An imaging method and apparatus based on calm water surfaces

Abstract

This application belongs to the field of imaging technology and relates to an imaging method and apparatus based on a calm water surface. The method includes: acquiring an observation scene of a calm water surface environment and constructing an observation model of the calm water surface environment; based on the observation model of the calm water surface environment, using ray tracing, calculating the propagation distance difference between the direct wave and the multipath signal to obtain a compensated phase; based on the compensated phase, moving the multipath target to the actual target location to obtain a compensated image; using a self-focusing algorithm based on weighted minimum entropy to correct the phase error of the compensated image to obtain a corrected image; when the image entropy of the corrected image meets a preset condition, using the current image as the output image. Using this application, the accuracy of target positioning can be improved by utilizing multipath signals, and the target amplitude can also be enhanced by utilizing multipath signals, thereby improving the target's noise resistance and improving the target imaging quality.

Description

Technical Field

[0001] This application relates to the field of imaging technology, and in particular to an imaging method and apparatus based on a calm water surface. Background Technology

[0002] In today's era, the widespread use of drones has brought many conveniences.

[0003] Due to their low flight altitude, slow speed, weak thermal signature, and small size, coupled with the complex low-altitude environment, drones are difficult to detect using traditional wireless equipment (such as radar) and detection devices. Therefore, using wireless equipment for detection has become an effective technical means, with Ku-band wireless equipment being an ideal choice for detecting drones due to its unique technical characteristics.

[0004] Ku-band radios operate at wavelengths below 3 centimeters, providing high-resolution and high-precision detection capabilities, crucial for identifying low, slow, and small targets. Compared to other bands, Ku-band radios offer more accurate positioning, but have a relatively shorter range. These short-wavelength radios are particularly suitable for short-range fire control, providing a 50-degree field of view in all directions and the ability to rotate 360 ​​degrees to detect targets from all directions. The high-frequency characteristics of Ku-band radios give them higher resolution when detecting small drones, which is essential for distinguishing targets from background noise in complex environments. Furthermore, the high resolution of Ku-band radios not only aids in target detection but also provides precise target position and velocity information, crucial for subsequent countermeasures. These characteristics make Ku-band radios important in drone detection and countermeasure systems, especially in scenarios requiring precise identification and rapid response.

[0005] Therefore, Ku-band radio equipment has advantages such as high resolution, high sensitivity, low cost, and high maneuverability in detecting unauthorized drone flights, playing an irreplaceable role, especially in the surveillance of sensitive areas such as important waterways. With further technological advancements, Ku-band radio equipment is expected to play an even greater role in future drone detection and countermeasures.

[0006] Multipath interference is a major challenge for wireless equipment when detecting drones, especially in aquatic environments. Multipath propagation refers to the phenomenon where a signal travels along multiple paths to the receiver, resulting in varying arrival times due to different path lengths, thus causing signal interference and attenuation. In aquatic environments, buildings, water surfaces, and terrain can all become sources of signal reflection, increasing the complexity of multipath effects and making drone signal detection and tracking even more difficult.

[0007] Taking a lake environment as an example, the water flow in lakes is relatively slow, and the surface reflection is more specular, resulting in strong multipath signal interference. During detection, the SAR two-dimensional images obtained by radio equipment often contain multipath targets, thus affecting image quality. If the positions of multipath targets are not corrected and multipath signals are not effectively utilized, problems such as blurred imaging results and unclear target counts may occur. Therefore, research on how to effectively utilize multipath signals is crucial for improving the imaging quality of radio equipment in multipath environments.

[0008] In existing technologies, some use inverse ray tracing to locate the true position of the target based on high-order multipath signals, while others use music algorithms to estimate time delays under the influence of multipath effects, thereby effectively distinguishing between direct wave signals and multipath signals.

[0009] However, the above methods are all aimed at the target localization process. Using multipath signals to locate the target's true position will result in the loss of detailed target information, leading to the loss of useful information. In tasks such as target recognition, this may lead to incorrect analysis results and make it difficult to improve the accuracy of target localization. Summary of the Invention

[0010] Therefore, it is necessary to provide an imaging method and apparatus based on calm water surface to address the above-mentioned technical problems. This method and apparatus can improve the accuracy of target positioning by utilizing multipath signals, enhance the target amplitude by utilizing multipath signals to improve the signal-to-noise ratio, thereby improving the target's noise resistance, further improving the accuracy of target positioning, and improving the target imaging quality.

[0011] An imaging method based on a calm water surface includes:

[0012] Obtain observation scenes of calm water surface environments and construct observation models of calm water surface environments;

[0013] Based on the observation model of a calm water surface environment, the ray tracing method is used to calculate the propagation distance difference between the direct wave and the multipath signal to obtain the compensated phase; based on the compensated phase, the multipath target is moved to the actual target position to obtain the compensated image;

[0014] A self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the compensated image to obtain the corrected image;

[0015] When the image entropy of the corrected image meets the preset conditions, the current image is used as the output image.

[0016] In one embodiment, when the image entropy of the corrected image does not meet the preset condition, a self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the corrected image to obtain the next corrected image, until the image entropy of the next corrected image meets the preset condition.

[0017] In one embodiment, based on an observation model of a calm water surface environment, a ray tracing method is used to calculate the propagation distance difference between the direct wave and the multipath signal to obtain a compensated phase, including:

[0018] The reflection path is determined based on the observation model of a calm water surface environment;

[0019] Based on the reflection path, the direct wave and multipath signal are obtained, and the propagation distance difference between the direct wave and the multipath signal is calculated.

[0020] The compensation phase is obtained based on the difference in propagation distance.

[0021] In one embodiment, determining the reflection path based on an observation model of a calm water surface environment includes:

[0022] Based on the observation model of a calm water surface environment, and by means of mirror symmetry, the mirror image of the radio device about the reflecting surface is obtained.

[0023] The direct wave propagation distance is defined by the first straight line between the wireless equipment and the target point, and the multipath signal propagation distance is defined by the second straight line between the mirror wireless equipment and the target point. The intersection of the second straight line and the reflecting surface is the reflection point.

[0024] Based on the length of the reflection point, the effective reflection point is obtained when the reflection point is within the range of the reflecting surface.

[0025] When verifying that there are no obstructions between the radio equipment and the target, and between the mirror radio equipment and the target, the reflection path is determined based on the target point, the effective reflection point, the radio equipment, and the mirror radio equipment.

[0026] In one embodiment, when verifying that there is an obstruction between the radio device and the target or between the mirror radio device and the target, the mirror radio device about the reflective surface of the radio device is obtained again by mirror symmetry, and the effective reflection point is obtained again until it is verified that there is no obstruction between the radio device and the target or between the mirror radio device and the target.

[0027] In one embodiment, a self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the compensated image to obtain a corrected image, including:

[0028] An azimuth-to-Fourier transform is performed on the compensated image to construct a phase error model;

[0029] Based on the phase error model, the least squares estimation criterion is used to define the weighted entropy of the compensation image and obtain the phase error cost function;

[0030] Based on the phase error cost function, the compensated image is subjected to phase error correction and inverse Fourier transform to obtain the corrected image.

[0031] In one embodiment, the phase error model is as follows:

[0032] ;

[0033] In the formula, For the phase error model, For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal phase, For the first The weighting coefficients of each distance cell are inversely proportional to the phase variance of that distance cell.

[0034] In one embodiment, the weighted entropy of the compensated image is:

[0035] ;

[0036] ;

[0037] In the formula, To compensate for the weighted entropy of the image, For the first Each azimuth unit signal. For pixel image density, For pixel energy, The total energy of the image.

[0038] In one embodiment, the phase error cost function is:

[0039] ;

[0040] In the formula, This is the error phase estimate. This is the error phase.

[0041] An imaging device based on a calm water surface, comprising:

[0042] The acquisition module is used to acquire observation scenes of calm water surface environments and construct observation models of calm water surface environments.

[0043] The compensation module is used to calculate the propagation distance difference between the direct wave and the multipath signal based on the observation model of the calm water surface environment and the ray tracing method to obtain the compensation phase; based on the compensation phase, the multipath target is moved to the actual target position to obtain the compensation image;

[0044] The correction module is used to correct the phase error of the compensated image using a self-focusing algorithm based on weighted minimum entropy, so as to obtain the corrected image.

[0045] The output module is used to output the current image when the image entropy of the corrected image meets the preset conditions.

[0046] The aforementioned imaging method and device based on calm water surfaces constructs an observation model of the calm water environment, employs ray tracing to calculate the propagation distance difference between the direct wave and the multipath signal, moves the multipath target to the actual target location, enhances the target amplitude, and then uses a self-focusing algorithm based on weighted minimum entropy to focus on the multipath target and the target in the azimuth direction. This effectively solves the problem of multipath target azimuth offset caused by diffuse reflection due to the fluidity of the lake water. It can improve the target positioning accuracy by utilizing multipath signals and enhance the target amplitude, thereby improving the target's noise resistance and improving the target imaging quality. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating an imaging method based on a calm water surface in one embodiment;

[0048] Figure 2 This is a schematic diagram illustrating the observation model obtained by modeling a real-world scenario in one embodiment.

[0049] Figure 3 This is a schematic diagram of various parameters in a scenario from one embodiment;

[0050] Figure 4 This is a two-dimensional single-view complex image in one embodiment;

[0051] Figure 5 This is a two-dimensional single-view complex image (i.e., the compensated image) obtained after multipath distance compensation in one embodiment.

[0052] Figure 6 This is a two-dimensional single-view complex image (i.e., a corrected image) obtained after processing by a self-focusing algorithm in one embodiment.

[0053] Figure 7 For one embodiment Figure 4 A schematic diagram of azimuth slice analysis;

[0054] Figure 8 For one embodiment Figure 4A schematic diagram of performing distance-oriented slice analysis;

[0055] Figure 9 For one embodiment Figure 5 A schematic diagram of azimuth slice analysis;

[0056] Figure 10 For one embodiment Figure 5 A schematic diagram of performing distance-oriented slice analysis;

[0057] Figure 11 For one embodiment Figure 6 A schematic diagram of azimuth slice analysis;

[0058] Figure 12 For one embodiment Figure 6 A schematic diagram of performing distance-oriented slice analysis;

[0059] Figure 13 This is a structural block diagram of an imaging device based on a calm water surface in one embodiment. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0061] Furthermore, the use of terms such as "first" and "second" in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of those features. In the description of this application, "multiple sets" means at least two sets, such as two sets, three sets, etc., unless otherwise explicitly specified.

[0062] In this application, unless otherwise expressly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection, an electrical connection, a physical connection, or a wireless communication connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two elements or the interaction between two elements, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0063] Furthermore, the technical solutions of the various embodiments of this application can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by this application.

[0064] This application provides an imaging method based on a calm water surface, such as... Figure 1 The flowchart shown, in one embodiment, includes:

[0065] Step 101: Obtain the observation scene of the calm water surface environment and construct the observation model of the calm water surface environment.

[0066] Specifically:

[0067] To obtain the observation scene of a calm water surface environment, since the reflecting surface is approximately mirror-like, the target, the mirrored radio equipment, and the radio equipment are always on the same plane. The various parameters of the scene can be determined from the measured data, thereby constructing an observation model of the calm water surface environment.

[0068] The specific modeling process described in this step is based on existing technology and will not be elaborated upon here.

[0069] Step 102: Based on the observation model of the calm water surface environment, the ray tracing method is used to calculate the propagation distance difference between the direct wave and the multipath signal to obtain the compensation phase; based on the compensation phase, the multipath target is moved to the actual target position to obtain the compensation image.

[0070] Specifically:

[0071] Based on the observation model of a calm water surface environment, the reflection path is determined; based on the reflection path, the direct wave and multipath signal are obtained, and the propagation distance difference between the direct wave and the multipath signal is calculated; based on the propagation distance difference, the compensation phase is obtained; based on the compensation phase, the multipath target is moved to the actual target position to obtain the compensation image.

[0072] More specifically:

[0073] Based on the observation model of a calm water surface environment, and by means of mirror symmetry, the mirror image of the radio device about the reflecting surface is obtained.

[0074] The direct wave propagation distance is defined by the first straight line between the wireless equipment and the target point, and the multipath signal propagation distance is defined by the second straight line between the mirror wireless equipment and the target point. The intersection of the second straight line and the reflecting surface is the reflection point.

[0075] Based on the length of the reflection point:

[0076] ;

[0077] In the formula, The horizontal distance between the reflection point and the target. The width of the reflective surface. For the target height, For the height of the wireless equipment;

[0078] When the reflection point is verified to be within the range of the reflecting surface, a valid reflection point is obtained; if the reflection point is verified to be outside the range of the reflecting surface, a new valid reflection point is searched for. If the new reflection point is also outside the range of the reflecting surface, then it is a normal imaging process, and the process ends here.

[0079] When it is verified that there are no obstructions between the radio equipment and the target, and between the mirror radio equipment and the target, the reflection path is determined based on the target point, the effective reflection point, the radio equipment, and the mirror radio equipment;

[0080] When verifying that there are obstructions between the radio equipment and the target or between the mirror radio equipment and the target, the mirror radio equipment about the reflecting surface is obtained again from the observation model of the calm water surface environment based on mirror symmetry. The reflection point is re-determined, and the effective reflection point is re-verified and obtained until it is verified that there are no obstructions between the radio equipment and the target or between the mirror radio equipment and the target.

[0081] Based on the reflection path, the direct wave and multipath signal are obtained, and the propagation distance difference between the direct wave and the multipath signal is calculated:

[0082] ;

[0083] In the formula, The difference in propagation distance between the direct wave and the multipath signal. The width of the reflecting surface. For the height of the goal, The height of a wireless equipment vehicle (such as a radar vehicle);

[0084] Based on the difference in propagation distance, the compensated phase is obtained:

[0085] ;

[0086] In the formula, To compensate for the phase, The imaginary unit, The number of grid cells that a multipath target needs to move. For distance to discrete time, The distance is the length of the discrete Fourier transform.

[0087] Based on the compensated phase, the multipath target is moved to the actual target position to obtain the compensated image.

[0088] In this step, the multipath target is moved to the location of the real target to obtain a compensated image, which can enhance the amplitude of the real target and improve the signal-to-noise ratio.

[0089] Step 103: The phase error of the compensated image is corrected by using a self-focusing algorithm based on weighted minimum entropy to obtain the corrected image.

[0090] Specifically:

[0091] An azimuth-to-Fourier transform is performed on the compensated image to construct a phase error model. Based on the phase error model, the weighted entropy of the compensated image is defined using the least squares estimation criterion, and the phase error cost function is obtained. Based on the phase error cost function, the compensated image is subjected to phase error correction and inverse Fourier transform to obtain the corrected image.

[0092] More specifically:

[0093] Perform an azimuth-to-Fourier transform on the compensated image to construct a phase error model:

[0094] ;

[0095] In the formula, For the phase error model, For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal phase, For the first The weighting coefficients of each distance cell are inversely proportional to the phase variance of that distance cell;

[0096] Based on the phase error model, the weighted entropy of the compensated image is defined using the least squares estimation (WLS) criterion:

[0097] ;

[0098] ;

[0099] In the formula, To compensate for the weighted entropy of the image, For the first Each azimuth unit signal. For pixel image density, For pixel energy, The total energy of the image;

[0100] Based on the weighted entropy of the compensated image, the phase error cost function is derived as follows:

[0101] ;

[0102] In the formula, This is the error phase estimate. For error phase;

[0103] Based on the phase error cost function, the compensated image is subjected to phase error correction and inverse Fourier transform to obtain the corrected image.

[0104] In this step, an autofocus algorithm based on Weighted Minimum Entropy Autofocus (WMEA) is used to further align the target with the multipath target to improve imaging quality.

[0105] Step 104: When the image entropy of the corrected image meets the preset conditions, the current image is used as the output image.

[0106] Specifically:

[0107] When the image entropy of the corrected image meets the preset conditions, the current image is used as the output image;

[0108] When the image entropy of the corrected image does not meet the preset conditions, a self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the corrected image to obtain the next corrected image, until the image entropy of the next corrected image meets the preset conditions.

[0109] In this step, the preset conditions refer to: the image entropy reaching a set threshold (which is obtained by the phase error model, and how it is obtained is a matter of existing technology) or the number of iterations reaching a set upper limit.

[0110] The aforementioned imaging method based on calm water surfaces constructs an observation model of the calm water environment, employs ray tracing to calculate the propagation distance difference between the direct wave and the multipath signal, moves the multipath target to the actual target location, enhances the target amplitude, and then uses a weighted minimum entropy-based self-focusing algorithm to focus on the multipath target and the target in the azimuth direction. This effectively solves the problem of multipath target azimuth offset caused by diffuse reflection due to the fluidity of the lake water. It can improve the target positioning accuracy by utilizing multipath signals and enhance the target amplitude, thereby improving the target's noise resistance and improving the target imaging quality.

[0111] It should be understood that, although Figure 1The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0112] In one specific embodiment, the method of this application is verified using measured data. A model of the measured scenario is constructed (a multipath environment observation model is built), resulting in a schematic diagram of the observation model as shown below. Figure 2 As shown, A represents the hovering drone, and O represents the river dam. Since the reflecting surface is approximately mirror-like, the radio equipment, propagating signals, and target are all in the same plane. Therefore, the model is further simplified. A schematic diagram of the scene parameters is shown below. Figure 3 As shown, A is a hovering drone with coordinates of B is the vehicle-mounted radio equipment, with coordinates as follows: C represents the mirrored vehicle-mounted radio device, with coordinates as follows: , R 1 represents a direct wave. R 2 represents a multipath signal. F The normal is given, and the angles of incidence and refraction are both 1 / 2. , L The width of the lake. L 1 represents the length of the reflection point, and the simulation parameters are shown in Table 1.

[0113] Table 1: Simulation Parameters

[0114]

[0115] The data acquired by the wireless equipment vehicle is used to obtain a two-dimensional single-view complex image through a back projection algorithm, such as... Figure 4 As shown. Ray tracing was used to calculate the multipath signal propagation distance of the scene. Substituting the measured data, the multipath signal propagation distance was 612m. Based on the 1.3m difference between the multipath signal and the direct wave propagation distance, the multipath target was moved to the target location. The resulting two-dimensional single-view complex image after multipath distance compensation is shown below. Figure 5As shown, the diffuse reflection caused by the fluidity of the lake surface leads to multipath target azimuth shift, resulting in a certain degree of target azimuth broadening and a decrease in azimuth resolution. The application of weighting coefficients in the WMEA algorithm can effectively reduce the clutter and noise caused by multipath target movement, thereby achieving better focusing results. This is because the WMEA algorithm weights the phase variance of each distance cell, allowing high-quality samples to play a dominant role in entropy convergence. Furthermore, the WMEA algorithm uses weighted entropy to establish a cost function and estimates the error phase through an iterative algorithm to achieve motion error compensation. Compared with the traditional Minimum Entropy Autofocus (MEA) algorithm, WMEA can effectively improve the convergence speed of iteration. For large scene models, the efficiency is significantly improved. The two-dimensional single-view complex image obtained after processing by the above autofocus algorithm is shown below. Figure 6 As shown.

[0116] right Figure 4 , Figure 5 , Figure 6 Slice analysis was performed separately (including azimuth slice analysis and range slice analysis), and the results are as follows: Figures 7 to 12 As shown, all three parameters of the range slice are improved. This is because the multipath target is moved to the target location, which improves the target's signal-to-noise ratio, enhances its noise resistance, and increases the amplitude, consistent with the previous theoretical derivation. After processing by the self-focusing algorithm, the target's impact response width, integral sidelobe ratio, and peak sidelobe ratio are all significantly improved, consistent with the theoretical analysis.

[0117] This application also provides an imaging device based on a calm water surface, such as... Figure 13 As shown, in one embodiment, it includes: an acquisition module 1301, a compensation module 1302, a correction module 1303, and an output module 1304, wherein:

[0118] The acquisition module 1301 is used to acquire the observation scene of the calm water surface environment and construct the observation model of the calm water surface environment.

[0119] The compensation module 1302 is used to calculate the propagation distance difference between the direct wave and the multipath signal using the ray tracing method based on the observation model of the calm water surface environment, so as to obtain the compensation phase; based on the compensation phase, the multipath target is moved to the actual target position to obtain the compensation image;

[0120] The correction module 1303 is used to perform phase error correction on the compensation image using a self-focusing algorithm based on weighted minimum entropy to obtain a corrected image;

[0121] The output module 1304 is used to use the current image as the output image when the image entropy of the corrected image meets the preset conditions.

[0122] For specific limitations regarding an imaging device based on a calm water surface, please refer to the limitations of an imaging method based on a calm water surface mentioned above, which will not be repeated here. Each module in the above device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0123] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

[0124] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. An imaging method based on a calm water surface, characterized in that, include: Obtain observation scenes of calm water surface environments and construct observation models of calm water surface environments; Based on the observation model of a calm water surface environment, the ray tracing method is used to calculate the propagation distance difference between the direct wave and the multipath signal to obtain the compensated phase; based on the compensated phase, the multipath target is moved to the actual target position to obtain the compensated image; A self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the compensated image to obtain the corrected image; When the image entropy of the corrected image meets the preset conditions, the current image is used as the output image; When the image entropy of the corrected image does not meet the preset conditions, a self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the corrected image to obtain the next corrected image, until the image entropy of the next corrected image meets the preset conditions. Based on the observation model of a calm water surface environment, the ray tracing method is used to calculate the propagation distance difference between the direct wave and the multipath signal in order to obtain the compensated phase, including: The reflection path is determined based on the observation model of a calm water surface environment; Based on the reflection path, the direct wave and multipath signal are obtained, and the propagation distance difference between the direct wave and the multipath signal is calculated. The compensation phase is obtained based on the difference in propagation distance; Based on the observation model of a calm water surface environment, the reflection path is determined, including: Based on the observation model of a calm water surface environment, and by means of mirror symmetry, the mirror image of the radio device about the reflecting surface is obtained. The direct wave propagation distance is defined by the first straight line between the wireless equipment and the target point, and the multipath signal propagation distance is defined by the second straight line between the mirror wireless equipment and the target point. The intersection of the second straight line and the reflecting surface is the reflection point. Based on the length of the reflection point, the effective reflection point is obtained when the reflection point is within the range of the reflecting surface. When verifying that there are no obstructions between the radio equipment and the target, and between the mirror radio equipment and the target, the reflection path is determined based on the target point, the effective reflection point, the radio equipment, and the mirror radio equipment; When verifying that there are obstructions between the radio equipment and the target or between the mirrored radio equipment and the target, the mirrored radio equipment about the reflective surface is obtained again from the mirror symmetry, and the effective reflection point is obtained again until it is verified that there are no obstructions between the radio equipment and the target or between the mirrored radio equipment and the target.

2. The imaging method based on a calm water surface according to claim 1, characterized in that, A self-focusing algorithm based on weighted minimum entropy is used to correct the phase error of the compensated image, resulting in a corrected image, including: An azimuth-to-Fourier transform is performed on the compensated image to construct a phase error model; Based on the phase error model, the least squares estimation criterion is used to define the weighted entropy of the compensation image and obtain the phase error cost function; Based on the phase error cost function, the compensated image is subjected to phase error correction and inverse Fourier transform to obtain the corrected image.

3. The imaging method based on a calm water surface according to claim 2, characterized in that, The phase error model is as follows: ； In the formula, For the phase error model, For the first Each azimuth unit signal. For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal, For the first Phase variance of the signal in each distance unit For the first Each distance unit signal phase, For the first The weighting coefficients of each distance cell are inversely proportional to the phase variance of that distance cell.

4. The imaging method based on a calm water surface according to claim 3, characterized in that, The weighted entropy of the compensated image is: ； ； In the formula, To compensate for the weighted entropy of the image, For the first Each azimuth unit signal. For pixel image density, For pixel energy, The total energy of the image.

5. The imaging method based on a calm water surface according to claim 4, characterized in that, The phase error cost function is: ； In the formula, This is the error phase estimate. This is the error phase.

6. An imaging device based on a calm water surface, characterized in that, An imaging method based on a calm water surface according to any one of claims 1 to 5, comprising: The acquisition module is used to acquire observation scenes of calm water surface environments and construct observation models of calm water surface environments. The compensation module is used to calculate the propagation distance difference between the direct wave and the multipath signal based on the observation model of the calm water surface environment and the ray tracing method to obtain the compensation phase; based on the compensation phase, the multipath target is moved to the actual target position to obtain the compensation image; The correction module is used to correct the phase error of the compensated image using a self-focusing algorithm based on weighted minimum entropy, so as to obtain the corrected image. The output module is used to output the current image when the image entropy of the corrected image meets the preset conditions.

Images