CN112379349A - Method, device, equipment and storage medium for classifying foreign matters on airport pavement - Google Patents
Method, device, equipment and storage medium for classifying foreign matters on airport pavement Download PDFInfo
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- CN112379349A CN112379349A CN202011351007.XA CN202011351007A CN112379349A CN 112379349 A CN112379349 A CN 112379349A CN 202011351007 A CN202011351007 A CN 202011351007A CN 112379349 A CN112379349 A CN 112379349A
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- 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
Abstract
The present disclosure provides a method, an apparatus, a device and a storage medium for classifying foreign matters on an airport pavement, wherein the method comprises the following steps: the method comprises the steps of scanning an airport runway by using a polarized millimeter wave radar, obtaining radar data of the airport runway, extracting relevant data of an airport pavement foreign object to be detected from the radar data, calculating polarization characteristic statistics of the airport pavement foreign object to be detected according to the relevant data, obtaining characteristic data of the airport pavement foreign object to be detected, and classifying the airport pavement foreign object to be detected according to the characteristic data of the airport pavement foreign object to be detected by using a trained classifier. The multi-polarization millimeter wave radar is introduced, observation information is increased, and monitoring probability is improved. The method can monitor the target all day long, divide the hazard grade, start a corresponding emergency plan aiming at the early warning grade level of the foreign matters on the airport pavement, guide the related departments and units to work in a linkage way, quickly close and clean the runway, and ensure the ground operation safety of the aircraft.
Description
Technical Field
The disclosure belongs to the technical field of radar, and particularly relates to a polarized millimeter wave radar-based airport pavement foreign matter classification method, device, equipment and storage medium.
Background
The invasion of Foreign Objects (FOD) on the airport runway seriously threatens the safety of the flight and can cause personal injury and death. According to statistics, 64% of foreign matters on the airport pavement are small stone and asphalt shedding blocks, 14% are metal parts, 10% are shedding objects such as plastics and luggage cases, 8% are drifting objects such as paper and 4% are other objects. In the actual operation process, the hazard level of the monitored foreign matters to the normal operation of the flight is often needed to be known, so that corresponding treatment measures are taken to ensure the safe and efficient operation of the flight. According to a prevention manual of a national main office airport department of civil aviation safety technology center, runway foreign matters can be classified into three levels of high-risk, medium-risk and low-risk according to the damage level of taking off and landing of an airplane, for example, waterproof plastic cloth, metal parts and foreign matters with the weight of more than 1 kg seriously damage the ground operation safety of the airplane, easily cause damage of engine blades and tire burst, are foreign matters on the surface of a high-risk runway and need to be removed immediately; newspapers, packing cases, broken stones and the like have certain harm to the ground operation safety of the aircraft, and foreign matters on the surface of the medium-risk runway can be removed after the current patrol is finished; leaves, paper scraps, non-metal fragmentary garbage and the like have small harm to the ground operation safety of the aircraft, are foreign matters on the low-risk runway surface, and can be removed after the runway is closed. In order to improve the utilization efficiency of the runway, the foreign matters in the runway need to be classified according to the danger level.
Most research works at present focus on runway foreign matter monitoring, and researches on classification and danger level judgment of runway foreign matters are relatively few. The method mainly adopts a mode of manual timing inspection (mainly by naked eyes), namely, after-the-fact classification and identification; another real-time early warning method is to use optical or infrared products to perform classification and identification.
The manual timed patrol mode is characterized in that the International Civil Aviation Organization (ICAO) stipulates four times of inspection per day, the method is low in efficiency and unreliable, non-real-time supervision is achieved, and potential safety hazards of operation exist. And the airport runway foreign object monitoring system has larger limitation on the photoelectric sensor at night and in foggy weather.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
Technical problem to be solved
In view of the above-mentioned shortcomings of the prior art, a primary object of the present disclosure is to provide a polarized millimeter wave radar-based airport pavement foreign object classification method, which is intended to at least partially solve at least one of the above-mentioned technical problems.
(II) technical scheme
In order to achieve the above object, according to one aspect of the present disclosure, there is provided an airport pavement foreign object classification method based on polarized millimeter wave radar, the method including:
scanning an airport runway by using a polarized millimeter wave radar to obtain radar data of the airport runway;
extracting relevant data of the airport pavement foreign object to be detected from the radar data;
calculating the polarization characteristic statistic of the airport pavement foreign matter target to be detected according to the related data to obtain the characteristic data of the airport pavement foreign matter target to be detected;
and classifying the airport pavement foreign matter target to be detected according to the characteristic data of the airport pavement foreign matter target to be detected by utilizing the trained classifier.
In another aspect, the present disclosure provides an airport pavement foreign matter classification device based on polarized millimeter wave radar, the device including:
the acquisition module scans the airport runway by using the polarized millimeter wave radar and acquires radar data of the airport runway;
the extraction module is used for extracting relevant data of the airport pavement foreign object from the radar data;
the calculation module is used for calculating the polarization characteristic statistic of the airport pavement foreign matter target according to the related data to obtain the characteristic data of the airport pavement foreign matter target;
and the classification module is used for classifying the airport pavement foreign matter targets according to the feature data of the airport pavement foreign matter targets by utilizing the trained classifier.
Further, the apparatus further comprises:
the creating module is used for creating an airport pavement foreign matter feature database based on the millimeter wave radar based on the feature data of the airport pavement foreign matter target;
and the training module is used for training a preset classifier by utilizing an airport pavement foreign matter characteristic database of the polarized millimeter wave radar to obtain the trained classifier.
In another aspect, the present disclosure provides an electronic device, comprising:
a communicator for communicating with a server;
a processor;
a memory storing a computer executable program which, when executed by the processor, causes the processor to execute one of the above-described methods of polarized millimeter wave radar-based classification of airport pavement foreign matter.
In another aspect, the present disclosure provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for polarized millimeter wave radar-based classification of airport pavement foreign matter as described above.
(III) advantageous effects
(1) The optical airport pavement foreign matter early warning level system overcomes the problem that the performance of the optical airport pavement foreign matter is poor or completely fails under the environments such as haze, night, severe weather and the like, so that the target cannot be classified, the problem that the airport pavement foreign matter is difficult to classify in real time is fully solved, the target can be monitored all day long, the damage level is divided, a corresponding emergency plan is started according to the airport pavement foreign matter early warning level, related departments and units are guided to work in a linkage mode, the runway is quickly closed and cleaned, and a set of efficient and safe airport pavement foreign matter disposal mechanism is formed.
(2) The multi-polarization millimeter wave radar is introduced, observation information can be increased, and the monitoring probability of the target is improved.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flowchart of a method for classifying foreign objects on an airport pavement according to an embodiment of the present disclosure;
FIG. 2 is a scene diagram of a multi-angle multi-polarization irradiation test performed by a vector network analyzer in a microwave darkroom according to an embodiment of the present disclosure;
fig. 3 is a radar irradiation layout diagram of a plurality of targets at a plurality of angles according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an airport pavement foreign object classification device according to an embodiment of the present disclosure;
fig. 5 shows a hardware configuration diagram of an electronic device.
Detailed Description
For purposes of promoting a clear understanding of the objects, features, aspects and advantages of the present disclosure, the present disclosure will be described in further detail below with reference to specific embodiments thereof, which are illustrated in the accompanying drawings. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the scope of protection of the present disclosure.
Fig. 1 is a schematic flow chart of a method for classifying an airport pavement foreign object according to an embodiment of the present disclosure, as shown in fig. 1, the method includes the following steps:
s101, scanning an airport runway by using a polarized millimeter wave radar to acquire radar data of the airport runway;
when the airport pavement foreign matter is monitored, the polarized millimeter wave radar needs to monitor small foreign matters in a short distance, and the polarized millimeter wave radar is required to have a distance blind area as small as possible and high distance resolution. The millimeter wave radar for monitoring foreign matters on airport pavement usually adopts a linear frequency modulation continuous wave system, and the transmitted signal is assumed to be
Wherein f is0If u is the chirp rate of the chirp signal, the echo signals of the airport pavement foreign object at different distances can be expressed as
Tau is echo time delay caused by a foreign object on an airport pavement, a difference frequency signal can be obtained after echo signals are subjected to frequency mixing and filtering, and the difference frequency signal can be expressed as
Wherein K is the amplitude of the echo of the airport pavement foreign object, and lambda is the radar wavelength.
According to the principle, by means of a polarized millimeter wave radar system (the present disclosure takes typical horizontal/vertical polarization as an example), runway foreign matter multichannel echo data containing polarization information can be acquired.
S102, extracting relevant data of the airport pavement foreign object to be detected from the radar data.
S103, calculating the polarization characteristic statistic of the airport pavement foreign matter target to be detected according to the related data to obtain the characteristic data of the airport pavement foreign matter target to be detected;
respectively carrying out pulse compression processing and constant false alarm rate monitoring processing (CFAR) on a plurality of channels, and obtaining a scattering polarization matrix S of the airport pavement foreign object:
where the first subscripts of S and θ denote the polarization of the receiving antenna, the second subscript denotes the polarization of the transmitted signal, H denotes the horizontal polarization, and V denotes the vertical polarization. A is the echo amplitude and theta is the echo phase. For reciprocal airport pavement foreign object, S can be considered approximatelyHV≈SVH。
And the polarization characteristic statistic is to adopt polarization invariant to characterize the polarization scattering characteristic of the target, and two characteristic quantities are selected by optimization and respectively are a trace P and a depolarization coefficient D of the power matrix.
The trace of the power matrix is a constant amount of rotation around the radar line of sight and represents the total power received by a pair of orthogonally polarized antennas. The RCS value of the airport pavement foreign matter target under full polarization is represented, and the RCS value can roughly reflect the magnitude of the echo energy of the airport pavement foreign matter target. The trace P of the power matrix may be represented by the elements of the scattering matrix S:
P＝|SHH|2+|SVV|2+|SHV|2+|SVH|2
the depolarization coefficient D approximately reflects the number of the airport pavement foreign object target scattering centers, and for some isolated scattering centers, D is usually less than 0.5; the larger value (D is more than 0.5 and less than or equal to 1) is more corresponding to the combined airfield pavement foreign matter targets of a plurality of scattering centers. The depolarization factor D may be represented by the following elements:
wherein S is1＝SHH+SVV。
S104, classifying the airport pavement foreign matter target to be detected according to the characteristic data of the airport pavement foreign matter target to be detected by using the trained classifier;
and obtaining the classification results of the foreign matters on the high-crisis runway surface, the foreign matters on the medium-crisis runway surface and the foreign matters on the low-crisis runway surface.
Further, before monitoring the airport pavement foreign matter, it is necessary to establish an airport pavement foreign matter feature database based on a polarized millimeter wave radar and train a preset classifier using the airport pavement foreign matter feature database of the polarized millimeter wave radar, and the method specifically includes:
typical airport pavement foreign matter targets (such as high-risk airport pavement foreign matter: metals, medium-risk airport pavement foreign matter: crushed stone, low-risk airport pavement foreign matter: plastics) with various known hazard levels are arranged on the airport runway;
and repeating the steps S101-S103 until all known characteristic data of the airport pavement foreign matters are acquired.
The method comprises the steps of training a preset classifier by utilizing an airport pavement foreign matter feature database of a polarized millimeter wave radar to obtain the trained classifier, performing dichotomy by utilizing an SVM (support vector machine) training model, and performing multiple classification by utilizing RBF (radial basis function).
Fig. 2 is a scene diagram of a multi-angle and multi-polarization irradiation test performed by a vector network analyzer in a microwave darkroom according to an embodiment of the present disclosure, as shown in fig. 2, a multi-angle and multi-polarization irradiation test is performed by a vector network analyzer in a microwave darkroom. Two standard gain horn antennas (Ka wave band) are adopted, and polarized data is obtained by changing the fixed mode of the polarized port surface of the antenna. The distance between the receiving and transmitting antennas is about 17cm, the airport pavement foreign matter target is placed on the turntable with foam, and the distance between the antennas and the airport pavement foreign matter target is about 80 cm.
Fig. 3 is a radar irradiation layout diagram of a plurality of airport pavement foreign object targets at a plurality of angles according to an embodiment of the present disclosure, as shown in fig. 3, (a) an airport pavement foreign object target object diagram, (b) 0-degree directional irradiation, (c) 45-degree directional irradiation, (d) 90-degree directional irradiation, (e) 135-degree directional irradiation, and (f) 180-degree directional irradiation.
The following table shows statistical results of the classification accuracy of the single polarization and the multi-polarization respectively at each angle, which are provided by the embodiment of the present disclosure.
Fig. 4 is a schematic structural diagram of an airport pavement foreign object classification apparatus according to an embodiment of the present disclosure, and as shown in fig. 4, the present disclosure further provides an apparatus including:
Before monitoring airport pavement foreign matter, an airport pavement foreign matter feature database based on a polarized millimeter wave radar and a classifier preset by training of the airport pavement foreign matter feature database using the polarized millimeter wave radar need to be established, and the method specifically comprises the following steps:
typical airport pavement foreign matter targets (such as high-risk airport pavement foreign matter: metals, medium-risk airport pavement foreign matter: crushed stone, low-risk airport pavement foreign matter: plastics) with various known hazard levels are arranged on the airport runway;
the acquisition module 301 scans an airport runway by using a polarized millimeter wave radar and acquires radar data of the airport runway;
an extraction module 302 for extracting data related to the airport pavement foreign object from the radar data,
the calculation module 303 is configured to calculate a polarization characteristic statistic of the airport pavement foreign object according to the relevant data to obtain characteristic data of the airport pavement foreign object;
repeating the process until all known characteristic data of the airport pavement foreign matters are acquired;
a creating module 304, which is used for creating an airport pavement foreign object feature database based on the millimeter wave radar based on the feature data of the airport pavement foreign object target;
the training module 305 trains a preset classifier by using the airport pavement foreign matter feature database of the polarized millimeter wave radar to obtain a trained classifier;
when monitoring the airport pavement foreign matter target that awaits measuring, specifically include: the acquisition module 301 scans an airport runway by using a polarized millimeter wave radar and acquires radar data of the airport runway;
an extraction module 302, which extracts the relevant data of the airfield pavement foreign object to be detected from the radar data;
the calculation module 303 is configured to calculate a polarization characteristic statistic of the airfield pavement foreign object target to be detected according to the relevant data to obtain characteristic data of the airfield pavement foreign object target to be detected;
the classification module 306 classifies the airport pavement foreign object to be detected according to the feature data of the airport pavement foreign object to be detected by using the trained classifier.
The present disclosure also provides an electronic device 200, comprising:
a communicator 210 for communicating with a server;
a processor 220;
a memory 230 storing a computer executable program comprising the method for classifying airfield pavement foreign matter as described above.
Fig. 5 schematically shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 5, the electronic device 200 includes a communicator 210, a processor 220 and a memory 230. The electronic device 200 may perform a method according to an embodiment of the present disclosure.
In particular, processor 220 may include, for example, a general purpose microprocessor, an instruction set processor and/or related chip set and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 220 may also include onboard memory for caching purposes. Processor 220 may be a single processing unit or a plurality of processing units for performing different actions of a method flow according to embodiments of the present disclosure.
The present disclosure also provides a computer-readable storage medium having stored thereon a computer program comprising the method for classifying airfield pavement foreign matter as described above. The computer-readable storage medium may be embodied in the apparatuses/devices described in the above embodiments; or may be present separately and not assembled into the device/apparatus. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, a computer-readable storage medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical fiber cable, radio frequency signals, etc., or any suitable combination of the foregoing.
The above-mentioned embodiments, objects, technical solutions and advantages of the present disclosure are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present disclosure, and are not intended to limit the present disclosure, and those skilled in the art will understand that various combinations and/or combinations of the various embodiments of the present disclosure and/or the features recited in the claims can be made, and even if such combinations and/or combinations are not explicitly described in the present disclosure, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (10)
1. A polarized millimeter wave radar-based airport pavement foreign matter classification method is characterized by comprising the following steps:
scanning an airport runway by using a polarized millimeter wave radar to acquire radar data of the airport runway;
extracting relevant data of the airport pavement foreign object to be detected from the radar data;
calculating the polarization characteristic statistic of the airport pavement foreign matter target to be detected according to the relevant data to obtain the characteristic data of the airport pavement foreign matter target to be detected;
and classifying the airport pavement foreign matter target to be detected according to the characteristic data of the airport pavement foreign matter target to be detected by utilizing the trained classifier.
2. The method of classifying airport pavement foreign matter based on polarized millimeter wave radar according to claim 1,
randomly placing known airport pavement foreign object targets with various hazard levels on the airport runway;
scanning an airport runway by using a polarized millimeter wave radar to acquire radar data of the airport runway;
extracting relevant data of the airport pavement foreign object from the radar data;
calculating polarization characteristic statistics of the airport pavement foreign matter target according to the related data to obtain characteristic data of the airport pavement foreign matter target;
repeating the steps until all known characteristic data of the airport pavement foreign matters are acquired;
establishing an airport pavement foreign matter feature database based on the millimeter wave radar based on the feature data of the airport pavement foreign matter target;
and training a preset classifier by using the airport pavement foreign matter feature database of the polarized millimeter wave radar to obtain the trained classifier.
3. The method for classifying foreign objects on the airport pavement based on polarized millimeter wave radar according to claim 1, wherein the related data comprises: and the multi-polarization data and the multi-channel data of the airport pavement foreign matter to be detected.
4. The method for classifying foreign objects on the airport pavement based on polarized millimeter wave radar as claimed in claim 1, wherein the polarized millimeter wave radar comprises a multi-polarized millimeter wave radar.
5. The method for classifying airport pavement foreign matter based on polarized millimeter wave radar according to claim 3, wherein the multichannel data of the airport pavement foreign matter to be detected is subjected to pulse compression processing and constant false alarm rate detection processing respectively to obtain a scattering polarization matrix S of the airport pavement foreign matter target to be detected:
wherein the first subscript of S and θ represents the polarization of the receiving antenna, the second subscript represents the polarization of the transmitted signal, H represents the horizontal polarization, V represents the vertical polarization, a represents the echo amplitude, and θ represents the echo phase.
6. The method for classifying the airport pavement foreign matters based on the polarized millimeter wave radar as claimed in claim 1, wherein the polarized characteristic statistic is polarization scattering characteristic of the target by using polarization invariant quantity, two characteristic quantities are selected by optimization, namely a trace P and a depolarization coefficient D of a power matrix, and the trace P of the power matrix can be represented by an element of a scattering matrix S:
P＝|SHH|2+|SVV|2+|SHV|2+|SVH|2
the depolarization factor D may be represented by the following elements:
wherein S is1＝SHH+SVV。
7. An airport pavement foreign matter classification device based on polarized millimeter wave radar, the device comprising:
the system comprises an acquisition module, a data acquisition module and a data processing module, wherein the acquisition module is used for scanning an airport runway by using a polarized millimeter wave radar and acquiring radar data of the airport runway;
the extraction module is used for extracting relevant data of the airport pavement foreign object from the radar data;
the calculation module is used for calculating the polarization characteristic statistic of the airport pavement foreign matter target according to the related data to obtain the characteristic data of the airport pavement foreign matter target;
and the classification module is used for classifying the airport pavement foreign matter target according to the feature data of the airport pavement foreign matter target by utilizing the trained classifier.
8. The polarized millimeter wave radar-based airport pavement foreign object classification apparatus of claim 7, further comprising:
the creating module is used for creating an airport pavement foreign matter feature database based on the millimeter wave radar based on the feature data of the airport pavement foreign matter target;
and the training module is used for training a preset classifier by utilizing the airport pavement foreign matter characteristic database of the polarized millimeter wave radar to obtain the trained classifier.
9. An electronic device, characterized in that the device comprises:
a communicator for communicating with a server;
a processor;
a memory storing a computer executable program which when executed by the processor causes the processor to perform the method of polarized millimeter wave radar airport pavement foreign object classification as recited in claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method for classifying foreign objects on an airport pavement of a polarized millimeter wave radar as set forth in claims 1 to 6.
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