CN114114199A - Sorting method and sorting device for synthetic aperture radar signal parameters - Google Patents
Sorting method and sorting device for synthetic aperture radar signal parameters Download PDFInfo
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Abstract
The application discloses a sorting method and a sorting device for synthetic aperture radar signal parameters. The sorting method comprises the following steps: receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types; screening a first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signal to obtain a second parameter set; filling the second parameter set into a multidimensional coordinate system with dimensionality determined by the radar signal parameter category to obtain signal data spatial distribution; obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution; calculating a pulse repetition period of the synthetic aperture radar from the set of signal data; and outputting a signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period. And the automatic sorting of the synthetic aperture radar signals is realized by combining the intra-pulse characteristics and the multi-dimensional clustering sorting algorithm.
Description
Technical Field
The application relates to the technical field of electronic reconnaissance, in particular to a sorting method and a sorting device for synthetic aperture radar signal parameters.
Background
Synthetic Aperture Radar (hereinafter referred to as SAR) is carried on air and space platforms such as satellites, airplanes and unmanned aerial vehicles, can work in L, C, X, Ku and other radio frequency bands, and can perform long-distance high-resolution imaging reconnaissance on the ground all day long and all day long to obtain ground target information. For SAR reconnaissance threats, interference on SAR by transmitting electromagnetic signals is an effective countermeasure approach, and effective electromagnetic interference on SAR radar depends on real-time sorting out parameters of the transmitted signals. In recent years, various radar signal sorting technologies have been developed, such as a signal sorting technology based on a histogram algorithm, a signal sorting technology based on an artificial neural network algorithm, a signal sorting technology based on a K-Means algorithm, and the like.
In the process of realizing the prior art, the inventor finds that:
the existing sorting method aims to sort out all radar signal types and parameters in a measuring environment, and has respective defects aiming at the parameter measurement of SAR radar signals. The traditional histogram algorithm needs to process the arrival time of all pulse signals in the space, and the calculation amount is large. The artificial neural network algorithm has poor real-time performance and complex hardware implementation. The K-Means algorithm needs to predict the types of the radars in the space in advance, and is not suitable for automatic sorting of unknown radar signals and the like.
Therefore, a related technical scheme for sorting the synthetic aperture radar signal parameters is needed, which has the advantages of small calculation amount, simple hardware implementation, high instantaneity and pertinence.
Disclosure of Invention
The embodiment of the application provides a related technical scheme for sorting synthetic aperture radar signal parameters, which has the advantages of small calculated amount, simple hardware implementation, high instantaneity and pertinence, and is used for solving the technical problems of large calculated amount, complex hardware implementation, poor instantaneity, weak pertinence and the like in the existing sorting method.
The application provides a method for sorting synthetic aperture radar signal parameters, which comprises the following specific steps:
receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types;
screening the first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signal to obtain a second parameter set;
filling the second parameter set into a multidimensional coordinate system with dimensionality determined by the radar signal parameter category to obtain signal data spatial distribution;
obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution;
calculating a pulse repetition period of the synthetic aperture radar from the set of signal data;
and outputting a signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
Further, the radar signal parameter categories include pulse width, bandwidth, and frequency.
Further, the intra-pulse characteristics include at least one of chirp, large bandwidth, long pulse width, and specific operating frequency.
Further, obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution, and the method comprises the following specific steps:
determining a dimension data set corresponding to the signal data spatial distribution;
calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
and obtaining a signal data set of the synthetic aperture radar according to the data points.
Further, calculating a pulse repetition period of the synthetic aperture radar according to the signal data set, comprising the following specific steps:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
The application still provides a sorting unit to synthetic aperture radar signal parameter, includes:
the receiving module is used for receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types;
the screening module is used for screening the first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signals to obtain a second parameter set;
the coordinate processing module is used for filling the second parameter set into a multidimensional coordinate system with dimensions determined by the radar signal parameter types to obtain signal data spatial distribution;
the algorithm processing module is used for obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution;
a calculation module for calculating a pulse repetition period of the synthetic aperture radar according to the signal data set;
and the output module is used for outputting the signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
Further, the radar signal parameter categories include pulse width, bandwidth, and frequency.
Further, the intra-pulse characteristics include at least one of chirp, large bandwidth, long pulse width, and specific operating frequency.
Further, the algorithm processing module is specifically configured to:
determining a dimension data set corresponding to the signal data spatial distribution;
calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
and obtaining a signal data set of the synthetic aperture radar according to the data points.
Further, the calculation module is specifically configured to:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
The embodiment provided by the application has at least the following beneficial effects:
by combining intra-pulse characteristics and a multi-dimensional clustering sorting algorithm, the technical problems of large calculated amount, complex hardware implementation, poor real-time performance, weak pertinence and the like in the conventional sorting method are effectively solved, and the practicability of the sorting technology is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a flowchart of a method for sorting synthetic aperture radar signal parameters according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a method for acquiring a signal data set in a method for sorting synthetic aperture radar signal parameters according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a sorting apparatus for synthetic aperture radar signal parameters according to an embodiment of the present disclosure.
100 sorting unit to synthetic aperture radar signal parameter
11 receiving module
12 screening module
13 coordinate processing module
14 algorithm processing module
15 calculation module
And 16, outputting the module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Synthetic Aperture Radar (hereinafter referred to as SAR) is carried on air and space platforms such as satellites, airplanes and unmanned aerial vehicles, can work in L, C, X, Ku and other radio frequency bands, and can perform long-distance high-resolution imaging reconnaissance on the ground all day long and all day long to obtain ground target information.
Referring to fig. 1, a method for sorting synthetic aperture radar signal parameters provided in the present application includes the following specific steps:
s100: and receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types.
It will be appreciated that in the context of synthetic aperture radar radiation source signals, radiation source signals for other types of radar may also be present. The radiation source signal here can be understood as an electromagnetic wave emitted when the radar reconnaissance the target, and has certain radar signal parameters such as frequency, bandwidth, pulse width, amplitude, phase and the like. The radar signal parameters include conventional parameters and intra-pulse characteristic parameters. By analyzing the received radar radiation source signals, data can be classified and collected according to the radar signal parameter types, and a corresponding parameter set is obtained. The parameter set here corresponds to the first parameter set. It is clear that the first set of parameters does not comprise all detected radar signal parameters, but only a few key actually required radar signal parameters have to be collected. And data collection is carried out according to the radar signal parameter types, and the collected data set has strong pertinence and controllable data total amount. It should be noted that the synthetic aperture radar herein includes satellite-borne, airborne and missile-borne synthetic aperture radars. The operation modes of the synthetic aperture radar here include scanning, strip, beam, sliding beam, and the like.
Further, in a preferred embodiment of the present invention, the radar signal parameter categories include pulse width, bandwidth and frequency.
It should be noted that, the analysis of the target SAR scout signal at least needs to analyze the pulse width, bandwidth and frequency of the scout signal. Correspondingly, the first parameter set obtained through analysis at least comprises a pulse width attribute parameter, a bandwidth attribute parameter and a frequency attribute parameter of the scout signal. In addition, the radar signal parameter category may further include parameters such as amplitude, phase, power, and arrival time, and the corresponding first parameter set may further include attribute parameters such as amplitude, phase, power, and arrival time. In a specific implementation process, conventional parameters such as pulse width, bandwidth, frequency, power, arrival time and the like of radar signals in the surrounding environment and intra-pulse characteristic parameters can be measured through the radar receiver and the signal processing module.
S200: and screening the first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signal to obtain a second parameter set.
It is obvious that synthetic aperture radar signals have some significantly different characteristics compared to general radar signals. According to the characteristic information of the synthetic aperture radar signal, the synthetic aperture radar signal and the general radar signal can be effectively distinguished. In a specific embodiment, the collected first parameter set may be preliminarily screened according to a chirp characteristic of the SAR radar signal, to obtain a preliminarily subtracted second parameter set including parameters of the synthetic aperture radar signal. It should be noted that, the SAR radar signal is a chirp signal in the pulse, and a signal that does not meet the characteristic can be filtered out from the first parameter set according to the characteristics in the pulse. Obviously, the preliminary screening of the data set can also be performed by other specific intra-pulse features of the synthetic aperture radar signal, such as: large bandwidth, long pulse width, specific operating frequency, etc. The intra-pulse feature may be a single feature or a combination of several features.
Further, in a preferred embodiment of the present invention, the intra-pulse characteristic includes at least one of chirp, large bandwidth, long pulse width and specific operating frequency.
It will be appreciated that synthetic aperture radar signals have a wide variety of intra-pulse characteristics and can be distinguished from typical radar signals from a variety of angles. Such as: chirp modulation (LFM) is a spread spectrum modulation technique that does not require a pseudo-random code sequence. In the radar positioning technology, linear frequency modulation can increase the radio frequency pulse width, improve the average transmitting power, increase the communication distance and simultaneously keep enough signal spectrum width without reducing the distance resolution of the radar. It should be noted that the intra-pulse characteristics of the synthetic aperture radar signal include chirp, large bandwidth, long pulse width, specific operating frequency, and the like. In a specific implementation, any one of the intravascular features may be used for data set screening. For some applications with high requirements on data accuracy, intra-pulse features with relatively obvious features can be selected, or two or more intra-pulse features can be selected to be combined, and then corresponding data sets are screened according to the combined features.
S300: and filling the second parameter set into a multidimensional coordinate system with dimensionality determined by the radar signal parameter category to obtain signal data spatial distribution.
It should be noted that, for the preliminarily processed second parameter set to play its specific role, it needs to be converted into a specific working scenario. In one embodiment, assuming the selected radar signal parameter categories are pulse width, bandwidth and frequency, dimension 3 may be determined, and the multidimensional coordinate system is determined as a three-dimensional coordinate system. At this time, a three-dimensional coordinate system may be established with the pulse width as an x-axis, the bandwidth as a y-axis, and the frequency as a z-axis, and the diluted radar signal is filled into the three-dimensional coordinate system, that is, the second parameter set is correspondingly filled into the established three-dimensional coordinate system. Thereby, a spatial distribution of signal data of the second set of parameters in the three-dimensional coordinate system is obtained. Obviously, if the radar signal parameter category is other categories, the dimensions thereof are correspondingly determined, and accordingly, the dimensions of a specific multidimensional coordinate system can be determined.
S400: and obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution.
It will be appreciated that, after the determined spatial distribution of the signal data is obtained, the corresponding second parameter set has been mapped to the multidimensional coordinate system, and may participate in the subsequent sorting process of the synthetic aperture radar signal parameters in another data format. A dataset in a multidimensional coordinate system may be referred to as a multidimensional dataset. The process of dividing a collection of physical or abstract objects into classes composed of similar objects is called clustering. The multidimensional clustering sorting algorithm can be understood as a multidimensional clustering algorithm for sorting. The clustering algorithm can be understood as cluster analysis, which can also be called group analysis, is a statistical analysis method for researching (sample or index) classification problems, and is also an important algorithm for data mining. In a specific application process, assuming that the selected radar signal parameter categories are pulse width, bandwidth and frequency, the multidimensional clustering sorting algorithm can be used for calculating each data in the multidimensional data set according to the calculation conditions of the multidimensional clustering sorting algorithm. Therefore, data points belonging to the SAR radar are sorted according to the operation result, and a signal data set of the SAR radar signal consisting of pulse width, bandwidth, frequency information and the like can be obtained.
Specifically, in a preferred embodiment provided by this application, please refer to fig. 2, a signal data set of the synthetic aperture radar is obtained through a multidimensional clustering and sorting algorithm according to the spatial distribution of the signal data, which includes the following specific steps:
s401: determining a dimension data set corresponding to the signal data spatial distribution;
s402: calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
s403: and obtaining a signal data set of the synthetic aperture radar according to the data points.
It can be understood that the spatial distribution of the signal data is a direct representation of the original data set in the multidimensional coordinate system, and the mapping data of the spatial distribution of the signal data in the multidimensional coordinate system can be extracted to participate in the subsequent calculation process. In one embodiment, the selected radar signal parameter classes are assumed to be pulse width, bandwidth and frequencyAnd (4) determining the multi-dimensional coordinate system to be a three-dimensional coordinate system. At this time, a three-dimensional coordinate system may be established with the pulse width as the x-axis, the bandwidth as the y-axis, and the frequency as the z-axis, and the diluted radar signal is filled into the three-dimensional coordinate system, that is, the second parameter set is correspondingly filled into the established three-dimensional coordinate system, so that a dimension data set D = (D) including information of the pulse width, the bandwidth, the frequency, and the like may be obtained1(x1,y1,z1),d2(x2,y2,z2),…,dm(xm,ym,zm)). For the dimension data set D, the minimum radius and the minimum number minN can be preset, then a multidimensional clustering sorting algorithm is used for calculating each data in the dimension data set D, data points belonging to the SAR radar are sorted out, and a signal data set consisting of information such as pulse width, bandwidth and frequency of the SAR radar signal can be obtained. In particular generating the signal data set, the following steps may be taken:
step a: all elements in the dimension dataset D are labeled as "unvisited".
Step b: randomly selecting an element D in a dimension data set Dn(xn,yn,zn) And the element d isnThe label "unvisited" of (1) is updated to "visited", and examined in a three-dimensional coordinate system with dnWhether or not at least minN points are contained within a region centered and radius is the spatial radius.
Step c: if the check in step b is yes, a new class C is created, dnFill in class C, and will be given dnAll points contained within the region centered and radius in space are placed in the new data set N and step d is then performed. If the check in step b is "not yes", then d is addednAnd (4) marking the mark as a foreign point, screening out the dimension data set D, and then executing the step b.
Step d: randomly selecting a point d marked as 'unvisited' from the data set Nn', labeled "visited", then examined in a three-dimensional coordinate system with dnWhether or not the region's central radius is a spatial radius contains at leastminN point.
Step e: if the check in step d is "yes", it will be referred to as dn' centered, radius is all points contained within a region of spatial radius are placed in dataset N, while dn' if not already a point in any class, then dn' put into class C, then perform step f. If the check in step d is "no", step f is performed directly.
Step f: and judging whether all the points in the data set N are marked as 'visited', if so, executing the step g. If not, step d is performed.
Step g: at this time, all points in the class C are all pulse signals of the same SAR radar. And then the pulse width, bandwidth and frequency corresponding to the points are the pulse width, bandwidth and frequency of the SAR radar signal. For more accurate data, the pulse widths of the points are added and averaged, the bandwidth is added and averaged, and the frequency is added and averaged, namely the final pulse width, bandwidth and frequency of the SAR radar. Then step h is performed.
Step h: and judging whether all the points in the dimension data set D are marked as 'visited', if so, finishing the multi-dimensional clustering sorting, and obtaining several classes C, namely several SAR radar signals. If not, re-executing step b.
S500: and calculating the pulse repetition period of the synthetic aperture radar according to the signal data set.
It is noted that a pulse repetition period, also referred to as a Pulse Repetition Interval (PRI), is the time interval between one pulse and the next. The signal data set obtained through the operation of the multidimensional clustering sorting algorithm has large information content, and corresponding data can be selected from the signal data set to calculate the pulse repetition period of the synthetic aperture radar.
Further, in a preferred embodiment provided by the present application, the calculating a pulse repetition period of the synthetic aperture radar according to the signal data set includes the following specific steps:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
It will be appreciated that the signal data set contains the synthetic aperture radar pulse information. In calculating the pulse repetition period, each pulse in the synthetic aperture radar signal may be first sorted out from the signal data set, and the corresponding pulse arrival time may be calculated. Then, the pulse arrival time is processed by a sequential difference histogram method, and the pulse repetition Period (PRI) of the synthetic aperture radar is calculated. It is noted that the sequential difference histogram method here can be understood as a serial difference histogram algorithm (SDIF). The sequence difference histogram algorithm (SDIF) is an improved algorithm based on the cumulative difference histogram algorithm (CDIF).
S600: and outputting a signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
It is noted that the signal data set contains a plurality of important parameters of the synthetic aperture radar, and the pulse repetition period is also one of the important parameters of the synthetic aperture radar. The signal data set and pulse repetition period cover substantially all important parameters of the synthetic aperture radar, whereby the synthetic aperture radar can be effectively distinguished from general radars. The signal data set here generally includes pulse width, bandwidth, frequency, etc. After parameters such as pulse width, bandwidth, frequency, repetition period and the like of all SAR radar signals are obtained through measurement and calculation, the parameters can be transmitted to an interference module in real time to carry out subsequent interference work.
The beneficial effect of this application mainly has: the method has the advantages of strong real-time performance, strong pertinence, small calculated amount and simple hardware implementation. It should be noted that, to realize interference on the SAR radar signal, the operations of detecting and transmitting the interference signal must be completed within the scanning time of the main lobe. Moreover, most of the scanning time needs to be reserved for transmitting interference signals, and the requirement on the real-time performance of reconnaissance is high. Usually, the scout scanning time of the main lobe of the SAR radar can be completed only by seconds. The multi-dimensional clustering sorting method can sort out the targets only by tens of milliseconds, and the remaining time can be used for transmitting interference signals. Because SAR radar signals generally have the characteristics of large bandwidth, long pulse width, linear frequency modulation, specific working frequency and the like, most other radar signals can be screened out by utilizing the characteristics, the data volume is effectively reduced, and the calculation speed is improved.
Referring to fig. 3, the present application further provides a sorting apparatus 100 for sorting synthetic aperture radar signal parameters, comprising:
the receiving module 11 is configured to receive and process radar radiation source signals to obtain a first parameter set collected according to radar signal parameter categories;
the screening module 12 is configured to screen the first parameter set according to an intra-pulse feature of a synthetic aperture radar signal to obtain a second parameter set;
the coordinate processing module 13 is configured to fill the second parameter set into a multidimensional coordinate system with dimensions determined by the radar signal parameter categories, so as to obtain signal data spatial distribution;
the algorithm processing module 14 is configured to obtain a signal data set of the synthetic aperture radar through a multidimensional clustering sorting algorithm according to the signal data spatial distribution;
a calculation module 15, configured to calculate a pulse repetition period of the synthetic aperture radar according to the signal data set;
and the output module 16 is configured to output a signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
It will be appreciated that in the context of synthetic aperture radar radiation source signals, radiation source signals for other types of radar may also be present. The radiation source signal here can be understood as an electromagnetic wave emitted when the radar reconnaissance the target, and has certain radar signal parameters such as frequency, bandwidth, pulse width, amplitude, phase and the like. The radar signal parameters include conventional parameters and intra-pulse characteristic parameters. By analyzing the received radar radiation source signals, data can be classified and collected according to the radar signal parameter types, and a corresponding parameter set is obtained. The parameter set here corresponds to the first parameter set. It is clear that the first set of parameters does not comprise all detected radar signal parameters, but only a few key actually required radar signal parameters have to be collected. And data collection is carried out according to the radar signal parameter types, and the collected data set has strong pertinence and controllable data total amount. It should be noted that the synthetic aperture radar herein includes satellite-borne, airborne and missile-borne synthetic aperture radars. The operation modes of the synthetic aperture radar here include scanning, strip, beam, sliding beam, and the like.
Synthetic aperture radar signals have some significantly different characteristics compared to typical radar signals. According to the characteristic information of the synthetic aperture radar signal, the synthetic aperture radar signal and the general radar signal can be effectively distinguished. In a specific embodiment, the collected first parameter set may be preliminarily screened according to a chirp characteristic of the SAR radar signal, to obtain a preliminarily subtracted second parameter set including parameters of the synthetic aperture radar signal. It should be noted that, the SAR radar signal is a chirp signal in the pulse, and a signal that does not meet the characteristic can be filtered out from the first parameter set according to the characteristics in the pulse. Obviously, the preliminary screening of the data set can also be performed by other specific intra-pulse features of the synthetic aperture radar signal, such as: large bandwidth, long pulse width, specific operating frequency, etc. The intra-pulse feature may be a single feature or a combination of several features.
It should be noted that, for the preliminarily processed second parameter set to play its specific role, it needs to be converted into a specific working scenario. In one embodiment, assuming the selected radar signal parameter categories are pulse width, bandwidth and frequency, dimension 3 may be determined, and the multidimensional coordinate system is determined as a three-dimensional coordinate system. At this time, a three-dimensional coordinate system may be established with the pulse width as an x-axis, the bandwidth as a y-axis, and the frequency as a z-axis, and the diluted radar signal is filled into the three-dimensional coordinate system, that is, the second parameter set is correspondingly filled into the established three-dimensional coordinate system. Thereby, a spatial distribution of signal data of the second set of parameters in the three-dimensional coordinate system is obtained. Obviously, if the radar signal parameter category is other categories, the dimensions thereof are correspondingly determined, and accordingly, the dimensions of a specific multidimensional coordinate system can be determined.
Obviously, after the determined spatial distribution of the signal data is obtained, the corresponding second parameter set is mapped to the multidimensional coordinate system, and may participate in the subsequent sorting process of the synthetic aperture radar signal parameters in another data form. A dataset in a multidimensional coordinate system may be referred to as a multidimensional dataset. The process of dividing a collection of physical or abstract objects into classes composed of similar objects is called clustering. The multidimensional clustering sorting algorithm can be understood as a multidimensional clustering algorithm for sorting. The clustering algorithm can be understood as cluster analysis, which can also be called group analysis, is a statistical analysis method for researching (sample or index) classification problems, and is also an important algorithm for data mining. In a specific application process, assuming that the selected radar signal parameter categories are pulse width, bandwidth and frequency, the multidimensional clustering sorting algorithm can be used for calculating each data in the multidimensional data set according to the calculation conditions of the multidimensional clustering sorting algorithm. Therefore, data points belonging to the SAR radar are sorted according to the operation result, and a signal data set of the SAR radar signal consisting of pulse width, bandwidth, frequency information and the like can be obtained.
It is noted that a pulse repetition period, also referred to as a Pulse Repetition Interval (PRI), is the time interval between one pulse and the next. The signal data set obtained through the operation of the multidimensional clustering sorting algorithm has large information content, and corresponding data can be selected from the signal data set to calculate the pulse repetition period of the synthetic aperture radar.
The signal data set contains a plurality of important parameters of the synthetic aperture radar, and the pulse repetition period is also one of the important parameters of the synthetic aperture radar. The signal data set and pulse repetition period cover substantially all important parameters of the synthetic aperture radar, whereby the synthetic aperture radar can be effectively distinguished from general radars. The signal data set here generally includes pulse width, bandwidth, frequency, etc. After parameters such as pulse width, bandwidth, frequency, repetition period and the like of all SAR radar signals are obtained through measurement and calculation, the parameters can be transmitted to an interference module in real time to carry out subsequent interference work.
Further, in a preferred embodiment of the present invention, the radar signal parameter categories include pulse width, bandwidth and frequency.
It should be noted that, the analysis of the target SAR scout signal at least needs to analyze the pulse width, bandwidth and frequency of the scout signal. Correspondingly, the first parameter set obtained through analysis at least comprises a pulse width attribute parameter, a bandwidth attribute parameter and a frequency attribute parameter of the scout signal. In addition, the radar signal parameter category may further include parameters such as amplitude, phase, power, and arrival time, and the corresponding first parameter set may further include attribute parameters such as amplitude, phase, power, and arrival time. In a specific implementation process, conventional parameters such as pulse width, bandwidth, frequency, power, arrival time and the like of radar signals in the surrounding environment and intra-pulse characteristic parameters can be measured through the radar receiver and the signal processing module.
Further, in a preferred embodiment of the present invention, the intra-pulse characteristic includes at least one of chirp, large bandwidth, long pulse width and specific operating frequency.
It will be appreciated that synthetic aperture radar signals have a wide variety of intra-pulse characteristics and can be distinguished from typical radar signals from a variety of angles. Such as: chirp modulation (LFM) is a spread spectrum modulation technique that does not require a pseudo-random code sequence. In the radar positioning technology, linear frequency modulation can increase the radio frequency pulse width, improve the average transmitting power, increase the communication distance and simultaneously keep enough signal spectrum width without reducing the distance resolution of the radar. It should be noted that the intra-pulse characteristics of the synthetic aperture radar signal include chirp, large bandwidth, long pulse width, specific operating frequency, and the like. In a specific implementation, any one of the intravascular features may be used for data set screening. For some applications with high requirements on data accuracy, intra-pulse features with relatively obvious features can be selected, or two or more intra-pulse features can be selected to be combined, and then corresponding data sets are screened according to the combined features.
Further, in a preferred embodiment provided in this application, the algorithm processing module 14 is specifically configured to:
determining a dimension data set corresponding to the signal data spatial distribution;
calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
and obtaining a signal data set of the synthetic aperture radar according to the data points.
It can be understood that the spatial distribution of the signal data is a direct representation of the original data set in the multidimensional coordinate system, and the mapping data of the spatial distribution of the signal data in the multidimensional coordinate system can be extracted to participate in the subsequent calculation process. In one embodiment, assuming the selected radar signal parameter categories are pulse width, bandwidth, and frequency, a three-dimensional coordinate system can be determined. At this time, a three-dimensional coordinate system may be established with the pulse width as the x-axis, the bandwidth as the y-axis, and the frequency as the z-axis, and the diluted radar signal is filled into the three-dimensional coordinate system, that is, the second parameter set is correspondingly filled into the established three-dimensional coordinate system, so that a dimension data set D = (D) including information of the pulse width, the bandwidth, the frequency, and the like may be obtained1(x1,y1,z1),d2(x2,y2,z2),…,dm(xm,ym,zm)). For the dimension data set D, the minimum radius and the minimum number minN can be preset, then a multidimensional clustering sorting algorithm is used for calculating each data in the dimension data set D, data points belonging to the SAR radar are sorted out, and a signal data set consisting of information such as pulse width, bandwidth and frequency of the SAR radar signal can be obtained. In particular generating the signal data set, the following steps may be taken:
step a: all elements in the dimension dataset D are labeled as "unvisited".
Step b: number of dimensionRandomly selecting an element D from the data set Dn(xn,yn,zn) And the element d isnThe label "unvisited" of (1) is updated to "visited", and examined in a three-dimensional coordinate system with dnWhether or not at least minN points are contained within a region centered and radius is the spatial radius.
Step c: if the check in step b is yes, a new class C is created, dnFill in class C, and will be given dnAll points contained within the region centered and radius in space are placed in the new data set N and step d is then performed. If the check in step b is "not yes", then d is addednAnd (4) marking the mark as a foreign point, screening out the dimension data set D, and then executing the step b.
Step d: randomly selecting a point d marked as 'unvisited' from the data set Nn', labeled "visited", then examined in a three-dimensional coordinate system with dn' is the center, radius is the spatial radius, and contains at least minN points.
Step e: if the check in step d is "yes", it will be referred to as dn' centered, radius is all points contained within a region of spatial radius are placed in dataset N, while dn' if not already a point in any class, then dn' put into class C, then perform step f. If the check in step d is "no", step f is performed directly.
Step f: and judging whether all the points in the data set N are marked as 'visited', if so, executing the step g. If not, step d is performed.
Step g: at this time, all points in the class C are all pulse signals of the same SAR radar. And then the pulse width, bandwidth and frequency corresponding to the points are the pulse width, bandwidth and frequency of the SAR radar signal. For more accurate data, the pulse widths of the points are added and averaged, the bandwidth is added and averaged, and the frequency is added and averaged, namely the final pulse width, bandwidth and frequency of the SAR radar. Then step h is performed.
Step h: and judging whether all the points in the dimension data set D are marked as 'visited', if so, finishing the multi-dimensional clustering sorting, and obtaining several classes C, namely several SAR radar signals. If not, re-executing step b.
Further, in a preferred embodiment provided in this application, the calculating module 15 is specifically configured to:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
It will be appreciated that the signal data set contains the synthetic aperture radar pulse information. In calculating the pulse repetition period, each pulse in the synthetic aperture radar signal may be first sorted out from the signal data set, and the corresponding pulse arrival time may be calculated. Then, the pulse arrival time is processed by a sequential difference histogram method, and the pulse repetition Period (PRI) of the synthetic aperture radar is calculated. It is noted that the sequential difference histogram method here can be understood as a serial difference histogram algorithm (SDIF). The sequence difference histogram algorithm (SDIF) is an improved algorithm based on the cumulative difference histogram algorithm (CDIF).
The beneficial effect of this application mainly has: the method has the advantages of strong real-time performance, strong pertinence, small calculated amount and simple hardware implementation. It should be noted that, to realize interference on the SAR radar signal, the operations of detecting and transmitting the interference signal must be completed within the scanning time of the main lobe. Moreover, most of the scanning time needs to be reserved for transmitting interference signals, and the requirement on the real-time performance of reconnaissance is high. Usually, the scout scanning time of the main lobe of the SAR radar can be completed only by seconds. The multi-dimensional clustering sorting method can sort out the targets only by tens of milliseconds, and the remaining time can be used for transmitting interference signals. Because SAR radar signals generally have the characteristics of large bandwidth, long pulse width, linear frequency modulation, specific working frequency and the like, most other radar signals can be screened out by utilizing the characteristics, the data volume is effectively reduced, and the calculation speed is improved.
The embodiment provided by the application has at least the following beneficial effects:
by combining intra-pulse characteristics and a multi-dimensional clustering sorting algorithm, the technical problems of large calculated amount, complex hardware implementation, poor real-time performance, weak pertinence and the like in the conventional sorting method are effectively solved, and the practicability of the sorting technology is improved.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for sorting synthetic aperture radar signal parameters is characterized by comprising the following specific steps:
receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types;
screening the first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signal to obtain a second parameter set;
filling the second parameter set into a multidimensional coordinate system with dimensionality determined by the radar signal parameter category to obtain signal data spatial distribution;
obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution;
calculating a pulse repetition period of the synthetic aperture radar from the set of signal data;
and outputting a signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
2. The sorting method of claim 1, wherein the radar signal parameter categories include pulse width, bandwidth, and frequency.
3. The sorting method according to claim 1, wherein the intra-pulse characteristics include at least one of chirp, large bandwidth, long pulse width, and specific operating frequency.
4. The sorting method according to claim 1, wherein the signal data set of the synthetic aperture radar is obtained by a multidimensional clustering sorting algorithm according to the signal data spatial distribution, and the method comprises the following specific steps:
determining a dimension data set corresponding to the signal data spatial distribution;
calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
and obtaining a signal data set of the synthetic aperture radar according to the data points.
5. The sorting method according to claim 1, wherein calculating a pulse repetition period of the synthetic aperture radar from the set of signal data comprises the specific steps of:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
6. A sorting device for synthetic aperture radar signal parameters, comprising:
the receiving module is used for receiving and processing radar radiation source signals to obtain a first parameter set collected according to the radar signal parameter types;
the screening module is used for screening the first parameter set according to the intra-pulse characteristics of the synthetic aperture radar signals to obtain a second parameter set;
the coordinate processing module is used for filling the second parameter set into a multidimensional coordinate system with dimensions determined by the radar signal parameter types to obtain signal data spatial distribution;
the algorithm processing module is used for obtaining a signal data set of the synthetic aperture radar through a multi-dimensional clustering sorting algorithm according to the signal data spatial distribution;
a calculation module for calculating a pulse repetition period of the synthetic aperture radar according to the signal data set;
and the output module is used for outputting the signal parameter set of the synthetic aperture radar according to the signal data set and the pulse repetition period.
7. The sorting apparatus according to claim 6, wherein the radar signal parameter categories include pulse width, bandwidth, and frequency.
8. The sorting apparatus according to claim 6, wherein the intra-pulse characteristics include at least one of chirp, large bandwidth, long pulse width, and specific operating frequency.
9. The sorting apparatus of claim 6, wherein the algorithmic processing module is specifically configured to:
determining a dimension data set corresponding to the signal data spatial distribution;
calculating elements in the dimension data set by using a multi-dimensional clustering sorting algorithm according to a preset minimum radius and a preset minimum number, and sorting out data points of the synthetic aperture radar;
and obtaining a signal data set of the synthetic aperture radar according to the data points.
10. The sorting apparatus of claim 6, wherein the calculation module is specifically configured to:
calculating pulse arrival times in the signal data set;
and calculating the pulse repetition period of the synthetic aperture radar by a sequential histogram method according to the pulse arrival time.
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