CN117148307B - Empty drift detection method and device based on dual-polarized radar radix fusion processing - Google Patents

Empty drift detection method and device based on dual-polarized radar radix fusion processing Download PDF

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CN117148307B
CN117148307B CN202311408693.3A CN202311408693A CN117148307B CN 117148307 B CN117148307 B CN 117148307B CN 202311408693 A CN202311408693 A CN 202311408693A CN 117148307 B CN117148307 B CN 117148307B
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doppler
channel
echo
empty
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CN117148307A (en
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黄建开
殷加鹏
安孟昀
李永祯
王雪松
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National University of Defense Technology
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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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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  • Computer Networks & Wireless Communication (AREA)
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  • Radar Systems Or Details Thereof (AREA)

Abstract

The application relates to a method and a device for detecting empty drift based on dual-polarized radar radix fusion processing. The method comprises the following steps: obtaining a distance-Doppler echo by performing fast Fourier transform on echo data of a double channel through matched filtering, calculating according to the distance-Doppler echo to obtain various polarized Doppler base data parameters, judging whether a suspected empty drift target exists or not by adopting a low-threshold constant false alarm probability detector on the reflectivity of an H channel on a radar PPI graph, if the suspected empty drift target exists, constructing a membership function to fuzzify various polarized Doppler base data parameters, generating a fuzzy function, finally solving the fuzzy function by solving posterior probability, judging according to posterior probability and a preset threshold, and determining whether the empty drift target exists or not according to a judging result. The method does not need an accurate mathematical model, and has strong adaptability and high robustness.

Description

Empty drift detection method and device based on dual-polarized radar radix fusion processing
Technical Field
The application relates to the technical field of radar signal processing, in particular to a method and a device for detecting an empty drift based on dual-polarized radar base fusion processing.
Background
The random discarded air-floating objects can cause great threat to aviation safety, and the air-floating objects are unpowered floating objects which are difficult to observe because the air-floating objects are mostly made of plastics and rubber. Air balloon, which is widely used and commonly used in business and life, is a festival celebration prop and an entertainment toy. However, free-discarded or uncontrolled air-flutter balloons can pose a great threat to aviation safety, with the sudden appearance of air-flutter balloons at airports and their periphery and on airlines increasing in threat to civil aviation safety. The method has the advantages that the existing dual-polarized radar of the airport is used for efficiently and quickly detecting nearby air-floating balloons and sending out early warning in advance. Because of the complex environment near the airport, the continuous increase of electromagnetic equipment generates a plurality of electromagnetic interferences, and weak echoes of the air-floating balloon are often submerged in the electromagnetic interferences and noise, thereby affecting the detection performance of the radar on the air-floating balloon targets.
However, in the existing detection method for the weak and small targets In the complex scene, specific processing is required to be performed on an In-phase-Quadrature (IQ) data layer to obtain a detection result, however, the amount of IQ data generated by actually running meteorological radar scanning is huge and cannot be stored, so that only the base data generated by the IQ data is stored for inverting the meteorological parameters. The stably running weather radar signal processing flow is already determined and solidified, and the signal processing flow is difficult to modify at the bottom layer to adapt to a new detection method. The IQ data processing-based method is more difficult to embed into existing stably operating radars than the method using the base data as input.
In summary, the application range of the IQ data processing and detecting method based on the weather radar is greatly limited, and the processing method based on the weather radar base data has no more requirements on the processing system and the signal processing flow of the existing radar, so that the novel radar function can be further endowed on the aspects of not affecting the signal processing flow and the weather detection function of the existing radar.
Disclosure of Invention
Based on the above, it is necessary to provide a method and a device for detecting a drift object based on dual-polarized radar radix fusion processing, which can rapidly detect a weak drift object while suppressing false alarms caused by electromagnetic interference and clear sky background.
A method for detecting airborne matter based on dual polarized radar radix fusion processing, the method comprising:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated;
and resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
In one embodiment, the polarization doppler data parameters further include: differential reflectivity, speed of H channel, spectral width of H channel, correlation coefficient of two channels, speed difference of two channels and spectral width difference of two channels.
In one embodiment, the determining whether the suspected empty drift target exists on the radar PPI map by using the low-threshold constant false alarm probability detector for the H-channel reflectivity includes:
the low threshold constant false alarm probability detector comprises 3 units, namely a background unit, a protection unit and a unit to be detected;
calculating to obtain a detection threshold according to the number of the background units and the numerical value of each background unit;
and comparing the detection threshold value with the numerical value of the unit to be detected, if the numerical value of the unit to be detected is larger than the detection threshold value, judging that a suspected empty floating target exists, and judging that the suspected empty floating target does not exist on the side of the detection threshold value.
In one embodiment, the detection threshold value obtained by calculating according to the number and the numerical value of the background units adopts the following formula:
；
in the above-mentioned description of the invention,representing the detection threshold,/->Represents scale factors->Representing the number of said background elements,and a numerical value representing each of the background units.
In one embodiment, the membership function is:
in the above, subscriptsRepresenting each of said polarization Doppler-based data parameters, i.e +.>Wherein->Representing differential reflectivity, +.>Indicating the speed of H channel, +.>Represents the spectral width of the H channel, < >>Representing the correlation coefficient of two channels, +.>Representing the speed difference of the two channels +.>Representing the difference in spectral width of the two channels, +.>Values representing the respective polarization doppler data parameters, are given>Represents the first turning point of the membership function, < ->Representing the second turning point of the membership function,a flag bit representing a membership function, and +.>。
In one embodiment, membership functions corresponding to the polarization doppler base data parameters are respectively:
，/>，/>，/>，and->。
In one embodiment, the blurring function is:
；
in the above-mentioned description of the invention,representing the transpose.
In one embodiment, deblurring the blur function includes: according to a fuzzy reasoning principle, different weights are given to each polarization Doppler base data parameter in the fuzzy function as follows:
。
then solving the posterior probability to perform the deblurring, and adopting the following formula:
；
in the above-mentioned description of the invention,representing the posterior probability,/->Representing summation(s)>Representing the blur function.
In one embodiment, the determining according to the posterior probability and a preset threshold, and determining whether the null drift target exists according to the determination result includes: and if the posterior probability is larger than the preset threshold, determining that the null drift target exists, otherwise, determining that the null drift target does not exist.
A device for detecting airborne matter based on dual polarized radar radix fusion processing, the device comprising:
the distance-Doppler echo obtaining module is used for obtaining echo data of the matched filtering double channels and carrying out fast Fourier transform on the echo data to obtain a distance-Doppler echo;
the polarization Doppler data base data parameter calculation module is used for calculating each polarization Doppler data base data parameter according to the distance-Doppler echo, wherein the polarization Doppler data base data parameter comprises the reflectivity of an H channel;
the low threshold constant false alarm probability detector judging module is used for judging whether a suspected empty floating target exists or not by adopting the low threshold constant false alarm probability detector for the reflectivity of the H channel on the radar PPI graph;
the fuzzy function generation module is used for constructing a membership function to fuzzify each polarized Doppler base data parameter and generating a fuzzy function if the suspected empty floating target exists;
and the empty-floating target detection module is used for performing defuzzification on the fuzzy function by solving the posterior probability, judging according to the posterior probability and a preset threshold, and determining whether an empty-floating target exists according to a judgment result.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated;
and resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated;
and resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
According to the method and the device for detecting the empty drift based on the dual-polarized radar radix fusion processing, the distance-Doppler echo is obtained through fast Fourier transform on the echo data of the dual-channel through matched filtering, each polarized Doppler base data parameter is obtained through calculation according to the distance-Doppler echo, whether a suspected empty drift target exists or not is judged through a low-threshold constant false alarm probability detector on the reflectivity of an H channel on a radar PPI chart, if the suspected empty drift target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, a fuzzy function is generated, finally, the fuzzy function is defuzzified through solving posterior probability, judgment is carried out according to the posterior probability and a preset threshold, and whether the empty drift target exists or not is determined according to a judgment result. The method improves the detection probability of the target by reducing the threshold of the constant false alarm probability detector, and then utilizes the polarization Doppler characteristic parameter to construct a fuzzy logic decision device to effectively inhibit the false alarm. The input required by the method is weather base data parameters generated by the weather radar, and the method is endowed with wide applicability of new functions on the basis of not affecting the current weather radar business functions. The method has the advantages of no need of an accurate mathematical model, small calculated amount, strong adaptability and no influence on the service function of the original radar, can be embedded into the existing running dual-polarized weather radar, and has high robustness.
Drawings
FIG. 1 is a flow diagram of a method for detecting airborne matter based on dual polarized radar radix fusion processing in one embodiment;
FIG. 2 is a schematic diagram of an H-channel reflectivity radar PPI in one embodiment;
FIG. 3 is a schematic diagram illustrating a processing reference window of a CFAR detector in one embodiment;
FIG. 4 is a diagram showing the detection result of the low threshold of the H-channel PPI reflectivity CFAR detector in one embodiment;
FIG. 5 is a schematic diagram of detection results of a detection according to a method for detecting airborne matter based on a dual polarized radar radix fusion process in one embodiment;
FIG. 6 is a flow chart of a method for detecting airborne matter based on a dual polarized radar radix fusion process in another embodiment;
FIG. 7 is a block diagram of an empty drift detection device based on dual polarized radar radix fusion processing in one embodiment;
fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
As shown in fig. 1, a method for detecting a drift based on dual-polarized radar radix fusion processing is provided, which comprises the following steps:
step S100, acquiring echo data of the double channels subjected to matched filtering, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
step S110, calculating according to the distance-Doppler echo to obtain various polarization Doppler base data parameters, wherein the polarization Doppler base data parameters comprise the reflectivity of an H channel;
step S120, judging whether a suspected empty drift target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of an H channel on a radar PPI diagram;
step S130, if the suspected empty floating target exists, a membership function pair is constructed, and the polarized Doppler base data parameters are fuzzified, and a fuzzy function is generated;
and step S140, the fuzzy function is deblurred by solving the posterior probability, judgment is carried out according to the posterior probability and a preset threshold, and whether a null drift target exists is determined according to a judgment result.
In this embodiment, the difference of polarization doppler characteristic distribution of the empty drift and electromagnetic interference and clear sky background noise are utilized for detection. First, the detection is performed on the PPI (Plan Position Indicator, in-plane position indicator, abbreviated as PPI) by a low threshold CFAR (Constant 0 Alarm Rate Detector, detector with Constant false alarm probability, abbreviated as CFAR) detector. And the false alarm is further removed by utilizing the difference of distribution characteristics of the air-floating target and electromagnetic interference and clear air background on the polarization-Doppler domain.
The method specifically uses the difference of polarization parameter distribution such as differential reflectivity, speed, spectrum width, correlation coefficient, speed difference of two channels, spectrum width difference of two channels and the like of different targets. For the spectrum width and the correlation coefficient, the spectrum width of the empty floating target is smaller, the correlation coefficient is larger, and the spectrum width of electromagnetic interference and clear sky background is larger and the correlation coefficient is smaller. For the speed difference of the two channels and the spectrum width difference of the two channels, the speed difference of the two channels and the spectrum width difference of the two channels of the air-floating target are smaller, and the speed difference of the two channels and the spectrum width difference of the two channels of electromagnetic interference and clear air background are larger. And designing a fuzzy polarization parameter algorithm by utilizing the characteristics to further detect the target. In the application, the hollow floating object is exemplified by a hollow floating balloon, and in practical application, the hollow floating object can also be a plastic bag, which refers to all unpowered floating objects made of plastic and rubber and difficult to observe.
In step S100, the detection signal is transmitted by the polarization-Doppler weather radar to the airspace to be detected, and the pulse echo data is subjected to matched filtering by H, V dual channels to continuouslyThe pulses are a group of pulses within a coherent processing time (Coherent processing time, CPI), in practice +.>. Performing fast Fourier transform on the group of data to obtain RD spectrum echo +.>：
（1）
In the case of the formula (1),subscript->Representing->Channel or->Channel (S)>Representation->Within a group of CPI channels, the distance is +.>Is>Echo complex data>Expressed as fast fourier transform, ">Indicating speed, & lt->。
In step S110, the calculating the range-doppler echo to obtain each polarization doppler-based data parameter further includes: differential reflectivity (R),Speed of the channel, +.>The spectral width of a channel, the correlation coefficient of two channels, the speed difference of two channels and the spectral width difference of two channels.
Specifically, the following formula is used for calculation:
using RD spectral echo in equation (1)The spectral power can be calculated as:
（2）
and echo according to RD spectrumFurther get +.>The reflectivity of the channel is:
（3）
in the formula (3) of the present invention,indicating radar->Channel constant (I)>Representation->Noise correction factor of the channel.
As shown in FIG. 2 for radarChannel reflectivity, where the abscissa represents lateral distance and the ordinate represents longitudinal distance, and it can be seen from fig. 2 that the weak echo air balloon target and the clear sky background are indistinguishable, especially the air-conditioned balloon at the process (4.8 km-6.5 km), and that electromagnetic interference is present.
Calculating a correlation coefficient defining two channels, and adopting the following formula:
（4）
calculating differential reflectivity by adopting the following formula:
（5）
calculation ofThe speed of the channel is calculated using the following formula:
（6）
calculation ofThe spectral width of the channel is calculated by the following formula:
（7）
calculating the speed difference of the two channels, and adopting the following formula:
（8）
calculating the spectrum width difference of the connecting channel, and adopting the following formula:
（9）
in step S120, determining whether a suspected empty drift target exists on the radar PPI map by using a low-threshold constant false alarm probability detector for the H-channel reflectivity includes: based on the polarization Doppler data base parameter calculated in step S110, radar returns are processed on the PPIAnd (5) detecting and marking the average CFAR of the low-threshold two-dimensional unit by the channel reflectivity. As shown in fig. 3, the CFAR detection includes 3 different units for performing target detection, namely a background unit, a protection unit and a unit to be detected. And n1 and n3 in fig. 3 are set to 2, and n2 and n4 are set to 3. Wherein the value of the unit to be detected is +.>Calculating a detection threshold value according to the number of the background units and the numerical value of each background unit>Will detect threshold +.>The value of the unit to be detected +.>Comparing, if the unit to be detected is +>Is greater than the detection threshold +.>And judging that the suspected empty floating target exists, and carrying out a subsequent fuzzy logic judgment on the base data parameter of the area, and judging whether the suspected empty floating target does not exist or not.
Specifically, a detection threshold is calculatedThe following formula is adopted:
（10）
in the formula (10) of the present invention,representing a detection threshold value->Represents scale factors->Representing the number of background units, +.>The values representing the respective background cells.
The detection result shown in fig. 4 is obtained through the detection of the low threshold CAFR, wherein the abscissa represents the transverse distance, and the ordinate represents the longitudinal distance, and a plurality of false alarms generated due to clear sky background and electromagnetic interference can be seen from the graph.
In step S130, a corresponding membership function is respectively constructed for each polarization doppler data parameter, wherein the membership function is expressed as:
（11）
in equation (11), subscriptsRepresenting the respective polarization Doppler-based data parameters, i.e.>Wherein->Representing differential reflectivity, +.>Indicating the speed of H channel, +.>Represents the spectral width of the H channel, < >>Representing the correlation coefficient of two channels, +.>Representing the speed difference of the two channels +.>Representing the difference in spectral width of the two channels, +.>Values representing the respective polarization doppler data parameters, are given>Represents the first turning point of the membership function, < ->Representing the second turning point of the membership function, < ->A flag bit representing a membership function, and +.>。
Specifically, membership functions corresponding to the polarization doppler base data parameters are respectively:
，/>，/>，/>，and->And writing the membership functions into a vector form to generate a fuzzy function expressed as:
（12）
in the formula (12) of the present invention,representing the transpose.
In step S140, different weights are given to the polarization doppler base data parameters in the fuzzy function according to the fuzzy inference principle as follows:
（13）
then solving the posterior probability to perform the deblurring, and adopting the following formula:
（14）
in the case of the formula (14),representing posterior probability>Representing summation(s)>Representing a blurring function.
Judging according to the posterior probability and a preset threshold, and determining whether the empty floating target exists according to the judging result comprises the following steps: if the posterior probability is greater than a preset threshold, determining that the null-floating target exists, otherwise, determining that the null-floating target does not exist.
In one embodiment, the threshold may be set to。
As shown in fig. 5, in order to obtain a detection result after removing a large number of false alarms through the fuzzy logic algorithm, wherein the abscissa represents the transverse distance, and the ordinate represents the longitudinal distance, comparing fig. 4 and fig. 5, it can be seen that all the air balloon targets are detected and the false alarms caused by electromagnetic interference and clear sky background are suppressed after the detection through the method.
In this embodiment, when the method is implemented, the implementation may also be performed according to the flowchart shown in fig. 6.
In the above-mentioned empty drift detection method based on the fusion processing of dual polarized radar cardinality, the present application provides a detection method based on the fusion processing of cardinality data, aiming at the problem of detecting empty drift by a polarized Doppler weather radar. The method is suitable for the polarization Doppler weather radar to rapidly detect the balloon targets in the weak sky and inhibit false alarms caused by electromagnetic interference and clear sky background, has the advantages of small calculated amount, wide applicability and no influence on the service function of the original radar, and can be embedded into the existing running dual-polarized weather radar.
The method comprises the steps of firstly, increasing the detection probability of a target by reducing the threshold of a CFAR detector, and then utilizing a polarization Doppler characteristic parameter to construct a fuzzy logic decision device to effectively inhibit false alarms. The input required by the algorithm is weather base data parameters generated by the weather radar, and the new function is given to the weather radar on the basis of not affecting the current weather radar business function. For the multi-scanning result of the polarization Doppler weather phased array radar, the method provided by the invention can rapidly and simultaneously process the Doppler multi-beam scanning result, inhibit a large number of false alarms, and simultaneously correctly detect the target and form the track. The method provided by the invention does not need an accurate mathematical model, and has strong adaptability and high robustness.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 7, there is provided a null drift detection device based on a dual polarized radar base fusion process, including: a range-doppler echo obtaining module 200, a polarization doppler data parameter calculating module 210, a low threshold constant false alarm probability detector judging module 220, a blur function generating module 230 and a null-floating target detecting module 240, wherein:
the distance-Doppler echo obtaining module 200 is used for obtaining echo data of the matched filtering double channels and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
a polarization doppler-based data parameter calculation module 210, configured to calculate each polarization doppler-based data parameter according to the range-doppler echo, where the polarization doppler-based data parameter includes a reflectivity of an H-channel;
the low threshold constant false alarm probability detector judging module 220 is configured to judge whether a suspected empty floating target exists by using a low threshold constant false alarm probability detector for the reflectivity of the H channel on the radar PPI map;
the fuzzy function generating module 230 is configured to construct a membership function to fuzzify each of the polarization doppler base data parameters and generate a fuzzy function if it is determined that a suspected null drift target exists;
and the empty-floating target detection module 240 is configured to perform deblurring on the fuzzy function by solving a posterior probability, determine according to the posterior probability and a preset threshold, and determine whether an empty-floating target exists according to a determination result.
The specific limitation of the empty drift detection device based on the dual-polarized radar radix fusion process can be referred to as the limitation of the empty drift detection method based on the dual-polarized radar radix fusion process, and is not repeated herein. The modules in the above-mentioned empty drift detection device based on dual-polarized radar radix fusion processing can be implemented in whole or in part by software, hardware and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method for detecting airborne objects based on dual polarized radar radix fusion processing. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated;
and resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target exists, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated;
and resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims (8)

1. The empty drift detection method based on dual-polarized radar base fusion processing is characterized by comprising the following steps of:
acquiring echo data of the matched filtering double channels, and performing fast Fourier transform on the echo data to obtain a distance-Doppler echo;
calculating according to the distance-Doppler echo to obtain various polarization Doppler data parameters, wherein the polarization Doppler data parameters comprise the reflectivity of an H channel;
judging whether a suspected empty floating target exists or not by adopting a low-threshold constant false alarm probability detector for the reflectivity of the H channel on a radar PPI diagram;
if the suspected empty floating target is judged to exist, a membership function is constructed to fuzzify each polarized Doppler base data parameter, and a fuzzy function is generated, wherein the membership function is expressed as:
；
in the above, subscriptsRepresenting each of the polarization Doppler-based data parameters, i.e
Wherein->Representing differential reflectivity, +.>Indicating the speed of H channel, +.>Represents the spectral width of the H channel, < >>Representing the correlation coefficient of two channels, +.>Representing the difference in velocity of the two channels,representing the difference in spectral width of the two channels, +.>Values representing the respective polarization doppler data parameters, are given>Represents the first turning point of the membership function, < ->Representing the second turning point of the membership function, < ->A flag bit representing a membership function, anMembership functions corresponding to the polarization Doppler base data parameters are respectively as follows:
，/>，/>，/>，and->；
And resolving the fuzzy function by solving posterior probability, judging according to the posterior probability and a preset threshold, and determining whether a null drift target exists according to a judging result.
2. The method of airborne matter detection of claim 1, wherein said polarization doppler data base parameter further comprises: differential reflectivity, speed of H channel, spectral width of H channel, correlation coefficient of two channels, speed difference of two channels and spectral width difference of two channels.
3. The method of detecting airborne objects according to claim 2, wherein said determining whether a suspected airborne object exists using a low threshold constant false alarm probability detector for H-channel reflectivity on a radar PPI map comprises:
the low threshold constant false alarm probability detector comprises 3 units, namely a background unit, a protection unit and a unit to be detected;
calculating to obtain a detection threshold according to the number of the background units and the numerical value of each background unit;
and comparing the detection threshold value with the numerical value of the unit to be detected, if the numerical value of the unit to be detected is larger than the detection threshold value, judging that a suspected empty floating target exists, and judging that the suspected empty floating target does not exist on the side of the detection threshold value.
4. A method of detecting airborne matter as claimed in claim 3, wherein the detection threshold value calculated from the number and value of the background units is expressed by the following formula:
；
in the above-mentioned description of the invention,representing the detection threshold,/->Represents scale factors->Representing the number of said background units, +.>And a numerical value representing each of the background units.
5. The method of detecting airborne matter of claim 4, wherein said fuzzy function is:
；
in the above-mentioned description of the invention,representing the transpose.
6. The method of airborne matter detection of claim 5, wherein deblurring said blur function comprises: according to a fuzzy reasoning principle, different weights are given to each polarization Doppler base data parameter in the fuzzy function as follows:
；
then solving the posterior probability to perform the deblurring, and adopting the following formula:
；
in the above-mentioned description of the invention,representing the posterior probability,/->Representing summation(s)>Representing the blur function.
7. The method of detecting airborne objects of claim 6, wherein determining whether an airborne object exists based on the posterior probability and a predetermined threshold comprises: and if the posterior probability is larger than the preset threshold, determining that the null drift target exists, otherwise, determining that the null drift target does not exist.
8. Empty drift detection device based on double polarization radar base fusion processing, its characterized in that, the device includes:
the distance-Doppler echo obtaining module is used for obtaining echo data of the matched filtering double channels and carrying out fast Fourier transform on the echo data to obtain a distance-Doppler echo;
the polarization Doppler data base data parameter calculation module is used for calculating each polarization Doppler data base data parameter according to the distance-Doppler echo, wherein the polarization Doppler data base data parameter comprises the reflectivity of an H channel;
the low threshold constant false alarm probability detector judging module is used for judging whether a suspected empty floating target exists or not by adopting the low threshold constant false alarm probability detector for the reflectivity of the H channel on the radar PPI graph;
the fuzzy function generation module is used for constructing a membership function to fuzzify each polarized Doppler base data parameter and generating a fuzzy function if the suspected empty floating target exists, wherein the membership function is expressed as:
；
in the above, subscriptsRepresenting each of the polarization Doppler-based data parameters, i.e
Wherein->Representing differential reflectivity, +.>Indicating the speed of H channel, +.>Represents the spectral width of the H channel, < >>Representing the correlation coefficient of two channels, +.>Representing the difference in velocity of the two channels,representing two-waySpectral width difference of the channel->Values representing the respective polarization doppler data parameters, are given>Represents the first turning point of the membership function, < ->Representing the second turning point of the membership function, < ->A flag bit representing a membership function, anMembership functions corresponding to the polarization Doppler base data parameters are respectively as follows:
，/>，/>，/>，and->；
And the empty-floating target detection module is used for performing defuzzification on the fuzzy function by solving the posterior probability, judging according to the posterior probability and a preset threshold, and determining whether an empty-floating target exists according to a judgment result.
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