Micro Synthetic Aperture Radar Based Scene Matching Guidance System

Abstract

The present invention relates to the technical field of radar data processing, and discloses a scene matching guidance system based on a micro synthetic aperture radar, including a multi-dimensional acquisition module and an intelligent matching module. The system obtains SAR image data of all target areas and SAR image data provided in real time by echo signals through the multi-dimensional acquisition module, classifies and forms a data set. The multi-dimensional acquisition module performs standardization processing on the data set, analyzes and generates a digital elevation model. The intelligent matching module analyzes the authenticity of the SAR image of each target area, generates a corresponding credibility index, sets a monitoring period with a fixed duration, and then analyzes the fluctuation index of the real-time signal intensity and the matching index of the SAR image to quantify the data quality and matching potential. The dynamic monitoring has high image accuracy. The intelligent matching module sets a fluctuation threshold to determine whether there is a delay problem with the SAR image, and then performs scene matching guidance and synchronizes the flight path according to the credibility index, the matching index, and the digital elevation model. The scene matching guidance has strong applicability.

Description

Technical Field

[0001] The present invention relates to the technical field of radar data processing, and specifically to a scene matching guidance system based on a micro synthetic aperture radar. Background Art

[0002] A micro synthetic aperture radar is a miniaturized synthetic aperture radar system, which is suitable for aircraft, missiles, small satellites, vehicles or other mobile devices, etc. by reducing the system size, cost and power consumption. Although it is of micro size, the synthetic aperture radar technology still has a high resolution and can synthesize a longer effective beam to achieve high-resolution imaging ability. The micro synthetic aperture radar emits microwave signals to the target area through the radar host. These signals will be reflected back after encountering the target. The radar antenna sequentially records the echo signals reflected back at different positions, and then, according to the phase and amplitude information of these signals, uses the relative motion between the target and the radar to simulate the imaging of a large aperture antenna. Range focusing is to determine the distance of the target by analyzing the delay information in the echo signal, that is, to calculate the distance between the target and the radar according to the time elapsed from the radar transmitting the signal to receiving the echo. Azimuth focusing is to use the Doppler effect generated by the relative motion between the radar and the target to determine the position of the target in the azimuth direction according to the Doppler frequency shift. By focusing on the information in these two directions, a high-resolution two-dimensional image of the target is finally obtained. In the actual use process, the frequency band of the microwave signals emitted by the micro synthetic aperture radar covers multiple bands such as Ku, X, L, Ka, W, etc., which can meet the requirements of different application scenarios, and is equipped with an advanced data processing system, which can process and analyze the monitoring data in real time and then transmit it to the ground station or command center in real time through the communication system. This provides timely and accurate positioning information for decision-makers and helps to better guide the operation.

[0003] At present, the scene matching guidance system of traditional micro synthetic aperture radar mainly relies on static data for analysis. This method is easily affected by various factors such as atmospheric interference, resulting in low guidance efficiency and poor accuracy. In addition, the traditional system uses a single matching mechanism and is difficult to adapt to rapidly changing scenes, so its reference value in actual use is low. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] Aiming at the deficiencies of the prior art, the present invention provides a scene matching guidance system based on a micro synthetic aperture radar, which has the advantages of high dynamic monitoring image accuracy, strong applicability of scene matching guidance, etc., and solves the problems of low efficiency, poor accuracy and low reference value of the scene matching guidance system of traditional micro synthetic aperture radar.

[0006] (II) Technical Solutions

[0007] To achieve the above object, the present invention provides the following technical solutions: A scene matching guidance system based on a micro synthetic aperture radar, comprising a multi-dimensional acquisition module and an intelligent matching module;

[0008] The multi-dimensional acquisition module is composed of a reference scene unit, a radar scene unit and a preprocessing unit. The reference scene unit collects reference data sets through a network connection to a mapping satellite. The reference data sets include SAR image data of all target areas. The radar scene unit collects real-time data sets through a network connection to a micro synthetic aperture radar. The real-time data sets include SAR image data provided by echo signals in real time. The preprocessing unit performs standardization processing on the reference data sets and the real-time data sets, and analyzes and generates a digital elevation model and transmits it to the intelligent matching module through a network;

[0009] The intelligent matching module is composed of an image evaluation unit, a real-time analysis unit and a scene matching unit. The image evaluation unit analyzes the authenticity of the SAR image of each target area according to the reference data sets and generates a corresponding credibility index The real-time analysis unit is set with a monitoring period of a fixed duration and combines with the real-time data sets to analyze the fluctuation index of the real-time signal intensity and the matching index of the SAR image The scene matching unit is set with a fluctuation threshold within a fixed range and combines with the fluctuation index to judge whether there is a delay problem in the SAR image, and then according to the credibility index , the matching index , the digital elevation model perform scene matching guidance and synchronous track.

[0010] Preferably, the expression of the reference data sets is , to represent the SAR image data of the first target area to the th target area. The SAR image data of the target area includes echo signal intensity, ground distance, slant range and layover area, represents the area of a single target area.

[0011] Preferably, the expression of the real-time data sets is , to represent the SAR image data provided by the echo signal for the first time to the th time. The SAR image data provided by the echo signal includes real-time signal intensity, azimuth resolution, range resolution and signal-to-noise ratio, Indicates the time point for obtaining the SAR image data of the echo signal.

[0012] Preferably, the standardization process is as follows:

[0013] Collect the meteorological parameters of all target areas through network connection to the big data platform. The meteorological parameters include temperature, air pressure, wind speed, wind direction, aerosol mass concentration, and atmospheric stratification stability;

[0014] Use the MODTRAN atmospheric radiative transfer model, input the meteorological parameters of all target areas, remove the noise of signal attenuation and phase delay, and eliminate the distortion problem of the atmosphere on the SAR images in the reference data set and the real-time data set.

[0015] Preferably, the digital elevation model The analysis process is as follows:

[0016] Collect the geographical information of all target areas through network connection to the big data platform. The geographical information includes longitude and latitude coordinates, altitude, location identification, and topography;

[0017] Use image processing software, combine the geographical information of all target areas and the reference data set after standardization, and establish a digital elevation model , which is used to eliminate the geometric distortion problem of the SAR images in the reference data set and the real-time data set.

[0018] Preferably, the credibility index The calculation process is as follows:

[0019] According to the reference data set, extract the SAR image data of the th target area, and mark the echo signal strength of the th target area as , mark the ground distance of the th target area as , mark the slant range of the th target area as , mark the layover area of the th target area as , mark the area of the th target area as ,

[0020] ;

[0021] In the formula, represents the weight for the echo signal strength, represents the weight for the ratio of ground distance to slant range, represents the weight for the ratio of layover area to target area, 、 and are both constants, and , represents that according to , and weights, the credibility index of the th target area is calculated as .

[0022] Preferably, the calculation process of the fluctuation index is as follows:

[0023] According to the real-time data set, the real-time signal strength within the monitoring period is statistically analyzed and marked as , to represent the real-time signal strengths of the SAR image data provided for the first time to the th time;

[0024] ;

[0025] In the formula, represents the average value of the real-time signal strength within the monitoring period , represents the real-time signal strength of the th time of providing SAR image data, , represents that according to the standard deviation formula, the fluctuation index of the real-time signal strength within the monitoring period is calculated.

[0026] Preferably, the calculation process of the matching index is as follows:

[0027] According to the real-time data set, the SAR image data provided for the th time of the echo signal is extracted, and the azimuth resolution of the th SAR image is marked as , the range resolution of the th SAR image is marked as , and the signal-to-noise ratio of the th SAR image is marked as ;

[0028] ;

[0029] In the formula, represents the weight for the azimuth resolution, represents the weight for the range resolution, represents the weight for the signal-to-noise ratio, , and are all constants, and , represents calculating the matching index 、 and weight, and obtaining the matching index of the th SAR image. .

[0030] Preferably, when the fluctuation index exceeds the fluctuation threshold , it indicates that there is a delay problem in the SAR image, and it is recommended to adjust the time difference and then perform scene matching guidance.

[0031] Preferably, the scene matching unit arranges the target areas according to the credibility index from high to low. When the fluctuation index is included in the fluctuation threshold , preferably select the SAR image with a high matching index and the target area with a high credibility index for scene matching guidance, and synchronize the track in the digital elevation model according to the matching result.

[0032] Compared with the prior art, the present invention provides a scene matching guidance system based on a micro synthetic aperture radar, having the following beneficial effects:

[0033] 1. The present invention connects a mapping satellite and a micro synthetic aperture radar through a multi-dimensional acquisition module network, obtains SAR image data of all target areas and SAR image data provided by real-time echo signals, classifies and forms a reference data set and a real-time data set. The multi-dimensional acquisition module uses the MODTRAN atmospheric radiation transfer model, inputs meteorological parameters of all target areas, removes noise of signal attenuation and phase delay, eliminates the distortion problem of the atmosphere on the SAR images in the reference data set and the real-time data set, uses image processing software, combines geographical information of all target areas and the reference data set after standardization processing, and establishes a digital elevation model , which is used to eliminate the geometric distortion problem of the SAR images in the reference data set and the real-time data set, significantly improves the authenticity and consistency of the SAR images. The intelligent matching module analyzes the authenticity of the SAR image of each target area according to the reference data set, generates a corresponding credibility index , sets a monitoring period with a fixed duration , then analyzes the fluctuation index of the real-time signal intensity and the matching index of the SAR image, quantifies the data quality and matching potential, and has high dynamic monitoring image accuracy.

[0034] 2. The intelligent matching module of the present invention sets a fluctuation threshold within a fixed range to determine whether there is a delay problem in the SAR image. When the fluctuation index exceeds the fluctuation threshold , it indicates that there is a delay problem in the SAR image. It is recommended to adjust the time difference and then perform scene matching guidance to avoid incorrect matching caused by unstable data. The scene matching unit arranges the target areas according to the credibility index from high to low. When the fluctuation index is included in the fluctuation threshold , the SAR image with a high matching index is preferentially selected for scene matching guidance with the target area with a high credibility index . This effectively improves the guidance accuracy, and according to the matching result, the track is synchronized in the digital elevation model . The scene matching guidance has strong applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a system flowchart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] Since the traditional micro synthetic aperture radar scene matching guidance system mainly relies on static data for analysis, this method is easily affected by various factors such as atmospheric interference, resulting in low guidance efficiency and poor accuracy. In addition, the traditional system uses a single matching mechanism and is difficult to adapt to rapidly changing scenes, with low reference value in actual use. Therefore, a scene matching guidance system based on a micro synthetic aperture radar is provided. Please refer to Figure 1 , the scene matching guidance system based on a micro synthetic aperture radar includes a multi-dimensional acquisition module and an intelligent matching module;

[0038] The multi-dimensional acquisition module consists of a reference scene unit, a radar scene unit, and a preprocessing unit. The reference scene unit collects a reference data set through a network connection to a mapping satellite. The reference data set includes SAR image data of all target areas. The expression of the reference data set is , to represent the first target area to the SAR image data of a target area, where the SAR image data of the target area includes echo signal intensity, ground range, slant range, and layover area. Represents the area of a single target area;

[0039] The radar scene unit acquires real-time data sets by connecting to a micro synthetic aperture radar through a network. The real-time data sets include SAR image data provided by the echo signal in real time. The expression of the real-time data sets is , to Represents the SAR image data provided by the echo signal from the first time to the th time. The SAR image data provided by the echo signal includes real-time signal intensity, azimuth resolution, range resolution, and signal-to-noise ratio. Represents the time point for acquiring the SAR image data of the echo signal, covering the static geographical information and dynamic real-time signals of the target area. The combination of the two can comprehensively depict the electromagnetic characteristics and geometric features of the target area;

[0040] The preprocessing unit performs standardization processing on the reference data set and the real-time data set, and analyzes and generates a digital elevation model , and transmits it to the intelligent matching module through the network;

[0041] The standardization processing process is as follows:

[0042] Acquire the meteorological parameters of all target areas by connecting to a big data platform through the network. The meteorological parameters include temperature, air pressure, wind speed, wind direction, aerosol mass concentration, and atmospheric stability;

[0043] Use the MODTRAN atmospheric radiative transfer model, input the meteorological parameters of all target areas, remove the noise of signal attenuation and phase delay, and eliminate the distortion problem of the atmosphere on the SAR images in the reference data set and the real-time data set;

[0044] Digital elevation model The analysis process is as follows:

[0045] Acquire the geographical information of all target areas by connecting to a big data platform through the network. The geographical information includes longitude and latitude coordinates, altitude, location identifier, and topography;

[0046] Use image processing software, combine the geographical information of all target areas and the standardized reference data set, and establish a digital elevation model , which is used to eliminate the geometric distortion problem of the SAR images in the reference data set and the real-time data set, and significantly improve the authenticity and consistency of the SAR images;

[0047] The intelligent matching module consists of an image evaluation unit, a real-time analysis unit, and a scene matching unit. The image evaluation unit analyzes the authenticity of the SAR image of each target area based on the reference data set and generates a corresponding credibility index. , the credibility index The calculation process is as follows:

[0048] According to the reference data set, extract the SAR image data of the th target area, and mark the echo signal strength of the th target area as , mark the ground distance of the th target area as , mark the slant range of the th target area as , mark the layover area of the th target area as , mark the area of the th target area as ,

[0049] ;

[0050] In the formula, represents the weight for the echo signal strength, represents the weight for the ratio of the ground distance to the slant range, represents the weight for the ratio of the layover area to the target area, , and are all constants, and , represents calculating the credibility index , and of the th target area according to the weights, and so on. Each target area has a corresponding credibility index , ensuring the balance of subsequent evaluation results;

[0051] The real-time analysis unit sets a monitoring period with a fixed duration , and then analyzes the fluctuation index of the real-time signal strength and the matching index of the SAR image in combination with the real-time data set;

[0052] The calculation process of the fluctuation index is as follows:

[0053] According to the real-time data set, count the real-time signal strength within the monitoring period and mark it as , to represent the real-time signal intensity of the SAR image data provided for the first to the th time;

[0054] ;

[0055] In the formula, represents the average value of the real-time signal intensity within the monitoring period , represents the real-time signal intensity of the th time the SAR image data is provided, , represents the fluctuation index of the real-time signal intensity calculated according to the standard deviation formula within the monitoring period . The smaller the fluctuation index , the more stable the echo signal and the better the quality of the SAR image; The calculation process of the matching index

[0056] is as follows: Extract the SAR image data provided for the

[0057] th time of the echo signal from the real-time data set, and mark the azimuth resolution of the th SAR image as , mark the range resolution of the th SAR image as , and mark the signal-to-noise ratio of the th SAR image as ; ;

[0058] ;

[0059] In the formula, represents the weight for the azimuth resolution, represents the weight for the range resolution, represents the weight for the signal-to-noise ratio, , and are all constants, and , represents the matching index , and of the th SAR image calculated according to the weights, quantifying the data quality and matching potential, and dynamically monitoring the high image accuracy;

[0060] The scene matching unit is set with a fixed range of fluctuation thresholds ​, determine whether there is a delay problem in the SAR image, and the fluctuation index exceeds the fluctuation threshold indicating that there is a delay problem in the SAR image. It is recommended to adjust the time difference and then perform scene matching guidance to avoid mis-matching caused by unstable data. The scene matching unit arranges the target areas according to the credibility index from high to low. When the fluctuation index is included in the fluctuation threshold , preferentially select the SAR image with a high matching index and the target area with a high credibility index for scene matching guidance, which effectively improves the guidance accuracy. According to the matching result, synchronize the track in the digital elevation model . Specifically, in the application scenario of disaster monitoring, preferentially match the areas with stable terrain and high signal-to-noise ratio, which can ensure the credibility of the disaster situation assessment. In the application scenario of military navigation, it is possible to preferentially select the flight path with the smallest geometric distortion and stable real-time signal. The scene matching guidance has strong applicability.

[0061] Example 1: In this experiment, a drone equipped with a micro synthetic aperture radar was selected as the experimental object. After statistics, within 5 minutes, the real-time signal intensities of the 5 echo signals providing SAR image data were 4V, 8V, 6V, 5V, and 7V respectively. The calculation process of the fluctuation index of the drone SAR image data is as follows:

[0062] ;

[0063] In the formula, represents the average value of the real-time signal intensities within 5 minutes, represents the real-time signal intensity of the first time providing SAR image data, . According to the standard deviation formula, the fluctuation index of the drone SAR image data within 5 minutes is calculated to be 2V. The fluctuation threshold is set to 1 - 5V. After judgment, the fluctuation index of the drone SAR image data is included in the fluctuation threshold . The SAR image has no delay problem. Preferentially select the SAR image with a high matching index and the target area with a high credibility index for scene matching guidance, and synchronize the track in the digital elevation model according to the matching result.

[0064] Example 2: In this experiment, an aircraft equipped with a miniature synthetic aperture radar was selected as the experimental object. After monitoring, the aircraft has received 3 sets of SAR image data provided by the echo signal. Among them, the azimuth resolution of the first set of SAR images is 0.5 meters, the range resolution is 1.0 meter, and the signal-to-noise ratio is 20 dB. The matching index of the first set of SAR image data The calculation process is as follows: ;

[0065] In the formula, represents the weight for the azimuth resolution, represents the weight for the range resolution, represents the weight for the signal-to-noise ratio, , and are all constants, and , according to , and weights, the matching index of the first set of SAR image data is calculated to be 6.5. By analogy, the matching index of the second set of SAR image data is 5.5, and the matching index of the third set of SAR image data is 5.0. After judgment, the first set of SAR image data with a matching index of 6.5 and a high reliability index are preferentially selected for scene matching guidance of the target area, and according to the matching result, the track is synchronized in the digital elevation model .

[0066] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A scene matching guidance system based on a micro synthetic aperture radar, characterized in that: It includes a multi-dimensional acquisition module and an intelligent matching module; The multi-dimensional acquisition module consists of a reference image unit, a radar image unit, and a preprocessing unit. The reference image unit acquires a reference data set by connecting to a mapping satellite through a network. The reference data set includes SAR image data of all target areas. The radar image unit acquires a real-time data set by connecting to a micro synthetic aperture radar through a network. The real-time data set includes SAR image data provided by echo signals in real time. The preprocessing unit performs normalization processing on the reference data set and the real-time data set, and analyzes and generates a digital elevation model , and transmits it to the intelligent matching module through a network; The intelligent matching module consists of an image evaluation unit, a real-time analysis unit, and a scene matching unit. The image evaluation unit analyzes the authenticity of each target area SAR image based on the reference data set and generates a corresponding credibility index. ; The said trust index The calculation process is as follows: Extract the SAR image data of the th target area according to the reference data set, and mark the echo signal intensity of the th target area as , mark the ground range of the th target area as , mark the slant range of the th target area as , mark the layover area of the th target area as , mark the area of the th target area as , ； In the formula, represents the weight for the echo signal strength, represents the weight for the ratio of ground range to slant range, represents the weight for the ratio of the layover area to the target area, , and are all constants, and , represents that according to the , and weights, the credibility index of the th target area is calculated as ; The real-time analysis unit is set with a monitoring period of a fixed duration , and combined with the real-time data set, analyze the fluctuation index of the real-time signal strength and the matching index of the SAR image ; The fluctuation index The calculation process is as follows: Statistically monitor the real-time signal strength within the monitoring period according to the real-time data set, and label it as ; , to represent the real-time signal strength of the SAR image data provided from the first time to the th time; ； In the formula, represents the average value of the real-time signal strength during the monitoring period, represents the real-time signal strength of the th SAR image data provided, , represents the fluctuation index of the real-time signal strength calculated according to the standard deviation formula during the monitoring period ; The matching index The calculation process is as follows: Extract the SAR image data provided for the th time from the real-time data set, and mark the azimuth resolution of the th SAR image as , mark the range resolution of the th SAR image as , and mark the signal-to-noise ratio of the th SAR image as ; ； In the formula, represents the weight for azimuth resolution, represents the weight for range resolution, represents the weight for signal-to-noise ratio, 、 and are all constants, and , represents that according to the 、 and weights, the matching index of the th SAR image is calculated as ; The scene matching unit is set with a fluctuation threshold within a fixed range , combined with the fluctuation index , to determine whether there is a delay problem in the SAR image, and then based on the credibility index , matching index , digital elevation model to perform scene matching guidance and synchronous track.

2. The scene matching guidance system based on a micro synthetic aperture radar according to claim 1, characterized in that: The expression of the reference data set is , to represent the SAR image data of the first target area to the th target area. The SAR image data of the target area includes echo signal intensity, ground distance, slant range, and layover area. represents the area of a single target area.

3. The scene matching guidance system based on a micro synthetic aperture radar according to claim 2, characterized in that: The expression of the real-time data set is , to represent the SAR image data provided by the echo signal for the first to the th time. The SAR image data provided by the echo signal includes real-time signal intensity, azimuth resolution, range resolution, and signal-to-noise ratio. represents the time point when the SAR image data of the echo signal is acquired.

4. The scene matching guidance system based on a micro synthetic aperture radar according to claim 3, characterized in that: The standardized processing flow is as follows: Collect meteorological parameters of all target areas through network connection to the big data platform. The meteorological parameters include temperature, air pressure, wind speed, wind direction, aerosol mass concentration, and atmospheric stratification stability; Use the MODTRAN atmospheric radiative transfer model, input the meteorological parameters of all target areas, remove the noise of signal attenuation and phase delay, and eliminate the distortion problem of the atmosphere on the SAR images in the reference data set and the real-time data set.

5. The scene matching guidance system based on a micro synthetic aperture radar according to claim 4, wherein: The digital elevation model The analysis process is as follows: Collect geographical information of all target areas through network connection to the big data platform. The geographical information includes longitude and latitude coordinates, altitude, location identification, and topography; Using image processing software, combining the geographical information of all target areas and the standardized reference dataset, a digital elevation model is established to eliminate the geometric distortion problems of SAR images in the reference dataset and the real-time dataset.

6. The scene matching guidance system based on a micro synthetic aperture radar according to claim 5, characterized in that: The fluctuation index exceeds the fluctuation threshold , indicating that there is a delay problem in the SAR image. It is recommended to adjust the time difference and then perform scene matching guidance.

7. The scene matching guidance system based on a micro synthetic aperture radar according to claim 6, characterized in that: The scene matching unit arranges the target areas in descending order of the credibility index When the fluctuation index is included in the fluctuation threshold preferably select the SAR image with a high matching index and the target area with a high credibility index for scene matching guidance, and synchronize the track in the digital elevation model according to the matching result.

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