Method, apparatus and device for estimating parameters of ground moving targets based on shadows

Abstract

This application relates to a method, device, and apparatus for estimating parameters of ground moving targets based on shadows. The method constructs a geometric model for imaging moving targets using terahertz video SAR (terahertz SAR) in a spotlight mode, and based on this geometric model, obtains a mathematical model of the moving target's echo. After representing the echo signal obtained by detecting a ground moving scene using the terahertz video SAR using this mathematical model, the method estimates the target's range velocity by the relative offset between the target image and the shadow in azimuth, estimates the target's azimuth velocity by frequency broadening between the target image and the shadow in azimuth, and estimates the target's range acceleration by compensating for the quadratic phase and modulating the quadratic phase frequency. This method enables accurate target parameter estimation.

Description

Technical Field

[0001] The present application relates to the field of radar signal processing technology, and in particular to a method, device and equipment for estimating parameters of ground moving targets based on shadows. Background Art

[0002] Video SAR (video SAR) is designed to continuously acquire high-resolution images of a scene, detect and monitor moving targets within it, and estimate the motion state of ground-moving targets. Numerous methods have been proposed for parameter estimation of ground-moving targets, particularly for video SAR in the terahertz band.

[0003] These parameter estimation methods are generally divided into two categories: Doppler-based motion parameter estimation methods and shadow-based moving target parameter estimation methods. Doppler-based motion parameter estimation methods estimate the azimuth and range velocity of a moving target by estimating the Doppler center frequency and modulation rate. However, this method is complex, and the expression for the motion parameter is not a function of a single variable, resulting in inaccurate results.

[0004] However, with the advent of terahertz video SAR (terahertz SAR), many researchers have discovered that in the terahertz frequency band, due to the short imaging synthesis time, most ground moving targets are left with a sufficiently clear, low-energy area at their location. This area is the moving target's shadow. Furthermore, due to the Doppler effect of the moving target, the image of the moving target is offset in the radar's azimuth. The Doppler frequency shift between the shadow and the target image is used to estimate the range and velocity of the moving target. However, the estimated average velocity of the moving target is inaccurate due to the shadow's shape changing between frames. Summary of the Invention

[0005] Based on this, it is necessary to provide a shadow-based ground moving target parameter estimation method, device and equipment that can accurately estimate target parameters in response to the above technical problems.

[0006] A method for estimating parameters of a ground moving target based on shadows, the method comprising:

[0007] Construct a geometric model for imaging moving targets using terahertz video SAR in spotlight mode, as well as a mathematical model for the echo of moving targets;

[0008] Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model;

[0009] Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0010] Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value;

[0011] Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0012] Based on the two-dimensional image of the ground motion 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;

[0013] Based on the two-dimensional image of the ground motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth;

[0014] estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0015] The parameters of the moving target are estimated based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0016] In one embodiment, in the geometric model, the distance from the radar to the center of the ground motion scene is expressed as:

[0017] ;

[0018] In the above formula, Indicates the center position of the radar carrying platform, represents the speed of the radar-carrying platform, Indicates slow time;

[0019] The distance between the radar and the moving target is expressed as:

[0020] ;

[0021] In the above formula, represents the coordinates of the moving target, 、 、 as well as They represent the azimuth velocity, azimuth acceleration, range velocity, and range acceleration of the moving target respectively.

[0022] In one embodiment, generating a two-dimensional image of a ground motion scene according to the echo signal includes:

[0023] After compensating the echo signal for the residual video phase term and the distance term, an echo signal in the range time domain and the azimuth time domain is obtained;

[0024] Performing Fourier transform in the range direction and the azimuth direction on the echo signal of the range time domain and the azimuth time domain to obtain a two-dimensional image of the ground motion scene.

[0025] In one embodiment, the range velocity of the moving target is estimated based on the azimuth frequency shift using the following formula:

[0026] ;

[0027] In the above formula, represents the measured azimuth frequency shift, represents the wavelength, Indicates the distance from the radar to the center of the ground motion scene.

[0028] In one embodiment, the azimuth velocity of the moving target is estimated based on the bandwidth using the following formula:

[0029] ;

[0030] In the above formula, Indicates the expansion factor.

[0031] In one embodiment, the range acceleration of the moving target is estimated based on the azimuth frequency modulation value and the azimuth velocity of the moving target using the following formula:

[0032] ;

[0033] In the above formula, Indicates the recorded azimuth frequency modulation value.

[0034] The present application also provides a device for estimating parameters of a ground moving target based on shadows, the device comprising:

[0035] The echo mathematical model construction module is used to construct the geometric model of terahertz video SAR moving target imaging in the spotlight mode, as well as the echo mathematical model of the moving target;

[0036] an echo signal acquisition module, configured to acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and to display the echo signal in the form of the echo mathematical model;

[0037] a target image extraction module, configured to obtain a two-dimensional image of a ground motion scene according to the echo signal, and extract a target image of a moving target from the two-dimensional image;

[0038] an azimuth frequency modulation value obtaining module, configured to perform an azimuth inverse Fourier transform on the target image to obtain a one-dimensional range image of the moving target, perform secondary phase compensation on the target image based on the one-dimensional range image, and record the azimuth frequency modulation value;

[0039] An imaging position obtaining module is used to perform azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image;

[0040] a range velocity estimation module, configured to measure, based on the two-dimensional image of the ground motion scene, an 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;

[0041] an azimuth velocity estimation module, configured to measure the azimuth bandwidth 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 azimuth velocity of the moving target according to the bandwidth;

[0042] a range acceleration estimation module, configured to estimate the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0043] The parameter estimation completion module 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.

[0044] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0045] Construct a geometric model for imaging moving targets using terahertz video SAR in spotlight mode, as well as a mathematical model for the echo of moving targets;

[0046] Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model;

[0047] Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0048] Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value;

[0049] Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0050] Based on the two-dimensional image of the ground motion 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;

[0051] Based on the two-dimensional image of the ground motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth;

[0052] estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0053] The parameters of the moving target are estimated based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0054] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0055] Construct a geometric model for imaging moving targets using terahertz video SAR in spotlight mode, as well as a mathematical model for the echo of moving targets;

[0056] Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model;

[0057] Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0058] Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value;

[0059] Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0060] Based on the two-dimensional image of the ground motion 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;

[0061] Based on the two-dimensional image of the ground motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth;

[0062] estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0063] The parameters of the moving target are estimated based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0064] The shadow-based method, device, and equipment for estimating parameters of ground moving targets construct a geometric model for terahertz video SAR moving target imaging in spotlight mode and a mathematical model of the target's echo. Based on this mathematical model, the echo signal obtained by detecting a ground moving scene using the terahertz video radar is represented. The method then estimates the target's range velocity by the relative offset between the target image and the shadow in azimuth, the target's azimuth velocity by frequency broadening in azimuth between the target image and the shadow, and the target's range acceleration by compensating for the quadratic phase and modulating the quadratic phase frequency. This method enables accurate target parameter estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 1 is a flow chart of a method for estimating parameters of a ground moving target based on shadows in one embodiment;

[0066] Figure 2 Schematic diagram of a geometric model for THz-ViSAR stationary target imaging in a spotlight mode according to one embodiment;

[0067] Figure 3 This is a schematic diagram of the refocusing results when the range velocity is 1 m / s in an experiment;

[0068] Figure 4 This is a schematic diagram of the imaging results of a moving target in an experiment;

[0069] Figure 5 This is a schematic diagram of the refocusing results when the azimuth velocity is 50 m / s in an experiment;

[0070] Figure 6 In an experiment, the azimuth acceleration is 2 m / s 2 Schematic diagram of time refocusing results;

[0071] Figure 7 is a structural block diagram of a ground moving target parameter estimation device based on shadow in one embodiment;

[0072] Figure 8 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0073] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0074] Due to the complexity of actual flight paths and imaging scenarios, Doppler parameters derived from the distance of a moving target to the antenna phase center, such as the instantaneous Doppler frequency and instantaneous Doppler modulation rate, are subject to multiple variables, including the target's initial position, the radar's velocity, and acceleration. Estimating motion parameters using Doppler parameters is difficult to simply correlate, resulting in inaccurate estimates of moving target parameters. The shape of the moving target's shadow can change due to scene noise, making the outline unclear and inaccurate, leading to inaccurate velocity estimates.

[0075] To solve the above problems, in order to obtain accurate and reliable moving target parameters, this paper proposes a ground moving target parameter estimation method based on shadow, which includes the following steps:

[0076] Step S100 : constructing a geometric model for imaging a moving target using terahertz video SAR in a spotlight mode, and a mathematical model for the echo of the moving target.

[0077] Step S110 , obtaining an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and displaying the echo signal in the form of an echo mathematical model.

[0078] Step S120 , obtaining a two-dimensional image of the ground motion scene according to the echo signal, and extracting a target image of the moving target from the two-dimensional image.

[0079] Step S130 , performing an inverse Fourier transform on the target image in azimuth to obtain a one-dimensional range image of the moving target, performing a quadratic phase compensation on the target image based on the one-dimensional range image, and recording the azimuth frequency modulation value.

[0080] Step S140 , performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain the imaging position of the target image.

[0081] Step S150 : Based on the two-dimensional image of the ground motion scene, the azimuth frequency shift of the imaging position of the target image relative to the shadow of the moving target is measured, and the range velocity of the moving target is estimated according to the azimuth frequency shift.

[0082] Step S160 : Based on the two-dimensional image of the ground motion scene, measure the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimate the azimuth velocity of the moving target according to the bandwidth.

[0083] Step S170 , estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target.

[0084] Step S180 , completing parameter estimation of the moving target based on the range velocity, azimuth velocity, and range acceleration of the moving target.

[0085] In the present application, a method for estimating the range velocity of a moving target is proposed by estimating the relative offset of the moving target image and shadow in azimuth, estimating the azimuth velocity of the moving target by frequency broadening of the target image and shadow in azimuth, and estimating the range acceleration of the moving target by compensation of the quadratic phase and the frequency modulation of the quadratic phase.

[0086] In this paper, we first show the inference process of the theoretical part of this method. We assume that the radar emits a pulse with a width of The linear frequency modulation signal is expressed as:

[0087] (1)

[0088] In formula (1), , is the center frequency of the linear FM signal, To adjust the frequency, For quick time, For slow time.

[0089] Then the signal from the radar structure to the moving target P is Expressed as:

[0090] (2)

[0091] In formula (2), is the speed of light, The distance between the radar and the moving target.

[0092] Considering the beamforming mode with the distance from the radar to the irradiation center as the reference distance, the reference signal can be expressed as:

[0093] (3)

[0094] In formula (3), the distance from the radar to the center of the ground motion scene.

[0095] like , the signal after Dechirp (de-skewing and de-modulation) processing is:

[0096] (4)

[0097] In the above formula, represents the signal amplitude, represents the phase term.

[0098] In formula (4):

[0099] (5)

[0100] After compensating the residual video phase term and distance term, the echo signal can be expressed as:

[0101] (6)

[0102] Next, perform distance Fourier transform on formula (6) to obtain:

[0103] (7)

[0104] In formula (7), 、 They represent the azimuth pulse width and difference frequency respectively.

[0105] Furthermore, a geometric model of THz video SAR moving target imaging is constructed in the spotlight mode, such as Figure 2 As shown, we can get the formula (6) .

[0106] refer to Figure 2 , on the flight trajectory of the radar-carrying platform, the coordinates are Point B is the flight center of the airborne platform, and the flight speed, that is, the speed of the radar-carrying platform, is , the corresponding coordinates of the moving target p are , and its azimuthal velocity is , the acceleration is , the range velocity is , the acceleration is 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:

[0107] (8)

[0108] The distance between the radar and the moving target is expressed as:

[0109] (9)

[0110] Further:

[0111] (10)

[0112] Further sorting out formula (10) yields:

[0113] (11)

[0114] Substituting formula (11) into formula (6), the first-order phase term is expressed as:

[0115] (12)

[0116] The quadratic phase term is expressed as:

[0117] (13)

[0118] The imaging position of the moving target is further described, where the range frequency domain position is:

[0119] (14)

[0120] The azimuth frequency domain position is:

[0121] (15)

[0122] Convert the above distance frequency domain position and azimuth frequency domain position into time domain position, i.e. imaging position:

[0123] (16)

[0124] because, , , , the main factor affecting the displacement of the moving target is the range velocity. Then formula (15) can be simplified as:

[0125] (17)

[0126] In formula (17), Indicates wavelength.

[0127] According to formula (17), the range velocity can be obtained as:

[0128] (18)

[0129] Furthermore, the azimuth frequency modulation in the phase term of the quadratic term in formula (13) is Expressed as:

[0130] (19)

[0131] According to formula (16), the imaging position With real location The relationship in azimuth is:

[0132] (20)

[0133] In formula (20), Since the imaging position in the azimuth direction is offset and there is image expansion and contraction, the expansion coefficient Expressed as:

[0134] (twenty one)

[0135] Stretch factor The expansion factor is proportional to the azimuth spread of the moving target. That is, if the true spread (shadow) of the moving target and the azimuth spread of the target image are known, the azimuth spread of the moving target can be estimated.

[0136] because , , , the azimuth acceleration has little effect on the defocus of the target. The azimuth velocity, range velocity and range acceleration can all have a significant impact on the imaging of the moving target. For slow-moving targets, formula (19) can be simplified to:

[0137] (twenty two)

[0138] The distance acceleration can be obtained using the following formula:

[0139] (twenty three)

[0140] Because the azimuth frequency modulation It is related to the azimuth velocity and range acceleration. The azimuth frequency modulation is estimated through the image displacement algorithm. , if the azimuth velocity of the moving target is known, the range acceleration can be estimated.

[0141] The above is the theoretical derivation process of this method. Next, the specific steps of this method are introduced.

[0142] In step S100, first construct Figure 2 As shown, the THz video SAR motion in spotlight mode

[0143] The geometric model of target imaging has been introduced above. Based on this geometric model, the distance from the radar to the center of the ground moving scene and the distance from the radar to the moving target are obtained as shown in formulas (8) and (9). We will not repeat them here.

[0144] In step S110, the terahertz frequency band video SAR carried by the aircraft detects the ground motion scene and obtains an echo signal. The echo signal is represented in the form of an echo mathematical model, namely, formula (4), formula (5) and formula (11).

[0145] In this embodiment, generating a two-dimensional image of a ground motion scene based on an echo signal includes: compensating the echo signal for the residual video phase term and the distance term to obtain an echo signal in the range time domain-azimuth time domain, performing a range and azimuth Fourier transform on the echo signal in the range time domain-azimuth time domain to obtain a two-dimensional image of the ground motion scene.

[0146] Specifically, the echo signal of the range time domain-azimuth time domain is obtained as shown in formula (6).

[0147] In step S120, the target image of the moving target is extracted from the two-dimensional image of the ground motion scene, and an inverse Fourier transform is performed in the azimuth direction to obtain a one-dimensional range image of the moving target, which is expressed as shown in formula (7).

[0148] In step S130, quadratic phase compensation is performed based on the one-dimensional range image of the moving target, and the azimuth frequency modulation value corresponding to the optimal phase compensation is recorded. The quadratic phase term is expressed as shown in formula (13).

[0149] because, , , , the azimuth acceleration has little effect on the defocus of the target. For slow-moving targets, the azimuth Doppler frequency modulation expression is simplified as shown in formula (22).

[0150] In step S140, the moving target is subjected to azimuth Fourier transform to obtain a target image of the moving target. The time domain position (imaging position) of the target image is, as shown in formula (16).

[0151] In step S150, based on the two-dimensional image, 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.

[0152] In step S160, based on the imaging position The coordinates of the moving target In terms of the relationship between the azimuth and the image scaling coefficient, by substituting formula (21) into formula (20), we can get the following formula:

[0153] (twenty four)

[0154] In formula (24), It represents the expansion coefficient, which is the ratio of the width of the moving target in the azimuth direction, that is, the width of the shadow of the moving target and the target image in the azimuth direction. If it is known, the azimuthal velocity can be obtained by substituting its value into formula (24).

[0155] In step S170, the azimuth frequency modulation 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.

[0156] In step S180, the parameter estimation of the moving target is completed based on the range velocity, azimuth velocity and range acceleration estimated in steps S150, S160 and S170.

[0157] In this paper, the effectiveness of this method is also demonstrated through experiments. In the experiments, the technical parameters used for imaging of both simulation and measured data are shown in Table 1.

[0158] Table 1 Parameters of simulation and measured data imaging

[0159]

[0160] First, estimate the distance and speed of the moving target. Figure 3 The speed in the distance is There are 9 moving targets in the shadow area, and the range and speed of all targets are After refocusing, the image is obtained in the target area. By measuring, the azimuth frequency shift of the target image and the shadow , the distance to the target position , the slope distance is , terahertz band , according to the formula , find , which is basically the same as the setting result.

[0161] Figure 4 This is the image of the 333rd frame of data from a flight test conducted in a certain place. The test parameters are shown in Table 1, which is the beam mode. The azimuth frequency shift measurement value from the moving target to the shadow is , the distance to the target position , the slope distance is , terahertz band , according to the formula , find Select the 355th frame image, take the lower end of the prominent point as the reference, and move the moving target distance to ,time , the estimated range velocity is , there is a slight error between the two, and another method is used to prove the accuracy of this method.

[0162] Furthermore, the azimuth velocity of the moving target is estimated. Figure 5 yes As a result of refocusing the moving target, the actual position of the moving target is in the shadow area. After refocusing, the target is focused on the target area. Comparing the azimuth width of the shadow area and the target area, it can be seen that the width of the target area is narrow. The width of the target area and the shadow area is related to the ratio of the azimuth speed of the moving target to the radar flight speed. According to the measurement, the azimuth width of the shadow area is 67 frequency points (1470-1537), and the actual azimuth width of the moving target after refocusing is 11 frequency points (1284-1295). According to the formula The shrinkage ratio, , estimated azimuth velocity , which is close to the theoretical value.

[0163] Figure 4 In the measured data, the width of the shadow area and the width of the target reflect the relationship between the azimuth speed of the moving target and the radar flight speed. Through windowing measurement, the azimuth width of the target image is 1.035 times the azimuth width of the shadow (0.1071 / 0.1035). , the estimated azimuth velocity is , the azimuth speed of the moving target is very small.

[0164] Finally, the distance acceleration of the moving target is estimated. Figure 6 for The result of moving target refocusing. The shadow area represents the real position of the moving target, and the target image area represents the position of the moving target image. The shadow area and the target area have the same width in azimuth. There is no azimuth velocity, and the two-dimensional phase during refocusing comes from the range acceleration. According to the measurement, the azimuth width of the shadow is 66 frequency points (1284-1350), and the azimuth width of the target image after refocusing is 67 frequency points (1470-1537), indicating that the moving target has not expanded or contracted in azimuth. The range acceleration compensates the quadratic phase, and its azimuth frequency modulation is 2623.6 Hz / s, which is calculated by the formula ,make , calculate the distance acceleration , basically in line with expectations.

[0165] The above-mentioned shadow-based method for estimating ground moving target parameters estimates the target's range velocity by using the relative offset between the target image and its shadow in azimuth; the target's azimuth velocity is estimated by frequency broadening of the target image and its shadow in azimuth; and the target's range acceleration is estimated by compensating for the quadratic phase and using the frequency modulation of the quadratic phase. Compared with other Doppler-based motion parameter estimation methods, this method extracts relatively independent moving target parameters, unaffected by other motion parameters, resulting in a more accurate estimate. Furthermore, this method incorporates field-measured imaging methods, making it more practical.

[0166] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1 At least part of the steps 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, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0167] In one embodiment, Figure 7 As shown, a device for estimating parameters of a ground moving target based on shadow is provided, comprising: an echo mathematical model construction module 200, an echo signal acquisition module 210, a target image extraction module 220, an azimuth frequency modulation value acquisition module 230, an imaging position acquisition module 240, a range velocity estimation module 250, an azimuth velocity estimation module 260, a range acceleration estimation module 270, and a parameter estimation completion module 280, wherein:

[0168] An echo mathematical model construction module 200 is used to construct a geometric model for imaging a moving target using terahertz video SAR in a spotlight mode and an echo mathematical model for the moving target;

[0169] The echo signal acquisition module 210 is used to acquire the echo signal obtained by detecting the ground motion scene by the terahertz video radar, and to display the echo signal in the form of the echo mathematical model;

[0170] a target image extraction module 220 for obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0171] An azimuth frequency modulation value obtaining module 230 is configured to perform an azimuth inverse Fourier transform on the target image to obtain a one-dimensional range image of the moving target, perform a quadratic phase compensation on the target image based on the one-dimensional range image, and record the azimuth frequency modulation value;

[0172] An imaging position obtaining module 240 is configured to perform azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0173] a range velocity estimation module 250 for measuring, based on the two-dimensional image of the ground motion scene, an 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;

[0174] An azimuth velocity estimation module 260 is configured to measure the azimuth bandwidth 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 azimuth velocity of the moving target based on the bandwidth;

[0175] a range acceleration estimation module 270 for estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0176] The parameter estimation completion module 280 is used to complete parameter estimation of the moving target based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0177] For the specific limitations of the shadow-based ground moving target parameter estimation device, please refer to the limitations of the shadow-based ground moving target parameter estimation method above, which will not be repeated here. The various modules in the above-mentioned shadow-based ground moving target parameter estimation device can be implemented in whole or in part by software, hardware, and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0178] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. 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 via a network connection. When the computer program is executed by the processor, a method for estimating parameters of a ground moving target based on shadows is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a key, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0179] Those skilled in the art will understand that Figure 8The structure shown in the figure is only a block diagram of a part of the structure 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 shown in the figure, or combine certain components, or have a different component arrangement.

[0180] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0181] Construct a geometric model for imaging moving targets using terahertz video SAR in spotlight mode, as well as a mathematical model for the echo of moving targets;

[0182] Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model;

[0183] Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0184] Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value;

[0185] Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0186] Based on the two-dimensional image of the ground motion 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;

[0187] Based on the two-dimensional image of the ground motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth;

[0188] estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0189] The parameters of the moving target are estimated based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0190] 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:

[0191] Construct the geometric model of terahertz video SAR moving target imaging in the spotlight mode and the mathematical model of the moving target's echo;

[0192] Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model;

[0193] Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image;

[0194] Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value;

[0195] Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image;

[0196] Based on the two-dimensional image of the ground motion 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;

[0197] Based on the two-dimensional image of the ground motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth;

[0198] estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target;

[0199] The parameters of the moving target are estimated based on the range velocity, azimuth velocity and range acceleration of the moving target.

[0200] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the 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-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may 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 (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0201] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0202] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and such modifications and improvements are intended to fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for estimating parameters of ground moving targets based on shadows, characterized in that: The method comprises: Construct a geometric model for imaging moving targets using terahertz video SAR in spotlight mode, as well as a mathematical model for the echo of moving targets; Acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and display the echo signal in the form of the echo mathematical model; Obtaining a two-dimensional image of a ground motion scene according to the echo signal, and extracting a target image of a moving target from the two-dimensional image; Performing an inverse Fourier transform on the target image in azimuth 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 an azimuth frequency modulation value; Performing azimuth Fourier transform on the one-dimensional range image of the moving target to obtain an imaging position of the target image; Based on the two-dimensional image of the ground motion 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 motion scene, measuring the azimuth bandwidth of the target image relative to the shadow of the moving target, and estimating the azimuth velocity of the moving target according to the bandwidth; estimating the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target; The parameters of the moving target are estimated based on 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, characterized in that: In the geometric model, the distance from the radar to the center of the ground motion scene is expressed as: ； In the above formula, Indicates the center position of the radar carrying platform, represents the speed of the radar-carrying platform, Indicates slow time; The distance between the radar and the moving target is expressed as: ； In the above formula, represents the coordinates of the moving target, 、 、 as well as They represent the azimuth velocity, azimuth acceleration, range velocity, and range acceleration of the moving target respectively.

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

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

5. The method for estimating ground moving target parameters based on shadow according to claim 4, characterized in that: The azimuth velocity of the moving target is estimated based on the bandwidth using the following formula: ； In the above formula, Indicates the expansion factor.

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

7. A device for estimating parameters of ground moving targets based on shadows, characterized in that: The device comprises: The echo mathematical model construction module is used to construct the geometric model of terahertz video SAR moving target imaging in the spotlight mode, as well as the echo mathematical model of the moving target; an echo signal acquisition module, configured to acquire an echo signal obtained by detecting a ground motion scene using a terahertz video radar, and to 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 a ground motion scene according to the echo signal, and extract a target image of a moving target from the two-dimensional image; an azimuth frequency modulation value obtaining module, configured to perform an azimuth inverse Fourier transform on the target image to obtain a one-dimensional range image of the moving target, perform secondary phase compensation on the target image based on the one-dimensional range image, and record the azimuth frequency modulation value; An imaging position obtaining module is used to perform 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, based on the two-dimensional image of the ground motion scene, an 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; an azimuth velocity estimation module, configured to measure the azimuth bandwidth 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 azimuth velocity of the moving target according to the bandwidth; a range acceleration estimation module, configured to estimate the range acceleration of the moving target based on the azimuth frequency modulation value and the azimuth velocity of the moving target; The parameter estimation completion module 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.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: 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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