Terahertz radar adaptive aperture bp imaging method based on target scattering characteristics

Abstract

The present application belongs to the technical field of radar imaging, and particularly relates to a terahertz radar adaptive aperture BP imaging method based on target scattering characteristics. In the two-dimensional imaging process of a terahertz synthetic aperture radar, the scattering characteristics of original echo energy are analyzed in a stepwise direction, an optimal aperture division threshold is obtained through iteration based on a maximum entropy criterion, the original echo data are adaptively divided into sub-apertures, the sub-aperture imaging results are weighted and superimposed to obtain a final imaging result, the acquisition capability of target detail information is improved, the imaging effect of a terahertz SAR artificial complex target is effectively improved, and the present application is a high-efficiency method for fine imaging of a terahertz synthetic aperture radar artificial target. In addition, the present application does not involve complex calculation operations, and the implementation mode is relatively simple.

Description

Technical Field

[0001] This invention belongs to the field of radar imaging technology, specifically relating to a terahertz radar adaptive aperture BP imaging method based on target scattering characteristics. Background Technology

[0002] Terahertz (THz) waves are electromagnetic radiation between millimeter waves and infrared light, with a frequency range of 0.1 THz to 10 THz and a corresponding wavelength range of 0.03 mm to 3.00 mm. In recent years, terahertz waves have been widely used in medicine, communications, passenger security checks, agricultural product inspection, and national defense due to their significant and unique characteristics, such as strong penetration, strong anti-interference ability, narrow beamwidth, and high carrier frequency. Notably, their combination with synthetic aperture radar (SAR) has overcome many limitations and bottlenecks, offering greater research value and broader application prospects. Terahertz SAR, while retaining the readability of optical images, possesses stronger penetration capabilities, enabling it to operate not only in complex environments such as smoke and fog but also to achieve non-intrusive, long-range, high-resolution imaging of objects.

[0003] Because terahertz wavelengths are much smaller than the observed target, the echo signals from terahertz radar targets typically exhibit a multi-scattering center effect, i.e., non-uniform scattering due to surface undulations. In this case, even targets on the order of ten centimeters exhibit anisotropic echo scattering characteristics. Due to this characteristic of terahertz radar, the echo energy and scattering coherence angle vary significantly with the azimuth angle when observing targets. Therefore, existing constant aperture imaging methods may lead to severe coherence angle mismatch during terahertz radar data imaging processing. This causes targets with weak radar cross section (RCS) to be masked by targets with strong RCS, reducing resolution, causing imaging scintillation, and loss of target detail information. Therefore, finding an adaptive aperture backpropagation (BP) imaging method for terahertz radar based on target scattering characteristics is of great significance, as it can reduce imaging scintillation and improve the acquisition of target detail information. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems and shortcomings by providing a terahertz radar adaptive aperture BP imaging method based on target scattering characteristics. This method analyzes the energy scattering characteristics of the original echo in each azimuth direction during the synthetic aperture radar (SAR) two-dimensional imaging process. Based on the maximum entropy criterion, it iteratively obtains the optimal aperture division threshold, adaptively divides the original echo data into apertures, and weights and superimposes the sub-aperture imaging results to obtain the final imaging result. This effectively improves the imaging effect of complex artificial targets using terahertz SAR and is a highly efficient terahertz synthetic aperture radar fine imaging method.

[0005] The technical solution of this invention is: a terahertz radar adaptive aperture BP imaging method based on target scattering characteristics, comprising the following steps:

[0006] S1. Calculate the energy information En(θ) for each echo.

[0007]

[0008] Where I(θ,t) and Q(θ,t) represent the real and imaginary parts of the received radar signal, respectively, and θ represents the azimuth angle. Here, t represents a rapid time variable in the radar ranging direction, which is related to the radar system and is equivalent to the pulse repetition interval (PRI).

[0009] S2. Take the average value of the energy obtained in the previous step to obtain the average energy across the entire pore size.

[0010]

[0011] S3. Set the initial energy threshold E for aperture division. th

[0012]

[0013] α is obtained by imaging multiple sets of measured data, using image entropy as an indicator, and employing a multi-iterative approximation method.

[0014]

[0015] Where N Ap η represents the number of sub-apertures at the current energy threshold. i and η max D represents the current sub-aperture energy and the maximum energy among all sub-apertures, respectively. i This is the current sub-aperture echo data. BP represents the image obtained by imaging the weighted echo data using the BP algorithm, and H represents the image entropy of the imaging result.

[0016] S4. Determine the energy threshold function E based on the obtained aperture size. th The aperture is divided into sub-apertures, and the sub-aperture images are obtained using the BP algorithm. The sub-aperture weights β are then calculated. i

[0017]

[0018] S5. The final imaging result is obtained by weighting and superimposing the sub-aperture BP imaging results, where the weight of each sub-aperture is β. i .

[0019] This invention analyzes the energy scattering characteristics of the original echo in each azimuth direction. Based on the maximum entropy criterion, it iteratively obtains the optimal aperture division threshold, performs adaptive aperture division on the original echo data, and weights and superimposes the sub-aperture imaging results to obtain the final imaging result, thereby improving the ability to acquire target detail information and effectively enhancing the imaging effect of terahertz SAR artificial complex targets.

[0020] The beneficial effects of this invention are that it can improve the imaging effect of terahertz SAR artificial complex targets, and the implementation process does not involve complex calculations. Attached Figure Description

[0021] Figure 1 This is a flowchart of the present invention;

[0022] Figure 2 This is a schematic diagram of a fixed aperture size divided into 5-degree apertures. It is an energy comparison diagram when divided into three sub-apertures (a), (b), and (c). The azimuth range of sub-aperture (a) is 295-300 degrees, the azimuth range of sub-aperture (b) is 300-305 degrees, and the azimuth range of sub-aperture (c) is 305-310 degrees. The upper right corner of the diagram is a real photo of the corresponding model.

[0023] Figure 3 This is the sub-aperture (a) imaging result;

[0024] Figure 4 This is the result of sub-aperture (b) imaging;

[0025] Figure 5 This is the result of sub-aperture (c) imaging;

[0026] Figure 6 These are actual photos of Model A;

[0027] Figure 7 These are actual photos of Model B;

[0028] Figure 8 This is the BP imaging result of Model A without using this method. The red box indicates the selected contrast feature regions and their corresponding numbers.

[0029] Figure 9 This is the imaging result of Model A using this method. The red box indicates the selected contrast feature regions and their corresponding numbers.

[0030] Figure 10 This is the BP imaging result of Model B without using this method. The red box indicates the selected contrast feature regions and their corresponding numbers.

[0031] Figure 11 This is the imaging result of Model B using this method. The red box indicates the selected contrast feature regions and their corresponding numbers.

[0032] Figure 12This is a comparison table of the image entropy and equivalent number of views (ENL) values ​​of the feature regions selected by Model A and Model B. Detailed Implementation

[0033] The present invention will now be described in detail with reference to the accompanying drawings and simulation examples to demonstrate its practicality.

[0034] As attached Figure 1 As shown, the terahertz radar adaptive aperture BP imaging method based on target scattering characteristics of this invention can effectively improve the imaging effect of complex artificial targets in terahertz SAR. It is a highly efficient fine imaging method for terahertz synthetic aperture radar. The specific implementation steps are as follows:

[0035] Step 1: Calculate the energy information En(θ) for each echo, using the following method:

[0036]

[0037] Among them, due to the received signal S r (θ,t) is a complex number. In our calculation, we divide the received signal into a real part I(θ,t) and an imaginary part Q(θ,t). Since we are integrating azimuth-wise, we introduce θ to represent the azimuth angle. Here, t represents a rapid time variable in the radar ranging direction, which is related to the radar system and is equivalent to the pulse repetition interval (PRI).

[0038] Step 2: Take the average value of the energy obtained in the previous step to obtain the average energy across the entire pore size. The calculation method is as follows:

[0039]

[0040] Step 3: Set the initial energy threshold E for aperture division th

[0041]

[0042] α is obtained by imaging multiple sets of measured data, using image entropy as an indicator, and employing a multi-iterative approximation method.

[0043]

[0044] Where N Ap η represents the number of sub-apertures at the current energy threshold. i and η max D represents the current sub-aperture energy and the maximum energy among all sub-apertures, respectively. i This is the current sub-aperture echo data. BP represents the image obtained by imaging the weighted echo data using the BP algorithm, and H represents the image entropy of the imaging result.

[0045] Step 4: Divide the energy threshold function E using the obtained aperture. th The aperture is divided into sub-apertures, and the sub-aperture images are obtained using the BP algorithm. The sub-aperture weights β are then calculated. i The calculation method is as follows:

[0046]

[0047] Step 5: The sub-aperture BP imaging results are weighted and superimposed to obtain the final imaging result, where the weight of each sub-aperture is β. i The final imaging result is as follows:

[0048]

[0049] Simulation Example

[0050] The above method is attached. Figure 1 The specific parameter settings for the operation process shown are as follows: circular SAR imaging mode is used, the radar slant range from the target is 3.2 meters, the radar height relative to the target is 0.2 meters, the transmitted signal is in the terahertz band, and the center carrier frequency is 0.34THz.

[0051] Figure 2 A schematic diagram of a fixed aperture size divided into 5 degrees is given, and an energy comparison diagram is shown when it is divided into three sub-apertures (a), (b), and (c). The azimuth range of sub-aperture (a) is 295-300 degrees, the azimuth range of sub-aperture (b) is 300-305 degrees, and the azimuth range of sub-aperture (c) is 305-310 degrees. The upper right of the figure is a real photograph of the corresponding model. For complex artificial targets, the energy fluctuation is usually very drastic, and there is an energy difference of 10 dB between the sub-apertures.

[0052] Figure 3 Sub-aperture (a) imaging results are presented;

[0053] Figure 4 Sub-aperture (b) imaging results are presented;

[0054] Figure 5 Sub-aperture (c) imaging results are presented;

[0055] Figure 6 Real-world images of model A are provided;

[0056] Figure 7 Real-world images of Model B are provided;

[0057] Figure 8 The BP imaging results of Model A without using this method are shown. The red boxes indicate the selected contrast feature regions and their corresponding numbers.

[0058] Figure 9The imaging results of Model A using this method are shown. The red boxes indicate the selected contrast feature regions and their corresponding numbers.

[0059] Figure 10 The BP imaging results of Model B without using this method are shown. The red boxes indicate the selected contrast feature regions and their corresponding numbers.

[0060] Figure 11 The imaging results of Model B using this method are shown. The red boxes indicate the selected contrast feature regions and their corresponding numbers.

[0061] Figure 12 A comparison table of the image entropy and equivalent number of views (ENL) of the feature regions selected by the two sets of models is provided.

[0062] By comparison Figure 3 , Figure 4 , Figure 5 The results clearly show that there are significant differences between the energy and imaging results of adjacent sub-apertures in the terahertz band. It is precisely because of this that existing constant aperture imaging methods may lead to severe coherence angle mismatch, which causes weak radar cross section (RCS) targets to be masked by strong RCS targets, reducing resolution, causing imaging scintillation effects and loss of target detail information.

[0063] By comparison Figure 8 , Figure 9 , Figure 10 , Figure 11 and review Figure 12 The image entropy and equivalent number of views (ENL) values ​​of the feature regions selected by the two sets of models given in the paper clearly show that, under the same image parameters, the imaging results using this method have less side lobe interference (the image entropy value decreases and the equivalent number of views decreases in region R2 of model A), and the target details are richer (the image entropy value increases and the equivalent number of views increases in other regions except region R2 of model A).

[0064] In conclusion, the method provided by this invention has practical value based on the processing results.

Claims

1. A terahertz radar adaptive aperture BP imaging method based on target scattering characteristics, characterized in that, Includes the following steps: S1. Calculate the energy information En(θ) for each echo: En(θ)=∫0 t [I 2 (θ,t)+Q 2 (θ,t)]dt Where I(θ,t) and Q(θ,t) represent the real and imaginary parts of the received radar signal, respectively, θ represents the azimuth angle, and t represents the rapid time variable in the radar ranging direction; S2. Take the average value of the acquired energy to obtain the average energy across the entire pore size. S3. Set the initial energy threshold E for aperture division. th : Where N Ap η represents the number of sub-apertures at the current energy threshold. i and η max D represents the current sub-aperture energy and the maximum energy among all sub-apertures, respectively. i This is the current sub-aperture echo data, BP is the image of the weighted echo data using the BP algorithm, and H is the image entropy of the calculated imaging result; S4. Determine the energy threshold function E based on the obtained aperture size. th The aperture is divided into sub-apertures, and the sub-aperture images are obtained using the BP algorithm. The sub-aperture weights β are then calculated. i : S5. The final imaging result is obtained by weighting and superimposing the sub-aperture BP imaging results, where the weight of each sub-aperture is β. i .

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