Inverse synthetic aperture radar signal processing method, device, equipment and medium

Abstract

The invention relates to the technical field of signal processing, and discloses an inverse synthetic aperture radar signal processing method and device, equipment and a medium, and the method comprises the steps: carrying out the frequency rearrangement of an initial time-frequency signal through a frequency rearrangement operator, and obtaining a rearranged time-frequency signal; determining an energy threshold condition according to the rearranged time-frequency signal, and performing trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory meeting the energy threshold condition; performing reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory; and performing time domain signal reconstruction according to the target time frequency trajectory to obtain a target imaging signal. According to the method, the problem that the utilization rate of the echo signals is low due to the fact that appropriate imaging time needs to be selected according to the echo signals is solved, the technical effect of remarkably expanding the selectable imaging time range is achieved, and then the definition and accuracy of the imaging result are improved so that the method can adapt to more complex movement conditions of the target object.

Description

Technical Field

[0001] The present application relates to the technical field of signal processing, and particularly to an inverse synthetic aperture radar signal processing method, apparatus, device, and medium. Background Art

[0002] Synthetic Aperture Radar (SAR) is a technology that uses radar for imaging. By a moving radar platform emitting signals to a target object during flight and receiving the echo signals of the target object for imaging. In synthetic aperture radar, through signal processing of the echo signals, a virtual large aperture is synthesized, thereby improving the imaging resolution. Similarly, Inverse Synthetic Aperture Radar (ISAR) uses the movement of the target object itself for imaging. By a stationary radar platform emitting signals to a moving target object and receiving the echo signals to analyze the movement information of the target object. Synthetic aperture radar is mainly used in fields such as ground imaging, ocean monitoring, military reconnaissance, and climate research. Inverse synthetic aperture radar is mainly used in military fields such as maritime target monitoring, air target monitoring, and dynamic target imaging. In actual situations, during the long-term inverse synthetic aperture radar processing, the complexity of the echo signals of the target object will increase, which will cause target defocusing in the imaging results, resulting in a decrease in the imaging effect and an inability to accurately obtain the image of the target object.

[0003] In related technologies, the ability to utilize echo signals for solving the above problems still needs to be improved. Summary of the Invention

[0004] The present application provides an inverse synthetic aperture radar signal processing method, apparatus, device, and medium, which solves the problem of low utilization rate of echo signals caused by the need to select an appropriate imaging time according to the echo signals, achieves the technical effect of significantly expanding the optional imaging time range, and further improves the clarity and accuracy of the imaging results, so as to adapt to more complex movement conditions of the target object.

[0005] To achieve the above object, the main technical solutions adopted in the present application include:

[0006] In a first aspect, an embodiment of the present application provides an inverse synthetic aperture radar signal processing method, and the method includes:

[0007] Performing frequency rearrangement on an initial time-frequency signal by using a frequency rearrangement operator to obtain a rearranged time-frequency signal; wherein, the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar;

[0008] Determine an energy threshold condition based on the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that satisfies the energy threshold condition;

[0009] Perform reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory;

[0010] Perform time-domain signal reconstruction based on the target time-frequency trajectory to obtain a target imaging signal.

[0011] The inverse synthetic aperture radar signal processing method proposed in the embodiments of the present application first performs frequency rearrangement on the initial time-frequency signal, so that the initial time-frequency signal can be concentrated on key frequencies, reducing the interference of noise and non-key frequency components; secondly, extract the initial time-frequency trajectory according to the energy threshold condition to extract the key frequency components in the signal, further suppressing the non-key frequency components and enhancing the performance of the key frequency components; finally, by performing reference direction correction on the initial time-frequency trajectory, the key frequency components converge further, improving the resolution and clarity of the imaging result, and at the same time being able to reduce the impact of the Doppler frequency change included in the echo signal on the imaging result, expanding the available range of the signal. Compared with the related technology, the present application uses the method of reference direction correction to solve the problem that it is necessary to select an appropriate imaging time according to the echo signal, resulting in a low utilization rate of the echo signal, so that in the long-term inverse synthetic aperture radar processing process, the echo signal at any time period can be used for imaging, significantly expanding the optional imaging time range, and thus being able to adapt to the scenarios of high-speed movement or complex targets. In addition, the present application also converges the frequency of the time-frequency signal to the key frequency and extracts the key frequency components, effectively improving the expression ability of the key frequency components and greatly enhancing the clarity and accuracy of the imaging result.

[0012] In a second aspect, the embodiments of the present application provide an inverse synthetic aperture radar signal processing device, and the device includes:

[0013] A frequency rearrangement module, configured to perform frequency rearrangement on the initial time-frequency signal by using a frequency rearrangement operator to obtain a rearranged time-frequency signal; wherein, the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar;

[0014] A trajectory extraction module, configured to determine an energy threshold condition according to the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that satisfies the energy threshold condition;

[0015] A reference direction correction module, configured to perform reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory;

[0016] A signal reconstruction module, configured to perform time-domain signal reconstruction according to the target time-frequency trajectory to obtain a target imaging signal.

[0017] In a third aspect, an embodiment of the present application provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the method described in any one of the above embodiments.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the method described in any one of the above embodiments.

[0019] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer instructions, and the computer instructions are used to cause a computer to execute the method described in any one of the above embodiments. Description of the Drawings

[0020] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 It is a step diagram of the inverse synthetic aperture radar signal processing method provided by the embodiment of the present application;

[0022] Figure 2 It is a schematic diagram of the set model of the inverse synthetic aperture radar processing process in the embodiment of the present application;

[0023] Figure 3 It is a step diagram of obtaining the initial time-frequency trajectory in the embodiment of the present application;

[0024] Figure 4 It is a step diagram of extracting the reference trajectory in the embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of trajectory extraction in the embodiment of the present application;

[0026] Figure 6 It is a step diagram of extracting the derivative trajectory in the embodiment of the present application;

[0027] Figure 7 It is a step diagram of obtaining the rearranged time-frequency signal in the embodiment of the present application;

[0028] Figure 8Schematic diagram for frequency rearrangement in the embodiment of this application;

[0029] Figure 9 Flow chart for obtaining the target time-frequency trajectory in the embodiment of this application;

[0030] Figure 10 Flow chart for obtaining the initial time-frequency signal in the embodiment of this application;

[0031] Figure 11 Three-view diagram of the target object in the simulation data experiment in the embodiment of this application;

[0032] Figure 12 Schematic diagram of the time-frequency signal of the target object in the simulation data experiment;

[0033] Figure 13a Schematic diagram for frequency rearrangement of the first interval in the simulation data experiment;

[0034] Figure 13b Schematic diagram for frequency rearrangement of the second interval in the simulation data experiment;

[0035] Figure 13c Schematic diagram for frequency rearrangement of the third interval in the simulation data experiment;

[0036] Figure 14 Schematic diagram of the target time-frequency trajectory of each interval in the simulation data experiment;

[0037] Figure 15a Schematic diagram of the first imaging result of the same target object using the RD algorithm and the RD algorithm + PGA algorithm;

[0038] Figure 15b Schematic diagram of the second imaging result of the same target object using the RD algorithm and the RD algorithm + PGA algorithm;

[0039] Figure 15c Schematic diagram of the third imaging result of the same target object using the RD algorithm and the RD algorithm + PGA algorithm;

[0040] Figure 16a Schematic diagram of the first imaging result of the same target object using this method;

[0041] Figure 16b Schematic diagram of the second imaging result of the same target object using this method;

[0042] Figure 16c Schematic diagram of the third imaging result of the same target object using this method;

[0043] Figure 17a Schematic diagram for frequency rearrangement of the time-frequency signal of the first target object in the actual data experiment in the embodiment of this application;

[0044] Figure 17b Schematic diagram for correcting the reference direction of the initial time-frequency trajectory of the first target object;

[0045] Figure 18a Schematic diagram for frequency rearrangement of the time-frequency signal of the second target object in the actual data experiment of the embodiment of the present application;

[0046] Figure 18b Schematic diagram for correcting the reference direction of the initial time-frequency trajectory of the second target object;

[0047] Figure 19a Schematic diagram of the imaging result of the first target object using the CS and RF+PGA algorithms;

[0048] Figure 19b Schematic diagram of the imaging result of the second target object using the CS and RF+PGA algorithms;

[0049] Figure 20a Schematic diagram of the imaging result of the first target object using the present method;

[0050] Figure 20b Schematic diagram of the imaging result of the second target object using the present method;

[0051] Figure 21 Module diagram of the inverse synthetic aperture radar signal processing system provided by the embodiment of the present application;

[0052] Figure 22 Schematic diagram of the structure of a computer device provided by the embodiment of the present application. Detailed implementation manners

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0054] Synthetic Aperture Radar (SAR) is a technology that uses radar for imaging. By a moving radar platform transmitting signals to a target object during flight and receiving the echo signals of the target object for imaging. In SAR, through signal processing of the echo signals, a virtual large aperture is synthesized, thereby improving the imaging resolution. Similarly, Inverse Synthetic Aperture Radar (ISAR) uses the movement of the target object itself for imaging. By a stationary radar platform transmitting signals to a moving target object and receiving the echo signals to analyze the motion information of the target object. Both SAR and ISAR have relatively wide applicable fields. SAR is mainly used in fields such as ground imaging, ocean monitoring, military reconnaissance, and climate research. ISAR is mainly used in military fields such as maritime target monitoring, air target monitoring, and dynamic target imaging.

[0055] In actual situations, during the long-term processing of ISAR, the complexity of the echo signals of the target object will increase. The target objects of ISAR include ships or airplanes, etc. The translational and rotational movements of these target objects will introduce complex range cell migration and Doppler frequency shift, which will in turn cause target defocusing in the imaging result, resulting in a decline in the imaging effect and the inability to obtain an accurate image of the target object. At the same time, the imaging time of ISAR needs to be selected according to the change trend of the Doppler frequency of the echo signals. When the Doppler frequency has a nearly horizontal steady motion, the target object is imaged at this time to estimate the motion of the target object. Relatively speaking, in most other time periods, the echo signals are not suitable for imaging, which in turn leads to the problem of too low utilization rate of the echo signals.

[0056] Based on the above problems, the present application provides a method, device, equipment, and medium for processing ISAR signals. The method includes: using a frequency rearrangement operator to perform frequency rearrangement on the initial time-frequency signal to obtain a rearranged time-frequency signal; wherein, the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the ISAR; determining an energy threshold condition according to the rearranged time-frequency signal, and performing trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that meets the energy threshold condition; performing reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory; and performing time-domain signal reconstruction according to the target time-frequency trajectory to obtain a target imaging signal.

[0057] The inverse synthetic aperture radar signal processing method provided by this application first performs frequency rearrangement on the initial time-frequency signal, so that the initial time-frequency signal can be concentrated on the key frequencies, reducing the interference of noise and non-key frequency components; secondly, extracts the initial time-frequency trajectory according to the energy threshold condition to extract the key frequency components in the signal, further suppressing the non-key frequency components and enhancing the performance of the key frequency components; finally, corrects the reference direction of the initial time-frequency trajectory, making the key frequency components converge further, improving the resolution and clarity of the imaging result, and at the same time being able to reduce the influence of the Doppler frequency change contained in the echo signal on the imaging result and expanding the available range of the signal.

[0058] Compared with the related technology, this application uses the method of reference direction correction to solve the problem of low utilization rate of echo signals caused by the need to select appropriate imaging time according to the echo signal, so that in the long-term inverse synthetic aperture radar processing process, the echo signals in any time period can be used for imaging, significantly expanding the optional imaging time range, and thus being able to adapt to the scenarios of high-speed movement or complex targets. In addition, this application also effectively improves the expression ability of the key frequency components by converging the frequencies of the time-frequency signal to the key frequencies and extracting the key frequency components, greatly improving the clarity and accuracy of the imaging result.

[0059] The inverse synthetic aperture radar signal processing method provided in this specification can be applied to the inverse synthetic aperture radar processing process, and the corresponding target objects can be ships, airplanes, vehicles, drones, etc. It can be understood that after appropriate modification, this application can also be used in other signal processing processes, such as synthetic aperture radar or other signal processing processes.

[0060] According to an embodiment of this application, an embodiment of an inverse synthetic aperture radar signal processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0061] In this embodiment, an inverse synthetic aperture radar signal processing method is provided, which can be used for the above inverse synthetic aperture radar processing process. Refer to Figure 1 As shown, the method includes:

[0062] S100. Use a frequency rearrangement operator to perform frequency rearrangement on the initial time-frequency signal to obtain a rearranged time-frequency signal; wherein, the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar.

[0063] S200. Determine the energy threshold condition based on the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that meets the energy threshold condition.

[0064] S300. Perform reference direction correction on the initial time-frequency trajectory to obtain the target time-frequency trajectory.

[0065] S400. Reconstruct the time-domain signal based on the target time-frequency trajectory to obtain the target imaging signal.

[0066] Refer to Figure 2 As shown, the inverse synthetic aperture radar processing process in this method can be represented by the three-dimensional coordinate system shown in the figure, which includes the global coordinate system XYZ and the local coordinate system UVW. The XY plane of the global coordinate system can represent the sea level, and the target object is taken as a ship for example. The position of the radar platform in the global coordinate system is (X S , Y S , Z S ), and the radar platform moves along the X direction of the global coordinate system at a speed V. The target object moves translationally on the XY plane of the global coordinate system at a speed of [v x , v y , 0]. In addition, the target object also performs three-dimensional swinging under the influence of sea waves, including rolling, pitching, and yawing, etc.

[0067] Specifically, the radar platform emits a linear frequency modulation (LFM) signal to the target object, and its form is as follows:

[0068]

[0069] where s(τ) is the transmitted signal; τ is the fast time, which is related to the signal propagation time; T p is the pulse duration; f c is the carrier frequency; K r is the frequency modulation rate. After the above signal is reflected by each scatterer in the target object, the radar platform can demodulate the received signal to obtain the echo signal, and its form is as follows:

[0070]

[0071] where s(τ, η) is the echo signal; η is the slow time, which is related to the movement speed of the radar platform; σ i is the backscattering coefficient of the i-th scatterer; w a is the azimuth weighting function; I is the number of scatterers; c is the speed of light; R i (η) is the instantaneous slant range between the i-th scatterer and the radar platform.

[0072]

[0073] Among them, R i (η) is the instantaneous slant range; x p (η), y p (η) and z p (η) are the position coordinates of the target object in the global coordinate system; X S , Y S and Z S are the initial position coordinates of the radar platform in the global coordinate system.

[0074] The form of the azimuth signal of the original echo signal is as follows:

[0075]

[0076] Among them, s τ (η) is the azimuth signal; A i is the amplitude of the i-th scatterer, φ i (η) is the phase of the i-th scatterer,

[0077]

[0078] Among them, R 0,i is the zero Doppler slant range of the i-th scatterer.

[0079] The initial time-frequency signal is obtained by performing a Short-Term Fourier Transform (STFT) on the original echo signal, and its form is as follows:

[0080]

[0081] Among them, G τ (η, ω) is the initial time-frequency signal; is the Fourier transform of the window function g(). The STFT spectrogram of the original echo signal can be obtained from the initial time-frequency signal.

[0082] Further, a frequency rearrangement operator is constructed according to the frequency distribution of the original echo signal in the initial time-frequency signal for frequency reallocation of the initial time-frequency signal. The physical meaning of the frequency rearrangement operator can be interpreted as determining the key frequency components in the original echo signal based on the local maxima of the initial time-frequency signal in the time-frequency plane, and taking the frequencies of the key frequency components as the ideal instantaneous frequencies. The initial time-frequency signal is frequency rearranged using the frequency rearrangement operator to obtain the rearranged time-frequency signal, so that other frequency components deviating from the key frequency components in the original time-frequency signal can be merged into the key frequency components, improving the convergence degree of the signal, thereby enhancing the clarity of the imaging result.

[0083] Furthermore, the rearranged time-frequency signal includes multiple frequency components, each of which converges to an ideal frequency trajectory, and each frequency component has its own time-frequency trajectory. If the imaging process is directly performed on the rearranged frequency signal, it will lead to energy defocusing and amplitude distortion of the target object, greatly affecting the imaging effect. Therefore, it is necessary to separately extract the time-frequency trajectories of each frequency component from the rearranged time-frequency signal for separate processing. The trajectory energy of each frequency component can be obtained according to its time-frequency trajectory. Among them, for the time-frequency trajectory with higher trajectory energy, the corresponding frequency component is a more important key frequency component in the rearranged time-frequency signal; while for the time-frequency trajectory with lower trajectory energy, the corresponding frequency component is a non-key frequency component in the rearranged time-frequency signal. These frequency components have nothing to do with the movement of the target object but will affect the clarity and accuracy of the imaging result. Through trajectory extraction, the initial time-frequency trajectory only contains the time-frequency trajectories of key frequency components, thereby improving the signal quality of the inverse synthetic aperture radar and enhancing the clarity and accuracy of the imaging result.

[0084] It can be understood that by setting the energy threshold condition in the trajectory extraction process, not only can non-key frequency components be filtered out, but also the number of extracted time-frequency trajectories can be adaptively controlled, enhancing the expression ability of the frequency components corresponding to the time-frequency trajectories for the movement of the target object.

[0085] Furthermore, the initial time-frequency trajectory is corrected in the reference direction to obtain the target time-frequency trajectory. Any time-frequency trajectory in the initial time-frequency trajectory represents the trend of the frequency of the corresponding frequency component changing with time. When the frequency changes significantly within a certain time period, if the radar signal in this time period is directly used for imaging, the energy defocusing problem in the imaging result will cause the scatterers to be indistinguishable from each other, thereby affecting the analysis of the position and movement of the target object. By correcting the initial time-frequency trajectory to the reference direction, the convergence degree of the frequency and energy in the radar signal is improved, the final imaging result is optimized, and the clarity of the imaging result is enhanced.

[0086] Furthermore, the target imaging signal is reconstructed in the time domain according to the target time-frequency trajectory. It should be noted that the target imaging signal is the time-domain signal obtained according to the target time-frequency trajectory, representing the signal obtained after the signal processing by this method. After transforming the target imaging signal into the frequency domain signal, it can be used for imaging the target object.

[0087] The inverse synthetic aperture radar signal processing method provided in this embodiment first performs frequency rearrangement on the initial time-frequency signal, so that the initial time-frequency signal can be concentrated on the key frequencies, reducing the interference of noise and non-key frequency components; secondly, extracts the initial time-frequency trajectory according to the energy threshold condition to extract the key frequency components in the signal, further suppressing the non-key frequency components and enhancing the performance of the key frequency components; finally, by correcting the reference direction of the initial time-frequency trajectory, the key frequency components converge further, improving the resolution and clarity of the imaging result, and at the same time being able to reduce the influence of the Doppler frequency change contained in the echo signal on the imaging result and expanding the available range of the signal.

[0088] Compared with the related technology, this application uses the method of reference direction correction to solve the problem that it is necessary to select an appropriate imaging time according to the echo signal, resulting in a low utilization rate of the echo signal, so that in the long-term inverse synthetic aperture radar processing process, the echo signal in any time period can be used for imaging, significantly expanding the optional imaging time range, and thus being able to adapt to the scenarios of high-speed movement or complex targets. In addition, this application also converges the frequency of the time-frequency signal to the key frequencies and extracts the key frequency components, effectively improving the expression ability of the key frequency components and greatly enhancing the clarity and accuracy of the imaging result.

[0089] Refer to Figure 3 As shown, as an embodiment of this application, the initial time-frequency trajectory includes a reference trajectory and a derivative trajectory; determine the energy threshold condition according to the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain the initial time-frequency trajectory that meets the energy threshold condition, including:

[0090] S210. Extract the time-frequency trajectory with the maximum trajectory energy from the rearranged time-frequency signal as the reference trajectory.

[0091] S220. Determine the energy threshold condition according to the trajectory energy of the reference trajectory.

[0092] S230. Extract the time-frequency trajectory that meets the energy threshold condition from the rearranged time-frequency signal as the derivative trajectory.

[0093] S240. Obtain the initial time-frequency trajectory according to the reference trajectory and the derivative trajectory.

[0094] Specifically, the energy threshold condition can be determined according to the threshold coefficient and the trajectory energy of the reference trajectory, so as to control the number of the extracted initial time-frequency trajectories by adjusting the threshold coefficient. Exemplarily, the form of the energy threshold condition can be as follows:

[0095]

[0096] Wherein, is the trajectory energy of the i-th time-frequency trajectory; is the trajectory energy of the reference trajectory; ρ is the threshold coefficient.

[0097] It should be noted that the number of derivative trajectories can be multiple. After obtaining any derivative trajectory, set the time-frequency coefficients of this derivative trajectory to zero, that is, remove this derivative trajectory in the subsequent trajectory extraction process. Repeat the above steps of extracting derivative trajectories until any time-frequency trajectory in the rearranged time-frequency signal no longer satisfies the energy threshold condition, then stop the trajectory extraction, and obtain the initial time-frequency trajectory according to the extracted reference trajectory and derivative trajectories.

[0098] In this embodiment, key frequency components in the signal are extracted through trajectory extraction, further suppressing non-key frequency components, so that the initial time-frequency trajectory only contains the time-frequency trajectories of key frequency components, effectively improving the expression ability of key frequency components, thereby improving the signal quality of the inverse synthetic aperture radar and enhancing the clarity and accuracy of the imaging result.

[0099] Refer to Figure 4 As shown in the figure, as an embodiment of the present application, extract the time-frequency trajectory with the largest trajectory energy from the rearranged time-frequency signal as the reference trajectory, including:

[0100] S212. Divide the time-frequency plane where the rearranged time-frequency signal is located in the time direction to obtain several time partitions.

[0101] S214. Determine the first search starting point according to the local maximum position of the rearranged time-frequency signal in any time partition.

[0102] S216. Starting from the first search starting point, determine the first search points in the time partitions before and after any time partition respectively; wherein, the first search points and the first search starting point satisfy the continuity condition.

[0103] S218. Obtain the first candidate trajectory according to the first search starting point and the first search points, and take the time-frequency trajectory with the largest energy in the first candidate trajectory as the reference trajectory.

[0104] Among them, the continuity condition can be that there is no discontinuity or jump between the first search point and the first search starting point, and the transition between them is smooth. It can be understood that after obtaining several first search points, the first search starting point and the first search points can jointly form a part of the first candidate trajectory. When searching for the first search points in other time partitions, it can be determined whether the time-frequency points satisfy the continuity condition with the above-mentioned part of the first candidate trajectory to determine the first search points.

[0105] Specifically, the time-frequency plane is divided in the time direction at the same time interval to obtain a number of time partitions, and each time partition contains the time-frequency trajectories corresponding to some frequency components in the rearranged time-frequency signal. Refer to Figure 5 as shown Figure 5 in which the time-frequency plane is divided into 4 time partitions, denoted by g = 1, g = 2, g = 3, and g = 4 respectively.

[0106] Furthermore, in any time partition, the local maximum value of the rearranged time-frequency signal in this time partition is selected as the first search starting point, and the trajectory search is started from the first search starting point. It can be understood that in this time partition, there are multiple time-frequency points that satisfy the continuity condition with the first search starting point. According to the above time-frequency points and the first search starting point, some first candidate trajectories in this time partition can be determined. Exemplarily, refer to Figure 5 as shown, in the time partition g = 3, the obtained part of the first candidate trajectories is

[0107] Furthermore, in all the time partitions before and after any of the above time partitions, the first search points that satisfy the continuity condition are searched, and the first candidate trajectories are formed by the continuous first search starting points and first search points. The number of the first candidate trajectories can be multiple. Refer to Figure 5 as shown, the first candidate trajectories can include the yellow trajectory and the blue trajectory in the figure, where the yellow trajectory includes and the blue trajectory includes

[0108] Furthermore, the first candidate trajectories are sorted according to the trajectory energy, and the first candidate trajectory with the largest trajectory energy is selected as the reference trajectory. The form of the reference trajectory is as follows:

[0109]

[0110] where is the estimated time-frequency trajectory of the i-th frequency component in the time-frequency plane; is the first-order derivative of the estimated time-frequency trajectory with respect to η, is the second-order derivative of the estimated time-frequency trajectory with respect to η; is the trajectory energy of the i-th estimated time-frequency trajectory; λ and β are regularization level adjustment parameters to prevent the interruption or jump of the time-frequency trajectory. After obtaining the reference trajectory, the time-frequency coefficients of the reference trajectory are set to zero to extract the derivative trajectories outside the reference trajectory.

[0111] Refer to Figure 6As shown in the figure, as an embodiment of the present application, when extracting the time-frequency trajectory that meets the energy threshold condition from the rearranged time-frequency signal as the derivative trajectory, it includes:

[0112] S232. Divide the time-frequency plane where the rearranged time-frequency signal is located in the time direction to obtain a number of time partitions;

[0113] S234. Determine the second search starting point according to the position of the local maximum value of the rearranged time-frequency signal in any time partition;

[0114] S236. Starting from the search starting point, determine the second search points in the time partitions before and after any time partition respectively; wherein, the second search point and the second search starting point satisfy the continuity condition;

[0115] S238. Obtain the second candidate trajectory according to the second search starting point and the second search point; and when the time-frequency trajectory with the maximum energy in the second candidate trajectory meets the energy threshold condition, use the time-frequency trajectory with the maximum energy as the derivative trajectory.

[0116] Specifically, similar to the method for extracting the reference trajectory, when extracting the derivative trajectory, first perform time partition division on the time-frequency plane where the rearranged time-frequency signal is located, determine the second search starting point in each time partition, and determine the second search points in multiple time partitions according to the continuity condition, so as to form a number of second candidate trajectories according to the second search starting point and the second search point.

[0117] Furthermore, after obtaining the second candidate trajectory, select the second candidate trajectory with the maximum trajectory energy, and judge whether the second candidate trajectory meets the energy threshold condition. If the second candidate trajectory meets the energy threshold condition, use it as the derivative trajectory.

[0118] Refer to Figure 7 As shown in the figure, as an embodiment of the present application, use the frequency rearrangement operator to perform frequency rearrangement on the initial time-frequency signal to obtain the rearranged time-frequency signal, including:

[0119] S110. For any time-frequency point in the initial time-frequency signal, use the frequency rearrangement operator to determine the rearranged frequency corresponding to the any time-frequency point.

[0120] S120. Perform time-frequency coefficient calculation according to the any time-frequency point and the rearranged frequency to obtain the rearranged time-frequency coefficient of the any time-frequency point.

[0121] S130. Perform frequency rearrangement on the corresponding time-frequency point in the initial time-frequency signal according to the rearranged time-frequency coefficient to obtain the rearranged time-frequency signal.

[0122] Specifically, the form of the frequency rearrangement operator is as follows:

[0123]

[0124] Among them, ω(η, ω) is a frequency rearrangement operator; Δ is the window size for finding local maxima. It can be understood that for the initial time-frequency signal with |G(η, ω)|≠0, that is, the part with frequency components, frequency rearrangement is performed based on the local maxima of the initial time-frequency signal to enhance the signal intensity locally in the initial time-frequency signal.

[0125] Furthermore, the frequency rearrangement operator takes the local maxima of the initial time-frequency signal in the time-frequency plane as the estimated value of the ideal instantaneous frequency trajectory, and its physical meaning can be expressed as:

[0126]

[0127] Among them, IF i (η, ω s ) is the i-th estimated ideal instantaneous frequency trajectory; ω s is the rearranged frequency. According to any time-frequency point and the rearranged frequency, the time-frequency coefficient is calculated to obtain the rearranged time-frequency coefficient of any time-frequency point, and according to the rearranged time-frequency coefficient, the rearranged time-frequency coefficients within the window function range are redistributed to the corresponding estimated ideal instantaneous frequency trajectories to obtain the rearranged time-frequency signal. The form of the rearranged time-frequency signal is as follows:

[0128]

[0129] Among them, LMSST τ (η, ω s ) is the rearranged time-frequency signal.

[0130] It should be noted that in this application, through frequency rearrangement, the frequency components deviating from the key frequency components can converge to the key frequency components, solving the problem of energy defocusing in the initial time-frequency signal, improving the convergence degree of the signal, reducing the interference of noise and non-key frequency components, and thus enhancing the clarity of the imaging result.

[0131] Refer to Figure 8 as shown. Figure 8The first schematic diagram in the upper left corner represents the initial time-frequency signal, the third schematic diagram in the lower right corner represents the rearranged time-frequency signal, and the second schematic diagram in the lower left corner represents the frequency rearrangement operator corresponding to the initial time-frequency signal and the rearranged time-frequency signal. From the thick yellow trajectory in the first schematic diagram, it can be seen that the energy defocusing problem of the initial time-frequency signal is relatively serious. Applying the frequency rearrangement operator to the initial time-frequency signal, the second schematic diagram can be obtained. The horizontal axis of the second schematic diagram corresponds to the frequency of the initial time-frequency signal, and the vertical axis of the second schematic diagram corresponds to the frequency of the rearranged time-frequency signal. It can be seen that the frequency components in the initial time-frequency signal within the frequency range of 50 to 135 can converge to the frequency component with a frequency of 80, thereby obtaining the third schematic diagram. From the third schematic diagram, it can be seen that the rearranged time-frequency signal has solved the energy defocusing problem in the initial time-frequency signal.

[0132] Referring to Figure 9 as shown, as an embodiment of the present application, performing reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory, including:

[0133] S310. Calculate the mean value of any initial time-frequency trajectory in the frequency direction to obtain the main frequency of any initial time-frequency trajectory.

[0134] S320. Adjust the frequency components of any initial time-frequency trajectory according to the main frequency, and adjust the trend of any initial time-frequency trajectory to a preset reference direction to obtain the target time-frequency trajectory of any initial time-frequency trajectory.

[0135] Specifically, the preset reference direction can be the horizontal direction. When the trend of the time-frequency trajectory is the horizontal direction, the frequencies in the corresponding frequency domain image can be focused on the corresponding frequencies. Through mean value calculation, the influence of high-order terms in the initial time-frequency trajectory is eliminated, making the change trend of the time-frequency trajectory become gentle. Adjust the frequency components according to the main frequency, adjust the frequency corresponding to any initial time-frequency trajectory to the main frequency, thereby adjusting the trend of any initial time-frequency trajectory to the horizontal direction to obtain the target time-frequency trajectory of any initial time-frequency trajectory. The form of the target time-frequency trajectory is as follows:

[0136]

[0137] Wherein, is the target time-frequency trajectory; N is the number of time domain sampling points.

[0138] Furthermore, the signal reconstruction specifically includes: performing signal reconstruction on the frequency components in the radar signal according to the rearranged time-frequency signal to obtain a reconstructed signal, and its form is as follows:

[0139]

[0140] A i =abs(sτ,i (η))

[0141] where s τ,i (η) is the i-th reconstructed signal; A i is the amplitude of the i-th reconstructed signal. The reconstructed signal is corrected in the reference direction according to the target time-frequency trajectory to obtain the target imaging signal, and its form is as follows:

[0142]

[0143] where is the i-th target imaging signal.

[0144] It should be noted that through the reference direction correction, the time-frequency trajectory within any time period can be focused on the corresponding frequency, thereby obtaining a clear imaging result. This method solves the problem that the appropriate imaging time needs to be selected according to the echo signal, resulting in low utilization rate of the echo signal, so that the echo signal in any time period can be used for imaging during the long-time inverse synthetic aperture radar processing, significantly expanding the optional imaging time range, and thus being able to adapt to the scenes of high-speed movement or complex targets.

[0145] Referring to Figure 10 shown below, as an embodiment of the present application, the initial time-frequency signal is obtained in the following manner:

[0146] S510. Preprocess the original echo signal; where the preprocessing includes at least one of range compression, range migration correction, and azimuth compression, and the range migration correction includes translational correction and rotational correction.

[0147] S520. Perform time-frequency transformation on the azimuth signal corresponding to the preprocessed original echo signal to obtain the initial time-frequency signal.

[0148] Specifically, after performing range compression on the original echo signal, its form is as follows:

[0149]

[0150] By performing range compression on the original echo signal, the resolution of the inverse synthetic aperture radar in the range direction is improved, and the ability of the original echo signal to express the range information of the target object is enhanced.

[0151] Furthermore, there is a range migration of the target object relative to the radar platform, and the range migration may be caused by the translation and rotation of the target object. Therefore, the instantaneous slant range between the scatterer and the radar platform can be regarded as a combination of time translation and rotation, and its form is as follows:

[0152] R i (η) = ||R o′,i(η)n(η)+r i (η)||≈R o′,i (η)+n(η) T r i (η)

[0153] where n(η) is the unit radar line-of-sight vector in the global coordinate system; r i (η) is the position vector of the i-th scatterer in the local coordinate system; R o′,i (η) is the distance between the radar platform and the center of the target object,

[0154]

[0155] where u 0 , v 0 and w 0 are the initial positions of the origin of the local coordinate system in the global coordinate system. Thus, the instantaneous slant range can be decomposed into the translational slant range caused by translation and the rotational slant range caused by rotation, and their forms are as follows respectively:

[0156] R i (η) = R tr (η)+R ro,i (η)

[0157] R tr (η) = R tr,i (η) = R o′,i (η)

[0158] R ro,i (η) = n(η) T r i (η)

[0159] where R tr (η) is the overall translational slant range of the target object; R tr,i (η) is the translational slant range of the i-th scatterer; R ro,i (η) is the rotational slant range of the i-th scatterer, and the rotational slant range changes of each scatterer are different.

[0160] Furthermore, the translational correction includes: the offset component caused by the change in the translational slant range is corrected by the distance alignment algorithm. The rotational correction includes: the offset component caused by the change in the rotational slant range is corrected by the Keystone transform. The form of the original echo signal after distance offset correction is as follows:

[0161]

[0162] Perform further azimuth compression on the above signal, thus completing the preprocessing process, and obtaining the corresponding azimuth signal according to the preprocessed original echo signal, and then obtaining the initial time-frequency signal.

[0163] Based on the inverse synthetic aperture radar signal processing method provided in the above embodiments, an experimental scenario of this method is described below. Refer to Figure 11 As shown, in this experimental scenario, the target object is a ship set model containing multiple scatterers. The number of scatterers is 301, and the coordinate spacing between each scatterer is 5 meters. Table 1 shows the motion parameters used to simulate the radar platform and the target object under sea state 5.

[0164] Table 1 Simulation parameters

[0165]

[0166] Refer to Figure 12 As shown, the initial time-frequency signal as shown in the figure can be obtained from this target object. The red frame in the figure represents the imaging interval, including the first interval (Interval1), the second interval (Interval2), and the third interval (Interval3).

[0167] Refer to Figure 13a As shown, based on the method provided in this application, the initial time-frequency signals in the first interval are respectively frequency rearranged to obtain the rearranged time-frequency signals. The left figure is the initial time-frequency signal of the first interval, and the right figure is the rearranged time-frequency signal of the first interval. Similarly, refer to Figure 13b As shown, Figure 13b The left figure in Figure 13c As shown, Figure 13c The left figure in

[0168] Refer to Figure 14 As shown, trajectory extraction and reference direction correction are performed on the rearranged time-frequency signals, and the obtained target time-frequency trajectories are as shown in the figure. The left figure is the target time-frequency trajectory of the first interval, the middle figure is the target time-frequency trajectory of the second interval, and the right figure is the target time-frequency trajectory of the third interval. Corresponding target imaging signals can be obtained according to the above target time-frequency trajectories.

[0169] Refer to Figure 15a As shown, the left figure is the imaging result obtained by imaging the target imaging signal of the target object in the first interval in this experimental scenario using the Range-Doppler Algorithm (RD), and the right figure is the imaging result obtained by imaging the target imaging signal of the target object in the first interval in this experimental scenario using the imaging algorithm combining the Range-Doppler Algorithm and the Phase Gradient Autofocusing Algorithm (PGA). Correspondingly, refer toFigure 15b As shown, where the left figure is the imaging result obtained by imaging the target imaging signal of the target object in the second interval using the RD algorithm, and the right figure is the imaging result obtained by imaging the target imaging signal of the target object in the second interval using the imaging algorithm combining the RD algorithm and the PGA algorithm. Refer to Figure 15c As shown, where the left figure is the imaging result obtained by imaging the target imaging signal of the target object in the third interval using the RD algorithm, and the right figure is the imaging result obtained by imaging the target imaging signal of the target object in the third interval using the imaging algorithm combining the RD algorithm and the PGA algorithm. As shown in the figure, it can be clearly seen from the imaging results obtained by the above algorithms that the target object has a defocusing problem and a clear image of the target object cannot be obtained.

[0170] Refer to Figures 16a to 16c As shown, the method provided by the present application is used to image the target imaging signals of the target object in the first interval, the second interval, and the third interval respectively. Compared with Figures 15a to 15c , it can be clearly seen that the present method can obtain a clear image of the target object in any interval and can provide different attitude images within the imaging time range.

[0171] Based on the inverse synthetic aperture radar signal processing method provided in the above embodiments, another experimental scenario of this method is described below. In this experimental scenario, the target object is an actual ship target. The radar signal data is spaceborne data provided by the Gaofen-3 satellite. The radar operates in a sliding spotlight mode with a resolution of 1 meter and an imaging width of 10 kilometers. The radar operates in the C band with a bandwidth of 240 MHz, a carrier frequency of 4373 Hz, and an integration time of 1.7151 seconds.

[0172] Since the rotation of the target object is not significant in this experimental scenario, the time-frequency trajectory of the target object is relatively stable throughout the integration period. Therefore, the entire time period can be selected for re-focusing processing. Refer to Figures 17a to 17b , which shows the result of signal processing of the first target object using the method provided by the present application, where Figure 17a shows the process of frequency rearrangement. It can be seen that the curvature of the time-frequency trajectory in the rearranged time-frequency signal is not obvious. Figure 17b shows the process of trajectory extraction and reference direction correction. Refer to Figures 18a to 18b , which shows the result of signal processing of the second target object using the method provided by the present application, where Figure 18a shows the process of frequency rearrangement. It can be seen that the curvature of the time-frequency trajectory in the rearranged time-frequency signal is not obvious. Figure 18b shows the process of trajectory extraction and reference direction correction.

[0173] Refer to Figure 19aAs shown, the left figure is the imaging result obtained by imaging the target imaging signal of the first target object in this experimental scenario using the Chirp Scaling (CS) algorithm, and the right figure is the imaging result obtained by imaging the target imaging signal of the first target object in this experimental scenario using an imaging algorithm that combines the RD algorithm and the PGA algorithm. Accordingly, referring to Figure 19b As shown, the left figure is the imaging result obtained by imaging the target imaging signal of the second target object in this experimental scenario using the CS algorithm, and the right figure is the imaging result obtained by imaging the target imaging signal of the second target object in this experimental scenario using an imaging algorithm that combines the RD algorithm and the PGA algorithm. As shown in the figure, from the imaging results obtained by the above algorithms, it can be seen that neither the CS algorithm nor the imaging algorithm that combines the RD algorithm and the PGA algorithm concentrates the defocus energy caused by the movement of the target object, resulting in a defocus problem of the target object in the imaging result and an inability to obtain a clear image of the target object.

[0174] Referring to Figure 20a As shown, the method provided by this application is used to image the target imaging signal of the first target object. Referring to Figure 20b As shown, the method provided by this application is used to image the target imaging signal of the second target object. Compared with Figures 19a to 19b , it can be clearly seen that this method can generate a clearer refocused image of the target object, and this method can be applied to the spaceborne situation and has a large applicable range.

[0175] Accordingly, please refer to Figure 21 , this embodiment of the application provides an inverse synthetic aperture radar signal processing device, and the device includes:

[0176] A frequency rearrangement module 2110, configured to perform frequency rearrangement on an initial time-frequency signal using a frequency rearrangement operator to obtain a rearranged time-frequency signal; wherein, the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar.

[0177] A trajectory extraction module 2120, configured to determine an energy threshold condition according to the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that meets the energy threshold condition.

[0178] A reference direction correction module 2130, configured to perform reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory.

[0179] A signal reconstruction module 2140, configured to perform time-domain signal reconstruction according to the target time-frequency trajectory to obtain a target imaging signal.

[0180] In some alternative embodiments, the initial time-frequency trajectory includes a reference trajectory and a derivative trajectory; the trajectory extraction module 2120 includes:

[0181] A reference trajectory extraction unit, configured to extract the time-frequency trajectory with the maximum trajectory energy from the rearranged time-frequency signal as the reference trajectory.

[0182] A threshold condition determination unit, configured to determine an energy threshold condition according to the trajectory energy of the reference trajectory.

[0183] A derivative trajectory extraction unit, configured to extract the time-frequency trajectories that meet the energy threshold condition from the rearranged time-frequency signal as the derivative trajectories.

[0184] A time-frequency trajectory determination unit, configured to obtain the initial time-frequency trajectory according to the reference trajectory and the derivative trajectories.

[0185] In some alternative embodiments, the reference trajectory extraction unit includes:

[0186] A time partition division subunit, configured to divide the time-frequency plane where the rearranged time-frequency signal is located in the time direction to obtain a plurality of time partitions.

[0187] A first starting point determination subunit, configured to determine a first search starting point according to the local maximum position of the rearranged time-frequency signal in any time partition.

[0188] A first search point determination subunit, configured to respectively determine a first search point in the time partition before any time partition and the time partition after any time partition starting from the first search starting point; wherein, the first search point and the first search starting point meet the continuity condition.

[0189] A first trajectory determination subunit, configured to obtain a first candidate trajectory according to the first search starting point and the first search point, and use the time-frequency trajectory with the maximum energy in the first candidate trajectory as the reference trajectory.

[0190] In some alternative embodiments, the derivative trajectory extraction unit includes:

[0191] A time partition division subunit, configured to divide the time-frequency plane where the rearranged time-frequency signal is located in the time direction to obtain a plurality of time partitions;

[0192] A second starting point determination subunit, configured to determine a second search starting point according to the local maximum position of the rearranged time-frequency signal in any time partition;

[0193] A second search point determination subunit, configured to respectively determine a second search point in the time partition before any time partition and the time partition after any time partition starting from the search starting point; wherein, the second search point and the second search starting point meet the continuity condition;

[0194] A second trajectory determination subunit, configured to obtain a second candidate trajectory according to a second search starting point and a second search point; and use the time-frequency trajectory with the maximum energy in the second candidate trajectory as the derivative trajectory when the time-frequency trajectory with the maximum energy satisfies the energy threshold condition.

[0195] In some alternative embodiments, the frequency rearrangement module 2110 includes:

[0196] A rearrangement frequency determination unit, configured to determine, for any time-frequency point in the initial time-frequency signal, a rearrangement frequency corresponding to the any time-frequency point by using a frequency rearrangement operator.

[0197] A time-frequency coefficient calculation unit, configured to calculate a time-frequency coefficient according to any time-frequency point and the rearrangement frequency to obtain a rearranged time-frequency coefficient of the any time-frequency point.

[0198] A signal frequency rearrangement unit, configured to perform frequency rearrangement on the corresponding time-frequency point in the initial time-frequency signal according to the rearranged time-frequency coefficient to obtain a rearranged time-frequency signal.

[0199] In some alternative embodiments, the reference direction correction module 2130 includes:

[0200] A frequency mean calculation unit, configured to calculate a mean value of any initial time-frequency trajectory in the frequency direction to obtain a main frequency of the any initial time-frequency trajectory.

[0201] A trajectory trend adjustment unit, configured to adjust the frequency component of any initial time-frequency trajectory according to the main frequency, and adjust the trend of the any initial time-frequency trajectory to a preset reference direction to obtain a target time-frequency trajectory of the any initial time-frequency trajectory.

[0202] In some alternative embodiments, the apparatus further includes an initial signal processing module, including:

[0203] A raw signal preprocessing unit, configured to preprocess a raw echo signal; wherein, the preprocessing includes at least one of range compression, range migration correction, and azimuth compression, and the range migration correction includes translation correction and rotation correction.

[0204] A signal time-frequency transformation unit, configured to perform time-frequency transformation on an azimuth signal corresponding to the preprocessed raw echo signal to obtain an initial time-frequency signal.

[0205] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be repeated here.

[0206] The inverse synthetic aperture radar signal processing device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0207] Please refer to Figure 22 , Figure 22 , which is a schematic structural diagram of a computer device provided by an embodiment of the present application. As shown in the figure, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 22 In

[0208] Processor 10 can be a central processor, a network processor, or a combination thereof. Among them, processor 10 can further include a hardware chip. The above hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0209] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0210] The memory 20 may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function. The data storage area may store data created according to the use of the computer device and the like. In addition, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely disposed relative to the processor 10, and these remote memories may be connected to the computer device through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0211] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive; the memory 20 may further include a combination of the above types of memory.

[0212] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0213] The embodiments of the present application also provide a computer-readable storage medium. The methods according to the embodiments of the present application may be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and to be stored in a local storage medium, so that the methods described herein can be processed by such software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may also include a combination of the above types of memory. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0214] The embodiments of the present application provide a computer program product. The computer program product includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods of any embodiment of the present application.

[0215] Although embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations fall within the scope defined by the appended claims.

[0216] The systems, devices, modules or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0217] For the convenience of description, the above devices are described by dividing them into various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0218] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0219] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one or more flows Figure 1 or multiple flows and / or blocks

[0220] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the specified functions in Figure 1 one or more flows Figure 1The functions specified in one or more boxes.

[0221] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0222] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent in such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the said element.

[0223] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0224] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

[0225] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for processing inverse synthetic aperture radar signals, characterized in that: The method comprises: The frequency reordering operator is used to reorder the frequency of the initial time-frequency signal to obtain a reordered time-frequency signal; wherein the frequency reordering operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar; Determining an energy threshold condition according to the rearranged time-frequency signal, and performing trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that meets the energy threshold condition; Performing reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory; The time domain signal is reconstructed according to the target time-frequency trajectory to obtain the target imaging signal.

2. The method according to claim 1, characterized in that The initial time-frequency trajectory includes a reference trajectory and a derived trajectory; the energy threshold condition is determined according to the rearranged time-frequency signal, and the trajectory is extracted from the rearranged time-frequency signal to obtain the initial time-frequency trajectory that meets the energy threshold condition, including: Extracting the time-frequency trajectory with the largest trajectory energy from the rearranged time-frequency signal as the reference trajectory; Determining the energy threshold condition according to the trajectory energy of the reference trajectory; Extracting the time-frequency trajectory satisfying the energy threshold condition from the rearranged time-frequency signal as the derived trajectory; The initial time-frequency trajectory is obtained according to the reference trajectory and the derived trajectory.

3. The method according to claim 2, characterized in that The step of extracting the time-frequency trajectory with the maximum trajectory energy from the rearranged time-frequency signal as the reference trajectory comprises: The time-frequency plane where the rearranged time-frequency signal is located is divided in the time direction to obtain a plurality of time partitions; Determine a first search starting point according to the local maximum position of the rearranged time-frequency signal in any time partition; Starting from the first search starting point, determining a first search point in a time partition before any time partition and in a time partition after any time partition respectively; wherein the first search point and the first search starting point meet a continuity condition; A first candidate trajectory is obtained according to the first search starting point and the first search point, and the time-frequency trajectory with the maximum energy in the first candidate trajectory is used as the reference trajectory.

4. The method according to claim 2, characterized in that: The step of extracting the time-frequency trajectory satisfying the energy threshold condition from the rearranged time-frequency signal as the derived trajectory comprises: The time-frequency plane where the rearranged time-frequency signal is located is divided in the time direction to obtain a plurality of time partitions; Determine a second search starting point according to the local maximum position of the rearranged time-frequency signal in any time partition; Starting from the search starting point, determining a second search point in a time partition before any time partition and in a time partition after any time partition respectively; wherein the second search point and the second search starting point meet a continuity condition; A second candidate trajectory is obtained according to the second search starting point and the second search point; and when the time-frequency trajectory with the maximum energy in the second candidate trajectory meets the energy threshold condition, the time-frequency trajectory with the maximum energy is used as the derived trajectory.

5. The method according to claim 1, characterized in that The method of using a frequency rearrangement operator to perform frequency rearrangement on the initial time-frequency signal to obtain a rearranged time-frequency signal includes: For any time-frequency point in the initial time-frequency signal, using the frequency rearrangement operator to determine a rearrangement frequency corresponding to the any time-frequency point; Calculate the time-frequency coefficient according to any time-frequency point and the rearrangement frequency to obtain the rearrangement time-frequency coefficient of any time-frequency point; The corresponding time-frequency points in the initial time-frequency signal are frequency-rearranged according to the rearranged time-frequency coefficients to obtain the rearranged time-frequency signal.

6. The method according to claim 1, characterized in that The performing reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory includes: Performing mean calculation on any initial time-frequency trajectory in the frequency direction to obtain the main frequency of any initial time-frequency trajectory; The frequency component of any of the initial time-frequency trajectories is adjusted according to the main frequency, and the trend of any of the initial time-frequency trajectories is adjusted to a preset reference direction to obtain a target time-frequency trajectory of any of the initial time-frequency trajectories.

7. The method according to any one of claims 1 to 6, characterized in that The initial time-frequency signal is obtained by: Preprocessing the original echo signal; wherein the preprocessing includes at least one of range compression, range offset correction and azimuth compression, and the range offset correction includes translation correction and rotation correction; The initial time-frequency signal is obtained by performing time-frequency transformation on the azimuth signal corresponding to the preprocessed original echo signal.

8. An inverse synthetic aperture radar signal processing device, characterized in that: The device comprises: A frequency rearrangement module, used to perform frequency rearrangement on the initial time-frequency signal using a frequency rearrangement operator to obtain a rearranged time-frequency signal; wherein the frequency rearrangement operator is constructed based on the initial time-frequency signal, and the initial time-frequency signal is obtained by performing time-frequency transformation on the original echo signal of the inverse synthetic aperture radar; A trajectory extraction module, used to determine an energy threshold condition according to the rearranged time-frequency signal, and perform trajectory extraction on the rearranged time-frequency signal to obtain an initial time-frequency trajectory that meets the energy threshold condition; A reference direction correction module, used to perform reference direction correction on the initial time-frequency trajectory to obtain a target time-frequency trajectory; The signal reconstruction module is used to reconstruct the time domain signal according to the target time-frequency trajectory to obtain the target imaging signal.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

Images