A high squint missile-borne SAR imaging method based on improved PFA

Abstract

The invention discloses a high-squint missile-borne SAR imaging method based on improved PFA, which calculates the intrapulse Doppler factor corresponding to each pulse of the echo according to radar parameters; multiplies the echo data by a scaling function in the time domain, then performs a range Fourier transform, and transforms the signal to the frequency domain; multiplies the signal transformed to the frequency domain by a matched filter function, then performs a range inverse Fourier transform, and transforms the signal back to the time domain; multiplies the signal by an inverse scaling function in the time domain, and continues to perform a range Fourier transform; multiplies the signal transformed to the frequency domain by a compensation function to obtain data processed in the range direction; performs an azimuth interpolation calculation on the data processed in the range direction to obtain data uniformly sampled in the wave number domain; performs range and azimuth Fourier transforms on the data uniformly sampled in the wave number domain, respectively, to obtain the final imaging result. The invention can effectively solve the position offset and defocus distortion phenomenon of the high-squint missile-borne SAR imaging result caused by the intrapulse Doppler effect, and ensure the imaging quality of the missile-borne SAR.

Description

Technical Field

[0001] The invention belongs to the technical field of radar imaging, and in particular relates to a high-squint missile-borne SAR imaging method based on an improved PFA. Background Art

[0002] Synthetic aperture radar (SAR) is carried on aircraft, missiles, satellites and other platforms because of its ability to detect targets all day and all weather and long-distance high-resolution imaging. It plays a very important role in the military and civilian fields. When the radar platform moves at a high speed and the pulse width of the transmitted signal is large (such as missile-borne radar), there is a large relative speed between the radar and the target, which will cause the single echo pulse to be modulated. Affected by the intra-pulse Doppler effect, the frequency modulation slope of each pulse will change. If the intra-pulse Doppler effect is not considered, the pulse compression result in the range will be defocused and the position of the pulse compression will change. In order to ensure the accuracy and quality of the image, a new algorithm is needed to process the missile-borne radar signal affected by the intra-pulse Doppler effect.

[0003] PFA (Polar Format Algorithm) can convert the signal from polar coordinate format to rectangular coordinate format for storage by resampling the signal in range and azimuth, realizing the decoupling of range and azimuth, and effectively solving the problem of moving cross-resolution unit (MTRC) far away from the central scattering point of the imaging area. PCS processing in range can avoid interpolation, which is simple, efficient and easy to implement in engineering. Therefore, this algorithm can be improved to realize the imaging processing of missile-borne signals. Summary of the invention

[0004] Purpose of the invention: The technical problem to be solved by the present invention is to provide a high-squint missile-borne SAR imaging method based on improved PFA, which obtains an image with good focusing effect by performing PCS processing in the range and interpolation processing in the azimuth on the echo signal affected by the intra-pulse Doppler effect. The method has the characteristics of simplicity, efficiency, good imaging quality and easy engineering implementation.

[0005] Technical solution: The invention discloses a high-squint airborne SAR imaging method based on improved PFA, comprising the following steps:

[0006] (1) Calculate the intra-pulse Doppler factor corresponding to each pulse of the echo based on radar parameters;

[0007] (2) Multiply the echo pulse by a scaling function in the time domain, then perform a range Fourier transform to transform the pulse signal into the frequency domain;

[0008] (3) Multiply the signal transformed into the frequency domain by the matched filter function, and then perform an inverse Fourier transform in the range direction to transform the signal back into the time domain;

[0009] (4) The signal is multiplied by the inverse scaling function in the time domain and then Fourier transformed in the distance direction;

[0010] (5) The signal transformed into the frequency domain is multiplied by the compensation function to obtain the data processed in the range direction;

[0011] (6) Perform azimuth interpolation calculation on the data processed in the range direction to obtain data uniformly sampled in the wavenumber domain;

[0012] (7) Perform Fourier transform on the data uniformly sampled in the wavenumber domain in the range and azimuth directions to obtain the final imaging result.

[0013] Furthermore, the intrapulse Doppler factor in step (1) is:

[0014]

[0015] In the formula, v r =vsinβ(t) is the radial velocity between the radar and the target, v is the radar movement speed, and β(t) is the angle between the radar and the target.

[0016] Furthermore, the scaling function in step (2) is:

[0017]

[0018] In the formula, τ represents the fast time variable, c is the speed of light, k r is the frequency modulation slope of the linear frequency modulation signal; is the distance scaling factor, where θ and are the instantaneous azimuth and elevation angles of the antenna phase center when the radar is moving, and the azimuth and elevation angles at the center of the synthetic aperture are θ c and R a is the distance between the antenna phase center and the scene center.

[0019] Furthermore, the matched filter function described in step (3) is:

[0020]

[0021] In the formula, f τ is the frequency domain variable corresponding to the distance fast time τ.

[0022] Furthermore, the inverse scaling function in step (4) is:

[0023]

[0024] In the formula, f c is the signal carrier frequency.

[0025] Furthermore, the compensation function in step (5) is:

[0026]

[0027] Among them, f τ is the frequency domain variable corresponding to the distance fast time τ, R a is the distance between the antenna phase center and the scene center, k r is the frequency modulation slope of the linear frequency modulation signal, δ r is the distance scaling factor.

[0028] Furthermore, the azimuth interpolation in step (6) is:

[0029]

[0030] Among them, sinc(x) is the interpolation kernel, and g(x) corresponding to the interpolation point x is equal to the sample g in the interpolation kernel. d The sum of the products of (i) and sin c(xi); the coordinates before and after interpolation are calculated as t a is the original azimuth time variable, t a ′ is the azimuth time variable after Keystone transformation.

[0031] Beneficial effects: Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention combines the preprocessing operation with the improved PFA algorithm to realize airborne SAR large squint imaging, performs PCS processing in the range and interpolation processing in the azimuth on the echo signal affected by the intra-pulse Doppler effect, and obtains an image with good focusing effect. It has the characteristics of simplicity and efficiency, good imaging quality, and easy engineering implementation. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0033] Figure 2 It is a schematic diagram of a simulation scenario of the present invention;

[0034] Figure 3 Schematic diagram of RCM trajectory; wherein (a) is a schematic diagram of RCM trajectory of the original PCS processing; (b) is a schematic diagram of RCM trajectory of the improved PCS processing of the present invention;

[0035] Figure 4 Schematic diagrams of PFA imaging results; wherein (a) is a schematic diagram of the original PFA imaging result based on PCS; (b) is a schematic diagram of the improved PFA imaging result of the present invention;

[0036] Figure 5is a two-dimensional point target response contour map of the center point O; wherein (a) is a contour map corresponding to the original PCS-based PFA imaging result; (b) is a contour map corresponding to the improved PFA imaging result of the present invention;

[0037] Figure 6 It is the contour map of the two-dimensional point target response of the edge point f; among them, (a) is the contour map corresponding to the original PFA imaging result based on PCS; (b) is the contour map corresponding to the improved PFA imaging result of the present invention. DETAILED DESCRIPTION

[0038] The present invention is further described in detail below with reference to the accompanying drawings.

[0039] like Figure 1 As shown, a high squint airborne SAR imaging method based on preprocessing and improved PFA includes the following steps:

[0040] Step 1: Calculate the intra-pulse Doppler factor corresponding to each pulse of the echo according to the radar parameters.

[0041] Affected by the intrapulse Doppler effect, the signal echo model of missile-borne SAR (ignoring the envelope effect) is expressed as

[0042]

[0043] In the formula, τ represents the fast time variable, t is the azimuthal time variable, c is the speed of light, and k is r is the frequency modulation slope of the linear frequency modulation signal, f c is the carrier frequency of the echo, R t is the instantaneous distance between the target and the radar. r =vsinβ(t) is the radial velocity between the radar and the target, v is the radar movement speed, and β(t) is the angle between the radar and the target.

[0044] The calculation method of intrapulse Doppler factor α is:

[0045]

[0046] Step 2: Multiply the echo pulse by the scaling function in the time domain, and then perform a range Fourier transform to transform the pulse signal into the frequency domain.

[0047] Scaling function The calculation method is:

[0048]

[0049] In the formula, is the distance scaling factor, where θ and are the instantaneous azimuth and elevation angles of the antenna phase center when the radar is moving, and the azimuth and elevation angles at the center of the synthetic aperture are θ c and R a is the distance between the antenna phase center and the scene center.

[0050] Step 3: Multiply the signal transformed into the frequency domain by the matched filter function, and then perform an inverse Fourier transform in the range direction to transform the signal back into the time domain.

[0051] Matched filter function H1(f τ ) is calculated as:

[0052]

[0053] In the formula, f τ is the frequency domain variable corresponding to the distance fast time τ.

[0054] Step 4: Multiply the signal by the inverse scaling function in the time domain and continue to perform distance Fourier transform.

[0055] Inverse scaling function The calculation method is:

[0056]

[0057] Step 5: Multiply the signal transformed into the frequency domain by the compensation function to obtain the data processed in the range direction.

[0058] Compensation function H2(f τ ) is calculated as:

[0059]

[0060] Step 6: Perform azimuth interpolation calculation on the data processed in the range direction to obtain data uniformly sampled in the wavenumber domain. The azimuth interpolation calculation formula is:

[0061]

[0062] Among them, sinc(x) is the interpolation kernel, and g(x) corresponding to the interpolation point x is equal to the sample g in the interpolation kernel. d The sum of the products of (i) and sin c(xi). The coordinates before and after interpolation are calculated as t a is the original azimuth time variable, t a ′ is the azimuth time variable after Keystone transformation.

[0063] Step 7: Perform a two-dimensional Fourier transform on the azimuthally resampled signal to obtain the final imaging result.

[0064] According to the missile-borne SAR echo model, the above echo and algorithm process are simulated on the simulation software MATLAB. The simulation scene is as follows: Figure 2 The echoes are processed according to the original distance PCS processing flow and the improved distance PCS processing flow in the present invention, and the distance migration lines after the distance processing are shown as follows: Figure 3 (a) and Figure 3 (b) as shown. Figure 3 (b) At a distance of Figure 3 (a) There is obvious displacement. The algorithm of the present invention compensates for the displacement caused by the intrapulse Doppler effect in the range direction. The imaging results obtained by performing azimuth interpolation, range FFT, and azimuth FFT on the above range processing results are shown in the figure below. Figure 4 (a) and Figure 4 (b) As the displacement in the distance direction is not compensated, Figure 4 The center point of the scene in (a) is not located at the center of the image. Figure 4 (b) corresponds to the actual scene, and the center point and edge point positions are centered in the entire image. A two-dimensional point target response contour map is made for the center point of the above imaging result. The contour maps corresponding to the original algorithm and the improved algorithm in the present invention are shown as follows: Figure 5 (a) and Figure 5 (b). Figure 5 As shown in (a), if the original algorithm process is used without considering the intrapulse Doppler effect, the side lobe and the main lobe will be stuck together in the two-dimensional point target response contour map at the center of the final imaging result, which will cause defocus distortion of the imaging result. Figure 5 (b) It is effectively proved that the algorithm process of the present invention has well dealt with the above problems. A two-dimensional point target response contour map is made for the scene edge point f. The contour maps corresponding to the original algorithm and the improved algorithm of the present invention are shown as follows: Figure 6 (a) and Figure 6 This simulation example proves that the algorithm flow of the present invention can effectively solve the position offset and defocus distortion phenomenon caused by the intra-pulse Doppler effect of the high-squint missile-borne SAR signal, and the imaging result has good focusing.

Claims

1. A high-squint missile-borne SAR imaging method based on improved PFA, characterized in that: The following steps are involved: (1) Calculate the intra-pulse Doppler factor corresponding to each pulse of the echo based on radar parameters; (2) Multiply the echo pulse by a scaling function in the time domain, then perform a range Fourier transform to transform the pulse signal into the frequency domain; (3) Multiply the signal transformed into the frequency domain by the matched filter function, and then perform an inverse Fourier transform in the range direction to transform the signal back into the time domain; (4) The signal is multiplied by the inverse scaling function in the time domain and then Fourier transformed in the distance direction; (5) The signal transformed into the frequency domain is multiplied by the compensation function to obtain the data processed in the range direction; (6) Perform azimuth interpolation calculation on the data processed in the range direction to obtain data uniformly sampled in the wavenumber domain; (7) Performing Fourier transform on the data uniformly sampled in the wavenumber domain in the range and azimuth directions to obtain the final imaging result; The intrapulse Doppler factor in step (1) is: In the formula, v r = vsinβ(t) is the radial velocity between the radar and the target, v is the radar motion speed, β(t) is the angle between the radar and the target; The scaling function in step (2) is: In the formula, τ represents the fast time variable, c is the speed of light, k r is the frequency modulation slope of the linear frequency modulation signal; is the distance scaling factor, where θ and are the instantaneous azimuth and elevation angles of the antenna phase center when the radar is moving, and the azimuth and elevation angles at the center of the synthetic aperture are θ c and R a is the distance between the antenna phase center and the scene center; The matched filter function described in step (3) is: In the formula, f τ is the frequency domain variable corresponding to the distance fast time τ; The inverse scaling function described in step (4) is: In the formula, f c is the signal carrier frequency; The compensation function described in step (5) is: Among them, f τ is the frequency domain variable corresponding to the distance fast time τ, R a is the distance between the antenna phase center and the scene center, k r is the frequency modulation slope of the linear frequency modulation signal, δ r is the distance scale transformation factor; The azimuth interpolation in step (6) is: Among them, sinc(x) is the interpolation kernel, and g(x) corresponding to the interpolation point x is equal to the sample g in the interpolation kernel. d The sum of the products of (i) and sin c(xi); the coordinates before and after interpolation are calculated as t a is the original azimuth time variable, t a ′ is the azimuth time variable after Keystone transformation.

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