CN113985404B - High-resolution runway foreign object detection system and phase drift correction method thereof - Google Patents
High-resolution runway foreign object detection system and phase drift correction method thereof Download PDFInfo
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Abstract
The invention discloses a high-resolution runway foreign object detection system and a phase drift correction method thereof, wherein the method comprises the following steps: observing the runway through an AS-SAR system, and generating a high-resolution image to carry out SPD modeling; processing the complex image acquired by the AS-SAR system to form a complex image sequence with a fixed length, and carrying out classification processing after feature extraction; estimating SPD of the obtained SPCP based on the SPD model to obtain an SPD estimation value; the phase of the current complex image is subtracted from the estimated SPD value to realize SPD correction of the image, and the AS-SAR complex image with high resolution after phase correction is output; the detection system is an AS-SAR system in the phase drift correction method; the invention obtains a high-resolution AS-SAR complex image after phase correction; the phase drift can be effectively inhibited, the stable target phase can be obtained, and a foundation is laid for subsequent SNR enhancement and target identification.
Description
Technical Field
The invention relates to the technical field of airport safety protection, in particular to a high-resolution runway foreign object detection system and a phase drift correction method thereof.
Background
Foreign Object Debris (FOD) includes foreign objects that may damage airplanes and equipment or threaten the safety of ground passengers in active areas such as airport personnel and airport runways. In recent years, with the rapid development of civil aviation industry in the world, it has been found that from time to time, FOD can puncture tires and damage airplanes, not only causing greater economic loss to airlines, but also presenting greater risks to flight safety and personnel safety. Therefore, research on FOD detection devices is urgent and receives increasing attention. At present, FOD detection equipment mainly comprises photoelectric detection equipment and radar detection equipment. The photoelectric detection equipment is low in installation and maintenance cost, the detection performance is continuously improved along with the development of an image processing technology, and the recognition rate is gradually improved. However, such improvements are limited by low light conditions such as nighttime, and are also susceptible to rain, snow and other extreme weather conditions. The radar detection equipment has the characteristics of high detection rate, high positioning accuracy, high reliability, full-day working, strong environmental adaptability and the like, and is the key point of the current research. However, the current radar detection equipment adopts a real-aperture working mode, and has the problems of low direction finding precision, difficult identification, high false alarm rate and the like.
Synthetic Aperture Radar (SAR) has high-resolution earth observation capability, can realize high-precision detection of a small ground target, and has great potential in the aspect of FOD target detection. An Arc-scanning synthetic aperture radar (AS-SAR) is a special SAR with an Arc aperture and has 360-degree omnibearing observation capability. The application of the FOD detection method in airport runways has natural advantages: the system antenna has small volume, light weight and low integral use cost; secondly, the system realizes extremely high imaging resolution through an algorithm, and is favorable for detecting small targets; thirdly, the system has lower requirements on the rotation precision of the platform and can keep higher target direction finding and distance measuring precision; and fourthly, the target information is richer, the target identification is facilitated, and the false alarm is reduced. At present, the university of the south of Hunan professor, the information technology Limited company of the gigahertz of the south of Hunan, and the like begin to utilize AS-SAR to detect FOD targets, and the basic flow of the detection is signal acquisition, imaging, coherent accumulation, detection, identification, and the like.
On the basis of meeting the requirement of Federal Communications Commission (FCC), in order to reduce atmospheric attenuation, effectively utilize an atmospheric window and better detect an FOD target with the size of about 1cm, the AS-SAR operating frequency is 94 GHz, and the operating wavelength is only 3.2 mm. Atmospheric phase perturbations may be caused by changes in the electromagnetic signal propagation path due to atmospheric scattering. And when the target is far away from the radar, phase disturbance caused by atmospheric changes such as temperature and humidity is more obvious. In general, the shorter the transmission signal wavelength, the more significant the atmospheric phase perturbation will be. Meanwhile, phase drift also exists in system hardware under different temperature conditions. The phase stability of the target is the basis for improving the signal-to-noise ratio by coherent accumulation and is an important characteristic of the background of target identification. Therefore, the phase drift affects the results of coherent accumulation, identification and the like in the system detection process. The present invention addresses this problem with phase drift correction. For ease of analysis, all of these phase drifts are collectively referred to as System Phase Drift (SPD).
Disclosure of Invention
The invention aims to provide a high-resolution runway foreign object detection system and a phase drift correction method thereof, and solves the problems that the existing runway foreign object detection system is easily influenced by the outside, so that the direction finding precision is low, the identification is difficult, the false alarm rate is high and the like.
The invention is realized in such a way that the phase drift correction method of the high-resolution runway foreign object detection system firstly models the SPD, then screens Stable Phase Control Points (SPCP), and then estimates the SPD through the SPCP, thereby realizing SPD correction.
The further technical scheme of the invention is as follows: modeling and estimating SPD:
Considering that the SPD is perturbed by the system itself and the atmospheric phase, Δ φ may be expressed as:
whereinIndicating the phase induced by the system itself,which represents the phase induced by the atmosphere,representing the noise phase. In general terms, the amount of the solvent to be used,is constant. It is known that the temperature and humidity of the atmosphere vary with time, resulting in non-uniformity of electromagnetic properties, causing the propagation speed and direction of electromagnetic waves to vary continuously as they pass through the atmosphere. When the atmosphere changes independently along with the distance direction and the azimuth direction, a binary linear function model of the SPD can be established:
whereinIs the wavelength of the carrier frequency and,is the ground range from the target to the radar,is the angle between the target and the initial scan direction of the radar.Are weighting coefficients.
As can be seen from equation (12), as long as three stable strong scattering points with high signal-to-noise ratio (SNR) are found, an equation set can be established by the phase shift thereof, and a weighting coefficient can be obtained by solving the equation set. The stable high signal-to-noise ratio strong scattering point is referred to herein as SPCP. In fact, it is possible to use,we can obtain a number of SPCPs much greater than 3. Therefore, the weighting coefficients will be estimated using the least squares method. LetThe equation can be expressed as a matrix as follows
For multiple SPCP points, the equation can be expressed in a matrix
Using a least squares algorithm, one can obtain
Due to the time continuity of the SPD caused by temperature and humidity changes, the estimated SPD may be filtered by a kalman filter. Establishing a state transition matrix, such as the formula:
whereinIs a gaussian noise that is a function of the noise,is a state transition matrix. The observation equation is determined as:
according to actual measurement, corresponding toOf the variance matrixIs 4, correspond toOf the variance matrixIs 9. And. Time domain filtering of SPCP may then be implemented.
The further technical scheme of the invention is as follows: the SPCP screening method comprises the following steps: the selection of SPCP is very important in the SPD computation process. For amplitude images, we define three functions of screening SPCP: local image contrastAmplitude dispersionAnd correlation coefficient. The screening process flow of SPCP is shown in fig. 4.
Make the sequence image asWhereinIs the number of images.Representing pixel pointsImage of (2)An amplitude value. Then, the user can use the device to perform the operation,the definitions are as follows.
For theFirst of all, obtainEach pixel inNeighborhood image slice ofThen calculating the average valueAnd standard deviation ofThen calculate
For theWe calculate the average value of the amplitude of each pixel in the radar sequence imageAnd standard deviation ofThen, it is calculated using the following formula:
the larger the amplitude information, the more stable it is. Due to the fact thatThe method only uses amplitude information for measurement, and has the advantages of small calculated amount, convenient extraction and the like.
For theThe correlation coefficient of each pixel in the sequence image needs to be according to the following equationFormula calculation
The larger the correlation, the stronger the correlation.The neighborhood of the involved pixels has a large number of computations, but is functionally stable and immune to noise.
Each of the extracted features is formed into a vector,. Considering that the value of each component of the feature vector is not uniform, it has different effects on the linear classifier, and thus it is necessary to normalize it.
Here, the feature vector is normalized according to the mahalanobis distance principle. Since the covariance matrix is a real symmetric matrix, the unitary matrix can be diagonalized, so
WhereinIs a unitary matrix of the matrix,is the average of the sample feature vectors,is a transposition of the two-dimensional image,a covariance eigenvalue matrix. The normalized feature vectorComprises the following steps:
in the classification process, a linear classification decision criterion is established:
whereinAre weight coefficients, which can be trained using known calibration target feature vectors. The classification process is broadly applicable when the radar performance is stable and consistent, and the SNR is large and meets the monitoring conditions.
Finally, the SPCP within a certain distance range from the runway is selected through distance constraint, and the accuracy of SPD estimation is further improved.
The further technical scheme of the invention is as follows: the correction method comprises the following steps: fig. 1 shows a complete flow of a phase drift correction method for a high-resolution runway foreign object detection system. It consists of four stages:
SPD modeling: observing the runway through an AS-SAR system, generating a high-resolution image, and modeling the SPD;
screening of SPCP: this stage can be done in real time or offline. To prevent FOD targets from being screened as SPCP, it requires data of empty scenes. It processes the sequence magnitude image by feature extraction and classification and sends the obtained SPCP to the second stage.
Estimation of SPD: in the actual processing, the SPCP provided in the first stage is used and based on the SPD model, the SPD between two complex images is estimated in real time by using an LS algorithm. And finally, performing a Kalman filter according to the multi-frame SPD (greater than 2) to acquire the SPD for correction.
SPD correction: the prospective correction is achieved by subtracting the SPD estimate, and a phase corrected sequence complex image is generated and output.
A high-resolution runway foreign object detection system is an AS-SAR system in the phase drift correction method.
The invention has the beneficial effects that: the method adopts the AS-SAR system to detect the foreign matters on the runway, has high-resolution ground observation capability, and can realize high-precision detection of the ground surface micro target; meanwhile, through the steps of SPD modeling, SPCP screening, SPD estimation and SPD correction recorded in the invention, the phase drift of the system caused by the system and the external environment can be effectively corrected, and the AS-SAR complex image with high resolution after phase correction is obtained; meanwhile, the invention can effectively inhibit phase drift and stabilize the target phase; the invention can realize SPD correction of the target in the AS-SAR system image, obtain stable target phase and lay a foundation for subsequent SNR enhancement and target identification.
Wherein the system cost is fully considered when the SPD modelsThe body and the external environment are influenced by the phase, and the body and the external environment are uniformly corrected; meanwhile, due to the fact that the time continuity of the SPD is caused by temperature and humidity changes, the SPD is estimated to be filtered through a Kalman filter, and the accuracy is improved; during SPCP screening, the contrast characteristic of a local image based on SNR is adopted during SPCP screening, and three functions of screening SPCP are defined: local image contrastAmplitude dispersionAnd correlation coefficientThe three characteristics are used jointly, so that the selected SPCP point is more stable; in order to reduce the influence of the features on the linear classifier during SPCP screening, the feature vector is normalized by using a covariance matrix, so that the contribution degrees of the three extracted features are consistent; aiming at the shape characteristics of the runway area, the distance from the screened SPCP point to the runway is limited to be smaller than a specified value through distance constraint, and the SPD of the runway area can be estimated more accurately; and (3) by utilizing the continuity of time change such as temperature, humidity and the like, time domain Kalman filtering is adopted for the estimated SPD, so that the abnormal value of the SPD is filtered, and the continuity of the estimated SPD value is improved.
Drawings
FIG. 1 is a flow chart of a phase drift correction method for a high resolution runway foreign object detection system provided by the present invention;
FIG. 2 is a diagram of the AS-SAR imaging geometry model provided by the present invention;
FIG. 3 is a diagram of the result of AS-SAR imaging of a runway in an uncorrected state;
FIG. 4 is a flow chart of SPCP screening provided by the present invention;
FIG. 5 is an AS-SAR imaging of a cylindrical target provided by the present invention;
FIG. 6 is a graph of the phase change of the cylindrical target 1 in FIG. 5 according to the present invention;
FIG. 7 is a comparison graph of SNR after coherent accumulation of cylindrical objects before and after SPD correction in FIG. 5 according to the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
It should be noted that the structures, ratios, sizes, and the like shown in the drawings attached to the present specification are only used for matching the disclosure of the present specification, so as to be understood and read by those skilled in the art, and are not used to limit the conditions of the present invention, so that the present invention has no technical essence, and any structural modification, ratio relationship change, or size adjustment should still fall within the scope of the present invention without affecting the efficacy and the achievable purpose of the present invention. In addition, the terms "upper", "lower", "left", "right", "middle" and "one" used in the present specification are for clarity of description, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not to be construed as a scope of the present invention.
The first embodiment is as follows:
a high resolution runway foreign object detection system: the detection system is an AS-SAR system: the AS-SAR is that the phase center of an antenna forms a circular arc aperture by using the rotation of a rotating arm, and then a high resolution image is generated by using the synthetic aperture principle. The detection system structure base is used for installing, storing and protecting other parts and is also used for fixing the radar and enabling the radar to work smoothly; the power supply device consists of an AC-DC converter, a battery and the like and provides power for the operation of the whole system; the turntable adopts the combination of a high-speed servo motor and a speed reducing mechanism, realizes the low-speed and high-torque input of the actuating mechanism through mechanical transmission, avoids the interval of low-speed vibration of the motor, accurately controls the motion process, and ensures the accuracy of the rotating position and the smoothness of the trigger pulse frequency; conductive slip rings are a rotating electrical interface that utilize sliding contact and electromagnetic coupling of conductive parts to address the problem of transferring power and data signals from a stationary structure to a rotating structure during unlimited continuous rotation; the rotating arm is an aluminum alloy square tube arranged on the rotary table, is hollow and is used for installing a radar sensor subsystem component; and finally, the antenna seat is arranged at the front part of the rotating arm and consists of an aluminum alloy substrate, a pitch support and a glass fiber reinforced plastic antenna housing, and the pitch posture is adjustable.
In FOD detection, it is necessary to detect small size targets and to separate multiple small targets in very close proximity. Therefore, on the basis of ensuring that the AS-SAR has a high image resolution, it should also ensure that the system itself has a high distance resolution. Here, the system bandwidth B is 1 GHz. The range resolution of the system can then be calculated as:
when the system turntable speed is 360 deg./min, the step size of each pulse is 0.02 deg., so the system's azimuth resolution is as follows:
the system uses a frequency-modulated continuous wave (FMCW) signal, the radar signal being as follows:
whereinIs the carrier frequency of the carrier wave,is the duration of the scan and is,is a repetition period of the time period of the first,is used for adjusting the frequency of the frequency,is the time within the modulation period. The microwave is reflected by the target, and the received radar signal is:
where Δ t is the echo delay,. R is the distance between the target and the radar and a is the amplitude attenuation coefficient.
The system receiver mixes the received signal with a reference signal to obtain a demodulated Intermediate Frequency (IF) signal:
The AS-SAR antenna is arranged on a mechanical rotating arm with a fixed length, and the relative motion with a target can be realized through the rotating arm, so that Doppler information is obtained. The geometric model of AS-SAR imaging is shown in FIG. 2, where G is the surface plane; o is the center of the axis of rotation, FOD target TfIs positioned on the G plane; h is the radar height; ap is the phase center of the radar antenna; l is the length of the rotating arm (distance from Ap to the axis of rotation);is the angular velocity, fillet, of the turntableCorresponding to timeA radar antenna Ap of (a), whereinIs the time corresponding to the closest distance between the antenna Ap and the target;is the angle between the OTf line and the plane of rotation of the radar swivel arm. Assume that the distance from the center of the rotation axis O to the target Tf is R, and at timeThe distance from the antenna Ap to the target is。
It can be seen that there are three exponential terms, corresponding to range Phase, Residual Video Phase (RVP), and azimuth doppler Phase. Therefore, the process of AS-SAR imaging can be divided into three steps: firstly, distance dimension pulse compression is carried out, matched filtering is carried out in a fast time, deskew processing is realized, and the echo signal-to-noise ratio of the radar is improved; the RVP compensation operation is to align the deskewed echoes in distance; and thirdly, azimuth dimension compression can be realized through a frequency domain algorithm. Suppose the horizontal beamwidth of the antenna isFrequency band and rotational speed of the turntableAnd carrier frequency wavelengthIn connection with this, the two-dimensional frequency domain data can be calculated by the following equation:
a phase-matched filter can be designed:
then the matched filter output is
WhereinThe amplitude coefficient. To pairTwo-dimensional inverse Fourier transform is carried out to obtain a time domain SAR image with polar coordinates. Fig. 3 shows a graph of uncorrected imaging results of the AS-SAR on a runway.
Example two:
a phase drift correction method of a high-resolution runway foreign object detection system comprises the steps of firstly modeling SPDs, then screening Stable Phase Control Points (SPCPs), and then estimating the SPDs through the SPCPs to further realize SPD correction.
Modeling and estimating SPD:
Considering that the SPD is perturbed by the system itself and the atmospheric phase, Δ φ may be expressed as:
whereinIndicating the phase induced by the system itself,which represents the phase induced by the atmosphere,representing the noise phase. AIn general terms, it is preferred that,is constant. It is known that the temperature and humidity of the atmosphere vary with time, resulting in non-uniformity of electromagnetic properties, causing the propagation speed and direction of electromagnetic waves to vary continuously as they pass through the atmosphere. When the atmosphere changes independently along with the distance direction and the azimuth direction, a binary linear function model of the SPD can be established:
whereinIs the wavelength of the carrier frequency and,is the ground range from the target to the radar,is the angle between the target and the initial scan direction of the radar.Are weighting coefficients.
As can be seen from equation (12), as long as three stable strong scattering points with high signal-to-noise ratio (SNR) are found, an equation set can be established by the phase shift thereof, and a weighting coefficient can be obtained by solving the equation set. The stable high signal-to-noise ratio strong scattering point is referred to herein as SPCP. In fact, we can obtain much more SPCP than 3. Therefore, the weighting coefficients will be estimated using the least squares method. LetThe equation can be expressed as a matrix as follows
For multiple SPCP points, the equation can be expressed in a matrix
Using a least squares algorithm, one can obtain
Due to the time continuity of the SPD caused by temperature and humidity changes, the estimated SPD may be filtered by a kalman filter. Establishing a state transition matrix, such as the formula:
whereinIs a gaussian noise that is a function of the noise,is a state transition matrix. The observation equation is determined as:
according to actual measurement, corresponding toOf the variance matrixIs 4, correspond toOf the variance matrixIs 9. And,. Time domain filtering of SPCP may then be implemented.
The further technical scheme of the invention is as follows: the SPCP screening method comprises the following steps: the selection of SPCP is very important in the SPD computation process. For amplitude images, we define three functions of screening SPCP: local image contrastAmplitude dispersionAnd correlation coefficient. The screening process flow of SPCP is shown in fig. 4.
Make the sequence image asWhereinIs the number of images.Representing pixel pointsImage of (2)An amplitude value. Then, the user can use the device to perform the operation,the definitions are as follows.
For theFirst of all, obtainEach pixel inNeighborhood image slice ofThen calculating the average valueAnd standard deviation ofThen calculate
For theWe calculate the average value of the amplitude of each pixel in the radar sequence imageAnd standard deviation ofThen, it is calculated using the following formula:
the larger the amplitude information, the more stable it is. Due to the fact thatThe method only uses amplitude information for measurement, and has the advantages of small calculated amount, convenient extraction and the like.
For theThe correlation coefficient of each pixel in the sequence image needs to be calculated according to the following formula
The larger the correlation, the stronger the correlation.The neighborhood of the involved pixels has a large number of computations, but is functionally stable and immune to noise.
Each of the extracted features is formed into a vector,. Considering that the value of each component of the feature vector is not uniform, it has different effects on the linear classifier, and thus it is necessary to normalize it.
Here, the feature vector is normalized according to the mahalanobis distance principle. Since the covariance matrix is a real symmetric matrix, the unitary matrix can be diagonalized, so
WhereinIs a unitary matrix of the matrix,is the average of the sample feature vectors, T is the transpose,a covariance eigenvalue matrix. The normalized feature vectorComprises the following steps:
in the classification process, a linear classification decision criterion is established:
whereinAre weight coefficients, which can be trained using known calibration target feature vectors. The classification process is broadly applicable when the radar performance is stable and consistent, and the SNR is large and meets the monitoring conditions.
Finally, the SPCP within a certain distance range from the runway is selected through distance constraint, and the accuracy of SPD estimation is further improved.
The correction method comprises the following steps: fig. 1 shows a complete flow of a phase drift correction method for a high-resolution runway foreign object detection system. It consists of four stages:
SPD modeling: observing the runway through an AS-SAR system, generating a high-resolution image, and modeling the SPD;
screening of SPCP: this stage can be done in real time or offline. To prevent FOD targets from being screened as SPCP, it requires data of empty scenes. It processes the sequence magnitude image by feature extraction and classification and sends the obtained SPCP to the second stage.
Estimation of SPD: in the actual processing, the SPCP provided in the first stage is used and based on the SPD model, the SPD between two complex images is estimated in real time by using an LS algorithm. And finally, performing a Kalman filter according to the multi-frame SPD (greater than 2) to acquire the SPD for correction.
SPD correction: the prospective correction is achieved by subtracting the SPD estimate, and a phase corrected sequence complex image is generated and output.
SPD correction is carried out on 8 cylindrical targets of scene actual measurement data by using the algorithm; the diameter and height of the target are both 4cm, and the AS-SAR image result is shown in FIG. 5.
Fig. 6 shows the phase change history of the cylindrical target 1 in fig. 5 before and after SPD correction. By contrast, before SPD correction, the phase change of the target 1 is severe and gradually increased; after SPD correction, the phase of target 1 tends to be consistent and is kept in a certain range. Therefore, the SPD correction algorithm can effectively inhibit phase drift and stabilize the target phase.
Fig. 7 shows an SNR comparison diagram after cylindrical target coherent accumulation before and after SPD correction, and it can be seen that after SPD correction, the target coherent accumulation SNR is significantly improved. Since the basis of coherent accumulation is the phase stability of the target, it is also shown from the side that the algorithm of the present invention can effectively correct the SPD to obtain a stable target phase.
In a word, through comparison of target phase change processes before and after SPD correction and comparison of SNR after target coherence accumulation, the method and the device can realize SPD correction of the target in the AS-SAR system image, obtain stable target phase and lay a foundation for subsequent SNR enhancement and target identification.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A phase drift correction method of a high-resolution runway foreign object detection system is characterized by comprising the following steps: the method comprises the following steps:
step one, modeling of a phase drift SPD: observing the runway through an AS-SAR system, generating a high-resolution image, and modeling a phase drift SPD to obtain a phase drift SPD model;
step two, screening stable phase control points SPCP: forming a complex image sequence with a fixed length on a complex image acquired through an AS-SAR system by adopting a first-in first-out principle, and carrying out classification processing after feature extraction;
estimating a phase drift SPD through a stable phase control point SPCP; estimating a phase drift SPD by adopting a least square algorithm based on the phase drift SPD model for the stable phase control point SPCP obtained in the step two to obtain an estimated value of the phase drift SPD;
step four, correcting the phase drift SPD: subtracting the estimated value of the phase drift SPD from the phase of the current complex image to realize the SPD correction of the phase drift of the image, and outputting the AS-SAR complex image with high resolution after the phase correction;
the modeling step of the phase drift SPD in the first step is as follows: observing the runway through an AS-SAR system to obtain two continuous images, considering the influence of phase drift SPD on phase difference by the system and atmospheric phase disturbance, and establishing a binary linear function model of the phase drift SPD when the atmosphere changes independently along with the distance direction and the azimuth direction;
the binary linear function model is as follows:
2. The method according to claim 1, wherein the step two is followed by a secondary Stable Phase Control Point (SPCP) screening step: and selecting a stable phase control point closer to the runway through distance constraint, then extracting a stable phase control point SPCP, and performing step three processing.
3. The method according to claim 1, wherein the phase drift SPD estimated value obtained in the third step is filtered by a Kalman filter to obtain a more accurate phase drift SPD estimated value.
4. The phase drift correction method of the high-resolution runway foreign object detection system according to claim 1, characterized in that Stable Phase Control Points (SPCP) are screened out, weighting coefficients in the binary linear function model are calculated through the Stable Phase Control Points (SPCP), and a phase drift (SPD) model is obtained.
5. The phase drift correction method of the high-resolution runway foreign object detection system according to any one of claims 1-3, wherein the second step of performing feature extraction comprises: for the amplitude image, three functions of screening the stable phase control points SPCP are defined: local image contrastAmplitude dispersionAnd correlation coefficient。
6. The phase drift correction method of the high-resolution runway foreign object detection system according to claim 5, characterized in that the classification in the step two is to normalize the extracted features, then train linear classifier parameters by combining feature vectors of stable phase control points of known scenes, and obtain the stable phase control points SPCP through linear classification screening.
7. The method for correcting the phase drift of the high-resolution runway foreign object detection system according to any one of claims 1-3, wherein the phase drift SPD is estimated through a Stable Phase Control Point (SPCP) in the third step, and the phase drift SPD between two complex images is estimated in real time by using the Stable Phase Control Point (SPCP) obtained in the second step and based on the phase drift SPD model obtained in the first step and a least square algorithm; and finally, filtering the Kalman filter according to the multi-frame phase drift SPD.
8. A high resolution runway foreign object detection system, wherein the detection system is an AS-SAR system in the phase drift correction method of any of claims 1 to 7.
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