the distance image time sequence, the time-frequency graph and the distance Doppler image time sequence according to the time relationship, analyzing the state of the target according to the characteristics of the image, marking three states that the included angle beta between the symmetric axis of the target and the sight line of the radar is in a maximum value, a minimum value and a middle value at corresponding time points, and obtaining the micro-motion characteristic of the foil strip by quantitatively inspecting the rotation period index.
The translation compensation specifically refers to the compensation of the overall translation motion of the target, and is the basis of a subsequent algorithm. The method assumes that the complex envelope between adjacent one-dimensional range profiles of the target does not change much within a certain accumulation time, and can be aligned in the range direction by using a cross-correlation method. The method comprises the following specific steps: firstly, obtaining a one-dimensional range profile of a target through pulse compression according to dynamic echo data of the target; secondly, carrying out envelope alignment of adjacent range profiles, wherein the alignment error is less than half of a range resolution unit; thirdly, in order to further compensate the high-frequency phase shift caused by the distance alignment error, the distance image is interpolated, and the residual phase difference value is estimated; finally, phase alignment is completed.
The specific steps of performing time-frequency image processing on the distance image sequence after the translation compensation are as follows: firstly, carrying out inverse Fourier transform on a single range profile along fast time to obtain frequency domain data; secondly, selecting a frequency point to obtain a target single-frequency response changing along with time; thirdly, performing short-time Fourier transform on n, n and M pulses in sequence to obtain an instantaneous Doppler image at the nth pulse moment; and finally, obtaining frequency domain data by traversing and arranging all instantaneous Doppler images according to time.
The specific steps of processing the distance Doppler image of the compensated range profile sequence are as follows: firstly, carrying out Fourier transform on a range profile sequence along slow time to obtain 1 range-instantaneous Doppler image; secondly, carrying out Fourier transform on n, n and M pulses in sequence to obtain an nth range-instantaneous Doppler image; finally, through traversal, multiple range-instantaneous Doppler images over slow time are obtained.
Compared with the prior art, the beneficial technical effects brought by the application are shown in that:
1. the method and the device respectively adopt the range profile sequence, the time-frequency diagram and the range-instantaneous Doppler image sequence to carry out micromotion characteristic analysis. Firstly, because the centroid movement of the foil strips can lead the range image sequence to incline, the Doppler value and the range-instantaneous Doppler image to shift, the translational compensation is firstly carried out before the micromotion characteristic analysis, and then the range image sequence after the translational compensation is respectively processed by the range image, the time-frequency image and the range Doppler image to obtain the state of the foil strips.
2. The time-frequency diagram reflects Doppler change processes of different scattering centers on the foil strip, and the time-frequency diagram of the micro-motion foil strip has the periodic characteristic and is the same as the micro-motion period of the foil strip. When the included angle beta between the radar sight line and the foil strip symmetry axis reaches an extreme value, the radial speed of each scattering center after translational compensation is 0, and all curves on the time-frequency diagram are overlapped. Therefore, the time-frequency diagram provides an intuitive means for the micromotion state analysis. In addition, because the equivalent sight line rotating speed of the foil strips is not uniform, the transverse accumulation time of the Doppler images cannot be too long, otherwise, the speed images are blurred due to overlarge rotating speed change in the accumulation time. In the present application, the equivalent line-of-sight rotation speed of the doppler image in a short time can be approximately regarded as constant.
3. The distance-instantaneous Doppler image can simultaneously reflect the distance and the Doppler velocity of each scattering center on the foil strip, and is also an important means for analyzing the micromotion characteristics. However, although the range-instantaneous doppler image has rich information, the understanding is not intuitive and even misunderstanding may be caused if it is simply interpreted as an ISAR image. This is because in range-doppler images the ordinate is the range, which coincides with the radial distribution of the scattering center, and the abscissa is the doppler, which reflects the rate of change of the radial position of the scattering center. For a target rotating at a constant speed, the change rate of the radial position of the scattering center is in direct proportion to the transverse position of the target, so that the range-doppler image can be understood as an ISAR image after being calibrated. The equivalent visual line rotating speed of the precession target is not uniform, and the calibration sizes of all images are different, so that the distance-instantaneous Doppler image sequence cannot intuitively correspond to the change of the foil strip posture. More specifically, when the included angle beta between the foil strip symmetry axis and the radar sight line is at an extreme value, the equivalent sight line rotating speed is 0, and the scattering centers of the targets in the distance-instantaneous Doppler image are all located on a zero Doppler line; before and after the angle β reaches and exceeds the extreme value, the foil strips are in the same attitude with respect to the radar line of sight but move in opposite directions, so their range-instantaneous doppler images will be symmetrical about the zero doppler line. In addition, because the equivalent sight line rotating speed of the foil strips is not uniform, the transverse accumulation time of the distance-instantaneous Doppler image cannot be too long, otherwise, the image blurring can be caused by too large rotating speed change in the accumulation time. In the application, the equivalent visual line rotating speed of the range-instantaneous Doppler image can be approximately considered to be unchanged in a short time, so that the focusing effect of the range-instantaneous Doppler image is better.
4. The method comprises the steps of obtaining micro time, micro frequency and micro distance of a foil cloud from data such as a high-resolution range profile (HRRP) time sequence, a Doppler time sequence and a distance-instantaneous Doppler profile (ISAR) time sequence, and according to research on the corresponding relation between the micro motion features of the foil cloud and the change rule of echo signals, extracting the micro motion features of the foil cloud. Traditional foil strip identification, such as the range-doppler identification technique closest to the present technique, is a study conducted in the two-dimensional signal domain, which can be viewed as projections of the range-doppler-time three-dimensional feature space on different axes. The technology is characterized in that a video image is added on the basis of existing one-dimensional range profile identification and two-dimensional range-Doppler identification, foil cloud echo signals are researched in a three-dimensional characteristic space, foil scattering characteristics are reviewed from a wider visual angle, extraction of the foil scattering characteristics is facilitated, and extraction of micro-time, micro-range and micro-Doppler characteristics of micro-motion of the foil is facilitated. The technology can be applied to engineering, and foil cloud can be identified no matter the detection target is a naval vessel, a city, an aircraft carrier and a military place.
Drawings
FIG. 1 is a distance-Doppler two-dimensional image of measured data of a ship and a foil strip cluster;
FIG. 2 is a flow chart of the translation compensation algorithm of the present application;
FIG. 3 is a flowchart of a rotation period estimation algorithm based on a range profile sequence according to the present application;
FIG. 4 is a flow chart of time-frequency diagram rendering according to the present application;
FIG. 5 is a flow chart of a range-Doppler image rendering process of the present application;
FIG. 6 is a dynamic echo micro-motion characteristic analysis of a foil strip at an included angle β of 45 °;
fig. 7 is a dynamic echo micromotion characteristic analysis of the foil strip at an included angle β of 90 °.
Detailed Description
Example 1
Referring to fig. 1-6 of the specification, this embodiment discloses:
a foil strip cloud identification method based on micro-motion characteristics is characterized by comprising the following steps: carrying out translation compensation on the output target dynamic echo data, and obtaining a range profile sequence after the translation compensation; respectively processing the range profile sequence subjected to the translational compensation by a range profile, a time-frequency graph and a range Doppler image to obtain a foil strip state; and contrasting and drawing the distance image time sequence, the time-frequency graph and the distance Doppler image time sequence according to the time relationship, analyzing the state of the target according to the characteristics of the image, marking three states that the included angle beta between the symmetric axis of the target and the sight line of the radar is in a maximum value, a minimum value and a middle value at corresponding time points, and obtaining the micro-motion characteristic of the foil strip by quantitatively inspecting the rotation period index.
Example 2
As another preferred embodiment of the present application, the present embodiment discloses:
the method and the device respectively adopt the range profile sequence, the time-frequency diagram and the range-instantaneous Doppler image sequence to carry out micromotion characteristic analysis. The processing flow is as shown in fig. 2, firstly, because the centroid motion of the foil strip can make the range image sequence generate inclination, the doppler value and the range-instantaneous doppler image generate offset, the translational compensation is firstly carried out before the micromotion characteristic analysis, and then the range image sequence after the translational compensation is respectively processed by the range image, the time-frequency image and the range-doppler image to obtain the state of the foil strip. A flowchart of a rotation period estimation algorithm based on a range profile sequence is shown in fig. 3.
As shown in FIG. 4, the time-frequency diagram reflects the Doppler change history of different scattering centers on the foil, and the time-frequency diagram of the micro-motion foil shows a periodic characteristic and has the same micro-motion period as the foil. When the included angle beta between the radar sight line and the foil strip symmetry axis reaches an extreme value, the radial speed (after translational compensation) of each scattering center is 0, and all curves on the time-frequency diagram are overlapped. Therefore, the time-frequency diagram provides an intuitive means for the micromotion state analysis. In addition, because the equivalent sight line rotating speed of the foil strips is not uniform, the transverse accumulation time of the Doppler images cannot be too long, otherwise, the speed images are blurred due to overlarge rotating speed change in the accumulation time. In the following flow chart, we consider that the equivalent line-of-sight rotational speed can be approximately regarded as constant in a short time.
As shown in FIG. 5, the range-instantaneous Doppler image can reflect the range and Doppler velocity of each scattering center on the foil strip at the same time, and is also an important means for analyzing the micromotion characteristics. However, although the range-instantaneous doppler image has rich information, the understanding is not intuitive and even misunderstanding may be caused if it is simply interpreted as an ISAR image. This is because in range-doppler images the ordinate is the range, which coincides with the radial distribution of the scattering center, and the abscissa is the doppler, which reflects the rate of change of the radial position of the scattering center. For a target rotating at a constant speed, the change rate of the radial position of the scattering center is in direct proportion to the transverse position of the target, so that the range-doppler image can be understood as an ISAR image after being calibrated. The equivalent visual line rotating speed of the precession target is not uniform, and the calibration sizes of all images are different, so that the distance-instantaneous Doppler image sequence cannot intuitively correspond to the change of the foil strip posture. More specifically, when the included angle beta between the foil strip symmetry axis and the radar sight line is at an extreme value, the equivalent sight line rotating speed is 0, and the scattering centers of the targets in the distance-instantaneous Doppler image are all located on a zero Doppler line; before and after the angle β reaches and exceeds the extreme value, the foil strips are in the same attitude with respect to the radar line of sight but move in opposite directions, so their range-instantaneous doppler images will be symmetrical about the zero doppler line.
In addition, because the equivalent sight line rotating speed of the foil strips is not uniform, the transverse accumulation time of the distance-instantaneous Doppler image cannot be too long, otherwise, the image blurring can be caused by too large rotating speed change in the accumulation time. In the following flow chart, it is considered that the equivalent line-of-sight rotation speed can be approximately considered to be constant in a short time, and therefore the focusing effect of the range-instantaneous doppler image is better.
And contrasting and drawing the range image time sequence, the time-frequency graph and the range Doppler image time sequence according to the time relationship, analyzing the state of the target according to the characteristics of the image, and marking four states that the included angle beta between the symmetric axis of the target and the sight line of the radar is at a maximum value, a minimum value and a middle value on corresponding time points. And verifying the reflecting degree of the dynamic echo signals to the micro-motion characteristics. The main indicators that can be quantitatively examined are the rotation period.
As shown in fig. 6 and 7, fig. 6 and 7 take echo signals of the foil strip at different angles as an example, and examine a range profile, a time-frequency diagram, and a range-doppler image of the echo signals of the foil strip to estimate the state of the foil strip. In addition, it can be seen from all three figures that the target inching period is about 1000 pulses (PRT 83us), which coincides with the set rotation period of 83 ms.
Example 3
As another preferred embodiment of the present application, the present embodiment discloses:
a foil cloud identification method based on micro-motion characteristics comprises the steps of performing translation compensation on output target dynamic echo data, and obtaining a range profile sequence after the translation compensation; respectively processing the range profile sequence subjected to the translational compensation by a range profile, a time-frequency graph and a range Doppler image to obtain a foil strip state; and contrasting and drawing the distance image time sequence, the time-frequency graph and the distance Doppler image time sequence according to the time relationship, analyzing the state of the target according to the characteristics of the image, marking three states that the included angle beta between the symmetric axis of the target and the sight line of the radar is in a maximum value, a minimum value and a middle value at corresponding time points, and obtaining the micro-motion characteristic of the foil strip by quantitatively inspecting the rotation period index.
The translation compensation specifically refers to the compensation of the overall translation motion of the target, and is the basis of a subsequent algorithm. The method assumes that the complex envelope between adjacent one-dimensional range profiles of the target does not change much within a certain accumulation time, and can be aligned in the range direction by using a cross-correlation method. The method comprises the following specific steps: firstly, obtaining a one-dimensional range profile of a target through pulse compression according to dynamic echo data of the target; secondly, carrying out envelope alignment of adjacent range profiles, wherein the alignment error is less than half of a range resolution unit; thirdly, in order to further compensate the high-frequency phase shift caused by the distance alignment error, the distance image is interpolated, and the residual phase difference value is estimated; finally, phase alignment is completed.
The specific steps of performing time-frequency image processing on the distance image sequence after the translation compensation are as follows: firstly, carrying out inverse Fourier transform on a single range profile along fast time to obtain frequency domain data; secondly, selecting a frequency point to obtain a target single-frequency response changing along with time; thirdly, performing short-time Fourier transform on n, n and M pulses in sequence to obtain an instantaneous Doppler image at the nth pulse moment; and finally, obtaining frequency domain data by traversing and arranging all instantaneous Doppler images according to time.
The specific steps of processing the distance Doppler image of the compensated range profile sequence are as follows: firstly, carrying out Fourier transform on a range profile sequence along slow time to obtain 1 range-instantaneous Doppler image; secondly, carrying out Fourier transform on n, n and M pulses in sequence to obtain an nth range-instantaneous Doppler image; finally, through traversal, multiple range-instantaneous Doppler images over slow time are obtained.
Claims (4)
1. A foil strip cloud identification method based on micro-motion characteristics is characterized by comprising the following steps: carrying out translation compensation on the output target dynamic echo data, and obtaining a range profile sequence after the translation compensation; respectively processing the range profile sequence subjected to the translational compensation by a range profile, a time-frequency graph and a range Doppler image to obtain a foil strip state; and contrasting and drawing the distance image time sequence, the time-frequency graph and the distance Doppler image time sequence according to the time relationship, analyzing the state of the target according to the characteristics of the image, marking three states that the included angle beta between the symmetric axis of the target and the sight line of the radar is in a maximum value, a minimum value and a middle value at corresponding time points, and obtaining the micro-motion characteristic of the foil strip by quantitatively inspecting the rotation period index.
2. The method for identifying the cloud of the foil strips based on the micro-motion characteristics as claimed in claim 1, wherein: the translation compensation specifically means compensation for the whole translation motion of the target, and the method specifically comprises the following steps: firstly, obtaining a one-dimensional range profile of a target through pulse compression according to dynamic echo data of the target; secondly, carrying out envelope alignment of adjacent range profiles, wherein the alignment error is less than half of a range resolution unit; thirdly, in order to further compensate the high-frequency phase shift caused by the distance alignment error, the distance image is interpolated, and the residual phase difference value is estimated; finally, phase alignment is completed.
3. The method for identifying the cloud of the foil strips based on the micro-motion characteristics as claimed in claim 1, wherein: the specific steps of performing time-frequency image processing on the distance image sequence after the translation compensation are as follows: firstly, carrying out inverse Fourier transform on a single range profile along fast time to obtain frequency domain data; secondly, selecting a frequency point to obtain a target single-frequency response changing along with time; thirdly, performing short-time Fourier transform on n, n and M pulses in sequence to obtain an instantaneous Doppler image at the nth pulse moment; and finally, obtaining frequency domain data by traversing and arranging all instantaneous Doppler images according to time.
4. The method for identifying the cloud of the foil strips based on the micro-motion characteristics as claimed in claim 1, wherein: the specific steps of processing the distance Doppler image of the compensated range profile sequence are as follows: firstly, carrying out Fourier transform on a range profile sequence along slow time to obtain 1 range-instantaneous Doppler image; secondly, carrying out Fourier transform on n, n and M pulses in sequence to obtain an nth range-instantaneous Doppler image; finally, through traversal, multiple range-instantaneous Doppler images over slow time are obtained.
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| CN115079103A (en) * | 2022-06-16 | 2022-09-20 | 北京理工大学 | Multi-domain feature and LightGBM-based foil strip interference resisting method |
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