Shadow-based ground moving target parameter estimation method, device and equipment

Abstract

The invention relates to a shadow-based ground moving target parameter estimation method, device and equipment, and the method comprises the steps: constructing a geometric model of terahertz video SAR (Synthetic Aperture Radar) moving target imaging in a bunching mode, and obtaining an echo mathematical model of a moving target based on the geometric model; after an echo signal obtained by detecting a ground motion scene by a terahertz video radar is expressed based on the echo mathematical model, the distance direction speed of a moving target is estimated through the relative offset of a moving target image and a shadow in the azimuth direction, and the distance direction speed of the moving target is calculated through the frequency broadening of the target image and the shadow in the azimuth direction. And estimating the azimuth direction speed of the moving target, and estimating the distance direction acceleration of the moving target according to the frequency modulation rate of the secondary phase through the compensation of the secondary phase. By adopting the method, accurate target parameter estimation can be obtained.

Description

Technical Field

[0001] This application relates to the technical field of radar signal processing, and particularly to a method, device, and equipment for estimating parameters of ground moving targets based on shadows. Background Art

[0002] The working task of video SAR is to continuously obtain high-resolution images of a scene, detect and monitor moving targets in the scene, and estimate the motion states of ground moving targets. For the parameter estimation of ground moving targets, especially for video SAR in the terahertz band, various parameter estimation methods have been proposed in the prior art.

[0003] These parameter estimation methods are basically divided into two categories. One is the motion parameter estimation method based on Doppler parameters, and the other is the motion target parameter estimation method based on shadows. Among them, the motion parameter estimation method based on Doppler parameter estimation estimates the azimuth and range velocities of moving targets by estimating the Doppler center frequency and the chirp rate. This estimation method has a complex processing process, and the expression of motion parameters is not a function of a single variable, resulting in inaccurate results.

[0004] However, with the emergence of terahertz video SAR, many scholars have found that in the terahertz band, when a moving target is irradiated by a radar, due to the short synthetic time of imaging, for most ground moving targets, a sufficiently clear low-energy area is left at the position of the moving target, and this area is the shadow of the moving target. At the same time, affected by the Doppler effect of the moving target, the image formed by the moving target is offset in the azimuth direction of the radar. The range velocity of the moving target is estimated by the Doppler frequency shift amount between the shadow and the target image. And due to the change in the shape of the shadow of the moving target through the movement of the shadow between different frames, the accuracy of the estimated average velocity of the moving target is not high. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method, device, and equipment for estimating parameters of ground moving targets based on shadows that can accurately estimate target parameters.

[0006] A method for estimating parameters of ground moving targets based on shadows, the method includes: Construct a geometric model of terahertz video SAR moving target imaging in spotlight mode and an echo mathematical model of the moving target; Obtain an echo signal detected by a terahertz video radar for a ground moving scene, and display the echo signal in the form of the echo mathematical model; Obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract a target image of the moving target in the two-dimensional image; Perform an inverse azimuth Fourier transform on the target image to obtain the one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; Perform an azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground moving scene, measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimate the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground moving scene, measure the frequency width of the target image relative to the shadow of the moving target in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency width; Estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

[0007] In one embodiment, in the geometric model, the distance from the radar to the center of the ground moving scene is expressed as: ; In the above formula, represents the center position of the radar carrying platform, represents the velocity of the radar carrying platform, represents the slow time; The distance from the radar to the moving target is expressed as: ; In the above formula, represents the coordinates of the moving target, , , and respectively represent the azimuth velocity, azimuth acceleration, range velocity, and range acceleration of the moving target.

[0008] In one embodiment, the generating the two-dimensional image of the ground moving scene according to the echo signal includes: After compensating the residual video phase term and range term of the echo signal, obtain the echo signal in range time domain - azimuth time domain; Perform range and azimuth Fourier transforms on the echo signal in range time domain - azimuth time domain to obtain the two-dimensional image of the ground moving scene.

[0009] In one embodiment, to estimate the range velocity of the moving target according to the azimuth frequency shift, the following formula is used: ; In the above formula, represents the measured azimuth frequency shift, represents the wavelength, represents the distance from the radar to the center of the ground moving scene.

[0010] In one embodiment, the azimuth velocity of the moving target is estimated according to the frequency bandwidth, and the following formula is adopted: ; In the above formula, represents the scaling coefficient.

[0011] In one embodiment, the range acceleration of the moving target is estimated according to the azimuth chirp rate value and the azimuth velocity of the moving target, and the following formula is adopted: ; In the above formula, represents the recorded azimuth chirp rate value.

[0012] The present application also provides a ground moving target parameter estimation device based on shadow, and the device includes: An echo mathematical model construction module, configured to construct a geometric model of terahertz video SAR moving target imaging in the spotlight mode and an echo mathematical model of the moving target; An echo signal acquisition module, configured to acquire an echo signal obtained by detecting a ground moving scene by a terahertz video radar, and display the echo signal in the form of the echo mathematical model; A target image extraction module, configured to obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract a target image of the moving target in the two-dimensional image; An azimuth chirp rate value obtaining module, configured to perform an inverse azimuth Fourier transform on the target image to obtain a one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; An imaging position obtaining module, configured to perform an azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image; A range velocity estimation module, configured to measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target based on the two-dimensional image of the ground moving scene, and estimate the range velocity of the moving target according to the azimuth frequency shift; An azimuth velocity estimation module, configured to measure the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction based on the two-dimensional image of the ground moving scene, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; A range acceleration estimation module, configured to estimate the range acceleration of a moving target according to the azimuth frequency modulation rate value and the azimuth velocity of the moving target; A parameter estimation completion module, configured to complete the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

[0013] A computer device, comprising a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Construct a geometric model for imaging a moving target in a spotlight-mode terahertz video SAR, and an echo mathematical model of the moving target; Obtain an echo signal detected by a terahertz video radar for a ground moving scene, and display the echo signal in the form of the echo mathematical model; Obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract a target image of the moving target from the two-dimensional image; Perform an inverse azimuth Fourier transform on the target image to obtain a one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth frequency modulation rate value; Perform an azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground moving scene, measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimate the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground moving scene, measure the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; Estimate the range acceleration of the moving target according to the azimuth frequency modulation rate value and the azimuth velocity of the moving target; Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

[0014] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Construct a geometric model for imaging a moving target in a spotlight-mode terahertz video SAR, and an echo mathematical model of the moving target; Obtain an echo signal detected by a terahertz video radar for a ground moving scene, and display the echo signal in the form of the echo mathematical model; Obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract a target image of the moving target from the two-dimensional image; Perform an inverse azimuth Fourier transform on the target image to obtain the one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; Perform an azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground motion scene, measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimate the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground motion scene, measure the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; Estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

[0015] The above method, device, and equipment for estimating parameters of ground moving targets based on shadows construct a geometric model of imaging of ground moving targets in a spotlight-mode terahertz video SAR and a mathematical model of the echo of the moving target. After representing the echo signal detected by the terahertz video radar for the ground motion scene based on this mathematical model of the echo, the range velocity of the moving target is estimated by the relative offset in the azimuth direction between the moving target image and the shadow, the azimuth velocity of the moving target is estimated by the frequency broadening in the azimuth direction between the target image and the shadow, and the range acceleration of the moving target is estimated by the chirp rate of the quadratic phase through the compensation of the quadratic phase. Precise target parameter estimation can be obtained by using this method. Description of the Drawings

[0016] Figure 1 It is a schematic flowchart of a method for estimating parameters of ground moving targets based on shadows in an embodiment; Figure 2 It is a schematic diagram of a geometric model of imaging of a stationary target in a spotlight-mode THz-ViSAR in an embodiment; Figure 3 It is a schematic diagram of the refocusing result when the range velocity is 1 m / s in an experiment; Figure 4 It is a schematic diagram of the imaging result of a moving target in an experiment; Figure 5 It is a schematic diagram of the refocusing result when the azimuth velocity is 50 m / s in an experiment; Figure 6 It is for an experiment where the azimuth acceleration is 2 m / s 2 when the refocusing result schematic diagram; Figure 7 It is a structural block diagram of a shadow-based ground moving target parameter estimation device in an embodiment; Figure 8 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0017] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] Since the actual track and imaging scene are very complex, the Doppler parameters deduced from the distance from the moving target to the antenna phase center, such as the instantaneous Doppler frequency and the instantaneous Doppler chirp rate, are subject to multiple variables, such as the initial position of the target, the moving speed and acceleration of the radar. It is difficult to simply correspond the motion parameters with the Doppler parameters through Doppler parameter-based motion parameter estimation, resulting in inaccurate estimation of the moving target parameters. Affected by the scene noise, the shape of the shadow of the moving target will change and the contour is not clear, and the estimated speed is inaccurate.

[0019] To solve the above problems, in order to obtain accurate and reliable moving target parameters, a shadow-based ground moving target parameter estimation method is proposed in this paper, including the following steps: Step S100, construct a geometric model of terahertz video SAR moving target imaging in spotlight mode and an echo mathematical model of the moving target.

[0020] Step S110, obtain the echo signal detected by the terahertz video radar for the ground moving scene, and display the echo signal in the form of the echo mathematical model.

[0021] Step S120, obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract the target image of the moving target in the two-dimensional image.

[0022] Step S130, perform an inverse Fourier transform in the azimuth direction on the target image to obtain a one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value.

[0023] Step S140, perform a Fourier transform in the azimuth direction on the one-dimensional range image of the moving target to obtain the imaging position of the target image.

[0024] Step S150, based on the two-dimensional image of the ground moving scene, measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimate the range velocity of the moving target according to the azimuth frequency shift.

[0025] Step S160: Based on the two-dimensional image of the ground motion scene, measure the frequency bandwidth of the target image relative to the moving target shadow in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency bandwidth.

[0026] Step S170: Estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target.

[0027] Step S180: Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity and range acceleration of the moving target.

[0028] In this application, a method for estimating the range velocity of a moving target by the relative offset of the moving target image and the shadow in the azimuth direction, estimating the azimuth velocity of the moving target by the frequency broadening of the target image and the shadow in the azimuth direction, and estimating the range acceleration of the moving target by the chirp rate of the quadratic phase through the compensation of the quadratic phase is proposed.

[0029] In this article, first, the inference process of the theoretical part of this method is shown. First, it is assumed that the radar emits a linear frequency modulation signal with a pulse width of which is expressed as: (1) In formula (1), , is the center frequency of the linear frequency modulation signal, is the chirp rate, is the fast time, is the slow time.

[0030] Then the signal from the radar structure to the moving target P is expressed as: (2) In formula (2), is the speed of light, is the distance from the radar to the moving target.

[0031] Considering the spotlight mode with the distance from the radar to the illumination center as the reference distance, the reference signal can be expressed as: (3) In formula (3), the distance from the radar to the center of the ground motion scene.

[0032] If , the signal after Dechirp processing is: (4) In the above formula, Indicates the signal amplitude, Indicates the phase term.

[0033] In Equation (4): (5) After compensating for the remaining video phase term and range term, the echo signal can be expressed as: (6) Next, perform a range Fourier transform on Equation (6) to obtain: (7) In Equation (7), and represent the azimuth pulse width and difference frequency, respectively.

[0034] Furthermore, construct a geometric model for imaging moving targets in a spotlight-mode terahertz video SAR, as Figure 2 shown, so as to obtain in Equation (6).

[0035] Referring to Figure 2 , on the flight trajectory of the radar-carrying platform, point B with coordinates is the flight center of the airborne platform, and the flight speed, i.e., the speed of the radar-carrying platform, is , and the coordinates of the corresponding moving target p are , its azimuth speed is , the acceleration is , the range speed is , and the acceleration is . Then, according to the geometric relationship of the imaging model, the distance from the radar to the center of the moving scene can be expressed as: (8) And the distance from the radar to the moving target is expressed as: (9) Furthermore: (10) Further organize Equation (10) to obtain: (11) Substitute Equation (11) into Equation (6) to obtain that the first-order phase term is expressed as: (12) And the second-order phase term is expressed as: (13) Furthermore, the imaging position of the moving target, where the range frequency-domain position is: (14) The azimuth frequency domain position is: (15) Converting the above range frequency domain position and azimuth frequency domain position into time domain position, i.e., the imaging position is: (16) Since,[[]] ,[[]] ,[[]] , the main factor affecting the offset of the moving target is the range velocity. Then formula (15) can be simplified to: (17) In formula (17),[[]] represents the wavelength.

[0036] Then according to formula (17), the range velocity can be obtained and expressed as: (18) Furthermore, the azimuth chirp rate in the quadratic phase term of formula (13) is expressed as: (19) And according to formula (16), it can be known that the imaging position and the true position have the following relationship in the azimuth direction: (20) In formula (20),[[]] . Since the imaging position in the azimuth direction is offset and there is image scaling, the scaling coefficient is expressed as: (21) The scaling coefficient is related to the azimuth velocity of the moving target. The scaling coefficient is proportional to the azimuth broadening of the moving target. That is, given the true broadening (shadow) of the moving target and the azimuth broadening of the target image, the azimuth velocity of the moving target can be estimated.

[0037] Since[[]] ,[[]] ,[[]] , the azimuth acceleration has little effect on the defocusing of the target. The azimuth velocity, range velocity and range acceleration can all have a greater impact on the imaging of the moving target. For slow moving targets, formula (19) can be simplified to: (22) Then the range acceleration can be obtained by the following formula: (23) Since the azimuth modulation frequency is related to the azimuth velocity and the range acceleration, the azimuth modulation frequency is estimated through the image displacement algorithm. Given the azimuth velocity of the moving target, the range acceleration can be estimated.

[0038] The above is the derivation process of the theory of this method. Next, the specific steps of this method will be introduced.

[0039] In step S100, first construct the geometric model of the terahertz video SAR moving target imaging in the spotlight mode as shown in Figure 2 . This geometric model has been introduced above, and based on this geometric model, the distances from the radar to the center of the ground moving scene and from the radar to the moving target shown in formulas (8) and (9) are obtained, which will not be elaborated here. In step S110, the terahertz-band video SAR carried on the aircraft detects the ground moving scene to obtain the echo signal. And this echo signal is represented in the form of an echo mathematical model, namely formulas (4), (5), and (11).

[0040] In this embodiment, generating the two-dimensional image of the ground moving scene from the echo signal includes: after compensating the residual video phase term and the range term of the echo signal, the echo signal in the range time domain - azimuth time domain is obtained, and the range and azimuth Fourier transforms are performed on the echo signal in the range time domain - azimuth time domain to obtain the two-dimensional image of the ground moving scene.

[0041] Specifically, the echo signal in the range time domain - azimuth time domain is as shown in formula (6).

[0042] In step S120, in the two-dimensional image of the ground moving scene, the target image of the moving target is extracted, and the inverse azimuth Fourier transform is performed to obtain the one-dimensional range image of the moving target, and its expression is as shown in formula (7).

[0043] In step S130, quadratic phase compensation is performed based on the one-dimensional range image of the moving target, and the azimuth modulation frequency value corresponding to the optimal phase compensation is recorded. Among them, the quadratic phase term is expressed as shown in formula (13).

[0044] Since

[0045] , , , , the influence of the azimuth acceleration on the defocusing of the target is very small. For slow-moving targets, after simplification, the expression of the azimuth Doppler modulation frequency is as shown in formula (22).

[0046] In step S140, a Fourier transform in the azimuth direction is performed on the moving target to obtain the target image of the moving target. Then, the time-domain position (imaging position) of the target image is as shown in formula (16).

[0047] In step S150, based on the two-dimensional image, and when the imaging position of the target image is known, the azimuth frequency shift of the target image relative to the shadow of the moving target is measured, and the measured azimuth frequency shift value is substituted into formula (18) to estimate the range velocity of the moving target.

[0048] In step S160, based on the imaging position and the relationship with the true position, i.e., the coordinates of the moving target in the azimuth direction, and the scaling coefficient of the image, substituting formula (21) into formula (20), the following formula can be obtained: (24) In formula (24), represents the scaling coefficient, which is the broadening ratio of the moving target in the azimuth direction, that is, the broadening of the shadow of the moving target and the target image in the azimuth direction. When is known, substituting its value into formula (24) can obtain the azimuth velocity.

[0049] In step S170, the azimuth chirp rate value recorded in step S130 and the azimuth velocity estimated in step S160 are substituted into formula (23) to estimate the range acceleration of the moving target.

[0050] In step S180, based on the range velocity, azimuth velocity, and range acceleration estimated in steps S150, S160, and S170, the parameter estimation of the moving target is completed.

[0051] In this article, the effectiveness of this method is also demonstrated through experiments. In the experiment, the technical parameters used for the imaging of simulation and measured data are shown in Table 1.

[0052] Table 1 Parameters for the imaging of simulation and measured data

[0053] First, the estimation of the range velocity of the moving target is performed. Figure 3 The simulation result for the range velocity being is as follows. There are 9 moving targets in the shadow area, and the range velocity of all targets is . After the refocusing process, the obtained image is in the target area. By measurement, the azimuth frequency shift between the target image and the shadow , the range position where the target is located , the slant range is , in the terahertz band , according to Equation , calculate , which is basically the same as the set result.

[0054] Figure 4 is the image formed by the 333rd frame data of a flight test conducted at a certain location. The test parameters are shown in Table 1 and it is in the spotlight mode. After measurement, the measured azimuth frequency shift of the moving target to the shadow , the range direction position where the target is located , the slant range is , in the terahertz band , according to Equation , calculate . Select the 355th frame image. Taking a special display point at the lower end as a reference, the moving target moves a distance of in the range direction, and the time is , and the estimated range direction velocity is . There is a small error between the two, and another method is used to prove the accuracy of this method.

[0055] Further, estimate the azimuth velocity of the moving target. Figure 5 is the result of the moving target refocusing. The real position of the moving target is in the shadow area. After refocusing, the target is focused in the target area. By comparing the azimuth broadening of the shadow area and the target area, it can be seen that the broadening of the target area is narrower. The broadening of the target area and the shadow area is related to the ratio of the azimuth velocity of the moving target and the radar flight velocity. After measurement, the azimuth broadening of the shadow area is 67 frequency points (1470 - 1537), and the actual azimuth broadening of the moving target after refocusing is 11 frequency points (1284 - 1295). According to the contraction ratio in Equation , , estimate the azimuth velocity , which is approximate to the theoretical value.

[0056] Figure 4 In, in the measured data, the broadening of the shadow area and the target area reflect the relationship between the azimuth velocity of the moving target and the radar flight velocity. Through windowing measurement, the azimuth broadening of the target image is 1.035 times that of the shadow azimuth width (0.1071 / 0.1035). With the actual carrier aircraft speed , the estimated azimuth velocity is , and the azimuth velocity of the moving target is very small.

[0057] Finally, estimate the range acceleration of the moving target. Figure 6 is Moving target refocusing result. The shaded area represents the true position of the moving target, and the target image area represents the position of the moving target image. The broadening of the shaded area and the target area in the azimuth direction is equal. Without azimuth velocity, the two-dimensional phase during refocusing comes from the range acceleration. It is measured that the broadening of the azimuth of the shadow is 66 frequency points (1284 - 1350), and the broadening of the azimuth of the target image after refocusing is 67 frequency points (1470 - 1537), indicating that there is no stretching of the moving target in the azimuth direction. The range acceleration compensates for the quadratic term phase, and its azimuth chirp rate is 2623.6 Hz / s. Through Equation , let , and the range acceleration is obtained, which basically meets the expectation.

[0058] In the above method for estimating ground moving target parameters based on the shadow, the range velocity of the moving target is estimated by the relative offset in the azimuth direction between the target image and the shadow; the azimuth velocity of the moving target is estimated by the frequency broadening in the azimuth direction between the target image and the shadow; the range acceleration of the moving target is estimated by the chirp rate of the quadratic phase through the compensation of the quadratic phase. Compared with other methods for estimating motion parameters based on Doppler parameters, the motion target parameters extracted by this method are relatively independent and are not affected by other motion parameters, and more accurate estimation can be obtained. At the same time, this method combines the measured imaging method and is more operable.

[0059] It should be understood that although each step in the flowchart of Figure 1 is shown in sequence according to the indication of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise clearly stated in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 at least a part of the steps in

[0060] may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential either, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps. Figure 7 As shown in The echo mathematical model construction module 200 is used to construct the geometric model of the moving target imaging in the spotlight mode of the terahertz video SAR and the echo mathematical model of the moving target; The echo signal acquisition module 210 is used to acquire the echo signal obtained by detecting the ground moving scene with the terahertz video radar and display the echo signal in the form of the echo mathematical model; The target image extraction module 220 is used to obtain the two-dimensional image of the ground moving scene according to the echo signal and extract the target image of the moving target in the two-dimensional image; The azimuth chirp rate value obtaining module 230 is used to perform the inverse Fourier transform in the azimuth direction on the target image to obtain the one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; The imaging position obtaining module 240 is used to perform the Fourier transform in the azimuth direction on the one-dimensional range image of the moving target to obtain the imaging position of the target image; The range velocity estimation module 250 is used to measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target based on the two-dimensional image of the ground moving scene and estimate the range velocity of the moving target according to the azimuth frequency shift; The azimuth velocity estimation module 260 is used to measure the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction based on the two-dimensional image of the ground moving scene and estimate the azimuth velocity of the moving target according to the frequency bandwidth; The range acceleration estimation module 270 is used to estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; The parameter estimation completion module 280 is used to complete the parameter estimation of the moving target according to the range velocity, azimuth velocity and range acceleration of the moving target.

[0061] For the specific definition of the device for parameter estimation of ground moving targets based on shadow, reference can be made to the definition of the method for parameter estimation of ground moving targets based on shadow in the above text, which will not be elaborated here. Each module in the above device for parameter estimation of ground moving targets based on shadow can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in the processor in the computer device in the form of hardware or be independent of it, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0062] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 8As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for estimating parameters of a ground moving target based on shadows. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad set on the outer shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0063] Those skilled in the art can understand that Figure 8 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0064] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented: Construct a geometric model of the moving target imaging of the terahertz video SAR in the spotlight mode, and an echo mathematical model of the moving target; Obtain the echo signal detected by the terahertz video radar for the ground moving scene, and display the echo signal in the form of the echo mathematical model; Obtain a two-dimensional image of the ground moving scene according to the echo signal, and extract the target image of the moving target in the two-dimensional image; Perform an inverse Fourier transform in the azimuth direction on the target image to obtain a one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; Perform a Fourier transform in the azimuth direction on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground moving scene, measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimate the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground motion scene, measure the frequency bandwidth of the target image relative to the moving target shadow in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; Estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity and range acceleration of the moving target.

[0065] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: Construct a geometric model of the moving target imaging in the spotlight-mode terahertz video SAR and a mathematical echo model of the moving target; Obtain the echo signal detected by the terahertz video radar for the ground motion scene, and display the echo signal in the form of the mathematical echo model; Obtain a two-dimensional image of the ground motion scene according to the echo signal, and extract the target image of the moving target in the two-dimensional image; Perform an inverse Fourier transform in the azimuth direction on the target image to obtain the one-dimensional range image of the moving target, perform quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth chirp rate value; Perform a Fourier transform in the azimuth direction on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground motion scene, measure the azimuth frequency shift of the imaging position of the target image relative to the moving target shadow, and estimate the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground motion scene, measure the frequency bandwidth of the target image relative to the moving target shadow in the azimuth direction, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; Estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; Complete the parameter estimation of the moving target according to the range velocity, azimuth velocity and range acceleration of the moving target.

[0066] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0067] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0068] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for estimating parameters of a ground moving target based on shadow, characterized in that, The method includes: Constructing a geometric model for terahertz video SAR moving target imaging in spotlight mode and an echo mathematical model of the moving target; Obtaining an echo signal detected by a terahertz video radar for a ground moving scene and presenting the echo signal in the form of the echo mathematical model; Obtaining a two-dimensional image of the ground moving scene based on the echo signal and extracting a target image of the moving target from the two-dimensional image; Performing an inverse azimuth Fourier transform on the target image to obtain a one-dimensional range image of the moving target, performing quadratic phase compensation on the target image based on the one-dimensional range image, and recording the azimuth chirp rate value; Performing an azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image; Based on the two-dimensional image of the ground moving scene, measuring the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target, and estimating the range velocity of the moving target according to the azimuth frequency shift; Based on the two-dimensional image of the ground moving scene, measuring the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction, and estimating the azimuth velocity of the moving target according to the frequency bandwidth; Estimating the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; Completing the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

2. The method for estimating ground moving target parameters based on shadow according to claim 1, wherein In the geometric model, the distance from the radar to the center of the ground moving scene is expressed as: ； In the above formula, represents the center position of the radar-carrying platform, represents the speed of the radar-carrying platform, represents the slow time; The distance from the radar to the moving target is expressed as: ； In the above formula, represents the coordinates of the moving target, , , and respectively represent the azimuth velocity, azimuth acceleration, range velocity, and range acceleration of the moving target.

3. The method for estimating ground moving target parameters based on shadow according to claim 2, characterized in that, The generating the two-dimensional image of the ground moving scene based on the echo signal includes: After compensating the residual video phase term and range term for the echo signal, obtaining an echo signal in range time domain - azimuth time domain; Performing range and azimuth Fourier transforms on the echo signal in range time domain - azimuth time domain to obtain the two-dimensional image of the ground moving scene.

4. The method for estimating ground moving target parameters based on shadow according to claim 3, wherein Estimating the range velocity of the moving target according to the azimuth frequency shift, using the following formula: ； In the above formula, represents the measured azimuth frequency shift, represents the wavelength, represents the distance from the radar to the center of the ground moving scene.

5. The method for estimating parameters of a ground moving target based on shadow according to claim 4, wherein Estimating the azimuth velocity of the moving target according to the frequency bandwidth, using the following formula: ； In the above formula, represents the expansion coefficient.

6. The method for estimating ground moving target parameters based on shadow according to claim 5, characterized in that Estimating the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target, using the following formula: ； In the above formula, represents the recorded azimuth modulation frequency value.

7. An apparatus for estimating parameters of a ground moving target based on shadow, characterized in that, The device includes: An echo mathematical model construction module for constructing a geometric model for terahertz video SAR moving target imaging in spotlight mode and an echo mathematical model of the moving target; An echo signal acquisition module for obtaining an echo signal detected by a terahertz video radar for a ground moving scene and presenting the echo signal in the form of the echo mathematical model; A target image extraction module for obtaining a two-dimensional image of the ground moving scene based on the echo signal and extracting a target image of the moving target from the two-dimensional image; An azimuth chirp rate value obtaining module for performing an inverse azimuth Fourier transform on the target image to obtain a one-dimensional range image of the moving target, performing quadratic phase compensation on the target image based on the one-dimensional range image, and recording the azimuth chirp rate value; An imaging position obtaining module, configured to perform azimuth Fourier transform on the one-dimensional range profile of the moving target to obtain the imaging position of the target image; A range velocity estimation module, configured to measure the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target based on the two-dimensional image of the ground motion scene, and estimate the range velocity of the moving target according to the azimuth frequency shift; An azimuth velocity estimation module, configured to measure the frequency bandwidth of the target image relative to the shadow of the moving target in the azimuth direction based on the two-dimensional image of the ground motion scene, and estimate the azimuth velocity of the moving target according to the frequency bandwidth; A range acceleration estimation module, configured to estimate the range acceleration of the moving target according to the azimuth chirp rate value and the azimuth velocity of the moving target; A parameter estimation completion module, configured to complete the parameter estimation of the moving target according to the range velocity, azimuth velocity, and range acceleration of the moving target.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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