Multi-channel space-borne SAR ship target imaging method based on multi-dimensional error estimation

Abstract

This invention discloses a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation. The method includes: constructing an initial echo signal model for each channel of a moving ship target in a multi-channel spaceborne synthetic aperture radar; embedding the azimuth frequency domain phase error into the initial echo signal model based on the formation mechanism of channel phase error and azimuth frequency domain phase error, and transforming the expression form of the channel phase error in the initial echo signal model to obtain a final signal model containing multi-dimensional errors for each channel; imaging the final signal model of each channel to obtain a sub-SAR image for each channel; compensating and merging the channel phase error and azimuth frequency domain phase error of each sub-SAR image in the image domain to obtain a multi-channel SAR image model; solving the multi-channel SAR image model to obtain the compensation estimation results of the channel phase error and azimuth frequency domain phase error, and obtaining the final SAR image. This application can effectively compensate for the channel phase error and azimuth frequency domain phase error in the image, improving imaging quality.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation. Background Technology

[0002] Multi-channel spaceborne synthetic aperture radar (SAR) achieves both high resolution and wide swath width by arranging multiple receiving channels along the antenna azimuth. When multiple channels simultaneously receive echo signals, the equivalent pulse repetition frequency (PRF) is increased. Therefore, while maintaining the same azimuth resolution, the range swath width can be significantly increased. Consequently, multi-channel spaceborne SAR systems are commonly used for observation of distant sea areas and for ship monitoring.

[0003] However, since ships in the open ocean are usually in motion, on the one hand, the ship's radial speed introduces phase errors between channels, causing unsuppressed blur components in the azimuth spectrum to appear as false targets in the final imaging results. On the other hand, the ship's azimuth speed generates phase errors in the azimuth frequency domain, which will cause the ship target to be out of focus in the final SAR image. False targets and defocus will seriously affect subsequent target identification and interpretation.

[0004] Therefore, there is an urgent need for a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation to solve the above problems. Summary of the Invention

[0005] This invention provides a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation, which can effectively compensate for channel phase errors and azimuth frequency domain phase errors in the image, thereby improving the imaging quality of ship targets. The technical solution is as follows:

[0006] On the one hand, a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation is provided, the method comprising:

[0007] Construct an initial echo signal model for each channel of a moving ship target in a multi-channel spaceborne synthetic aperture radar;

[0008] Based on the formation mechanism of channel phase error and azimuth frequency domain phase error, the azimuth frequency domain phase error is embedded into the initial echo signal model and the expression form of channel phase error in the initial echo signal model is transformed to obtain the final signal model containing multi-dimensional errors for each channel.

[0009] The final signal model of each channel is imaged to obtain a sub-SAR image for each channel;

[0010] In the image domain, the channel phase error and azimuth frequency domain phase error of each sub-SAR image are compensated and merged to obtain a multi-channel SAR image model.

[0011] The multi-channel SAR image model is solved to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and the final SAR image is obtained.

[0012] On the other hand, a multi-channel spaceborne SAR ship target imaging device based on multidimensional error estimation is provided, the device comprising:

[0013] The first model building unit is used to build the initial echo signal model of the moving ship target in each channel of the multi-channel spaceborne synthetic aperture radar.

[0014] The second model construction unit is used to embed the azimuth frequency domain phase error into the initial echo signal model based on the formation mechanism of channel phase error and azimuth frequency domain phase error, and transform the expression form of channel phase error in the initial echo signal model to obtain the final signal model containing multi-dimensional errors for each channel.

[0015] The first imaging unit is used to image the final signal model of each channel to obtain a sub-SAR image for each channel;

[0016] The third model building unit is used to compensate and merge the channel phase error and azimuth frequency domain phase error of each sub-SAR image in the image domain to obtain a multi-channel SAR image model.

[0017] The solution unit is used to solve the multi-channel SAR image model to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and to obtain the final SAR image.

[0018] On the other hand, a computer device is provided, the computer device including a memory and a processor, the memory for storing computer programs, and the processor for executing the computer programs stored in the memory to implement the steps of the multi-channel spaceborne SAR ship target imaging method based on multidimensional error estimation described above.

[0019] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, it implements the steps of the multi-channel spaceborne SAR ship target imaging method based on multidimensional error estimation described above.

[0020] On the other hand, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the multi-channel spaceborne SAR ship target imaging method based on multidimensional error estimation described above.

[0021] This invention provides a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation. In this embodiment, firstly, based on the formation mechanism of channel phase error and azimuth frequency domain phase error, the errors of both dimensions are characterized in a specific form in the original echo signal model to obtain the final signal model for each channel and then image it. Then, in the image domain, the channel phase error and azimuth frequency domain phase error of each sub-SAR image are estimated and compensated, thereby obtaining the focused final image. This method can not only eliminate the inter-channel phase error introduced by the ship's radial speed and eliminate false targets, but also eliminate the azimuth frequency domain phase error caused by the ship's azimuth speed, avoiding defocus. Furthermore, error compensation in each dimension is completed in the image domain, which can greatly improve processing speed and computational efficiency. Therefore, this application can effectively compensate for multi-dimensional phase errors caused by ship rotational motion, suppress the occurrence of false targets, eliminate defocus, and improve image quality. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation provided by an embodiment of the present invention;

[0024] Figure 2 This is a SAR image without multidimensional error correction provided in an embodiment of the present invention;

[0025] Figure 3 This is a SAR image after multidimensional error correction using the method of this application, provided in an embodiment of the present invention;

[0026] Figure 4 This is an embodiment of the present invention that provides a... Figure 2 A magnified view of the ship target circled in the center;

[0027] Figure 5 This is an embodiment of the present invention that provides a... Figure 3 A magnified view of the ship target circled in the center;

[0028] Figure 6 This is a structural diagram of a multi-channel spaceborne SAR ship target imaging device based on multidimensional error estimation, provided in an embodiment of the present invention.

[0029] Figure 7This is a hardware architecture diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] The specific implementation of the method in this application is described in detail below.

[0032] Please refer to Figure 1 This invention provides a multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation, the method comprising:

[0033] Step 100: Construct the initial echo signal model of the moving ship target in each channel of the multi-channel spaceborne synthetic aperture radar;

[0034] Step 102: Based on the formation mechanism of channel phase error and azimuth frequency domain phase error, embed the azimuth frequency domain phase error into the initial echo signal model and transform the expression form of channel phase error in the initial echo signal model to obtain the final signal model containing multi-dimensional errors for each channel.

[0035] Step 104: Image the final signal model of each channel to obtain a sub-SAR image for each channel;

[0036] Step 106: Compensate and merge the channel phase error and azimuth frequency domain phase error of each sub-SAR image in the image domain to obtain a multi-channel SAR image model.

[0037] Step 108: Solve the multi-channel SAR image model to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and obtain the final SAR image.

[0038] In this embodiment, firstly, based on the formation mechanism of channel phase error and azimuth frequency domain phase error, the errors of both dimensions are characterized in a specific form in the original echo signal model to obtain the final signal model for each channel and then image it. Then, in the image domain, the channel phase error and azimuth frequency domain phase error of each sub-SAR image are estimated and compensated, thereby obtaining the focused final image. This method can not only eliminate the inter-channel phase error introduced by the ship's radial speed and eliminate false targets, but also eliminate the azimuth frequency domain phase error caused by the ship's azimuth speed, avoiding defocus. Furthermore, error compensation in each dimension is completed in the image domain, which can greatly improve processing speed and computational efficiency. Therefore, this application can effectively compensate for multi-dimensional phase errors caused by ship rotational motion, suppress the occurrence of false targets, eliminate defocus, and improve image quality.

[0039] The following description Figure 1 The execution method of each step is shown.

[0040] First, for step 100, an initial echo signal model of the ship target in each channel of the multi-channel spaceborne synthetic aperture radar is constructed, including:

[0041] Step A1: Construct the imaging geometric model parameters for a multi-channel spaceborne synthetic aperture radar (SAR) target. The geometric model parameters include the number of azimuth receiving channels, the azimuth time when the radar beam center points to the ship target, the slant range between the antenna phase center and the ship target, and the radial and azimuth velocities of the ship target.

[0042] Step A2: Based on the geometric model parameters, construct the instantaneous slant range from the ship target to the reference channel, where the reference channel is the antenna phase center.

[0043] In this step, the instantaneous slant distance from the ship target to the reference channel is... It can be expressed as the following formula:

[0044]

[0045] Step A3: Based on the geometric model parameters, construct the instantaneous slant distance from the ship target to each channel.

[0046] In this step, assume the first m The displacement between each channel and the reference channel is , Then from the target ship P to the... m The instantaneous slant range of each receiving channel can be expressed as follows:

[0047]

[0048] Step A4: Based on the instantaneous slant range from the ship target to the reference channel and the instantaneous slant range from the ship target to each receiving channel, construct the bidirectional slant range of the echo signal received by each channel in the azimuth slow time.

[0049] In this step, the first m Each channel is in a slow position. The bidirectional slant range of the received echo signal can be expressed as follows:

[0050]

[0051] Step A5: Based on the two-way slant range, construct the initial echo signal model of the ship targets in each channel.

[0052] In this step, the first m Theoretical SAR echo signal of each channel It can be expressed as the following formula:

[0053]

[0054] In two-way slant distance In the middle, ignore The effect on the range signal, and substituting the simplified result into the above equation, yields the... m The initial echo signal model for each channel is shown in the following equation:

[0055] (1)

[0056] In the formula, This indicates that when the distance is fast, the time is The direction and slow time are At that time, the first m The initial echo signal of each channel; It is a complex constant; The envelope of the transmitted signal; This indicates that when the distance is fast, the time is The direction and slow time are At that time, the instantaneous slant distance from the ship target to the reference channel; For the first m Displacement between each channel and the reference channel; Equivalent speed; This is the antenna azimuth pattern; The azimuth time when the radar beam center points to the moving target P; The frequency modulation rate of the LFM signal; denoted as λ, where λ is the radial velocity of the target; c is the speed of light. Wavelength; This indicates that when the distance is fast, the time is The direction and slow time are At that time, the echo signal of the ship target received by the reference channel; Indicates the first m Phase error of each channel.

[0057] Regarding step 102: Based on the formation mechanism of channel phase error and azimuth frequency domain phase error, the azimuth frequency domain phase error is embedded into the initial echo signal model and the expression form of channel phase error in the initial echo signal model is transformed to obtain the final signal model containing multi-dimensional errors for each channel.

[0058] In this step, firstly, when the ship target has rotational motion, the phase error of its channel also changes with distance. Therefore, the channel phase error in formula (1) can be... Modeled as a phase error that varies with distance Secondly, let Indicates the time delay caused by ship movement with bearing. The defocusing error due to the change in slant range r, i.e., the azimuth frequency domain phase error, is then embedded into the initial echo signal to obtain the final signal model containing multidimensional errors, as shown in the following equation:

[0059] (2)

[0060] In the formula, The first part represents the multidimensional error. m The final echo signal of each channel; This indicates that when the distance is fast, the time is The direction and slow time are At that time, the echo signal of the ship target received by the reference channel; For the first m Displacement between each channel and the reference channel; Equivalent speed; This indicates that the m-th channel varies with the slope distance. r Varying phase error, r The slant range between the antenna phase center and the ship target P; Indicates the time delay caused by ship movement with bearing. and slant distance r Varying phase error.

[0061] For step 104: Image the final signal model of each channel to obtain a sub-SAR image for each channel, including:

[0062] For each channel, the following steps are performed: range compression is applied to the data for that channel; ship target signals are extracted from the compressed data; a spectrum recovery algorithm is applied to the data for that channel; and imaging processing is performed on the spectrum-recovered data for each channel to obtain the sub-SAR image for that channel. .

[0063] Due to this sub-SAR image It is obtained by performing spectrum recovery and imaging processing based on the signal model shown in equation (2), therefore, It includes channel phase error and azimuth frequency domain phase error, and each error needs to be compensated.

[0064] For step 106, the channel phase error and azimuth frequency domain phase error of each sub-SAR image are compensated and merged in the image domain to obtain a multi-channel SAR image model, including:

[0065] Channel phase error compensation is performed for each sub-SAR image separately;

[0066] Each sub-SAR image after channel phase error compensation is merged;

[0067] The merged image is subjected to a fast Fourier transform to transform it to the azimuth frequency domain, and azimuth frequency domain phase error compensation is performed in the azimuth frequency domain.

[0068] A multi-channel SAR image model is obtained by performing a fast inverse Fourier transform on the image after azimuth frequency domain phase error compensation.

[0069] After the above steps, the expression for the multi-channel SAR image model is as follows:

[0070] (3)

[0071] In the formula, For the overall SAR image; and These are the pixel labels for the azimuth and range directions, respectively. n For azimuth frequency domain labeling, For the first one without phase compensation m Sub-SAR images of each channel; M This represents the total number of channels; The range channel phase error to be corrected; The azimuth frequency domain phase error to be corrected; FFT represents Fast Fourier Transform; IFFT represents Inverse Fast Fourier Transform.

[0072] In formula (3), in the image domain, through In the SAR graph of the compensator Channel phase error in the middle, eliminating false targets; through The azimuth frequency domain phase error in the synthesized image is compensated to eliminate defocus.

[0073] However, the image processing effect depends on the accurate estimation of each phase error. In this application, the multidimensional error estimation is modeled as an image optimization problem, as detailed in step 108.

[0074] In some implementations, step 108 includes:

[0075] Step B1 uses minimizing the image entropy of the final SAR image as the optimization objective of the multi-channel SAR image model.

[0076] In this step, the image entropy can be expressed as:

[0077] (4)

[0078]

[0079] Step B2: Based on the optimization objective, the SAR image optimization problem is transformed into a problem of solving a multidimensional error matrix, and the objective function of the multidimensional error matrix is ​​constructed.

[0080] In this step, the objective function is:

[0081]

[0082] In the formula, Here is the channel phase error matrix, which is... M × L dimensional matrix, the first M Line 1 L The elements corresponding to the column are ; The azimuth frequency domain phase error matrix is, which is N × L dimensional matrix, the first N Line 1 L The elements corresponding to the column are ; IE Image entropy; K , L These represent the total number of pixels in the azimuth and range directions, respectively. The energy of the SAR image.

[0083] Step B3: Solve the objective function based on the preset algorithm to obtain the final compensation values ​​for the channel phase error and the azimuth frequency domain phase error.

[0084] In this step, the objective function is solved using both the quasi-Newton descent method and the coordinate descent method, including:

[0085] a) Initialize the multidimensional error matrix; the objective function gradients of the channel phase error and the azimuth frequency domain phase error can be expressed as follows: and . The Middlem Line 1 The element corresponding to the column is , The Middle n Line 1 The element corresponding to the column is .

[0086] b) Keep the azimuth frequency domain phase error unchanged, and update the channel phase error by calculating the gradient descent direction using the quasi-Newton method.

[0087] c) Keep the channel phase error constant and update the azimuth frequency domain phase error by calculating the descent direction of the azimuth frequency domain phase error gradient.

[0088] d) Iteratively update the channel phase error and azimuth frequency domain phase error until the iteration termination condition is met, and obtain the final channel phase error compensation value. Azimuth frequency domain phase error compensation value .

[0089] Step B4: Input the final compensation value into the multi-channel SAR image model to obtain the final SAR image.

[0090] In this step, after phase error correction and multi-channel image fusion, the final focused SAR image can be represented as:

[0091]

[0092] In the formula, For the final SAR image; The final estimate of the channel phase error; The final estimate of the azimuth frequency domain phase error.

[0093] To verify the effectiveness of the method described in this application, the inventors used the following embodiments to verify the image processing effect of the method. The simulation parameters of this embodiment are shown in Table 1:

[0094] Table 1 Simulation parameters of the embodiment

[0095]

[0096] Using the above data, the experimental results are as follows: Figures 2-5 As shown. Among them, Figure 2 This is a SAR image without multidimensional error correction. Figure 3 The image is a SAR image after multidimensional error correction using the method described in this application. Figure 4 To Figure 2 A magnified view of the ship target circled in the center; Figure 5 To Figure 3 A magnified view of the ship target circled in the center. From Figure 2 and Figure 4 It can be seen that without multidimensional error estimation and correction, false targets appear on both sides of the real ship target, and the real ship target also becomes out of focus due to its movement. This indicates that existing methods cannot effectively suppress false targets and defocusing. Figure 3 and Figure 5 As can be seen, after multidimensional error correction, false targets were successfully suppressed and real ship targets were well focused, indicating that the method of this application can effectively compensate for multidimensional phase errors introduced by ship motion, and verifying the correctness and effectiveness of the multi-channel spaceborne SAR ship target focusing method of this invention.

[0097] In summary, the method proposed in this application can correct multidimensional errors based on the rotational motion of target ships in the open sea. It has greater versatility in actual ship identification applications, adapts to various error types, and can effectively focus ship targets under different motion scenarios.

[0098] like Figure 6 , Figure 7 As shown, this embodiment of the invention provides a multi-channel spaceborne SAR ship target imaging device based on multi-dimensional error estimation. The device embodiment can be implemented through software, hardware, or a combination of both. From a hardware perspective, as... Figure 6 The diagram shown is a hardware architecture diagram of a computing device for a multi-channel spaceborne SAR ship target imaging device based on multi-dimensional error estimation, provided in an embodiment of the present invention. Except for... Figure 6 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 7 As shown, a device in a logical sense is formed by the CPU of the computing device in which it is located reading the corresponding computer program from the non-volatile memory into the memory for execution.

[0099] Please refer to Figure 7 This invention provides a multi-channel spaceborne SAR ship target imaging device based on multi-dimensional error estimation, the device comprising:

[0100] The first model building unit 700 is used to build the initial echo signal model of the moving ship target in each channel of the multi-channel spaceborne synthetic aperture radar.

[0101] The second model building unit 702 is used to embed the azimuth frequency domain phase error into the initial echo signal model and transform the expression form of the channel phase error in the initial echo signal model based on the formation mechanism of channel phase error and azimuth frequency domain phase error, so as to obtain the final signal model containing multi-dimensional errors for each channel.

[0102] The first imaging unit 704 is used to image the final signal model of each channel to obtain a sub-SAR image of each channel;

[0103] The third model building unit 706 is used to compensate and merge the channel phase error and azimuth frequency domain phase error of each sub-SAR image in the image domain to obtain a multi-channel SAR image model.

[0104] Solver 708 is used to solve the multi-channel SAR image model, obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and obtain the final SAR image.

[0105] In some implementations, the first model building unit 700 is used to perform the following operations:

[0106] The imaging geometric model parameters of the multi-channel spaceborne synthetic aperture radar (SAR) target are constructed. The geometric model parameters include the number of azimuth receiving channels, the azimuth time when the radar beam center points to the ship target, the slant range between the antenna phase center and the ship target, and the radial velocity and azimuth velocity of the ship target.

[0107] Based on the geometric model parameters, the instantaneous slant range from the ship target to the reference channel is constructed, where the reference channel is the antenna phase center;

[0108] Based on the geometric model parameters, the instantaneous slant range from the ship target to each channel is constructed respectively;

[0109] Based on the instantaneous slant range from the ship target to the reference channel and the instantaneous slant range from the ship target to each receiving channel, the bidirectional slant range of the echo signal received by each channel in the azimuth slow time is constructed.

[0110] Based on bidirectional slant range, an initial echo signal model of ship targets in each channel is constructed.

[0111] In some implementations, the final signal model incorporating multidimensional errors is as follows:

[0112]

[0113] In the formula, The first part represents the multidimensional error. m The final echo signal of each channel; This indicates that when the distance is fast, the time is The direction and slow time are At that time, the echo signal of the ship target received by the reference channel; For the first m Displacement between each channel and the reference channel; Equivalent speed; This indicates that the m-th channel varies with the slope distance. r Varying phase error, r The slant range between the antenna phase center and the ship target P; Indicates the time delay caused by ship movement with bearing. and slant distance r Varying phase error.

[0114] In some implementations, the third model building unit 706 is used to perform the following operations:

[0115] Channel phase error compensation is performed for each sub-SAR image separately;

[0116] Each sub-SAR image after channel phase error compensation is merged;

[0117] The merged image is subjected to a fast Fourier transform to transform it to the azimuth frequency domain, and azimuth frequency domain phase error compensation is performed in the azimuth frequency domain.

[0118] A multi-channel SAR image model is obtained by performing a fast inverse Fourier transform on the image after azimuth frequency domain phase error compensation.

[0119] In some implementations, the expression for the multi-channel SAR image model is:

[0120]

[0121] In the formula, For the overall SAR image; and These are the pixel labels for the azimuth and range directions, respectively. n For azimuth frequency domain labeling, For the first one without phase compensation m Sub-SAR images of each channel; M This represents the total number of channels; The range channel phase error to be corrected; The azimuth frequency domain phase error to be corrected; FFT represents Fast Fourier Transform; IFFT represents Inverse Fast Fourier Transform.

[0122] In some implementations, the solver 708 is used to perform the following operations:

[0123] Minimizing the image entropy of the final SAR image is used as the optimization objective of the multi-channel SAR image model;

[0124] Based on the optimization objective, the SAR image optimization problem is transformed into a problem of solving a multidimensional error matrix, and an objective function for the multidimensional error matrix is ​​constructed.

[0125] The objective function is solved based on a preset algorithm to obtain the final compensation values ​​for the channel phase error and the azimuth frequency domain phase error.

[0126] The final compensation value is then input into the multi-channel SAR image model to obtain the final SAR image.

[0127] In some implementations, the objective function is:

[0128]

[0129]

[0130]

[0131] In the formula, Here is the channel phase error matrix, which is... M × L dimensional matrix, the first M Line 1 L The elements corresponding to the column are ; The azimuth frequency domain phase error matrix is, which is N × L dimensional matrix, the first N Line 1 L The elements corresponding to the column are ; IE Image entropy; K , L These represent the total number of pixels in the azimuth and range directions, respectively. The energy of the SAR image.

[0132] Embodiments of this application also provide a computer device, please refer to... Figure 7 The computer device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, at least one program, code set or instruction set being loaded and executed by the processor to implement the multi-channel spaceborne SAR ship target imaging method based on multidimensional error estimation provided in the above-described method embodiments.

[0133] The embodiments of this application also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation provided in the above-described method embodiments.

[0134] Embodiments of this application also provide a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium and executes the computer program, causing the computer device to perform any of the multi-channel spaceborne SAR ship target imaging methods based on multi-dimensional error estimation described in the above embodiments.

[0135] For ease of description, the above systems or devices are described separately as various modules or units based on their functions. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware components.

[0136] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0137] Finally, it should be noted that in this document, relational terms such as first, second, third, and fourth are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0138] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A multi-channel spaceborne SAR ship target imaging method based on multi-dimensional error estimation, characterized in that, The method includes: Construct an initial echo signal model for each channel of a moving ship target in a multi-channel spaceborne synthetic aperture radar; Based on the formation mechanism of channel phase error and azimuth frequency domain phase error, the azimuth frequency domain phase error is embedded into the initial echo signal model and the expression form of channel phase error in the initial echo signal model is transformed to obtain the final signal model containing multi-dimensional errors for each channel. The final signal model of each channel is imaged to obtain a sub-SAR image for each channel; In the image domain, the channel phase error and azimuth frequency domain phase error of each sub-SAR image are compensated and merged to obtain a multi-channel SAR image model. The multi-channel SAR image model is solved to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and the final SAR image is obtained. The expression for the multi-channel SAR image model is: In the formula, For the overall SAR image; and These are the pixel labels for the azimuth and range directions, respectively. n For azimuth frequency domain labeling, For the first one without phase compensation m Sub-SAR images of each channel; M This represents the total number of channels; The range channel phase error to be corrected; The azimuth frequency domain phase error to be corrected; FFT represents Fast Fourier Transform; IFFT represents Inverse Fast Fourier Transform; The multi-channel SAR image model is solved to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, resulting in the final SAR image, including: Minimizing the image entropy of the final SAR image is taken as the optimization objective of the multi-channel SAR image model; Based on the optimization objective, the SAR image optimization problem is transformed into a problem of solving a multidimensional error matrix, and an objective function for the multidimensional error matrix is ​​constructed. The objective function is solved based on a preset algorithm to obtain the final compensation values ​​for the channel phase error and the azimuth frequency domain phase error. The final compensation value is then input into the multi-channel SAR image model to obtain the final SAR image.

2. The method according to claim 1, characterized in that, The construction of the initial echo signal model for each channel of the ship target in the multi-channel spaceborne synthetic aperture radar includes: The imaging geometric model parameters of a multi-channel spaceborne synthetic aperture radar (SAR) target are constructed. The geometric model parameters include the number of azimuth receiving channels, the azimuth time when the radar beam center points to the ship target, the slant range between the antenna phase center and the ship target, and the radial velocity and azimuth velocity of the ship target. Based on the geometric model parameters, the instantaneous slant range from the ship target to the reference channel is constructed, where the reference channel is the antenna phase center; Based on the geometric model parameters, the instantaneous slant distance from the ship target to each channel is constructed respectively; Based on the instantaneous slant range from the ship target to the reference channel and the instantaneous slant range from the ship target to each receiving channel, the bidirectional slant range of the echo signal received by each channel in the azimuth slow time is constructed. Based on the bidirectional slant range, an initial echo signal model of the ship target in each channel is constructed.

3. The method according to claim 1, characterized in that, The final signal model containing multidimensional errors is as follows: In the formula, The first part represents the multidimensional error. m The final echo signal of each channel; This indicates that when the distance is fast, the time is The direction and slow time are At that time, the echo signal of the ship target received by the reference channel; For the first m Displacement between each channel and the reference channel; Equivalent speed; This indicates that the m-th channel varies with the slope distance. r Varying phase error, r The slant range between the antenna phase center and the ship target P; Indicates the time delay caused by ship movement with bearing. and slant distance r Varying phase error.

4. The method according to claim 1, characterized in that, The objective function is: In the formula, Here is the channel phase error matrix, which is... M × L dimensional matrix, the first M Line 1 L The elements corresponding to the column are ; The azimuth frequency domain phase error matrix is, which is N × L dimensional matrix, the first N Line 1 L The elements corresponding to the column are ; IE Image entropy; K , L These represent the total number of pixels in the azimuth and range directions, respectively. The energy of the SAR image.

5. A multi-channel spaceborne SAR ship target imaging device based on multidimensional error estimation, characterized in that, The apparatus for implementing the steps of any one of claims 1-4, the apparatus comprising: The first model building unit is used to build the initial echo signal model of the moving ship target in each channel of the multi-channel spaceborne synthetic aperture radar. The second model construction unit is used to embed the azimuth frequency domain phase error into the initial echo signal model based on the formation mechanism of channel phase error and azimuth frequency domain phase error, and transform the expression form of channel phase error in the initial echo signal model to obtain the final signal model containing multi-dimensional errors for each channel. The first imaging unit is used to image the final signal model of each channel to obtain a sub-SAR image for each channel; The third model building unit is used to compensate and merge the channel phase error and azimuth frequency domain phase error of each sub-SAR image in the image domain to obtain a multi-channel SAR image model. The solution unit is used to solve the multi-channel SAR image model to obtain the compensation estimation results of channel phase error and azimuth frequency domain phase error, and to obtain the final SAR image.

6. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the steps of the method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method described in any one of claims 1-4.

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