An efficient ISAR translational motion envelope compensation method based on iterative updating

Abstract

The present application relates to radar technology field, specifically to a kind of efficient ISAR translation envelope compensation method based on iterative updating, first construct the target echo complex matrix X of ISAR and envelope matrix then construct reference pulse number set, and calculate the total correlation level of pulse in set and other pulses, to determine reference pulse η, by calculating the correlation coefficient vector of reference pulse and other pulses and carrying out fitting processing, construct update weight coefficient vector E, based on this to reference pulse η as center to both ends are carried out pulse envelope offset estimation and compensation, to avoid the damage of abnormal pulse to reference envelope, improve environmental adaptability, by set overall pulse information to determine reference pulse iterative updating compensation, realize the fusion of local information and global information, improve the robustness of processing.The present application has the advantages of small amount of computation, easy to engineering implementation, effectively ensure the real-time updating of reference envelope and the efficient, robust realization of ISAR translation envelope compensation.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and specifically to an efficient ISAR translational envelope compensation method based on iterative updates. Background Technology

[0002] ISAR (Inverse Synthetic Aperture Radar) achieves high-resolution imaging of targets by observing the Doppler shift caused by the target's own motion. It effectively improves the three-dimensional spatial resolution of ground or air targets, providing all-weather, all-day imaging capabilities, and is a crucial component of early warning, reconnaissance, and surveillance systems. The theoretical basis of ISAR imaging is the turntable model, which assumes no overall range offset between the target and the radar, only that the target rotates. However, targets in ISAR imaging are generally non-cooperative, exhibiting not only rotational components but also significant overall translational motion relative to the radar. This non-cooperative nature of the target necessitates accurate estimation and compensation of its motion parameters to obtain clear ISAR imaging results.

[0003] Translational envelope compensation is crucial for ISAR imaging processing. It compensates for range cell migration caused by the overall motion of the target, ensuring that echoes from the same range cell in different pulses originate from the same target scatterer, thus achieving range alignment and providing a foundation for subsequent inter-pulse processing of ISAR imaging. The main methods for translational envelope compensation include local optimum and global optimum methods. The former estimates range cell migration using the similarity between adjacent pulses, but this method is prone to estimation errors when there are local jumps between pulses or environmental instabilities. The latter models the target motion and searches for parameters to achieve estimation and compensation, but because it uses the overall imaging effect as an evaluation metric, it involves a large computational load, which is not conducive to real-time system implementation. Therefore, this invention proposes an efficient ISAR translational envelope compensation method based on iterative updates. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides an efficient ISAR translational envelope compensation method based on iterative updates.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: an efficient ISAR translational envelope compensation method based on iterative updates, comprising the following steps:

[0006] S1: Construct an M×N dimensional complex echo data matrix model X and an amplitude matrix containing M pulses and N distance sampling points.

[0007] S2: Select the reference pulse η based on the overall coherence index;

[0008] S3: Obtain the reference pulse envelope Then, the echo envelope Ci of the i-th pulse is taken sequentially, and the cross-correlation vector CF is calculated. ηi The cross-correlation coefficient was then obtained. This is used to construct the correlation coefficient vector between the reference pulse η and the remaining (M-1) pulses. And obtained by fitting

[0009] S4: Construct and update the weight coefficient vector E;

[0010] S5: Starting from the reference pulse η, perform translational offset estimation and compensation pulse by pulse.

[0011] Preferably, step S1 specifically includes the following processing procedures:

[0012] S11: ISAR imaging is achieved through complex echoes of multiple coherent pulses from the same target. The echo signal of the m-th pulse and the n-th range sampling unit can be expressed as s(m, n):

[0013]

[0014] Where the subscript i represents the scattering point number within the distance sampling unit, a i τ represents the scattering coefficient of the i-th scatterer. n Let B represent the sampling time of the nth distance unit, and let R represent the signal bandwidth. i (m) represents the distance of the i-th scattering unit during the m-th pulse, f0 represents the radar's operating center frequency, c represents the electromagnetic wave propagation speed, and j is the imaginary unit;

[0015] S12: Arrange the echo signals s(m,n) in the form of one pulse echo per row to form an M×N dimensional complex echo matrix X:

[0016]

[0017] Where Υ is an M×N matrix representing a Gaussian white noise matrix, and each column corresponds to M pulse samples of a distance cell;

[0018] S13: Calculate the modulus of each element of the complex matrix X to obtain the magnitude matrix.

[0019] Preferably, step S2 specifically includes the following processing procedures:

[0020] S21: From the M pulses, arbitrarily select Q pulse numbers to construct a reference pulse number set Φ:

[0021] Φ = {m1, ..., m} q, ..., m Q |m q ∈{1, ..., M}};

[0022] S22: Take the q-th element m from the set (1≤q≤Q). q Corresponding The row vector is the reference pulse envelope F q :

[0023]

[0024] S23: Calculate m q The sum of correlation coefficients ρ between the reference pulse envelope and other line envelopes q ;

[0025] S24: Repeat S23 to construct the correlation coefficient vector Γ:

[0026] Γ=[ρ1,...,ρ Q ];

[0027] S25: Select the pulse number corresponding to the maximum correlation coefficient as the reference pulse η:

[0028]

[0029] Preferably, step S23 specifically includes the following processing procedures:

[0030] S231: Take the i-th (i≠m) q The envelope C of the pulse echo i :

[0031]

[0032] S232: Calculate the cross-correlation vector CF qi :

[0033] CF qi =ifft[fft(F q )·fft * (C i )]

[0034] The superscript * indicates taking the conjugate;

[0035] S233: Obtain the cross-correlation coefficient

[0036]

[0037] Where max{·} represents taking the maximum value of the vector element, and n (1≤n≤N) represents the distance cell index;

[0038] S234: Repeat S231-S233 until all rows have been traversed, and obtain... This is used to subsequently construct the correlation coefficient vector Γ and select the pulse number corresponding to the maximum correlation coefficient as the reference pulse η.

[0039] Preferably, step S3 specifically includes the following processing procedures:

[0040] S31: Obtain the reference pulse packet; network

[0041]

[0042] S32: Take the echo envelope C of the i-th pulse. i :

[0043]

[0044] S33: Calculate the cross-correlation vector CF ηi :

[0045]

[0046] S34: Obtain the cross-correlation coefficient

[0047]

[0048] S35: Repeat S32-S34 to construct the correlation coefficient vector between the reference pulse and all pulses.

[0049]

[0050] S36: Yes Polynomial fitting was performed to obtain

[0051] Preferably, step S4 specifically includes the following processing procedures:

[0052] S41: Calculate the difference vector ΔΓ of the reference pulse correlation coefficient sequence:

[0053]

[0054] in, This represents the difference between the correlation coefficient between the reference pulse and the m-th pulse and the fitted correlation coefficient;

[0055] S42: Obtain the standard deviation σΔΓ of the difference vector ΔΓ;

[0056] S43: Construct the baseline envelope update coefficient vector E:

[0057] E = [α1, ..., α] m , ..., α M ]

[0058] Where, α m =0.5*b m ,

[0059]

[0060] Where m = 1, 2, ..., M.

[0061] Preferably, step S5 specifically includes the following processing procedures:

[0062] S51: Initialize the baseline envelope

[0063]

[0064] S52: Initialize pulse offset g = 1;

[0065] S53: Based on the constructed baseline envelope update coefficient vector E, take the update coefficient α of the i = η + g pulse. i When α i When the value is 0, the echo of the previous pulse is used to assign the value to the current pulse:

[0066] [x(i,1),x(i,2),v,x(i,N)]=[x(i-1,1),x(i-1,2),...,x(i-1,N)]

[0067] And jump to S58, when α i When the value is not 0, take the echo envelope C. i :

[0068]

[0069] S54: Calculate the cross-correlation vector V i :

[0070]

[0071] S55: Obtain the relative offset ε i :

[0072]

[0073] in, For vector V i The index of the maximum value, f s Indicates the range sampling frequency;

[0074] S56: Compensate for the echo U of the i-th pulse i:

[0075]

[0076] Among them, U i = [x(i, 1), x(i, 2), ..., x(i, N)] is the vector of the i-th row of matrix X, and the compensation envelope vector W is obtained by taking the modulus of each element. i :

[0077] W i =[|x(i,1)|, |x(i,2)|,..., |x(i,N)|];

[0078] S57: Update baseline envelope

[0079]

[0080] S58: g = g + 1, repeat steps S53-S57 to achieve translational envelope compensation for all pulses with pulse numbers greater than the reference pulse number;

[0081] S59: Change the direction of iteration and initialize the baseline envelope. Initialize the pulse offset to g = -1, and execute steps S52-S57, then set g = g-1. Repeat this process to achieve translational envelope compensation for all pulses with pulse numbers less than the reference pulse number.

[0082] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0083] 1. This invention establishes a reliable reference pulse by determining the correlation coefficient distribution of multiple reference pulses in the entire pulse matrix. The update coefficient vector of the reference pulse envelope is constructed by the coherence between the reference pulse and all pulses. Based on this, pulse-by-pulse envelope offset estimation and compensation are performed from the reference pulse η as the center to both ends. This avoids the destruction of the reference envelope by abnormal pulses, improves the adaptability of the traditional local information method to the environment, effectively utilizes global information, realizes the fusion of the traditional local optimal method and the global optimal method, and improves the robustness of translational envelope compensation.

[0084] 2. In this invention, the destruction of the reference envelope by abnormal pulses is avoided by estimating the correlation and constructing the updated coefficients. The influence of pulse envelope changes on parameter estimation is avoided by updating and iterating the reference envelope, thereby improving the adaptability of the traditional local optimum method to the environment.

[0085] 3. The main calculations in this invention are related processing of the reference envelope and the processing envelope. The computational load is small and easy to implement in engineering. At the same time, it effectively ensures the real-time updating of the reference envelope and the efficient and robust implementation of ISRA translational envelope compensation. Attached Figure Description

[0086] Figure 1 This is a schematic diagram of the process of an efficient ISAR translational envelope compensation method based on iterative updates according to the present invention.

[0087] Figure 2 This is a schematic diagram of the echo matrix of the pulse-distance sampling unit in step S1 of this embodiment of the invention;

[0088] Figure 3 This is a flowchart illustrating the selection of the reference pulse in step S2 of this embodiment of the invention.

[0089] Figure 4 This is a schematic diagram of the correlation coefficient and fitting results in step S2 of this embodiment of the invention;

[0090] Figure 5 This is a flowchart of the translational offset estimation and compensation in step S3 of this embodiment of the invention;

[0091] Figure 6 This is a schematic diagram of the translational compensation result in step S2 of this embodiment of the invention. Detailed Implementation

[0092] The present invention will be further described below with reference to the accompanying drawings and embodiments, which illustrate the above and other technical features and advantages of the present invention. However, the following embodiments are merely preferred embodiments of the present invention and are not exhaustive.

[0093] Example:

[0094] like Figure 1-6 As shown, this invention provides an efficient ISAR translational envelope compensation method based on iterative updates, comprising the following steps:

[0095] S1: Construct an M×N dimensional complex echo data matrix model X and an amplitude matrix containing M pulses and N distance sampling points.

[0096] S2: Select the reference pulse η based on the overall coherence index;

[0097] S3: Obtain the reference pulse envelope Then, the echo envelope Ci of the i-th pulse is taken sequentially, and the cross-correlation vector CF is calculated. ηi The cross-correlation coefficient was then obtained. This is used to construct the correlation coefficient vector between the reference pulse η and the remaining (M-1) pulses. And obtained by fitting

[0098] S4: Construct and update the weight coefficient vector E;

[0099] S5: Starting from the reference pulse η, perform translational offset estimation and compensation pulse by pulse.

[0100] In this embodiment, step S1 specifically includes the following processing procedures:

[0101] S11: ISAR imaging is achieved through complex echoes of multiple coherent pulses from the same target. The echo signal of the m-th pulse and the n-th range sampling unit can be expressed as s(m, n):

[0102]

[0103] Where the subscript i represents the scattering point number within the distance sampling unit, a i τ represents the scattering coefficient of the i-th scatterer. n Let B represent the sampling time of the nth distance unit, and let R represent the signal bandwidth. i (m) represents the distance of the i-th scattering unit during the m-th pulse, f0 represents the radar's operating center frequency, c represents the electromagnetic wave propagation speed, and j is the imaginary unit;

[0104] S12: Arrange the echo signals s(m,n) in the form of one pulse echo per row to form an M×N dimensional complex echo matrix X:

[0105]

[0106] Where Υ is an M×N matrix representing a Gaussian white noise matrix, and each column corresponds to M pulse samples of a distance cell;

[0107] S13: Calculate the modulus of each element of the complex matrix X to obtain the magnitude matrix. like Figure 2 The image shows the 512x256 echo amplitude matrix in this embodiment, which contains some abnormal pulses.

[0108] In this embodiment, step S2 specifically includes the following processing procedures:

[0109] S21: From the M pulses, arbitrarily select Q pulse numbers to construct a reference pulse number set Φ:

[0110] Φ = {m1, ..., m} q , ..., m Q |m q ∈{1, ..., M}};

[0111] S22: Take the q-th element m from the set (1≤q≤Q). q Corresponding The row vector is the reference pulse envelope F q :

[0112]

[0113] S23: Calculate m q The sum of correlation coefficients ρ between the reference pulse envelope and other line envelopes q ;

[0114] S24: Repeat S23 to construct the correlation coefficient vector Γ:

[0115] Γ=[ρ1,...,ρ Q ];

[0116] S25: Select the pulse number corresponding to the maximum correlation coefficient as the reference pulse η:

[0117]

[0118] In this embodiment, step S23 specifically includes the following processing procedures:

[0119] S231: Take the i-th (i≠m) q The envelope C of the pulse echo i :

[0120]

[0121] S232: Calculate the cross-correlation vector CF qi :

[0122] CF qi =ifft[fft(F q )·fft * (C i )]

[0123] The superscript * indicates taking the conjugate;

[0124] S233: Obtain the cross-correlation coefficient

[0125]

[0126] Where max{·} represents taking the maximum value of the vector element, and n (1≤n≤N) represents the distance cell index;

[0127] S234: Repeat S231-S233 until all rows have been traversed, and obtain... This is used to subsequently construct the correlation coefficient vector Γ and select the pulse number corresponding to the maximum correlation coefficient as the reference pulse.

[0128] In this embodiment, step S3 specifically includes the following processing procedures:

[0129] S31: Obtain the reference pulse envelope

[0130]

[0131] S32: Take the echo envelope C of the i-th pulse. i :

[0132]

[0133] S33: Calculate the cross-correlation vector CF ηi :

[0134]

[0135] S34: Obtain the cross-correlation coefficient

[0136]

[0137] S35: Repeat S32-S34 to construct the correlation coefficient vector between the reference pulse and all pulses.

[0138]

[0139] S36: Yes Polynomial fitting was performed to obtain

[0140] In this embodiment, step S4 specifically includes the following processing procedures:

[0141] S41: Calculate the difference vector ΔΓ of the reference pulse correlation coefficient sequence:

[0142]

[0143] in, This represents the difference between the correlation coefficient between the reference pulse and the m-th pulse and the fitted correlation coefficient;

[0144] S42: Obtain the standard deviation σ of the difference vector ΔΓ ΔΓ ;

[0145] S43: Construct the baseline envelope update coefficient vector E:

[0146] E = [α1, ..., α] m , ..., α M ]

[0147] Where, α m =0.5*b m ,

[0148]

[0149] Where m = 1, 2, ..., M.

[0150] In this embodiment, step S5 specifically includes the following processing procedures:

[0151] S51: Initialize the baseline envelope

[0152]

[0153] S52: Initialize pulse offset g = 1;

[0154] S53: Based on the constructed baseline envelope update coefficient vector E, take the update coefficient α of the i-th pulse (η+g). i When α i When the value is 0, the echo of the previous pulse is used to assign the value to the current pulse:

[0155] [x(i,1),x(i,2),...,x(i,N)]=[x(i-1,1),x(i-1,2),...,x(i-1,N)]

[0156] And jump to S58, when α i When the value is not 0, take the echo envelope C. i :

[0157]

[0158] S54: Calculate the cross-correlation vector V i :

[0159]

[0160] S55: Obtain the relative offset ε i :

[0161]

[0162] in, For vector V i The index of the maximum value, f s Indicates the range sampling frequency;

[0163] S56: Compensate for the echo U of the i-th pulse i :

[0164]

[0165] Among them, U i = [x(i, 1), x(i, 2), ..., x(i, N)] is the vector of the i-th row of matrix X, and the compensation envelope vector W is obtained by taking the modulus of each element. i :

[0166] W i=[|x(i,1)|, |x(i,2)|,..., |x(i,N)|];

[0167] S57: Update baseline envelope

[0168]

[0169] S58: g = g + 1, repeat steps S53-S57 to achieve translational envelope compensation for all pulses with pulse numbers greater than the reference pulse number;

[0170] S59: Change the direction of iteration and initialize the baseline envelope. Initialize the pulse offset to g = -1, and execute steps S52-S57, then set g = g-1. Repeat this process to achieve translational envelope compensation for all pulses with pulse numbers less than the reference pulse number.

[0171] The working principle of this invention is as follows: First, the target echo complex matrix X and the envelope matrix of ISAR are constructed. Then, a reference pulse sequence set is constructed by randomly selecting a certain number of pulse sequences, and the total correlation level between the pulses in the set and other pulses is calculated to determine the reference pulse η. Then, by calculating the correlation coefficient vector of the reference pulse and performing fitting processing, an updated weight coefficient vector E is constructed. Offset estimation and compensation are performed at both ends with the reference pulse η as the center, thereby avoiding the destruction of the reference envelope by abnormal pulses and ensuring the real-time update of the reference envelope. This achieves translational envelope compensation of ISAR efficiently and robustly.

[0172] The above description is merely a preferred embodiment of the present invention and is illustrative rather than restrictive. Those skilled in the art will understand that many changes, modifications, and even equivalents can be made within the spirit and scope defined by the claims of the present invention, all of which will fall within the protection scope of the present invention.

Claims

1. A highly efficient ISAR translational envelope compensation method based on iterative updates, characterized in that, Includes the following steps: S1: Construct M pulses and N distance sampling points Complex echo data matrix model X and amplitude matrix ; S2: Select the reference pulse based on the overall coherence index. ; S3: Obtain the reference pulse envelope and take the first one in sequence. The echo envelope of each pulse Calculate the cross-correlation vector The cross-correlation coefficient was then obtained. To construct a reference pulse The correlation coefficient vector with the remaining (M-1) pulses And fit to obtain ; S4: Construct and update the weight coefficient vector Specifically, the processing steps include the following: S41: Calculate the difference vector of the reference pulse correlation coefficient sequence. : ； in, , indicating that the reference pulse and the first The difference between the correlation coefficient of each pulse and the fitted correlation coefficient; S42: Obtain the difference vector Standard deviation ; S43: Construct the baseline envelope update coefficient vector : ； in, , ； in, ; S5: Based on the reference pulse Starting from this point, translational offset estimation and compensation are performed pulse by pulse, specifically including the following processing steps: S51: Initialize the baseline envelope : ； S52: Initialize pulse offset g=1; S53: Update the coefficient vector based on the constructed baseline envelope. Take the first Update coefficients for each pulse ,when When the value is 0, the echo of the previous pulse is used to assign the value to the current pulse: ； And jump to S58, when When the value is not 0, take the echo envelope. : ； S54: Calculate the cross-correlation vector : ； S55: Obtain relative offset : ； in, For vectors The index at the maximum value Indicates the range sampling frequency; S56: Compensation Echo of each pulse : ； in, Let X be the vector of the i-th row of the matrix, and calculate the compensation envelope vector by taking the modulus of each element. : ； S57: Update baseline envelope : ； S58: g = g + 1, repeat steps S53-S57 to achieve translational envelope compensation for all pulses with pulse numbers greater than the reference pulse number; S59: Change the direction of iteration and initialize the baseline envelope. Initialize the pulse offset to g=-1, and execute steps S52-S57, taking g=g-1. Repeat this process to achieve translational envelope compensation for all pulses with pulse numbers less than the reference pulse number.

2. The efficient ISAR translational envelope compensation method based on iterative updates as described in claim 1, characterized in that, Step S1 specifically includes the following processing procedures: S11: ISAR imaging is achieved through complex echoes of multiple coherent pulses from the same target. Pulse, number The echo signal of the distance sampling unit can be expressed as : ； Among them, subscript Indicates the scattering point number within the distance sampling unit. Indicates the first The scattering coefficient of the scatterer Indicates the first The sampling time of each distance cell, Indicates signal bandwidth. Indicates the first Pulse time The distance between scattering units, Indicates the radar's operating center frequency. Indicates the speed of electromagnetic wave propagation. It is the imaginary unit; S12: Echo signal Arranged in a pattern where each row contains one pulse echo. dimensional echo complex matrix : ； in, for The matrix represents a Gaussian white noise matrix, with each column corresponding to M pulse samples of a distance cell; S13: Calculate the modulus of each element of the complex matrix X to obtain the magnitude matrix. .

3. The efficient ISAR translational envelope compensation method based on iterative updates as described in claim 2, characterized in that, Step S2 specifically includes the following processing procedures: S21: From the M pulses, arbitrarily select Q pulse numbers to construct a reference pulse number set. : ； S22: Take the first element from the set. element Corresponding The row vector is the reference pulse envelope. : ； S23: Calculation The sum of correlation coefficients between the reference pulse envelope and other line envelopes ; S24: Repeat S23 to construct the correlation coefficient vector. : ； S25: Select the pulse number corresponding to the maximum correlation coefficient as the reference pulse. : 。 4. The efficient ISAR translational envelope compensation method based on iterative updates as described in claim 2, characterized in that, Step S23 specifically includes the following processing procedures: S231: Take the first The envelope of each pulse echo : ； S232: Calculate the cross-correlation vector : ； Among them, superscript Indicates taking the conjugate; S233: Obtain the cross-correlation coefficient : ； in, This indicates taking the maximum value of the vector elements. Indicates the distance cell number; S234: Repeat S231-S233 until all rows have been traversed, and obtain... This is used for subsequent construction of the correlation coefficient vector. The pulse number corresponding to the largest correlation coefficient is selected as the reference pulse. .

5. The efficient ISAR translational envelope compensation method based on iterative updates according to claim 1, characterized in that: Step S3 specifically includes the following processing procedures: S31: Obtain the reference pulse envelope : ； S32: Take the first The echo envelope of each pulse : ； S33: Calculate the cross-correlation vector : ； S34: Obtain the cross-correlation coefficient : ； S35: Repeat S32-S34 to construct the correlation coefficient vector between the reference pulse and all pulses. : ； S36: Yes Polynomial fitting was performed to obtain .

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