A bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation

Abstract

A bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation belongs to the field of radar signal processing and radar imaging technology. The present invention solves the problems of poor anti-noise performance, difficulty in finding associated scattering points, and failure to eliminate azimuth defocusing effects in existing methods. The present invention uses bistatic ISAR echo phase coefficients to construct an equation group, obtains the ratio of the first-order coefficient to the constant coefficient of the bistatic coefficient and the estimated value of the effective rotational angular velocity by solving the equation group, and then estimates the constant coefficient of the bistatic coefficient using the receiver beam center direction and target distance information; constructs a compensation phase based on the estimated value to effectively compensate for image distortion and range defocusing, thereby achieving calibration of the inverse synthetic aperture radar image. The method of the present invention can be applied to bistatic inverse synthetic aperture radar imaging and calibration.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar signal processing and radar imaging, and in particular relates to a bistatic inverse synthetic aperture radar (ISAR) imaging and calibration method based on motion parameter estimation. Background Art

[0002] Due to its all-day, all-weather, long-range monitoring, and two-dimensional high-resolution imaging capabilities, inverse synthetic aperture radar (ISAR) has been widely used for target recognition and classification over the past few decades. Most research has focused on monostatic ISAR. However, when a target moves along the radar's line of sight (LOS), a monostatic ISAR cannot obtain a two-dimensional image of the target, a phenomenon known as the monostatic ISAR blind spot. Bistatic ISAR, by separating the transmitter and receiver, effectively overcomes this blind spot. It also offers advantages such as stealth, anti-interference, long detection range, and the ability to obtain richer target scattering characteristics. Consequently, bistatic ISAR has garnered increasing attention in recent years.

[0003] The primary task of a bistatic inverse synthetic aperture radar (ISAR) is to acquire high-quality, high-precision calibrated images. The main process consists of two stages: imaging and calibration. During the imaging process, image distortion and defocusing may occur due to the influence of the time-varying bistatic coefficient. Once the bistatic coefficient is estimated, these negative effects can be eliminated. The goal of the calibration process is to extract target size information and improve target recognition and classification accuracy. In a bistatic ISAR, the range and lateral scaling factors depend not only on the bandwidth of the transmitted signal and the effective rotational velocity of the target, but also on the bistatic coefficient. Therefore, the core of bistatic ISAR imaging and calibration lies in estimating the bistatic coefficient and the effective rotational velocity.

[0004] Kang MS et al. proposed a bistatic inverse synthetic aperture radar imaging and calibration algorithm based on tracking information in the paper "Bistatic-ISAR Cross-Range Scaling" (IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 4, pp. 1962-1973, August 2017). This algorithm uses the trajectory of a moving target acquired by a tracking device to estimate the bistatic coefficients and then estimates the effective angular velocity by calculating the phase coefficients of selected prominent points. However, this method is not feasible without a tracking device.

[0005] Later, Kang MS et al. proposed a tracking-free bistatic inverse synthetic aperture radar distortion correction and calibration algorithm in the paper "Bistatic-ISAR Distortion Correction and Range and Cross-Range Scaling" (IEEE Sensors Journal, vol. 17, no. 16, pp. 5068-5078, August 15, 2017). This algorithm predicts the phase coefficients of the extracted scatterers by performing phase unwrapping and least-squares fitting. Then, a particle swarm optimization algorithm is applied to maximize the established cost function to estimate the effective angular velocity and bistatic coefficients. However, this algorithm suffers from poor noise immunity.

[0006] In the paper "Bistatic ISAR distortion and defocusing analysis" (IEEE Transactions on Aerospace and Electronic Systems, vol. 52, no. 3, pp. 1168-1182, June 2016), Sun Sibo et al. proposed an algorithm for image distortion reduction based on scattering point correlation. This method requires finding correlated scattering points in bistatic and monostatic ISAR images. However, since bistatic and monostatic ISAR images are typically projected on different planes, finding correlated scattering points in the two images is difficult. Furthermore, none of the aforementioned methods consider eliminating the effect of azimuthal defocusing.

[0007] In summary, existing methods for estimating bistatic coefficients and effective angular velocity without tracking equipment have problems such as poor noise immunity, difficulty in finding associated scattering points, and failure to eliminate the azimuth defocus effect. Summary of the Invention

[0008] The purpose of the present invention is to solve the problems of poor noise resistance, difficulty in finding associated scattering points and failure to eliminate azimuth defocus effect in existing methods, and to propose a bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation.

[0009] The technical solution adopted by the present invention to solve the above technical problems is: a bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation, the method specifically comprising the following steps:

[0010] Step 1: The bistatic inverse synthetic aperture radar obtains echo data reflected by scattering points on the uniformly rotating target, and then performs range compression and motion compensation on the echo data to obtain echo data reflected by each scattering point on the uniformly rotating target after range compression and motion compensation;

[0011] Step 2: Based on the range-compressed and motion-compensated echo data reflected from each scattering point on the uniformly rotating target, obtain an estimate of the ratio of the first-order coefficient to the constant coefficient in the bistatic coefficient. and an estimate of the square of the effective angular velocity

[0012] Step 3: Calculate the bistatic angle at the initial moment, and then estimate the constant coefficient K0 in the bistatic coefficient based on the bistatic angle at the initial moment;

[0013] Step 4: Based on the estimated value and Construct the phase compensation term s of the i-th distance unit com,i , then multiply the phase compensation term of the i-th range unit by the echo data after range compression and motion compensation corresponding to the i-th range unit to obtain the echo data of the i-th range unit after phase compensation;

[0014] Step 5: compress the echo data of all range units after phase compensation in Step 4 in azimuth direction to obtain echo data after azimuth compression;

[0015] Step 6: Obtain a scattering point echo map based on the echo data compressed in azimuth direction;

[0016] Step 7: Obtain the target azimuth dimension y based on the scattering point echo map obtained in step 6 max , and then according to the constant coefficient K0 and the estimated value Calculate K1 and determine the target orientation size y max Is it satisfied Among them, κ w is the widening factor of the window function;

[0017] If it is not satisfied, the scattering point echo image is post-compensated and the post-compensated image is used as the inverse synthetic aperture radar calibration image;

[0018] If it is satisfied, the scattering point echo image obtained in step 6 is the inverse synthetic aperture radar calibration image.

[0019] Furthermore, the echo data after range compression and motion compensation processing reflected by each scattering point on the uniformly rotating target is specifically:

[0020]

[0021] Where σ is the bistatic scattering coefficient of the scattering point, B is the signal bandwidth, and T obs is the observation duration, rect(·) is the rectangular window function, sinc(·) is the Sigmoid function, j is the imaginary unit, λ is the carrier wavelength, t is the slow time, τ is the fast time delay variable, c is the speed of light, and f c is the center frequency, ξ, α, β and γ are the phase coefficients;

[0022]

[0023] Where K0 and K1 are the constant coefficient and first-order coefficient in the bistatic coefficient, (x, y) are the coordinates of the scattering point relative to the rotation center, and Ω eff is the effective angular velocity.

[0024] Furthermore, the specific process of step 2 is as follows:

[0025] Step 21: selecting a range unit based on the minimum normalized amplitude variance criterion and the processed echo data reflected from each scattering point;

[0026] Step 2: Determine the scattering point with the largest echo energy in each selected distance unit, and then use the polynomial phase estimation method to estimate the phase coefficient corresponding to each determined scattering point. The phase coefficient corresponding to the scattering point with the largest echo energy in the kth distance unit is recorded as ξ k ,α k ,β k ,γ k , k=1,2,…,K;

[0027] Step 23: Use the phase coefficients estimated in step 22 to construct the equation system:

[0028]

[0029] Among them, x k '=K0x k ,y k '=K0y k ,(x k ,y k ) is the coordinate value of the scattering point with the largest echo energy in the k-th range unit;

[0030] Step 24: Convert the equations of formula (3) into the following form:

[0031]

[0032] make but:

[0033]

[0034] Step 25: Substitute any set of phase coefficients obtained in step 22 into equation (5), and then solve equation (5) to obtain the three roots corresponding to the set of phase coefficients; similarly, solve the three roots corresponding to each set of phase coefficients obtained in step 22;

[0035] Then, based on all the positive roots obtained, we can get Estimated value of

[0036] Step 26: Estimated value Substitute into the equation group of formula (3), calculate a ratio according to each set of phase coefficients, and then calculate the mean of each ratio, and use the calculated mean as the estimation result

[0037] Furthermore, the specific process of step 21 is as follows:

[0038] Normalized amplitude variance NAV of the i-th distance unit i for:

[0039]

[0040] Among them, s i (n) is the processed echo data corresponding to the nth scattering point in the i-th range unit, E n (·) is the mean operation, |s i (n)| means s i the magnitude of (n);

[0041] Similarly, after calculating the normalized amplitude variance of each distance unit, the normalized amplitude variances of each distance unit are sorted in order from small to large, and the distance units corresponding to the normalized amplitude variances in the top K positions are selected.

[0042] Furthermore, in step 25, according to all the positive roots obtained, Estimated value of Specifically:

[0043] Cluster all positive roots, select the cluster with the largest density from the clustering results, calculate the mean of all positive roots in the selected cluster, and use the calculated mean as the estimated value

[0044] Furthermore, the specific process of step three is:

[0045] Use T, R and O to represent the positions of radar transmitter Tx, receiver Rx and target rotation center respectively, and let the line connecting T and R be represents the baseline of the bistatic inverse synthetic aperture radar, and the straight-line distance between T and R is L, and the straight-line distance between T and O is R T , let the line connecting R and O be The straight-line distance between R and O is R R ;

[0046] Will and The angle between Indicates the angle between the LOS direction of the receiving radar and the baseline direction, extended To point A, The length is equal to Then connect point A to T and make a line from R to The perpendicular line of , with the foot of the perpendicular being C;

[0047] Calculate θ0 using the law of sines for a triangle:

[0048]

[0049] Where θ0 is the bistatic angle at the initial moment, R RT =R R +R T , that is, R RT Represents R T and R R The distance and

[0050] Then the constant coefficient K0 of the bistatic coefficient is:

[0051] K0=cos(θ0 / 2) (10).

[0052] Furthermore, the specific process of step 4 is as follows:

[0053]

[0054] Among them, ξ i =τ i c / 2, i represents the distance unit index value, τ i is the fast time delay corresponding to the i-th range unit.

[0055] Furthermore, the specific process of step five is as follows:

[0056]

[0057] Among them, s rc (τ,f d ) is the echo data after azimuth compression, f d is the Doppler variable.

[0058] Furthermore, the specific process of step six is ​​as follows:

[0059]

[0060] Where ΔX and ΔY are the range resolution and azimuth resolution of the bistatic inverse synthetic aperture radar image, respectively, and X and Y are the coordinates of the range and azimuth dimensions, respectively;

[0061] Substituting equation (13) into equation (12) and taking the absolute value of the right side of equation (12) yields the scattering point echo map of the bistatic inverse synthetic aperture radar:

[0062]

[0063] Where I(X,Y) is the scattering point echo pattern of the bistatic inverse synthetic aperture radar.

[0064] Furthermore, the specific process of the post-compensation processing is as follows:

[0065] Step 7.1: Segment the scattering point echo map obtained in step 6, that is, define the segmentation step size. Then, the scattering point echo map is divided into various regions along the azimuth direction according to the segmentation step size, and the azimuth interval corresponding to each region is recorded as [-Ry p , -(R-1)y p ],(-(R-1)y p , -(R-2)y p ],…,(-y p ,0],(0,y p ],…,((R-2)y p ,(R-1)y p ],((R-1)y p ,Ry p ], 2R is the total number of azimuth intervals;

[0066] The azimuth interval is (ry p ,(r+1)y p ] is taken as the rth positive defocus area, and the azimuth interval is (-(r-1)y p , -(r-2)y p ] is taken as the rth negative defocus area, where r is a positive integer; the azimuth interval is (-y p ,0] and (0,y p ] is the non-defocused area;

[0067] Step 72: extract the image of each defocused area, perform inverse Fourier transform on the image of each defocused area in the azimuth dimension, and convert the image from the range-azimuth domain to the range-slow time domain;

[0068] Combine the rth positive defocused area image in the range-slow time domain with the post-compensation phase signal Multiply the rth negative defocus area image in the range-slow time domain with the post-compensation phase signal Multiply, perform Fourier transform on each multiplied image along the slow time dimension, transform the image of each defocused area from the range-slow time domain to the range-azimuth domain, synthesize the transformed image of each defocused area with the image of the non-defocused area to obtain the focused and calibrated inverse synthetic aperture radar image.

[0069] The beneficial effects of the present invention are:

[0070] The present invention eliminates the need for external tracking and angle measurement equipment. Using only the phase coefficient of the echo signal, the receiver beam center direction, and the measured distance information, it can accurately estimate the time-varying bistatic coefficient and effective rotational angular velocity. Based on the estimated results, it eliminates image distortion and defocusing effects, achieving inverse synthetic aperture radar image calibration without requiring the search for associated scattering points. Furthermore, the method performs well even under low signal-to-noise ratio conditions and exhibits high robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a flow chart of a bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation of the present invention;

[0072] Figure 2 This is a geometric model diagram of a bistatic inverse synthetic aperture radar and a space target;

[0073] Figure 3 Schematic diagram of the target perspective estimation process;

[0074] Figure 4 is the scattering point model of the simulation target;

[0075] Figure 5(a) shows the imaging result of the range Doppler algorithm at a -5dB signal-to-noise ratio;

[0076] Figure 5(b) shows the imaging result of the range Doppler algorithm under 0dB signal-to-noise ratio;

[0077] Figure 5(c) shows the imaging result of the range Doppler algorithm at a 5dB signal-to-noise ratio;

[0078] Figure 5(d) shows the imaging result of the range Doppler algorithm at a signal-to-noise ratio of 10 dB;

[0079] FIG6( a ) is a diagram showing the imaging result of the method of the present invention at a signal-to-noise ratio of -5 dB;

[0080] FIG6( b ) is an imaging result diagram of the method of the present invention at a signal-to-noise ratio of 0 dB;

[0081] FIG6( c ) is an imaging result diagram of the method of the present invention at a signal-to-noise ratio of 5 dB;

[0082] FIG6( d ) is an imaging result diagram of the method of the present invention at a signal-to-noise ratio of 10 dB;

[0083] Figure 7(a) shows the scattering point model of the Boeing 737;

[0084] Figure 7(b) shows the imaging result of the Boeing 737 model without post-compensation processing;

[0085] Figure 7(c) shows the imaging result of the Boeing 737 model after post-compensation processing. DETAILED DESCRIPTION

[0086] Specific implementation method 1: Combination Figure 1 This embodiment describes a bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation, wherein the motion parameter estimation includes estimation of bistatic coefficients and effective rotational angular velocity, and the method specifically includes the following steps:

[0087] Step 1: The bistatic inverse synthetic aperture radar obtains echo data reflected by scattering points on the uniformly rotating target, and then performs range compression and motion compensation on the echo data to obtain echo data reflected by each scattering point on the uniformly rotating target after range compression and motion compensation;

[0088] Step 2: Based on the range-compressed and motion-compensated echo data reflected from each scattering point on the uniformly rotating target, obtain an estimate of the ratio of the first-order coefficient to the constant coefficient in the bistatic coefficient. and an estimate of the square of the effective angular velocity

[0089] Step 3: Calculate the bistatic angle at the initial moment, and then estimate the constant coefficient K0 in the bistatic coefficient based on the bistatic angle at the initial moment;

[0090] Step 4: Based on the estimated value and Construct the phase compensation term s of the i-th distance unit com,i , then multiply the phase compensation term of the i-th range unit by the echo data after range compression and motion compensation corresponding to the i-th range unit to obtain the echo data of the i-th range unit after phase compensation;

[0091] Step 5: compress the echo data of all range units after phase compensation in Step 4 in azimuth direction to obtain echo data after azimuth compression;

[0092] Step 6: Obtain a scattering point echo map based on the echo data compressed in azimuth direction;

[0093] Step 7: Obtain the target azimuth dimension y based on the scattering point echo map obtained in step 6 max , and then according to the constant coefficient K0 and the estimated value Calculate K1 and determine the target orientation size y max Is it satisfied Among them, κ w is the widening factor of the window function;

[0094] If it is not satisfied, the scattering point echo image is post-compensated and the post-compensated image is used as the inverse synthetic aperture radar calibration image;

[0095] If it is satisfied, the scattering point echo image obtained in step 6 is the inverse synthetic aperture radar calibration image.

[0096] The present invention constructs a set of equations using bistatic ISAR echo phase coefficients. By solving these equations, the ratio of the first-order coefficient to the constant coefficient of the bistatic coefficient and an estimate of the effective rotational angular velocity are obtained. The constant coefficient of the bistatic coefficient is then estimated using the receiver beam center direction and target range information. Based on this, a compensation phase is constructed to effectively compensate for image distortion and range defocus, and the image is calibrated. For larger targets, azimuth defocus may occur. Therefore, after image calibration, it is necessary to determine whether the target requires post-compensation processing. If so, the image is post-compensated to obtain a focused, calibrated bistatic ISAR image.

[0097] Specific embodiment 2: This embodiment differs from specific embodiment 1 in that the echo data after range compression and motion compensation processing of each scattering point reflected on the uniformly rotating target is specifically:

[0098]

[0099] Where σ is the bistatic scattering coefficient of the scattering point, B is the signal bandwidth, and T obs is the observation duration, rect(·) is the rectangular window function, sinc(·) is the Sigmoid function, j is the imaginary unit, λ is the carrier wavelength, t is the slow time, τ is the fast time delay variable, c is the speed of light, and f c is the center frequency, ξ, α, β and γ are the phase coefficients;

[0100]

[0101] Where K0 and K1 are the constant coefficient and first-order coefficient in the bistatic coefficient, (x, y) are the coordinates of the scattering point relative to the rotation center, and Ω eff is the effective angular velocity.

[0102] Other steps and parameters are the same as those in the first embodiment.

[0103] Specific implementation method three: This implementation method is different from specific implementation methods one or two in that the specific process of step two is as follows:

[0104] Step 21: selecting a range unit based on the minimum normalized amplitude variance criterion and the processed echo data reflected from each scattering point;

[0105] Step 2: Determine the scattering point with the largest echo energy in each selected distance unit, and then use the polynomial phase estimation method to estimate the phase coefficient corresponding to each determined scattering point. The phase coefficient corresponding to the scattering point with the largest echo energy in the kth distance unit is recorded as ξ k ,α k ,β k ,γ k , k=1,2,…,K;

[0106] Step 23: Use the phase coefficients estimated in step 22 to construct the equation system:

[0107]

[0108] Among them, x k '=K0x k ,y k '=K0y k ,(x k ,y k ) is the coordinate value of the scattering point with the largest echo energy in the k-th range unit;

[0109] Step 24: Convert the equations of formula (3) into the following form:

[0110]

[0111] make but:

[0112]

[0113] Step 25: Substitute any set of phase coefficients obtained in step 22 into equation (5), and then solve equation (5) to obtain the three roots corresponding to the set of phase coefficients; similarly, solve the three roots corresponding to each set of phase coefficients obtained in step 22;

[0114] Then, based on all the positive roots obtained, we can get Estimated value of

[0115] Step 26: Estimated value Substitute into the equation group of formula (3), calculate a ratio according to each set of phase coefficients, and then calculate the mean of each ratio, and use the calculated mean as the estimation result

[0116] Other steps and parameters are the same as those in the first or second embodiment.

[0117] Specific embodiment 4: This embodiment differs from specific embodiments 1 to 3 in that the specific process of step 21 is as follows:

[0118] Normalized amplitude variance NAV of the i-th distance unit i for:

[0119]

[0120] Among them, s i (n) is the processed echo data corresponding to the nth scattering point in the i-th range unit, E n (·) is the mean operation, |s i (n)| means s i the magnitude of (n);

[0121] It should be noted that the distance unit i corresponds to the fast time dimension, the scattering point n corresponds to the slow time dimension, and one distance unit corresponds to multiple scattering points;

[0122] Similarly, after calculating the normalized amplitude variance of each distance unit, the normalized amplitude variances of each distance unit are sorted in order from small to large, and the distance units corresponding to the normalized amplitude variances in the top K positions are selected.

[0123] The other steps and parameters are the same as those in the first to third embodiments.

[0124] In this embodiment, the value of K is 5-8.

[0125] Specific embodiment 5: This embodiment differs from the specific embodiments 1 to 4 in that, in step 25, the obtained positive roots are obtained. Estimated value of Specifically:

[0126] Cluster all positive roots, select the cluster with the largest density from the clustering results, calculate the mean of all positive roots in the selected cluster, and use the calculated mean as the estimated value

[0127] The other steps and parameters are the same as those in the first to fourth embodiments.

[0128] The cubic equation of formula (5) has three roots. Obviously, for this cubic equation, there exists an equation equal to The positive root of . Since the cubic coefficient of equation (5) and the constant term 4γ2 are all positive, and according to the graphical characteristics of a cubic function, we know that the equation (5) must have a negative root (invalid solution). As for the third root, if it is negative, then the only positive root among the three roots is the true solution ( However, in reality, the true solutions obtained from each set of phase coefficients are not necessarily exactly the same. If the third root is also a positive root, it is difficult to determine which positive root is the true solution. In this case, the three roots of equation (5) are defined as Λ1, Λ2, and Λ3, where Λ2 represents a negative root, and Λ3 represents another positive root. The relationship between the roots and coefficients of a cubic equation is:

[0129]

[0130] Will Substituting the equation of formula (3) into the equation of formula (7), the expression of the third root Λ3 is transformed into:

[0131]

[0132] It is difficult to distinguish the magnitudes of Λ1 and Λ3 from Equation (8). However, the value of Λ3 is spatially variable because it depends on the distance of the scatterer and the crossover position. In contrast, Λ1 is constant (i.e., spatially invariant) because it is equal to Based on this, the present invention can use each set of phase coefficients to solve the equation to obtain the three roots of the equation. Then use the clustering algorithm to find the positive roots that are clustered together from these roots, and use the mean of the clustered positive roots as Ω eff 2 The estimated results.

[0133] It should be noted that due to Ω eff The sign of is unknown, the present invention can only estimate Ω eff The absolute value of the target is not used to estimate its true value. This may only result in the final calibrated ISAR image being mirror-symmetric about the cross-range axis, without affecting the estimation of the target size and shape. Therefore, the present invention does not strictly distinguish between absolute values ​​and true values.

[0134] Specific implementation method six: combination Figure 2 This embodiment is different from the first to fifth embodiments in that the specific process of step 3 is as follows:

[0135] Use T, R and O to represent the positions of radar transmitter Tx, receiver Rx and target rotation center respectively, and let the line connecting T and R be represents the baseline of the bistatic inverse synthetic aperture radar, and the straight-line distance between T and R is L, and the straight-line distance between T and O is R T , let the line connecting R and O be The straight-line distance between R and O is R R ;

[0136] Will and The angle between Indicates the angle between the LOS direction of the receiving radar and the baseline direction (i.e., the target viewing angle), extending To point A, The length is equal to Then connect point A to T and make a line from R to The perpendicular line of , with the foot of the perpendicular being C;

[0137] Calculate θ0 using the law of sines for a triangle:

[0138]

[0139] Where θ0 is the bistatic angle at the initial moment, R RT =R R +R T , that is, R RT Represents R T and R R The distance and

[0140] Then the constant coefficient K0 of the bistatic coefficient is:

[0141] K0=cos(θ0 / 2) (10)

[0142] The other steps and parameters are the same as those in the first to fifth embodiments.

[0143] From the one-dimensional distance image at the initial moment, we can get R RT -L is an estimated value with an estimated error less than half of the radar range resolution. The positions of the receiver Rx and transmitter Tx can be determined by the Global Positioning System or BeiDou Navigation Satellite System. Then, the distance between the receiver Rx and transmitter Tx positions can be calculated to estimate the length of the baseline L. Since the precise point positioning (PPP) accuracy of GPS or BDS can reach the centimeter level, the estimated error of L can be ignored. Then, by replacing R RT -Calculate R by adding the estimated values ​​of L and L RT The estimated value of R RT -Estimation error of L and L, R RT The estimated error will be in the meter level.

[0144] When the signal received by the receiver Rx exceeds the detection threshold, it indicates that the target is currently in the main beam of the receiver antenna, such as Figure 3According to the direction information of the receiver's beam center (provided by the antenna control system), the beam center angle, that is, the angle between the receiver's beam center and the baseline, can be determined and used as an estimate of the target viewing angle.

[0145] Finally, using L, R RT The estimated value of θ0 can be solved by solving the equation.

[0146] Specific embodiment 7: This embodiment differs from any one of specific embodiments 1 to 6 in that the specific process of step 4 is as follows:

[0147]

[0148] Among them, ξ i =τ i c / 2, i represents the distance unit index value, τ i is the fast time delay corresponding to the i-th range unit.

[0149] The other steps and parameters are the same as those in the first to sixth embodiments.

[0150] Specific embodiment eight: This embodiment differs from any one of specific embodiments one to seven in that the specific process of step five is as follows:

[0151]

[0152] Among them, s rc (τ,f d ) is the echo data after azimuth compression, f d is the Doppler variable.

[0153] The other steps and parameters are the same as those in the first to seventh embodiments.

[0154] Specific embodiment 9: This embodiment differs from any one of specific embodiments 1 to 8 in that the specific process of step 6 is as follows:

[0155]

[0156] Where ΔX and ΔY are the range resolution and azimuth resolution of the bistatic inverse synthetic aperture radar image, respectively, and X and Y are the coordinates of the range and azimuth dimensions, respectively;

[0157] Substituting equation (13) into equation (12) and taking the absolute value of the right side of equation (12) yields the scattering point echo map of the bistatic inverse synthetic aperture radar:

[0158]

[0159] Where I(X,Y) is the scattering point echo pattern of the bistatic inverse synthetic aperture radar.

[0160] The other steps and parameters are the same as those in Specific Embodiments 1 to 8.

[0161] Specific embodiment 10: This embodiment differs from specific embodiments 1 to 9 in that the specific process of the post-compensation processing is as follows:

[0162] Step 7.1: Segment the scattering point echo map obtained in step 6, that is, define the segmentation step size. Then, the scattering point echo map is divided into various regions along the azimuth direction according to the segmentation step size, and the azimuth interval corresponding to each region is recorded as [-Ry p , -(R-1)y p ],(-(R-1)y p , -(R-2)y p ],…,(-y p ,0],(0,y p ],…,((R-2)y p ,(R-1)y p ],((R-1)y p ,Ry p ], 2R is the total number of azimuth intervals;

[0163] The azimuth interval is (ry p ,(r+1)y p ] is taken as the rth positive defocus area, and the azimuth interval is (-(r-1)y p , -(r-2)y p ] is taken as the rth negative defocus area, where r is a positive integer; the azimuth interval is (-y p ,0] and (0,y p ] is the non-defocused area;

[0164] Step 72: extract the image of each defocused area, perform inverse Fourier transform on the image of each defocused area in the azimuth dimension, and convert the image from the range-azimuth domain to the range-slow time domain;

[0165] Combine the rth positive defocused area image in the range-slow time domain with the post-compensation phase signal Multiply the rth negative defocus area image in the range-slow time domain with the post-compensation phase signal Multiply, perform Fourier transform on each multiplied image along the slow time dimension, transform the image of each defocused area from the range-slow time domain to the range-azimuth domain, synthesize the transformed image of each defocused area with the image of the non-defocused area to obtain the focused and calibrated inverse synthetic aperture radar image.

[0166] The other steps and parameters are the same as those in Specific Embodiments 1 to 9.

[0167] The simulation parameters are as follows:

[0168] The target scattering point model used in the simulation is as follows: Figure 4 As shown in the simulation scenario, the transmitter is located at (5, 0, 0) km, the receiver is located at (-5, 0, 0) km, and the target is located at (0, 8.6, 0) km. The bistatic angle is 60°. The target's velocity is (0, -300, 347) m / s. The target's bistatic angular velocity is 0.03 rad / s, and its effective rotational angular velocity is 0.04 rad / s. The transmission parameters of the BISAR system are shown in Table 1. The receiver's beamwidth is 10°, and the maximum angular error between the beam center and the target is half the beamwidth. The echo signal-to-noise ratio (after pulse compression) is set to -5 dB, 0 dB, 5 dB, and 10 dB, respectively.

[0169] Table 1 System simulation parameters

[0170]

[0171] Figure 5(a)-Figure 5(d) These are the results of imaging the motion-compensated data directly using the range Doppler algorithm at different signal-to-noise ratios. The images exhibit significant distortion, with defocusing near the wings. Table 2 compares the estimated values ​​of the bistatic coefficients and target effective angular velocity using the proposed method with the true values. It can be seen that the estimated values ​​of the proposed method are very close to the true values.

[0172] Table 2 Estimation results of bistatic coefficients and effective rotation angular velocity

[0173]

[0174] Figure 6(a)-Figure 6(d) In order to obtain the imaging results at different signal-to-noise ratios using the method of the present invention, it can be seen that the method of the present invention effectively compensates for the image distortion and defocus effect at different signal-to-noise ratios and realizes image calibration.

[0175] Figure 4 Six scattering points (ABCDEF) were selected in the study. Table 3 lists the positions of these scattering points at different signal-to-noise ratios and their actual positions. Comparing the results shows that the positions of the scattering points on the map are very close to their actual positions, demonstrating that the method of the present invention has high calibration accuracy at different signal-to-noise ratios.

[0176] Table 3 Comparison of the coordinates of the six scattering points on the bistatic ISAR image at different signal-to-noise ratios and their true coordinates

[0177]

[0178] The post-compensation processing effect of the present invention will be further described below with reference to FIG. 7 .

[0179] The target scattering point model is shown in Figure 7(a). In the simulation scenario, the transmitter is located at (5, 0, 0) km, the receiver is located at (-5, 0, 0) km, and the target is located at (0, 8.6, 0) km. The bistatic angle is 60°. The target's velocity is (0, -300, 347) m / s. The target's bistatic angular velocity is 0.03 rad / s, and its effective rotational angular velocity is 0.04 rad / s. The transmission parameters of the BISAR system are shown in Table 1. The receiver's beamwidth is 10°, the maximum angular error between the beam center and the target is half the beamwidth, and the echo signal-to-noise ratio (after pulse compression) is 5 dB.

[0180] Figure 7(b) shows the imaging result obtained without post-compensation processing. The obvious defocusing effect can be seen from the local magnified image of the nose.

[0181] Figure 7(c) shows the imaging result after post-compensation processing. From the enlarged view of the nose, we can see that the defocus effect has been eliminated, and the scattered points have achieved a better focus effect. This comparison of the results shows that post-compensation processing can effectively deal with the azimuth defocus effect of large-scale targets.

[0182] The above examples are merely illustrative of the calculation model and process of the present invention and are not intended to limit the embodiments of the present invention. Persons skilled in the art will readily appreciate that other variations or modifications based on the above description are possible. This list of embodiments is not exhaustive; however, any obvious variations or modifications derived from the technical solution of the present invention remain within the scope of protection of the present invention.

Claims

1. A bistatic inverse synthetic aperture radar imaging and calibration method based on motion parameter estimation, characterized in that: The method specifically comprises the following steps: Step 1: The bistatic inverse synthetic aperture radar obtains echo data reflected by scattering points on the uniformly rotating target, and then performs range compression and motion compensation on the echo data to obtain echo data reflected by each scattering point on the uniformly rotating target after range compression and motion compensation; Step 2: Based on the range-compressed and motion-compensated echo data reflected from each scattering point on the uniformly rotating target, obtain an estimate of the ratio of the first-order coefficient to the constant coefficient in the bistatic coefficient. and an estimate of the square of the effective angular velocity ; The specific process of step 2 is: Step 21: selecting a range unit based on the minimum normalized amplitude variance criterion and the processed echo data reflected from each scattering point; Step 2: Determine the scattering point with the largest echo energy in each selected distance unit, and then use the polynomial phase estimation method to estimate the phase coefficient corresponding to each scattering point. The phase coefficient corresponding to the scattering point with the largest echo energy in a range unit is recorded as , ; Step 23: Use the phase coefficients estimated in step 22 to construct the equation system: (3) in, , For the The coordinate value of the scattering point with the largest echo energy in the range unit, is the effective angular velocity; Step 24: Convert the equations of formula (3) into the following form: (4) make ,but: (5) Step 25: Substitute any set of phase coefficients obtained in step 22 into equation (5), and then solve equation (5) to obtain the three roots corresponding to the set of phase coefficients; similarly, solve the three roots corresponding to each set of phase coefficients obtained in step 22; Then, based on all the positive roots obtained, we can get Estimated value of ; Step 26: Estimated value Substitute into the equation group of formula (3), calculate a ratio according to each set of phase coefficients, and then calculate the mean of each ratio, and use the calculated mean as the estimation result ; Step 3: Calculate the bistatic angle at the initial moment, and then estimate the constant coefficient in the bistatic coefficient based on the bistatic angle at the initial moment. ; Step 4: Based on the estimated value and Construction Phase compensation term of distance units , and then The phase compensation term of the distance unit is Multiply the echo data after range compression and motion compensation corresponding to the range unit to obtain the phase-compensated Echo data of range units; Step 5: compress the echo data of all range units after phase compensation in Step 4 in azimuth direction to obtain echo data after azimuth compression; Step 6: Obtain a scattering point echo map based on the echo data compressed in azimuth direction; Step 7: Obtain the target azimuth size based on the scattering point echo map obtained in step 6 , and then according to the constant coefficient and estimated values calculate , determine the target direction and size Is it satisfied ,in, is the widening factor of the window function, is the observation duration; If it is not satisfied, the scattering point echo map is post-compensated and the post-compensated image is used as the inverse synthetic aperture radar calibration image; If it is satisfied, the scattering point echo image obtained in step 6 is the inverse synthetic aperture radar calibration image.

2. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 1, wherein: The echo data after range compression and motion compensation processing of each scattering point on the uniformly rotating target is specifically: (1) in, is the bistatic scattering coefficient of the scattering point, is the signal bandwidth, is a rectangular window function, is the sine function, is an imaginary unit, is the carrier wavelength, For slow time, is the fast time delay variable, is the speed of light, is the center frequency, 、 、 and is the phase coefficient; (2) in, and are the constant coefficient and the first-order coefficient in the double base coefficient, are the coordinates of the scattering point relative to the center of rotation.

3. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 2, wherein: The specific process of step 21 is as follows: No. Normalized amplitude variance of distance units for: (6) in, For the The distance unit The processed echo data corresponding to the scattering points, To find the mean value, express the magnitude; Similarly, after calculating the normalized amplitude variance of each distance unit, sort the normalized amplitude variance of each distance unit in order from small to large, and select the one in the front. The distance unit corresponding to the normalized amplitude variance of the bit.

4. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 3, wherein: In the step 25, the obtained positive roots are obtained Estimated value of , specifically: Cluster all positive roots, select the cluster with the largest density from the clustering results, calculate the mean of all positive roots in the selected cluster, and use the calculated mean as the estimated value .

5. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 4, wherein: The specific process of step three is: use 、 and Denote the positions of radar transmitter Tx, receiver Rx and target rotation center respectively, let and Connection represents the baseline of the bistatic inverse synthetic aperture radar, and and The straight-line distance between them is L, let and The straight-line distance between ,make and The connection line is , and The straight-line distance between ; Will and The angle between , Indicates the angle between the LOS direction of the receiving radar and the baseline direction, extended to Point, make The length is equal to , and then Point and Connect them and make a line from arrive The perpendicular line of ; Calculate using the law of sines of a triangle : (9) in, is the bistatic angle at the initial moment, ,Right now express and The distance and Then the constant coefficient of the double base coefficient is for: (10)。 6. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 5, wherein: The specific process of step 4 is as follows: (11) in, , Represents the distance unit index value, It is The fast time delay corresponding to each distance unit.

7. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 6, wherein: The specific process of step five is: (12) in, is the echo data after azimuth compression, is the Doppler variable.

8. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 7, wherein: The specific process of step six is ​​as follows: (13) in, and are the range resolution and azimuth resolution of the bistatic inverse synthetic aperture radar image, respectively. X and Y are the coordinates of the range and azimuth dimensions, respectively. Substituting equation (13) into equation (12) and taking the absolute value of the right side of equation (12) yields the scattering point echo map of the bistatic inverse synthetic aperture radar: (14) in, It is the scattering point echo pattern of the bistatic inverse synthetic aperture radar.

9. The method for bistatic inverse synthetic aperture radar imaging and calibration based on motion parameter estimation according to claim 8, characterized in that: The specific process of the post-compensation processing is as follows: Step 7.1: Segment the scattering point echo map obtained in step 6, that is, define the segmentation step size. , and then divide the scattering point echo map into various regions along the azimuth direction according to the segmentation step size, and record the azimuth intervals corresponding to each region as , ,…, , ,…, , , is the total number of azimuth intervals; The azimuth interval is The region as the positive defocus area, and the azimuth interval is The region as the negative defocus regions, where is a positive integer; the azimuth interval is and The area is the non-defocus area; Step 72: extract the image of each defocused area, perform inverse Fourier transform on the image of each defocused area in the azimuth dimension, and convert the image from the range-azimuth domain to the range-slow time domain; The first Positive defocused area image and post-compensation phase signal Multiply the distance-slow time domain Negative defocus area image and post-compensation phase signal Multiply, perform Fourier transform on each multiplied image along the slow time dimension, transform the image of each defocused area from the range-slow time domain to the range-azimuth domain, synthesize the transformed image of each defocused area with the image of the non-defocused area to obtain the focused and calibrated inverse synthetic aperture radar image.

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