Embedded space-borne ISAR imaging method based on envelope phase uniform compensation

Abstract

The application relates to an embedded space-based ISAR imaging method based on envelope phase unified compensation, characterized in that the method comprises the following steps: obtaining echo data after pulse compression; performing translational motion compensation on the echo data after pulse compression through envelope phase unified compensation to obtain data after translational motion compensation; wherein the envelope phase unified compensation comprises envelope phase unified coarse compensation and envelope phase unified fine compensation; performing shift motion compensation on the data after translational motion compensation through a polar coordinate format algorithm to obtain data after shift motion compensation; and obtaining an imaging result according to the data after shift motion compensation. Through the above technical scheme, the translational motion compensation of data is completed under the consistency of the envelope and the phase through the envelope phase unified coarse compensation and the envelope phase unified fine compensation, the consistency of the envelope and the phase is ensured, and the distance shift motion of a large angle can be compensated through the polar coordinate format algorithm for distance shift motion compensation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar, in particular to an embedded space-based ISAR imaging method based on envelope phase unified compensation. BACKGROUND

[0002] In the field of modern radar technology, Inverse-Synthetic-Aperture-Radar (ISAR) as a non-cooperative target imaging technology, has attracted much attention due to its unique advantages. It does not need to rely on the target itself to transmit signals, but can achieve high-resolution two-dimensional imaging by receiving and processing the echo signals of target scattering. This feature makes ISAR play a crucial role in reconnaissance, target identification and civil monitoring.

[0003] At present, most of the radars for space target imaging belong to ground-based radars with limitations. Due to the fixed station position of the ground-based radar system, the ground-based space monitoring system has insufficient observation range, which cannot guarantee the safety of the entire space environment. At the same time, due to the long distance of small space targets and the influence of natural weather conditions (wind speed, weather, temperature, solar radiation, etc.), the energy of small targets received by traditional ground-based radars is weak, the noise proportion in the echo is large, and the echo signal-to-noise ratio is low, which increases the difficulty of imaging. The on-orbit spaceborne radar can take advantage of the advantages of radar imaging to monitor and track space targets all day and all weather.

[0004] In the ISAR imaging process, the translation (i.e. uniform linear motion) of the target often leads to image blurring, which affects the quality of the image and the recognition accuracy of the target. SUMMARY

[0005] In order to solve the above problems existing in the prior art, the present application provides an embedded space-based ISAR imaging method based on envelope phase unified compensation.

[0006] According to a first aspect of the embodiment of the present application, an embedded space-based ISAR imaging method based on envelope phase unified compensation is provided, the method comprising:

[0007] acquiring echo data after pulse compression; wherein the echo data after pulse compression is obtained according to an embedded space-based ISAR;

[0008] performing translation compensation on the echo data after pulse compression by envelope phase unified compensation to obtain data after translation compensation; wherein the envelope phase unified compensation comprises envelope phase unified coarse compensation and envelope phase unified fine compensation;

[0009] performing translation compensation on the data after translation compensation by polar coordinate format algorithm to obtain data after translation compensation;

[0010] According to the migration compensation data, an imaging result is obtained.

[0011] Optionally, the motion compensation of the pulse compressed echo data through the envelope phase unified compensation comprises:

[0012] The pulse compressed echo data is compensated through the envelope phase unified coarse compensation to obtain coarse compensated data;

[0013] The coarse compensated data is compensated through the envelope phase unified fine compensation to obtain the motion compensated data.

[0014] Optionally, the pulse compressed echo data is compensated through the envelope phase unified coarse compensation to obtain coarse compensated data, comprising:

[0015] The offset between the time delay of the first peak value corresponding to each group of echo data in the pulse compressed echo data and the time delay of the last peak value corresponding to the previous group of echo data is calculated through a cross-correlation algorithm to obtain the offset of each group of echo data;

[0016] According to the offset between each group of echo data, the time delay of the pulse compressed echo data is obtained;

[0017] According to the time delay of the pulse compressed echo data, an envelope phase unified coarse compensation function is constructed;

[0018] The pulse compressed echo data is compensated according to the envelope phase unified coarse compensation function to obtain coarse compensated data.

[0019] Optionally, the envelope phase unified coarse compensation function refers to the following formula:

[0020] ;

[0021] wherein, the envelope phase unified coarse compensation function is denoted as f (t), is an exponential function, is a slow time, is an envelope frequency, is a carrier frequency, is the time delay of the pulse compressed echo data, is an imaginary unit, is the speed of light, is the range resolution of a radar, is the bandwidth of the radar.

[0022] Optionally, the step of compensating the coarsely compensated data through the envelope phase unification fine compensation to obtain the translationally compensated data includes:

[0023] Calculate the normalized magnitude variance of the azimuth data;

[0024] Select data in the azimuth data whose normalized amplitude variance is less than a preset threshold as target data;

[0025] The phase error corresponding to the target data is obtained by conjugate multiplication and weighted least squares method;

[0026] Construct an envelope phase unified fine compensation function based on the phase error corresponding to the target data;

[0027] The coarsely compensated data is compensated using the envelope phase unified fine compensation function to obtain the translationally compensated data.

[0028] Optionally, the envelope phase unified fine compensation function refers to the following formula:

[0029] ;

[0030] in, This represents the envelope phase unified fine compensation function. It is an exponential function. For slow time, For envelope frequency, For carrier frequency, The time delay of the pulse-compressed echo data, The imaginary unit, At the speed of light, The phase error is... According to The obtained translational data.

[0031] Optionally, the data after translational compensation can be represented as follows:

[0032] ;

[0033] in, This represents the data after translational compensation. The data after coarse compensation, The number of the scattering point. The total number of the scattering points. For the first The amplitude of each distance unit, For the bandwidth of the radar, For window functions, Represents any scattering point Two-dimensional coordinates in a target local coordinate system.

[0034] Optionally, the moving compensation of the data after the parallel motion compensation by the polar coordinate format algorithm comprises:

[0035] Obtaining radial wave numbers and rotation angle data;

[0036] Obtaining azimuth wave numbers and distance wave numbers according to the radial wave numbers and the rotation angle data;

[0037] Obtaining interpolated azimuth wave numbers and interpolated distance wave numbers by interpolation of the extreme values of the azimuth wave numbers and the distance wave numbers;

[0038] Obtaining new radial wave numbers according to the interpolated azimuth wave numbers;

[0039] Obtaining distance-interpolated data according to the radial wave numbers and the new radial wave numbers;

[0040] Obtaining the moving compensation data according to the interpolated azimuth wave numbers and the interpolated distance wave numbers.

[0041] Optionally, the obtaining of the distance-interpolated data according to the radial wave numbers and the new radial wave numbers comprises:

[0042] Obtaining first relative positions according to the radial wave numbers and the new radial wave numbers;

[0043] Obtaining a first window function according to the first relative positions;

[0044] Selecting the data after the parallel motion compensation according to the first window function to obtain first selected data;

[0045] Interpolating the first selected data in the distance direction to obtain the distance-interpolated data.

[0046] Optionally, the obtaining of the moving compensation data according to the interpolated azimuth wave numbers and the interpolated distance wave numbers comprises:

[0047] Obtaining second relative positions according to the interpolated azimuth wave numbers and the interpolated distance wave numbers;

[0048] Obtaining a second window function according to the second relative positions;

[0049] Selecting the distance-interpolated data according to the second window function to obtain second selected data;

[0050] Interpolating the second selected data in the azimuth direction to obtain the moving compensation data.

[0051] The technical scheme provided by the application can include the following beneficial effects:

[0052] Through the above technical scheme, through the envelope phase unified coarse compensation and envelope phase unified fine compensation, the data motion compensation is completed under the consistency of the envelope and the phase, the consistency of the envelope and the phase is ensured, and the distance migration compensation is performed by using the polar coordinate format algorithm, so that the distance migration with a large angle can be compensated.

[0053] Other features and advantages of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0054] The accompanying drawings are included to provide a further understanding of the application and constitute a part of the specification, and are used together with the following specific embodiments to explain the application, but do not constitute a limitation on the application. In the drawings:

[0055] Figure 1 is a flow chart of an embedded space-based ISAR imaging method based on envelope phase unified compensation according to an exemplary embodiment.

[0056] Figure 2 is a DSP platform overall flow chart according to an exemplary embodiment.

[0057] Figure 3 is a DSP platform envelope phase unified coarse compensation data segmentation schematic diagram according to an exemplary embodiment.

[0058] Figure 4 is a DSP platform envelope phase unified coarse compensation flow chart according to an exemplary embodiment.

[0059] Figure 5 is a DSP platform envelope phase unified fine compensation flow chart according to an exemplary embodiment.

[0060] Figure 6 is a DSP platform polar coordinate format algorithm flow chart according to an exemplary embodiment.

[0061] Figure 7 is an envelope schematic diagram of original data according to an exemplary embodiment.

[0062] Figure 8 is a MATLAB envelope phase coarse compensation result schematic diagram according to an exemplary embodiment.

[0063] Figure 9 is a DSP platform envelope phase coarse compensation result schematic diagram according to an exemplary embodiment.

[0064] Figure 10is a MATLAB envelope phase fine compensation after phase diagram shown according to an exemplary embodiment.

[0065] Figure 11 is a DSP platform envelope phase fine compensation after phase diagram shown according to an exemplary embodiment.

[0066] Figure 12 is a MATLAB envelope phase fine compensation after imaging result diagram shown according to an exemplary embodiment.

[0067] Figure 13 is a DSP platform envelope phase fine compensation after imaging result diagram shown according to an exemplary embodiment.

[0068] Figure 14 is a MATLAB and DSP platform in a certain column of data in the distance sampling unit result comparison diagram shown according to an exemplary embodiment.

[0069] Figure 15 is a MATLAB and DSP platform in a certain row of data in the azimuth sampling unit result comparison diagram shown according to an exemplary embodiment.

[0070] Figure 16 is a MATLAB polar coordinate format algorithm imaging result diagram shown according to an exemplary embodiment.

[0071] Figure 17 is a DSP platform polar coordinate format algorithm imaging result diagram shown according to an exemplary embodiment.

[0072] Figure 18 is a MATLAB imaging result A point contour diagram shown according to an exemplary embodiment.

[0073] Figure 19 is a DSP platform imaging result A point contour diagram shown according to an exemplary embodiment. DETAILED DESCRIPTION

[0074] In order to facilitate the understanding of the present application scheme, first of all, the prior art related circumstances and the inventive concept of the present application are briefly described.

[0075] In the prior art, the translational compensation is usually divided into two steps of envelope alignment and initial phase correction. The envelope alignment is generally realized by a cross-correlation method, a modulo-2 distance method, a modulo-1 distance method or a minimum entropy method, and the initial phase correction is realized by a multi-single feature point method, a feature point synthesis method or a phase gradient autofocus method. However, because the envelope and the initial phase are compensated respectively, the consistency of the envelope and the phase cannot be guaranteed, and large errors may be caused in subsequent imaging steps such as Ksystone operation and PFA operation. Therefore, the present application provides an embedded space-based ISAR imaging method based on unified compensation of envelope and phase to solve the technical problem.

[0076] Figure 1 A flowchart of an embedded space-based ISAR imaging method based on unified compensation of envelope and phase according to an exemplary embodiment is shown in FIG. 1. Figure 1 As shown in the figure, the method comprises the following steps.

[0077] S101, compressed echo data; wherein the pulse compressed echo data is obtained according to the space-based ISAR.

[0078] S102, performing translational compensation on the pulse compressed echo data by unified compensation of envelope and phase to obtain data after translational compensation; wherein the unified compensation of envelope and phase comprises unified coarse compensation of envelope and phase and unified fine compensation of envelope and phase.

[0079] Optionally, S102 can comprise:

[0080] performing compensation on the pulse compressed echo data by unified coarse compensation of envelope and phase to obtain data after coarse compensation;

[0081] performing compensation on the data after coarse compensation by unified fine compensation of envelope and phase to obtain data after translational compensation.

[0082] Optionally, performing compensation on the pulse compressed echo data by unified coarse compensation of envelope and phase to obtain data after coarse compensation comprises:

[0083] calculating the offset between the time delay of the first peak value result of each group of echo data and the time delay of the last peak value result of the previous group of echo data in the pulse compressed echo data by a cross-correlation algorithm to obtain the offset of each group of echo data;

[0084] obtaining the time delay of the pulse compressed echo data according to the offset between each group of echo data;

[0085] constructing a unified coarse compensation function of envelope and phase according to the time delay of the pulse compressed echo data;

[0086] performing compensation on the pulse compressed echo data according to the unified coarse compensation function of envelope and phase to obtain data after coarse compensation.

[0087] It can be understood that the pulse compressed echo data can be demodulated, and the demodulated data can be coarsely compensated. The echo data is subjected to cross-correlation operation to obtain the offset of each group of echo data, and the offset of each group of echo data can be obtained according to the following formula:

[0088]

[0089] wherein, is a cross-correlation function about time delay , and and are envelopes of twice adjacent pulse compressed echo data, indicates fast time;

[0090] According to the above formula, the offset between the time delay of the first peak value corresponding to each group of pulse compressed echo data and the time delay of the last peak value corresponding to the previous group of echo data is obtained , wherein, indicates slow time.

[0091] Specifically, the envelope phase uniform coarse compensation function is referred to the following formula:

[0092]

[0093] wherein, indicates the envelope phase uniform coarse compensation function, is an exponential function, is slow time, is envelope frequency, is carrier frequency, is time delay of pulse compressed echo data, is an imaginary unit, is light speed, is distance resolution of radar, is bandwidth of radar.

[0094] Optionally, the data after coarse compensation is compensated by envelope phase uniform fine compensation to obtain data after translational compensation, including:

[0095] calculating normalized amplitude variance of azimuth data;

[0096] selecting data with normalized amplitude variance less than a preset threshold value in the azimuth data as target data;

[0097] acquiring phase error corresponding to the target data by conjugate multiplication and weighted least square method;

[0098] ​​An envelope phase uniform fine compensation function is constructed according to the phase error corresponding to the target data.

[0099] The data after coarse compensation is compensated by using the envelope phase uniform fine compensation function to obtain the data after motion compensation.

[0100] It can be understood that when the azimuth data in the data after coarse compensation is screened by using the normalized amplitude variance, the following normalized amplitude variance formula can be used:

[0101] ;

[0102] Wherein, denotes the normalized amplitude variance, is the average value of the echo sequence amplitude of the i th range unit, is the mean square error thereof.

[0103] It is worth mentioning that after the data with the normalized amplitude variance less than the preset threshold value in the azimuth data is selected as the target data, the phase difference history thereof is obtained by conjugate multiplication, and the phase difference history is estimated according to the weighted least square method to obtain , and then the sum is obtained according to , that is, when , the phase error corresponding to the target data is .

[0104] Specifically, the envelope phase uniform fine compensation function refers to the following formula:

[0105] ;

[0106] Wherein, denotes the envelope phase uniform fine compensation function, is an exponential function, is a slow time, is an envelope frequency, is a carrier frequency, is a time delay of the echo data after pulse compression, is an imaginary unit, is the speed of light, is the phase error corresponding to the error data, is the motion data obtained according to .

[0107] Optionally, the data after motion compensation refers to the following:

[0108] ;

[0109] Wherein, ​​​denotes the translational compensation data, denotes the coarse compensation data, denotes the serial number of the scattering point, denotes the total number of the scattering points, denotes the amplitude of the th distance unit, denotes the bandwidth of the radar, denotes the window function, denotes the two-dimensional coordinates of any scattering point in the target local coordinate system.

[0110] S103, by the polar coordinate format algorithm, the translational compensation data is compensated for migration, and the migration compensation data is obtained.

[0111] Optionally, S103 can include:

[0112] Obtain the radial wave number and the rotation angle data;

[0113] According to the radial wave number and the rotation angle data, the azimuth wave number and the distance wave number are obtained;

[0114] By the polar value of the azimuth wave number and the distance wave number, the interpolated azimuth wave number and the interpolated distance wave number are obtained;

[0115] According to the interpolated azimuth wave number, the new radial wave number is obtained;

[0116] According to the radial wave number and the new radial wave number, the distance interpolation data is obtained;

[0117] According to the interpolated azimuth wave number and the interpolated distance wave number, the migration compensation data is obtained.

[0118] According to the radar angle measurement information, the rotation angle data can be obtained, and the following formula is referred to:

[0119] ;

[0120] Wherein, denotes the rotation angle data at the th pulse moment, denotes the inverse cosine function, and denotes the initial unit vector of the radar pointing to the target at the th pulse moment.

[0121] Optionally, according to the radial wave number and the new radial wave number, the distance interpolation data includes:

[0122] According to the radial wave number and the new radial wave number, the first relative position is obtained;

[0123] According to the first relative position, the first window function is obtained;

[0124] The data after the translation compensation is filtered according to the first window function to obtain first filtered data.

[0125] The first filtered data is subjected to distance direction interpolation to obtain data after distance direction interpolation.

[0126] Optionally, the data after the migration compensation is obtained according to the interpolated azimuth wave number and the interpolated distance wave number, and the data after the migration compensation comprises:

[0127] The second relative position is obtained according to the interpolated azimuth wave number and the interpolated distance wave number.

[0128] The second window function is obtained according to the second relative position.

[0129] The data after the distance direction interpolation is filtered according to the second window function to obtain second filtered data.

[0130] The second filtered data is subjected to azimuth direction interpolation to obtain the data after the migration compensation.

[0131] S104, the imaging result is obtained according to the data after the migration compensation.

[0132] In an embodiment, the present application can be applied to a DSP (Digital Signal Processor) platform, which can be a TMS320C6678 DSP platform based on Ti. The platform integrates 8 C66x CorePac DSP cores, has a working frequency of 1 GHz, and a rated power consumption of 7.56 W. The data processing efficiency can be greatly improved under low power consumption conditions.

[0133] In the DSP platform, the operation speed is different due to different data storage locations. The fastest calculation speed is the L1 cache (level 1 cache), but it has a small space and is generally used for temporary storage of a small amount of data. The second is the L2 cache (level 2 cache), but the data is shared by each core and cannot be accessed by each other. The speed is similar to the MSMC (Muticore Shared Memory Controller) shared cache, which has a large capacity and can be accessed by each core. The next is the DDR (Double Data Rate) storage, which has the largest capacity but the slowest speed, and is generally used for storage of large data. In order to improve the operation speed, the system uses DMA (Direct Memory Access) to move the data required for operation from the DDR to the shared memory for processing. DMA can move a large amount of data in a short time, thereby improving the processing speed.

[0134] Further, Figure 2is a general flow chart of the DSP platform according to an exemplary embodiment, as Figure 2 As shown, when applied to the DSP platform, the present application can be roughly divided into the following parts: obtaining the pulse compressed echo data, 8-core synchronization, envelope phase unified coarse compensation, envelope phase unified fine compensation, polar coordinate format algorithm and completing imaging.

[0135] Figure 3 is a data segmentation schematic diagram of the envelope phase unified coarse compensation of the DSP platform according to an exemplary embodiment, Figure 4 is a flow chart of the envelope phase unified coarse compensation of the DSP platform according to an exemplary embodiment, the envelope phase unified coarse compensation function needs to calculate the time delay of each echo data by the cross-correlation method to construct the envelope phase unified coarse compensation function, and the cross-correlation method operation is to perform correlation calculation in the distance direction, and the time delay of the peak value of the correlation result is compensated.

[0136] To realize 8-core parallel acceleration, the echo data is divided into 8 parts in the azimuth direction, as Figure 3 As shown, each part contains the starting data of the next part, the offset between each group of echo data is obtained by calculating the offset of the time delay of the first peak value of each group of echo data and the time delay of the last peak value of the previous part, so as to compensate and obtain the complete time delay, and then construct the envelope phase unified coarse compensation function. The specific process can be referred to Figure 4 .

[0137] Figure 5 is a flow chart of the envelope phase unified fine compensation of the DSP platform according to an exemplary embodiment, the data after coarse compensation is divided into 8 parts in the distance direction, the absolute value of the data is calculated according to the core number of the DSP platform and stored in rows (azimuth direction), and it is judged whether the calculation of all data is completed. After the calculation of all data is completed, the absolute value of the stored data is indexed according to the core number, the normalized amplitude variance of each row of data (each azimuth direction data) is calculated, the threshold is selected according to the normalized amplitude variance, the data (target data) with the normalized amplitude variance less than the preset threshold is selected, the weight of the weighted least square is calculated according to the reciprocal of the normalized amplitude variance, the data is divided into 8 parts in columns, the phase error is obtained by the conjugate multiplication and the weighted least square of the 8 cores, so as to construct the envelope phase unified fine compensation function and compensate. The specific process is shown in Figure 5 .

[0138] Figure 6is a flow chart of a polar coordinate format algorithm of a DSP platform according to an exemplary embodiment, the radar obtains radial wave numbers and rotation angle data, calculates azimuth wave numbers and range wave numbers according to the radial wave numbers and the rotation angle data, uses the polar values of the azimuth wave numbers and the range wave numbers to perform interpolation to obtain interpolated azimuth wave numbers and range wave numbers, calculates new radial wave numbers according to the interpolated azimuth wave numbers, calculates a first relative position corresponding to the interpolated radial wave numbers according to the radial wave numbers and the new radial wave numbers, to avoid using data beyond the original data range during interpolation, calculates a first window function using the relative position of the interpolated radial wave numbers to perform data screening, performs distance direction interpolation on the screened data using a sinc interpolation method to obtain distance direction interpolated data, calculates corresponding rotation angles according to the interpolated azimuth wave numbers and the range wave numbers, and constructs a second window function in a similar manner to the window function used for screening the interpolated radial wave numbers, performs azimuth direction interpolation on the second screened data using a sinc interpolation method to obtain drift-compensated data. To realize 8-core parallel acceleration, the data is divided into 8 equal parts in the distance direction during distance direction interpolation, and a sinc interpolation operation is performed simultaneously, and the data is divided into 8 equal parts in the azimuth direction during azimuth direction interpolation, and a parallel sinc interpolation operation is performed. The process is shown in Figure 6 .

[0139] In an embodiment, the present application uses a radar signal with a carrier frequency of 10 GHz, a bandwidth of 1 GHz, and a pulse repetition frequency of 800 to perform simulation experiments, and the target is an airplane model composed of multiple points. Figure 7 is an envelope diagram of raw data according to an exemplary embodiment, Figure 8 is a MATLAB envelope phase coarse compensation result diagram according to an exemplary embodiment, Figure 9 is a DSP platform envelope phase coarse compensation result diagram according to an exemplary embodiment, it can be seen that the data envelope after the envelope phase unified coarse compensation in the present application applied to the DSP platform has been straightened. Figure 10 is a MATLAB envelope phase fine compensation result diagram according to an exemplary embodiment, Figure 11 is a DSP platform envelope phase fine compensation result diagram according to an exemplary embodiment, it can be seen that the phases after the MATLAB and DSP platform fine compensation are gathered. Figure 12 is a MATLAB envelope phase fine compensation result diagram according to an exemplary embodiment, Figure 13 is a DSP platform envelope phase fine compensation result diagram according to an exemplary embodiment, it can be seen that the translation has been compensated, but there is still drift. Figure 14 is a comparison diagram of the results of a certain column of data in the MATLAB and the DSP platform in the distance sampling unit according to an exemplary embodiment, Figure 15It is a comparison chart of the results of a certain row of data in MATLAB and DSP platform azimuth sampling unit according to an exemplary embodiment, and it can be seen that the error of MATLAB and DSP platform results is very small. Figure 16 It is a MATLAB polar coordinate format algorithm imaging result schematic diagram according to an exemplary embodiment, Figure 17 It is a DSP platform polar coordinate format algorithm imaging result schematic diagram according to an exemplary embodiment, and it can be seen that the drift has been compensated. Figure 18 and Figure 19 , Figure 18 It is a MATLAB imaging result A point contour schematic diagram according to an exemplary embodiment, Figure 19 It is a DSP platform imaging result A point contour schematic diagram according to an exemplary embodiment, and it can be found that the image focusing effect is good.

[0140] Since the application completes the data shift compensation in the consistency of envelope and phase by constructing the envelope phase unified compensation function, guarantees the consistency of envelope and phase, and adopts the polar coordinate format algorithm to compensate the distance drift, the application can compensate the distance drift with a large angle, can be applied to the TMS320C6678 DSP platform, and can meet the real-time requirement of space-based imaging in the case of low power consumption.

[0141] The preferred embodiments of the application are described in detail above with reference to the drawings, but the application is not limited to the specific details in the above-described embodiments, and various simple modifications can be made to the technical solutions of the application within the technical concept of the application, and these simple modifications all belong to the protection scope of the application.

[0142] In addition, it should be noted that each specific technical feature described in the above specific embodiments can be combined in any appropriate manner without contradiction, and in order to avoid unnecessary repetition, the application will not further describe various possible combination manners.

[0143] In addition, various different embodiments of the application can also be combined in any manner, as long as it does not deviate from the technical concept of the application, and it should be considered as disclosed by the application.

Claims

1. An embedded space-based ISAR imaging method based on envelope phase uniform compensation, characterized in that, The method comprises: acquiring pulse compressed echo data; wherein the pulse compressed echo data is obtained according to an embedded space-based ISAR; performing translational compensation on the pulse compressed echo data through envelope phase unified compensation to obtain translational compensated data; wherein the envelope phase unified compensation comprises envelope phase unified coarse compensation and envelope phase unified fine compensation; performing shifting compensation on the translational compensated data through a polar coordinate format algorithm to obtain shifting compensated data; obtaining imaging results according to the shifting compensated data; compensating the pulse compressed echo data according to the envelope phase unified coarse compensation function to obtain coarse compensated data, wherein the envelope phase unified coarse compensation function is expressed as follows: ； wherein denotes the envelope phase-unified coarse compensation function, is an exponential function, is a slow time, is an envelope frequency, is a carrier frequency, is a time delay of the pulse-compressed echo data, is the imaginary unit, is the speed of light, is a range resolution of the radar, is a bandwidth of the radar; compensating the coarse compensated data using the envelope phase unified fine compensation function to obtain the translational compensated data, wherein the envelope phase unified fine compensation function is expressed as follows: ； in, This represents the envelope phase unified fine compensation function. It is an exponential function. For slow time, For envelope frequency, For carrier frequency, The time delay of the pulse-compressed echo data, The imaginary unit, At the speed of light, For phase error, According to The obtained translational data.

2. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 1, characterized in that, The compensation of the pulse compressed echo data according to the envelope phase unified coarse compensation function to obtain coarse compensated data comprises: calculating the offset between the time delay of the first peak value result corresponding to each group of echo data in the pulse compressed echo data and the time delay of the last peak value result corresponding to the previous group of echo data through a cross-correlation algorithm to obtain the offset of each group of echo data; obtaining the time delay of the pulse compressed echo data according to the offset between each group of echo data; constructing an envelope phase unified coarse compensation function according to the time delay of the pulse compressed echo data; compensating the pulse compressed echo data according to the envelope phase unified coarse compensation function to obtain coarse compensated data.

3. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 1, characterized in that, The compensation of the coarse compensated data using the envelope phase unified fine compensation function to obtain the translational compensated data comprises: calculating the absolute value of the coarse compensated data according to the range direction and storing it in the azimuth direction to obtain azimuth direction data; calculating the normalized amplitude variance of the azimuth direction data; selecting data with a normalized amplitude variance less than a preset threshold value in the azimuth direction data as target data; obtaining the phase error corresponding to the target data through conjugate multiplication and weighted least squares method; constructing an envelope phase unified fine compensation function according to the phase error corresponding to the target data; compensating the coarse compensated data using the envelope phase unified fine compensation function to obtain the translational compensated data.

4. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 3, characterized in that, The translational compensated data is expressed as follows: ； wherein, denotes the data after the translational compensation, denotes the data after the coarse compensation, denotes the sequence number of the scattering point, denotes the total number of the scattering points, denotes the amplitude of the distance unit, denotes the bandwidth of the radar, denotes a window function, denotes the two-dimensional coordinate of an arbitrary scattering point in the local coordinate system of the target.

5. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 1, characterized in that, The shifting compensation on the translational compensated data through the polar coordinate format algorithm to obtain the shifting compensated data comprises: acquiring radial wave numbers and rotation angle data; obtaining azimuth wave numbers and range wave numbers according to the radial wave numbers and the rotation angle data; performing interpolation on the extreme values of the azimuth wave numbers and the range wave numbers to obtain interpolated azimuth wave numbers and interpolated range wave numbers; obtaining new radial wave numbers according to the interpolated azimuth wave numbers; obtaining range direction interpolated data according to the radial wave numbers and the new radial wave numbers; The migration-compensated data is obtained according to the interpolated azimuth wavenumber and the interpolated range wavenumber.

6. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 5, characterized in that, The obtaining of the range-interpolated data according to the radial wavenumber and the new radial wavenumber comprises: obtaining a first relative position according to the radial wavenumber and the new radial wavenumber; obtaining a first window function according to the first relative position; screening the shift-compensated data according to the first window function to obtain first screened data; range-interpolating the first screened data to obtain range-interpolated data.

7. The embedded space-based ISAR imaging method based on envelope phase uniform compensation according to claim 6, characterized in that, The obtaining of the migration-compensated data according to the interpolated azimuth wavenumber and the interpolated range wavenumber comprises: obtaining a second relative position according to the interpolated azimuth wavenumber and the interpolated range wavenumber; obtaining a second window function according to the second relative position; screening the range-interpolated data according to the second window function to obtain second screened data; azimuth-interpolating the second screened data to obtain the migration-compensated data.

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