Method and system for weakly defocused sea surface moving target velocity measurement and positioning based on equivalent centroid

Abstract

The application discloses a method for measuring velocity and positioning of a weakly defocused moving target on a sea surface based on an equivalent centroid, and belongs to the technical field of radar imaging; the method comprises the following steps: SAR imaging processing, selecting signals at two continuous azimuth time points, and performing SAR imaging by using a back-projection imaging algorithm; equivalent centroid calculation, calculating equivalent centroids of two continuous SAR images according to BP imaging results; target velocity estimation, obtaining a distance-direction velocity estimation value of the target; and target initial position estimation, obtaining an azimuth-direction initial position estimation value and a distance-direction initial position estimation value of the target. The application further provides a system for measuring velocity and positioning of a weakly defocused moving target on a sea surface based on an equivalent centroid. The method provided by the application can directly solve the problem that a SAR image of a uniform-speed moving target is difficult to position due to defocusing blur without depending on other auxiliary means, and will not cause any influence on the original SAR image.

Description

Technical Field

[0001] This invention relates to the field of radar imaging technology, specifically to a method and system for measuring and locating weakly defocused moving targets on the sea surface based on equivalent centroid. Background Technology

[0002] Surface ships are crucial targets for reconnaissance, surveillance, and strategic strikes. Monitoring and analyzing the parameters of maritime targets helps in understanding tactical intelligence such as ship distribution in key sea areas, and more accurately assesses the effectiveness of strikes against maritime targets. In SAR images of moving targets, the movement of ships causes defocusing, blurring, and positional shifts in the imaging. This introduces significant errors in velocity measurement and localization of moving targets. Currently, there are two main approaches to addressing the defocusing issue caused by target motion: one is to ignore the defocusing effect on low-speed targets, but this usually results in large errors, and the defocusing problem becomes unavoidable when the target speed is too high; the other is to refocus the SAR image using autofocusing techniques, but this method destroys the target's positional information in the SAR image, adversely affecting target localization.

[0003] Research on parameter estimation for moving sea surface targets is mainly divided into velocity parameters and position parameters. The velocity parameters of moving sea surface targets primarily include azimuth velocity and radial velocity. Azimuth velocity estimation methods include those based on the Wigner-Ville distribution, those based on fractional Fourier transform, and those based on the phase gradient autofocus (PGA) algorithm. Common methods for radial velocity estimation include those based on DPCA and ATI technology; however, these methods involve complex hardware configurations and place high demands on the performance of the flight platform.

[0004] The positional parameters of moving targets on the sea surface can be divided into azimuth and range. In naval warfare, accurate positioning of ship targets without other auxiliary reference points is crucial. Geometric calibration methods without control points utilize SAR system parameters for direct image positioning, typically employing a range-Doppler (RD) positioning model. The range-Doppler (RD) positioning model has three fundamental equations: the Earth model equation, the SAR Doppler equation, and the SAR slant range equation. Currently, methods for range-Doppler positioning using SAR images are only applicable to stationary targets; existing methods for solving the RD equations are difficult to directly apply to the parameter analysis of moving ships on the sea surface. Summary of the Invention

[0005] The purpose of this invention is to provide an efficient method and system for velocity measurement and localization of weakly divergent caustic targets on the sea surface based on equivalent centroid.

[0006] To address the aforementioned technical problems, this invention provides an efficient method for velocity measurement and localization of weakly defocused caustic targets on the sea surface based on equivalent centroids, comprising the following steps:

[0007] Acquire radar echo signals of moving targets at two consecutive azimuth times;

[0008] Based on the back projection imaging algorithm, SAR imaging is performed on the radar echo signals at two consecutive azimuth times to obtain the two-dimensional complex matrices S1 and S2 after imaging.

[0009] Based on a preset threshold T, the extracted two-dimensional matrix S is obtained from the two-dimensional complex matrices S1 and S2 after imaging. a1 With S a2 ;

[0010] Based on the extracted two-dimensional matrix S a1 With S a2 The equivalent centroid P is calculated. ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 );

[0011] For the equivalent centroid P ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 Perform azimuth velocity estimation to obtain estimated values ​​of azimuth velocity components;

[0012] Doppler center frequency estimation is performed on radar echo signals at two consecutive azimuth times to obtain the estimated value of Doppler center frequency of the echo signal;

[0013] The Doppler frequency shift is calculated based on the estimated Doppler center frequency of the echo signal.

[0014] Based on the azimuth velocity component estimates and the Doppler frequency shift, the range velocity component estimates are obtained.

[0015] Based on the equivalent centroid P ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 The initial position is estimated by using the azimuth velocity component estimate and the range velocity component estimate, resulting in the initial position component estimate of the azimuth and the initial position component estimate of the range.

[0016] Preferably, according to the back projection imaging algorithm, SAR imaging is performed on the radar echo signals at two consecutive azimuth times to obtain the two-dimensional complex matrices S1 and S2 after imaging. Specifically, the following steps are included:

[0017] Based on the radar echo signals at two consecutive azimuth times, construct two-dimensional complex matrices C1 and C2;

[0018] Transforming the two-dimensional complex matrices C1 and C2 into the range frequency domain yields the two-dimensional complex matrix S in the range frequency domain. rd1 With S rd2 ;

[0019] The imaging region (Z1:Z2, X1:X2) is discretized into a two-dimensional imaging grid G;

[0020] From the two-dimensional complex matrix S in the distance frequency domain rc1 With S rc2 Extracting a one-dimensional row vector R i1 With R i2 For a one-dimensional row vector R i1 With R i2 Interpolation is performed to obtain a one-dimensional interpolated signal R. ii1 With R ii2 ;

[0021] Calculate the distance R between the radar and the current two-dimensional imaging grid G. ia With delay t id ;

[0022] Based on the time delay t id The phase compensation factor Φ at the current time is calculated. i ;

[0023] Delay t id Corresponding to the one-dimensional interpolation signal R ii1 With R ii2 In, and according to the phase compensation factor Φ i Phase compensation is performed to obtain the compensated one-dimensional vector R. c1 With R c2 ;

[0024] Until the distance frequency domain two-dimensional complex matrix S is traversed. rc1 With S rc2 All the compensated one-dimensional vectors R c1 With R c2 Coherent accumulation is performed, and the reshape function is used to adjust it into a two-dimensional signal, resulting in two-dimensional complex matrices S1 and S2 after imaging.

[0025] Preferably, based on a preset threshold T, the extracted two-dimensional matrix S is obtained from the two-dimensional complex matrices S1 and S2 after imaging. a1 With Sa2 Specifically, it includes the following steps:

[0026] Normalize and transform the signal amplitudes of the two-dimensional complex matrices S1 and S2 after imaging to obtain the two-dimensional power signal matrix S. p1 With S p2 ;

[0027] Based on a preset threshold T, from the two-dimensional power signal matrix S p1 With S p2 Obtain the extracted two-dimensional matrix S a1 With S a2 .

[0028] Preferably, the formula for calculating the equivalent centroid is:

[0029]

[0030] z ct =z max

[0031] In the formula: S a For the extracted two-dimensional matrix S a1 With S a2 , where x is the sequence of coordinate values ​​in the X-direction of the imaging grid, and z max For the extracted two-dimensional matrix S a1 With S a2 The point of maximum amplitude in the Z direction.

[0032] Preferably, the formula for calculating the estimated azimuth velocity component is:

[0033]

[0034] In the formula: v x t1 and t2 are the estimated values ​​of the azimuth velocity components; t1 and t2 are the azimuth time points.

[0035] Preferably, the Doppler center frequency of the radar echo signal is estimated from two consecutive azimuth time points to obtain an estimated value of the Doppler center frequency of the echo signal. This specifically includes the following steps:

[0036] The two-dimensional complex matrix S in the distance frequency domain rc1 Perform an azimuth-to-Fourier transform to obtain the transformed two-dimensional complex matrix S. rd1 ;

[0037] The transformed two-dimensional complex matrix S rd1 Superimposing along the distance direction yields a one-dimensional matrix S. d1 ;

[0038] Obtain the one-dimensional matrix S d1 Maximum amplitude P max1Set the amplitude threshold to P max1 / 2; Transform the one-dimensional matrix S d1 The portion of the magnitude value above the amplitude threshold is set to 1, and the portion below the amplitude threshold is set to 0, resulting in a 0-1 sequence G;

[0039] Calculate the sum of the magnitudes E on both sides of the position i in sequence G. i1 With E i2 ;

[0040] Based on the sum of the amplitudes on both sides of the position E i1 With E i2 The energy difference ΔE is calculated.

[0041] Based on the energy difference ΔE and the preset error range threshold, the estimated value of the Doppler center frequency of the echo signal is obtained.

[0042] Preferably, the formula for calculating the Doppler frequency shift is:

[0043] f dp =f dc -f d0

[0044] In the formula: f dc f is an estimated value of the Doppler center frequency of the echo signal; d0 To obtain the Doppler frequency generated by radar motion based on radar system parameters.

[0045] Preferably, the formula for calculating the estimated value of the range velocity component is:

[0046]

[0047] In the formula: V z λ represents the estimated value of the velocity component in the range direction; λ is a coefficient.

[0048] Preferably, the formula for calculating the estimated value of the initial position component of the azimuth is:

[0049]

[0050] Where x0 is the estimated value of the initial position component in the azimuth direction; a, b, c, and K are all coefficients; b = -2V m (V m -v x (x) ct1 -Kt1),

[0051] The formula for calculating the estimated value of the initial position component in the range direction is:

[0052]

[0053] In the formula: z0 is the estimated value of the initial position component in the range direction.

[0054] This invention also provides a system for velocity measurement and positioning of weakly deflecting foveated targets on the sea surface based on an equivalent center of mass, comprising:

[0055] The acquisition module is used to acquire radar echo signals of two consecutive azimuth times of a moving target;

[0056] The projection imaging module is used to perform SAR imaging on radar echo signals at two consecutive azimuth times according to the back projection imaging algorithm, and obtain two-dimensional complex matrices S1 and S2 after imaging.

[0057] The extraction module is used to obtain the extracted two-dimensional matrix S from the two-dimensional complex matrices S1 and S2 after imaging, based on a preset threshold T. a1 With S a2 ;

[0058] The equivalent centroid calculation module is used to calculate the equivalent centroid based on the extracted two-dimensional matrix S. a1 With S a2 The equivalent centroid P is calculated. ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 );

[0059] The azimuth velocity estimation module is used to estimate the equivalent centroid P. ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 Perform azimuth velocity estimation to obtain estimated values ​​of azimuth velocity components;

[0060] The Doppler center frequency estimation module is used to estimate the Doppler center frequency of radar echo signals at two consecutive azimuth times, and obtain the estimated value of the Doppler center frequency of the echo signal.

[0061] The Doppler frequency shift calculation module is used to calculate the Doppler frequency shift based on the estimated value of the Doppler center frequency of the echo signal.

[0062] The range velocity component estimation module is used to obtain the range velocity component estimate based on the azimuth velocity component estimate and the Doppler frequency shift.

[0063] The initial position estimation module is used to estimate the position based on the equivalent centroid P. ct1 (z ct1 x ct1 ) and P ct2 (zct2 x ct2 The initial position is estimated by using the azimuth velocity component estimate and the range velocity component estimate, resulting in the initial position component estimate of the azimuth and the initial position component estimate of the range.

[0064] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0065] (1) The method provided by the present invention can directly solve the problem of difficult positioning of SAR images of uniformly moving targets with defocus and blur without relying on other auxiliary means, and will not have any impact on the original SAR image;

[0066] (2) The method provided by the present invention has low performance requirements for the flight platform, does not require artificial auxiliary points to measure the speed and position of moving targets on the sea surface, and the parameter estimation results are relatively accurate. Attached Figure Description

[0067] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0068] Figure 1 This is a flowchart of the steps of the method for measuring and locating weakly defocused caustic targets on the sea surface based on the equivalent centroid of the present invention.

[0069] Figure 2 This is a schematic diagram of the back projection imaging algorithm.

[0070] Figure 3 This is a schematic diagram of two consecutive azimuth time signals after distance compression;

[0071] Figure 4 This is a schematic diagram of SAR imaging of a moving target at two consecutive azimuth times.

[0072] Figure 5 This is a schematic diagram of the superposition of range-Doppler signals along the range direction;

[0073] Figure 6 This is a schematic diagram of the output results of the energy equalizer. Detailed Implementation

[0074] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0075] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0076] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0077] The present invention will now be described in further detail with reference to the accompanying drawings:

[0078] To address the problem of velocity measurement and localization of weakly defocused moving targets on the sea surface, this invention analyzes the defocusing and blurring characteristics of moving targets and proposes a method to map the imaging position to the equivalent centroid position. To further obtain the target's velocity and position parameters, continuous SAR imaging in the azimuth direction is performed. By obtaining the target's equivalent centroid position, multiple range-Doppler equations are established and solved. Then, combined with the target's Doppler offset, the target's velocity and position parameters are estimated, thus realizing a method for velocity measurement and localization of weakly defocused targets.

[0079] The method for measuring and locating weakly divergent caustic targets on the sea surface based on equivalent centroids of the present invention is implemented through the following steps:

[0080] (1) SAR imaging processing: Input the echo signal of the moving target, select the signals of two consecutive azimuth time points, and use the back projection (BP) imaging algorithm to perform SAR imaging respectively.

[0081] (2) Equivalent centroid calculation: Calculate the equivalent centroid of two consecutive SAR images based on the BP imaging results. The azimuth centroid coordinates are taken as the centroid coordinates of the azimuth expansion, and the range centroid coordinates are taken as the point with the maximum range amplitude. Replace the two azimuth imaging positions of the target with the equivalent centroid positions;

[0082] (3) Target velocity estimation: Two sets of range-Doppler equations are established by two sets of equivalent centroid positions. The equations are simplified to obtain the target azimuth velocity estimate and the relationship expression between velocity and initial position. The Doppler center frequency of the echo signal is estimated, and the Doppler frequency offset of the target is obtained according to the SAR system parameters, thereby obtaining the target range velocity estimate.

[0083] (4) Target initial position estimation: Substitute the estimated values ​​of azimuth velocity and range velocity obtained in step (3) into the relationship expression between velocity and initial position to obtain the estimated values ​​of the target's initial azimuth position and range position.

[0084] To determine whether a target is in a state of weak defocus, this invention uses the ratio of target velocity to radar velocity as a metric. When the ratio is less than a threshold of 0.1, the target is considered to be in a state of weak defocus.

[0085] The method for velocity measurement and localization of weakly divergent caustic targets on the sea surface based on equivalent centroid provided by this invention is specifically implemented through the following steps, the process of which is as follows: Figure 1 As shown.

[0086] Step 1: SAR Imaging Processing: Input the radar echo signal of the moving target, select radar echo signals from two consecutive azimuth time points, and perform SAR imaging using the back projection imaging algorithm. The back projection imaging algorithm flow is as follows: Figure 2 As shown.

[0087] (a) Select two consecutive two-dimensional echo signals at two consecutive azimuth times to obtain two two-dimensional complex matrices C1 and C2, with a matrix size of M. a ×N r ;

[0088] (b) Transform the two two-dimensional complex matrices C1 and C2 to the range frequency domain using MATLAB's fft function to obtain the range frequency domain two-dimensional complex matrix S. rd1 With S rd2 Multiplying the distance-frequency domain signal by the frequency-domain matched filter yields the frequency-domain matched filter.

[0089]

[0090] Then, by transforming back to the time domain using the IFT function, we obtain the two-dimensional complex matrix S after range-directed matched filtering. rc1 With S rc2 ;

[0091] (c) Discretize the imaging region (Z1:Z2, X1:X2) into a two-dimensional imaging grid G, the size of which is M. g ×N g ;

[0092] (d) Extract the two-dimensional complex matrix S in the distance frequency domain rc1 With S rc2 A one-dimensional row vector R with row index i i1 With R i2 The number of points is N r Use the interpft function to process vector R. i1 With R i2 Interpolation is performed with an interpolation factor of N1, resulting in N1N points. r One-dimensional interpolation signal R ii1 With R ii2 ;like Figure 3 As shown;

[0093] (e) Calculate the distance R between the radar and the current two-dimensional imaging grid G. ia With delay t id =2R ia / c, where c is the speed of light;

[0094] (f) Calculate the phase compensation factor Φ at the current time. i ,Right now

[0095] Φ i =exp[jπf0t id (2)

[0096] In the formula: exp is the exponent, j is the imaginary unit, and f0 is the carrier frequency.

[0097] (g) Delay t id Corresponding to the one-dimensional interpolation signal R ii1 With R ii2 In the middle, R ii1 With R ii2 Multiply by Φ respectively i Phase compensation is performed to obtain the compensated one-dimensional vector R. c1 With R c2 ;

[0098] (h) Update the row number index i to i+1, and repeat steps (d) to (g) to traverse all M. a At each azimuth time point, all compensated signals are coherently accumulated. The reshape function is then used to adjust the accumulated signal to a dimension of M. g ×N g The two-dimensional signal is used to obtain the two-dimensional complex matrices S1 and S2 after imaging. For example... Figure 4 As shown.

[0099] Step 2: Calculate the equivalent centroid: Find the point with the maximum amplitude in the two-dimensional complex matrices S1 and S2 after imaging, determine the left and right boundary points with a signal amplitude of T, extract the part of the two-dimensional complex matrices S1 and S2 after imaging with a signal amplitude greater than T, and calculate the centroid position of the signal segment respectively.

[0100] (a) Normalize the signal amplitudes of the two-dimensional complex matrices S1 and S2 after imaging and convert them into a two-dimensional power signal matrix S in dB. p1 With S p2 ;

[0101] (b) Find the two-dimensional power signal matrix S using the max function. p1 With S p2 The point of maximum power, i.e., the point where the peak value is 0dB, is marked as (i max1， j max1 ) and (i max2 j max2 Extract j max1 With j max2 The signals in the column, respectively from i max1 with i max2 Search to the left, record the first point where the power value is less than the threshold T, and mark the corresponding point as i. l1 with i l2 Then from i respectively max1 with i max2 Search to the right and record the first point where the power value is less than the threshold T, with the corresponding subscript i. r1 with i r2 ;

[0102] (c) Extracting the two-dimensional power signal matrix S p1 With S p2 The middle intervals are respectively in [i l1 :i r1 ] and [i l2 :i r2 The signal in ] is denoted as S a1 With S a2 The matrix has dimension M. s ×N g The equivalent centroid positions of the two SAR signals are calculated using formulas (3) and (4):

[0103]

[0104] z ct =z max (4)

[0105] Where S a The extracted two-dimensional matrix is ​​given by x, which is the sequence of coordinate values ​​in the X-direction of the imaging grid, and z. max For Sa The point where the magnitude of the matrix is ​​maximum in the Z direction. The equivalent centroid points P at azimuth equivalent centroid times t1 and t2 are obtained by calculating formulas (3) and (4). ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 ).

[0106] Step 3: Estimate target velocity: Based on the equivalent centroid positions at two azimuth times, first estimate the azimuth velocity component, then estimate the Doppler center frequency of the echo signal, and thus obtain the target's Doppler frequency shift. Combine the estimated azimuth velocity component with the target's Doppler frequency shift to estimate the target's range velocity component.

[0107] (a) The equivalent centroid P of the azimuth time t1 and azimuth time t2 obtained in step two ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 Substituting the position of the target into formula (5), we obtain the estimated value of the azimuth velocity component of the target in the X direction:

[0108]

[0109] (b) The two-dimensional complex matrix S in the distance frequency domain from step one rc1 The FFT function is used to perform an azimuth-to-Fourier transform, converting the signal to the range-Doppler domain, resulting in the transformed two-dimensional complex matrix S. rd1 ;

[0110] (c) Transform the two-dimensional complex matrix S rd1 Superimposing along the distance direction yields a length of M. a A one-dimensional matrix S of points d1 ;like Figure 5 As shown;

[0111] (d) Transform the one-dimensional matrix S d1 Use the abs function to obtain the modulus value and the max function to find its maximum amplitude P. max1 Set the amplitude threshold to P max1 / 2. Transform the one-dimensional matrix S d1 The portion of the magnitude value above the amplitude threshold is set to 1, and the portion below the amplitude threshold is set to 0, resulting in a length of M. a The 0-1 sequence G of points;

[0112] (e) Calculate the sum of the magnitudes on both sides of the position at index i for sequence G, i.e., E i1 and Ei2 The value;

[0113] (f) Determine the energy difference between the two sides at this time: ΔE = E i1 -E i2 Check if the error range is met. If not, update the index i to i+1 and continue iterating to step (e); if the condition is met, output the Doppler frequency f corresponding to the current index i. dc That is, the estimated value of the Doppler center frequency of the echo signal;

[0114] (g) Obtain the Doppler frequency f generated by radar motion based on radar system parameters. d0 Thus, the Doppler frequency shift f of the target is obtained. dp =f dc -f d0 ;

[0115] (h) The azimuth velocity component v of the echo signal x The estimated value and the target's Doppler frequency shift f dp Substituting the estimated value into formula (6), we obtain the range velocity component v of the target. z Estimated value:

[0116]

[0117] In the formula, λ represents the coefficient; θ L Represents the radar elevation angle, which is the angle between the line of sight and the altitude direction when the radar is looking at the side.

[0118] Step 4: Estimate the initial position of the target: Substitute the equivalent centroid position of the target obtained from imaging in Step 2 and the estimated values ​​of the range velocity component and azimuth velocity component obtained in Step 3 into the formula for estimating the initial position of the target to obtain the estimated values ​​of the initial position of the target in the azimuth and range directions.

[0119] (a) Converting the distance component to the velocity component v z With azimuth velocity component v x The estimated values ​​and the two sets of equivalent centroid positions P ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 Substituting into formula (7), we obtain the estimated value of the initial position component x0 in the azimuth direction:

[0120]

[0121] Where a, b, c, and K are all coefficients; b = -2V m (V m -vx (x) ct1 -Kt1), V m The speed of the radar.

[0122] (b) Transform the range to velocity component v z With azimuth velocity component v x The estimated values ​​and the two sets of equivalent centroid positions P ct1 (z ct1 x ct1 ) and P ct2 (z ct2 x ct2 Substituting into formula (8), we obtain the estimated value of the initial position component z0 in the range direction:

[0123]

[0124] in,

[0125] Implementation Case 1: Velocity and location measurement of a sea surface moving target with an initial position of (200, 0, 10000) m and a velocity of (6, 0, 3) m / s. The SAR flight altitude is set to 10000 m, the flight direction is due north, and the flight speed is 1000 m / s. The radar images the target twice, with each imaging time being 0.8 s and a time interval of 1 s. The radar system uses spotlight imaging mode. The main simulation parameters are shown in Table 1.

[0126] Table 1 Simulation parameters for continuous SAR imaging of moving targets

[0127]

[0128] The specific method for measuring and locating the velocity of a moving target is implemented through the following steps:

[0129] Step 1: SAR Imaging Processing

[0130] (a) Input two consecutive two-dimensional echo signals at two consecutive azimuth times to obtain two two-dimensional complex matrices C1 and C2 with a dimension of 1600×3601;

[0131] (b) Transform C1 and C2 to the range frequency domain using MATLAB's fft function to obtain the two-dimensional complex signal S in the range frequency domain. rd1 With S rd2 Multiplying the range-frequency domain signal by a frequency-domain matched filter, and then transforming it back to the time domain using the IFT function, yields the range-direction matched-filtered two-dimensional complex matrix S. rc1 With S rc2 ;

[0132] (c) Discretize the imaging region (9900m:10100m, 100m:300m) into a two-dimensional imaging grid G ​​with a dimension of 2001×2001;

[0133] (d) Extracting the two-dimensional complex matrix S rc1 With S rc2 A one-dimensional row vector R with row index i i1 With R i2 The number of points is 3601. Use the interpft function to process the one-dimensional data R. i1 With R i2 Interpolation is performed with an interpolation factor of 10, resulting in a one-dimensional interpolated signal R with 36010 points. ii1 With R ii2 ;

[0134] (e) Calculate the distance R between the radar and the imaging grid at the current azimuth time. ia With delay t id =2R ia / c, where c is the speed of light;

[0135] (f) Calculate the phase compensation factor Φ at the current azimuth time. i ;

[0136] (g) Delay t id Corresponding to the interpolated echo data R ii1 With R ii2 In the middle, R ii1 With R ii2 Multiply by Φ respectively i Phase compensation is performed to obtain the compensated one-dimensional signal R. c1 With R c2 ;

[0137] (h) Update the row number index i to i+1, and repeat steps (d) to (h). g The algorithm iterates through all 1600 azimuth time points and coherently accumulates all compensated signals. The reshape function is then used to reshape the accumulated signals into two-dimensional signals of dimension 2001×2001, resulting in two-dimensional complex matrices S1 and S2 after imaging.

[0138] Step 2: Calculate the equivalent centroid

[0139] (a) Normalize the signal amplitudes of the two-dimensional complex matrices S1 and S2 and convert them into a two-dimensional power signal matrix S in dB. p1 With S p2 ;

[0140] (b) Use the max function to find the two-dimensional matrix S p1 With S p2The maximum power point, i.e., the point with a peak value of 0dB, corresponds to the indices (148, 1007) and (172, 1015) of the two-dimensional power signal matrix. Extract the signals from columns 1007 and 1015, and search leftwards from points 148 and 172 respectively, recording the first point where the power value is less than -9dB, with indices 138 and 158. Then search rightwards from points 148 and 172 respectively, recording the first point where the power value is less than -9dB, with indices 162 and 182.

[0141] (c) Extracting the two-dimensional matrix S p1 With S p2 The signals whose subscripts in the intervals [138:162] and [158:182] are respectively denoted as S. a1 With S a2 Calculate S according to formulas (3) and (4). a1 With S a2 The equivalent centroid position is obtained, and the equivalent centroid P at time t1 = 0.4s is obtained. ct1 P is at time t2 = 1.4s, with a mass of (10000.60, 173.53)m and an equivalent centroid of t2 = 1.4s. ct2 The value is (10000.40, 185.48)m.

[0142] Step 3: Estimate the target speed

[0143] (a) The equivalent centroid P of the azimuth time t1 = 0.4s and the azimuth time t2 = 1.4s obtained in step two. ct1 (10000.60,173.53)m and P ct2 Substituting the position (10000.40,185.48)m into formula (5), we obtain the azimuth velocity component v of the target in the X direction. x The estimated value is 5.97 m / s;

[0144] (b) The two-dimensional complex matrix S obtained from the distance-directed matched filtering in step one... rc1 With S rc2 Using the FFT function to perform an azimuth-to-Fourier transform, the signal is converted to the range-Doppler domain, yielding a two-dimensional complex matrix S. rd1 With S rd2 ;

[0145] (c) Transform the two-dimensional complex matrix s rd1 Superimposing along the distance direction yields a one-dimensional matrix S with a length of 1600 points. d1 ;

[0146] (d) Transform the one-dimensional matrix S d1The modulus value is obtained using the abs function, and the maximum amplitude is found to be 1.00e6 using the max function. A threshold of 5.01e5 is set. The one-dimensional matrix S... d1 The portion of the modulus value above the threshold is set to 1, and the portion below the threshold is set to 0, resulting in a 0-1 sequence G with a length of 1600 points;

[0147] (e) Calculate the sum of the magnitudes on both sides of the position at index i for sequence G, i.e., E i1 and E i2 The value;

[0148] (f) Determine the energy difference between the two sides at this time: ΔE = E i1 -E i2 Check if the error range is met. If not, update the index i to i+1 and continue iterating to step (e); if the condition is met, output the Doppler frequency f corresponding to the current index i. dc The output of the energy equalizer is as follows: Figure 6 As shown, the Doppler center frequency f is obtained. dc The estimated value is 106.94 Hz;

[0149] (g) Obtain the Doppler frequency f generated by radar motion based on radar system parameters. d0 The frequency is 94.49 Hz, thus the Doppler frequency shift f of the target is obtained. dp The frequency is 12.45 Hz.

[0150] (h) The azimuth velocity component v of the echo signal x The estimated value of 5.97 m / s and the target's Doppler frequency shift f dp Substituting the estimated value of 12.45Hz into formula (6), we obtain the range velocity component v of the target. z The estimated value is 2.81 m / s.

[0151] Step 4: Estimate the initial position of the target

[0152] (a) Converting the distance component to the velocity component v z The estimated value of 2.81 m / s and the azimuth velocity component v x The estimated value is 5.97 m / s and the two sets of equivalent centroid positions P ct1 (10000.60,173.53)m and P ct2 Substituting (10000.40,185.48)m into formula (7), we get the value of variable a as 9.88e5, the value of variable b as -3.35e8, the value of variable c as 2.77e10, and the value of variable K as 11.95. Thus, we get the estimated value of the initial position component x0 of the azimuth direction as 198.03m.

[0153] (b) Transform the range to velocity component vz Estimated value: 2.81 m / s, azimuth velocity component v x The estimated value is 5.97 m / s, and the equivalent centroid positions P of the two sets are... ct1 (10000.60,173.53)m and P ct2 Substituting (10000.40,185.48)m and the estimated value of the initial position component x0 in the azimuth direction, 198.03m, into formula (8), we obtain the estimated value of the initial position component z0 in the range direction, which is 9999.91m.

[0154] This invention addresses the defocusing blurring caused by the motion of sea surface targets in SAR images. It proposes a method that uses an equivalent centroid to replace the unclear imaging position. By performing continuous imaging at different azimuth times, multiple range-Doppler equations are established and solved using the equivalent centroid position of the target. Combined with the Doppler frequency shift of the target, a method for measuring the velocity and locating weakly defocused moving targets on the sea surface is realized. The implementation process of this method is further described in detail through case analysis.

[0155] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules, units, or units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units, modules, or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0156] The units may or may not be physically separate. The components shown as units can be one or more physical units, meaning they can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0157] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0158] In particular, according to embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), it performs the functions defined in the methods of this invention. It should be noted that the computer-readable medium described above in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.

[0159] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0160] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for velocity measurement and localization of weakly defocused targets on the sea surface based on equivalent centroids, characterized in that, Includes the following steps: Acquire radar echo signals of moving targets at two consecutive azimuth times; Based on the radar echo signals from two consecutive azimuth time points, construct a two-dimensional complex matrix. and ; Two-dimensional complex matrix and Transforming to the range frequency domain yields a two-dimensional complex matrix in the range frequency domain. and ; The imaging area ( Discretize into a two-dimensional imaging grid G; From the two-dimensional complex matrix in the distance frequency domain and Extracting one-dimensional row vectors and For a one-dimensional row vector and Interpolation is performed to obtain a one-dimensional interpolated signal. and ; Calculate the distance between the radar and the current two-dimensional imaging grid G. With delay ; According to the delay The phase compensation factor at the current moment is calculated. ; Delay Corresponding to one-dimensional interpolation signal and In, and according to the phase compensation factor Phase compensation is performed to obtain a compensated one-dimensional vector. and ; Until the distance frequency domain two-dimensional complex matrix is ​​traversed. and All compensated one-dimensional vectors and Coherent accumulation is performed, and the signal is reshaped using the reshape function to obtain a two-dimensional complex matrix after imaging. and ; Based on a preset threshold T, from the imaged two-dimensional complex matrix and The extracted two-dimensional matrix is ​​obtained from the process. and ; Based on the extracted two-dimensional matrix and The equivalent centroid point is calculated. and ; For equivalent centroid and Azimuth velocity estimation is performed to obtain estimated values ​​of azimuth velocity components; Doppler center frequency estimation is performed on radar echo signals at two consecutive azimuth times to obtain the estimated value of Doppler center frequency of the echo signal; The Doppler frequency shift is calculated based on the estimated Doppler center frequency of the echo signal. Based on the azimuth velocity component estimates and the Doppler frequency shift, the range velocity component estimates are obtained. Based on the equivalent centroid and The initial position is estimated by using the azimuth velocity component estimate and the range velocity component estimate, resulting in the initial position component estimate of the azimuth and the initial position component estimate of the range.

2. The method for velocity measurement and positioning of weakly defocused caustic targets on the sea surface based on equivalent centroid according to claim 1, characterized in that, Based on a preset threshold T, from the imaged two-dimensional complex matrix and The extracted two-dimensional matrix is ​​obtained from the process. and Specifically, it includes the following steps: For the two-dimensional complex matrix after imaging and The signal amplitude is normalized and transformed to obtain a two-dimensional power signal matrix. and ; Based on a preset threshold T, from the two-dimensional power signal matrix and Obtain the extracted two-dimensional matrix and .

3. The method for velocity measurement and positioning of weakly defocused targets on the sea surface based on equivalent centroid according to claim 2, characterized in that: The formula for calculating the equivalent centroid is: In the formula: For the extracted two-dimensional matrix and , This is a sequence of coordinate values ​​in the X direction within the imaging grid. For the extracted two-dimensional matrix and The point of maximum amplitude in the Z direction.

4. The method for velocity measurement and positioning of weakly defocused caustic targets on the sea surface based on equivalent centroid according to claim 3, characterized in that: The formula for calculating the estimated azimuth velocity component is as follows: In the formula: These are estimates of the azimuth velocity components; and This indicates the location and time.

5. The method for velocity measurement and positioning of weakly defocused targets on the sea surface based on equivalent centroid according to claim 4, characterized in that, The Doppler center frequency of the radar echo signal is estimated from two consecutive azimuth time points. The estimated value of the Doppler center frequency of the echo signal is obtained by performing the following steps: The two-dimensional complex matrix in the frequency domain of the distance Perform an azimuth-to-Fourier transform to obtain the transformed two-dimensional complex matrix. ; Transformed two-dimensional complex matrix Superimposing along the distance direction yields a one-dimensional matrix. ; Obtain a one-dimensional matrix Maximum amplitude Set the amplitude threshold to ; one-dimensional matrix The portion of the magnitude value above the amplitude threshold is set to 1, and the portion below the amplitude threshold is set to 0, resulting in a 0-1 sequence. ; Calculate sequence Calculation at index The sum of the amplitudes on both sides of the point's position and ; Based on the sum of the amplitudes on both sides of the position and The energy difference was calculated. ; Based on energy difference By using the preset error range threshold, the estimated value of the Doppler center frequency of the echo signal is obtained.

6. The method for velocity measurement and positioning of weakly defocused targets on the sea surface based on equivalent centroid according to claim 5, characterized in that: The formula for calculating the Doppler frequency shift is: In the formula: This is an estimated value for the Doppler center frequency of the echo signal; To obtain the Doppler frequency generated by radar motion based on radar system parameters.

7. The method for velocity measurement and positioning of weakly defocused targets on the sea surface based on equivalent centroid as described in claim 6, characterized in that: The formula for calculating the estimated value of the range velocity component is as follows: In the formula: V Z This is an estimate of the range velocity component; For coefficients, This represents the radar elevation angle.

8. The method for velocity measurement and positioning of weakly defocused targets on the sea surface based on equivalent centroid according to claim 1, characterized in that, The formula for calculating the estimated initial position component of the azimuth direction is: in, These are the estimated values ​​of the initial position components of the azimuth direction; a, b, c, and K are all coefficients; , , , ; The speed of the radar; The formula for calculating the estimated value of the initial position component in the range direction is: In the formula: This is the estimated value of the initial position component in the range direction.

9. A system for velocity measurement and positioning of weakly divergent foveated targets on the sea surface based on an equivalent center of mass, used to implement the method for velocity measurement and positioning of weakly divergent foveated targets on the sea surface based on an equivalent center of mass as described in any one of claims 1-8, characterized in that, include: The acquisition module is used to acquire radar echo signals of two consecutive azimuth times of a moving target; The projection imaging module is used to perform SAR imaging on radar echo signals at two consecutive azimuth times according to the back projection imaging algorithm, and obtain the two-dimensional complex matrix after imaging. and ; The extraction module is used to extract data from the imaged two-dimensional complex matrix based on a preset threshold T. and The extracted two-dimensional matrix is ​​obtained from the process. and ; The equivalent centroid calculation module is used to calculate the equivalent centroid based on the extracted two-dimensional matrix. and The equivalent centroid point is calculated. and ; The azimuth velocity estimation module is used to estimate the equivalent centroid. and Azimuth velocity estimation is performed to obtain estimated values ​​of azimuth velocity components; The Doppler center frequency estimation module is used to estimate the Doppler center frequency of radar echo signals at two consecutive azimuth times, and obtain the estimated value of the Doppler center frequency of the echo signal. The Doppler frequency shift calculation module is used to calculate the Doppler frequency shift based on the estimated value of the Doppler center frequency of the echo signal. The range velocity component estimation module is used to obtain the range velocity component estimate based on the azimuth velocity component estimate and the Doppler frequency shift. The initial position estimation module is used to estimate the position based on the equivalent centroid. and The initial position is estimated by using the azimuth velocity component estimate and the range velocity component estimate, resulting in the initial position component estimate of the azimuth and the initial position component estimate of the range.

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