CN112180370B - SAR range reference signal processing method and device - Google Patents

Abstract

The invention provides a method and device for processing a SAR range reference signal, which mainly includes normalizing the time width of the transmitted pulse of the SAR chirp signal, moving the internal calibration response signal with time delay to the origin, performing least squares and orthogonal polynomial double fitting on the amplitude and phase value curves of the internal calibration reference signal, and reconstructing the range reference signal. The SAR range reference signal constructed by the present invention fits the inherent nonlinear component of the SAR internal calibration response signal, and at the same time suppresses random strays and crosstalk in signal interference, and as a SAR range matching function can meet the requirements of numerical stability and precision. The range pulse compression test is performed with the actual SAR echo data containing the ground corner reflector target, and the result is close to the ideal point target response effect.

Description

A SAR range reference signal processing method and device

Technical Field

The present invention relates to the technical field of synthetic aperture radar (SAR) signal processing, and in particular to a SAR range reference signal processing method and device.

Background Art

As an important means of earth observation, SAR has all-day and all-weather imaging capabilities. Usually, SAR radar uses linear frequency modulated pulses as radar transmission signals, and its system response function is used as a reference function to match filter the SAR range echo data to obtain the range resolution. With the improvement of range resolution, while increasing the bandwidth of the transmission signal, nonlinear distortion continues to occur in the SAR system response function, resulting in peak shift, main lobe widening, side lobe elevation and asymmetry after pulse compression.

SAR internal calibration is used to measure the amplitude and phase characteristics of radar. It can work in the early, middle and late stages of SAR data acquisition tasks. The collected internal calibration data can reflect the actual amplitude and phase characteristics of the SAR radar transceiver channel. Therefore, the SAR internal calibration response signal contains the signal distortion of the SAR system, and the error compensation method is used to eliminate the influence of signal distortion.

The error compensation method uses the numerical deviation between the SAR internal calibration response signal and the ideal linear frequency modulation signal to achieve amplitude correction and phase compensation during range pulse compression. In signal processing, the amplitude and phase error data copies of the SAR internal calibration response signal can be directly used or the error data can be fitted into an orthogonal (Legendre) polynomial model.

However, this method requires obtaining amplitude and phase error data or establishing an error model, and the algorithm is complex and the compensation effect is limited. Preliminary applications and evaluations in spaceborne SAR systems such as TerraSAR-X and Sentinel-1A show that due to the nonlinearity of the radar transceiver channel and the presence of mirror frequency interference, the amplitude and phase fitting data using the fifth-order polynomial are incomplete, which increases the sidelobe level of the target and cannot meet the numerical stability and accuracy requirements of the SAR range matching function.

Summary of the invention

1. Technical issues to be resolved

In view of this, in order to overcome at least one aspect of the above problems, the present invention provides a SAR range reference signal processing method and device.

(II) Technical solution

On one hand, the present invention provides a SAR range reference signal processing method, comprising: time normalizing the SAR transmission pulse width to obtain a SAR linear frequency modulation signal, centering the SAR linear frequency modulation signal with zeros to the range pulse compression processing points to obtain a linear frequency modulation reference signal; extracting SAR internal calibration loop sample data from SAR raw data to obtain an initial internal calibration loop response signal, pre-filling the signal with zeros to the range pulse compression processing points, and completing mean value processing to obtain an internal calibration response signal; performing pulse compression on the linear frequency modulation reference signal and the internal calibration response signal to obtain an internal calibration pulse pressure signal, and subtracting the peak position of the internal calibration pulse pressure signal from the ideal pulse pressure position of the linear frequency modulation signal to obtain a time The method comprises the following steps: performing a pre-zero filling on the internal calibration response signal to complete the time delay compensation and constructing an internal calibration reference signal; performing a double polynomial fitting of least squares and orthogonal polynomials on the internal calibration reference signal to obtain a second fitting polynomial of amplitude and phase; constructing a polynomial constant model based on the second fitting polynomial of amplitude and phase and filling the polynomial constant model with zeros in the middle to obtain a range reference signal; performing scene separation on the SAR raw data to obtain a scene of SAR raw echo data, filling the range data in the scene of SAR raw data with zeros in the middle in turn to form standard scene SAR echo data; performing range pulse compression on the standard scene SAR echo data and the range reference signal in turn to obtain a range Doppler image.

Optionally, the step of performing time normalization on the SAR transmit pulse width to obtain a SAR linear frequency modulation signal includes: constructing the SAR linear frequency modulation signal as follows:

Wherein, B is the SAR system bandwidth; T is the transmit pulse width; t is the time, and its time step Δt=2/(T·Samp); Samp is the sampling frequency, and the number of sampling points of the linear frequency modulation signal h _ref (t) is N _rr =T·Samp.

Optionally, the SAR internal calibration loop sample data includes: transmission internal calibration sample data, reception internal calibration sample data and public internal calibration sample data.

Optionally, the pre-zero padding includes: pre-pending the internal calibration response signal, and padding the back of the internal calibration response signal with zeros to the number of distance pulse compression processing points; completing the delay compensation includes: taking the subscript variable value corresponding to the peak value of the internal calibration pulse pressure signal minus the ideal pulse pressure position of the linear frequency modulation signal as the delay amount, using the delay amount as the subscript starting position of the internal calibration response signal after the pre-zero padding, moving the internal calibration response signal after the pre-zero padding forward, padding the back of the internal calibration response signal with zeros, the number of zeros is the delay amount, and the ideal pulse pressure position is 1/2 of the number of sampling points.

Optionally, the double polynomial fitting of least squares and orthogonal polynomials on the internal calibration reference signal includes: obtaining amplitude and phase numerical curves to be fitted from the internal calibration reference signal; performing least squares polynomial fitting on the amplitude and phase numerical curves to be fitted according to the initial fitting order, to obtain preliminary fitting polynomials of amplitude and phase; calculating the square error of the preliminary fitting polynomials of amplitude and phase, and judging whether the fitting result is not greater than a preset square error: if the fitting result is not greater than the preset square error, the fitting accuracy requirement is met; otherwise, increasing the fitting order until the increased square error can still meet the fitting accuracy requirement, to obtain the highest fittable order and the first fitting polynomials of amplitude and phase; performing orthogonal polynomial fitting on the first fitting polynomials of amplitude and phase according to the highest fittable order, to obtain orthogonal fitting polynomials of amplitude and phase; performing coefficient optimization on the orthogonal fitting polynomials of amplitude and phase, to form second fitting polynomials of amplitude and phase.

Optionally, performing least squares polynomial fitting on the amplitude and phase numerical curves to be fitted respectively includes: fitting the amplitude and phase numerical curves to be fitted as follows:

in, are the least squares fitting coefficients of amplitude and phase respectively; t is the time; n ₀ is the initial fitting order, They are the preliminary fitting polynomial for amplitude and the preliminary fitting polynomial for phase respectively.

Optionally, performing orthogonal polynomial fitting on the amplitude and phase first-fitting polynomials respectively includes: fitting the amplitude and phase first-fitting polynomials as:

in, are the orthogonal fitting coefficients of amplitude and phase respectively; t is the time; n is the highest fitting order; are orthogonal fitting polynomials for amplitude and phase respectively; _Pi (t) is the orthogonal basis function, _Pi (t) is:

Optionally, the coefficient optimization includes: truncating the high-order coefficients whose values tend to zero in the amplitude orthogonal fitting polynomial, taking the lower-order coefficients with larger values and effective, and forming a second-order fitting polynomial for amplitude; truncating the high-order coefficients whose values tend to zero in the phase orthogonal fitting polynomial, taking the lower-order coefficients with larger values and effective, and setting the 1st-order coefficients and the 2nd-order coefficients to zero, and forming a second-order fitting polynomial for phase.

Optionally, the SAR raw data is divided into scenes to obtain a scene of SAR raw echo data, and the range data in the scene of SAR raw echo data is filled with zeros in the center to form standard scene SAR echo data, which includes: reading the SAR raw data, arranging the range data in sequence along the azimuth direction to form a scene of SAR raw echo data; centering the range data in the scene of SAR raw echo data, and filling the range data with zeros before and after to the number of range echo data processing points to form standard scene SAR echo data.

Another aspect of the present invention provides a SAR range reference signal processing device, comprising: a first generating module, used to time-normalize the SAR transmission pulse width to obtain a SAR linear frequency modulation signal, and fill the SAR linear frequency modulation signal with zeros to the range pulse compression processing points to generate a linear frequency modulation reference signal; a second generating module, used to extract SAR internal calibration loop sample data to obtain an initial internal calibration loop response signal, pre-fill the initial internal calibration loop response signal with zeros to the range pulse compression processing points, and complete mean processing to generate an internal calibration response signal; a first constructing module, used to perform pulse compression on the linear frequency modulation reference signal and the internal calibration response signal to obtain an internal calibration pulse compression signal, and pre-fill the internal calibration response signal with zeros, The delay compensation is completed and an internal calibration reference signal is constructed; a double fitting module is used to perform double polynomial fitting of least squares and orthogonal polynomials on the internal calibration reference signal to obtain a second fitting polynomial of amplitude and phase; a second construction module is used to construct a polynomial constant model based on the second fitting polynomial of amplitude and phase and fill the polynomial constant model with zeros in the center to obtain a range reference signal; a third generation module is used to divide the SAR raw data into scenes to obtain a scene of SAR raw echo data, and fill the range data in the scene of SAR raw data with zeros in the center in turn to form standard scene SAR echo data; a third construction module is used to perform range pulse compression on the standard scene SAR echo data and the range reference signal in turn to construct a range Doppler image.

(III) Beneficial effects

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

(1) In the prior art, the range reference function is a linear frequency modulation pulse signal, and the variable range of its time domain signal is the SAR transmission pulse width, and the value is usually in the microsecond order. When fitting the polynomial, the fitting coefficients above the second order are too small, and it is difficult to ensure the accuracy of the model. The present invention adopts a linear frequency modulation signal model of SAR radar pulse width time normalization, and its pulse width time variation range is unified to between -1 and 1, which overcomes the problem of too small polynomial coefficients after numerical fitting and adapts to the numerical fitting of polynomials.

(2) The present invention moves the SAR internal calibration response signal forward to the origin through time delay compensation of the SAR internal calibration response signal, thereby solving the problem that the further the interval of the fitting node distribution deviates from the origin, the more seriously the normal equation group becomes ill-conditioned in the polynomial fitting. The 10th-order polynomial fitting of the amplitude and phase numerical curves of the internal calibration reference signal is realized. The square error of the amplitude fitting after fitting is ≤3.3× ^10-10 ; the square error of the phase fitting is ≤1.5× ^10-9 , which meets the fitting accuracy.

(3) In the prior art, the amplitude and phase numerical curve fitting of the internal calibration reference signal generally adopts a single polynomial fitting or an orthogonal (Legendre) polynomial fitting. These two fitting methods cannot perform high-precision fitting of random interference signals on the amplitude and phase numerical curves. The present invention adopts a dual fitting method of least squares and orthogonal polynomials: first, a high-order (above 10th order) least squares fitting polynomial is used to fit the inherent characteristics of the amplitude and phase numerical curves to construct a smooth fitting curve; then, an orthogonal polynomial quadratic fitting is performed. Due to the orthogonality of the fitting results, the coefficients of high-price items that tend to zero can be easily set to zero, which can effectively remove random errors. The distance reference signal constructed by the double polynomial fitting is used as a matching function. After pulse compression, it can approach the response effect of an ideal point target.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 schematically shows a flowchart of a method for processing a SAR range reference signal according to an embodiment of the present invention.

FIG. 2 is a flowchart of performing least squares and orthogonal polynomial fitting of a double polynomial on an internal calibration reference signal according to an embodiment of the present invention.

FIG. 3 is a curve showing the amplitude value of the initial internal calibration loop response signal according to an embodiment of the present invention.

FIG. 4 is a phase value curve of an initial internal calibration loop response signal according to an embodiment of the present invention.

FIG. 5 is an amplitude value curve to be fitted according to an embodiment of the present invention.

FIG. 6 is a phase value curve to be fitted according to an embodiment of the present invention.

FIG. 7 is a range Doppler image of a ground corner reflector (#3-15503) according to an embodiment of the present invention.

FIG. 8 is a range Doppler image of a ground corner reflector (#4-16160) according to an embodiment of the present invention.

9 is a comparison result of the pulse compression effect with the ideal point target response for a ground corner reflector (#3-15503) using the range reference signal H _fit (t) and the linear frequency modulation reference signal H _ref (t) according to an embodiment of the present invention as matching functions.

FIG. 10 is a comparison result of the pulse compression effect with the ideal point target response for a ground corner reflector (#4-16160) using the range reference signal H _fit (t) and the linear frequency modulation reference signal H _ref (t) according to an embodiment of the present invention as matching functions.

FIG. 11 schematically shows a block diagram of a SAR range reference signal processing device according to an embodiment of the present invention.

DETAILED DESCRIPTION

In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present invention. However, it is obvious that one or more embodiments may also be implemented without these specific details. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

It should be noted that, in the embodiments of the present invention, the appearance of "first" and "second" is only for distinguishing technical terms and convenience of description, and should not be understood as limiting the embodiments of the present invention. The terms "include", "comprise", etc. indicate the existence of the features, steps, operations and/or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

It should be understood that the number of points i on the horizontal axis in the drawings of the present invention is the number of sampling points N _rr Δt of the linear frequency modulation signal that divides a certain time between -1 and 1, so that

Where: Δt is the time step, t is the signal processing time, and -1≤t≤1 is satisfied. That is, within the preset time of signal processing, one sampling point is formed every time step.

FIG1 schematically shows a flow chart of a method for processing a SAR range reference signal according to an embodiment of the present invention.

As shown in FIG. 1 , the SAR range reference signal processing method according to the embodiment of the present invention may include, for example, operations S1 to S7 .

Referring to FIG. 1 , the present invention provides a SAR range reference signal processing method, comprising the following steps:

S1, time-normalize the SAR transmission pulse width to obtain a SAR linear frequency modulation signal, and fill the SAR linear frequency modulation signal with zeros to the range pulse compression processing points to obtain a linear frequency modulation reference signal.

Specifically, the linear frequency modulation signal h _ref (t) normalized by time using the SAR transmission pulse width is:

Wherein, B is the SAR system bandwidth; T is the transmit pulse width; and t is the time.

The linear frequency modulation signal h _ref (t) is centered, and zero padding is performed on the left and right sides of the signal. In order to achieve the number of zero padding points for the range pulse compression processing, the number of zero padding points on one side (left and right) N _r is: N _r = (NN _r - N _rr )/2, where NN _r is the number of processing points for the range pulse compression; N _rr is the number of sampling points of the linear frequency modulation signal, and N _rr = T × Samp, where Samp is the sampling frequency.

From the above, the linear frequency modulation reference signal H _ref (t) is:

In one embodiment of the present invention, the method of step S1 is described using original parameters of a SAR radar system.

The parameters of a SAR radar system include: SAR system bandwidth B is 360MHz; transmit pulse width T is 25μm; sampling frequency Samp is 480MHz; and the number of processing points _NNr of range-direction pulse compression is 28384.

The time-normalized linear frequency modulation signal h _ref (t) is:

It can be obtained that the number of sampling points N _rr of the linear frequency modulation signal is 12000, and the number of zero padding on one side (left side and right side) N _r is: N _r =(NN _r -N _rr )/2=8192.

The linear frequency modulation reference signal H _ref (t) is

S2, extracting the SAR internal calibration loop sample data from the SAR raw data, obtaining the initial internal calibration loop response signal, pre-padded it with zeros to the range pulse compression processing points, and completing the mean processing to obtain the internal calibration response signal.

The SAR raw data may be, for example, the actual acquisition task data segment - SAR.raw data file, and the SAR internal calibration loop sample data in the file header is read. The SAR internal calibration loop sample data includes transmitting internal calibration sample data, receiving internal calibration sample data and public internal calibration sample data.

Specifically, the sample data of the SAR internal calibration loop in the file header is read from the actual task data segment - SAR.raw data file, and the initial internal calibration loop response signal h _cal (t) is obtained as:

Among them, T _cal is the transmitting internal calibration sample data; R _cal is the receiving internal calibration sample data; CE _cal is the public internal calibration sample data.

The initial internal calibration loop response signal h _cal (t) is placed in front, and the signal h _cal (t) is padded with zeros at the rear, and the number of padded zeros NN _p is NN _p =NN _r -N _p , wherein NN _r is as described above; N _p is the number of sampling points of the initial internal calibration loop response signal.

The internal calibration loop response signal H _cal (t) is obtained as:

After averaging, the internal calibration response signal is obtained. for:

Wherein, N is the total number of internal calibrations, a positive integer; j is the number of internal calibrations, and its value is 1, 2, 3, ..., N; H _cal,j is the internal calibration loop response signal of the jth internal calibration.

In one embodiment of the present invention, sample data of the SAR internal calibration loop in the file header is read from the actual acquisition task data segment - SAR.raw data file to obtain the initial internal calibration loop response signal h _cal (t).

Fig. 3 is a curve of the amplitude value of the initial internal calibration loop response signal according to an embodiment of the present invention. Fig. 4 is a curve of the phase value of the initial internal calibration loop response signal according to an embodiment of the present invention.

3 and 4, the number of sampling points _Np of the internal calibration loop is 16128, the number of internal calibration times N is 4, and _NNr is as described above. It can be obtained that the number of zero padding _NNp is: _NNp = 28384-16128 = 12256.

The internal calibration loop response signal H _cal (t) is:

Therefore, the internal calibration response signal after mean processing can be obtained for:

S3, pulse compressing the linear frequency modulation reference signal and the internal calibration response signal to obtain an internal calibration pulse pressure signal, subtracting the peak position of the internal calibration pulse pressure signal from the ideal pulse pressure position of the linear frequency modulation signal to obtain the time delay, pre-padded the internal calibration response signal with zeros to complete the time delay compensation, and constructing an internal calibration reference signal.

The pre-zero filling includes: pre-adding the internal calibration response signal, and filling the rear side of the internal calibration response signal with zeros to the number of pulse compression processing points in the range direction;

Among them, completing the delay compensation includes: taking the subscript variable value corresponding to the peak value of the internal calibration pulse pressure signal minus the ideal pulse pressure position of the linear frequency modulation signal (1/2 of the number of sampling points) as the delay amount, taking the delay amount as the subscript starting position of the internal calibration response signal after pre-padded with zeros, moving the internal calibration response signal after pre-padded with zeros forward, and padding the back side of the internal calibration response signal with zeros, and the number of zeros padded on the back side is the delay amount.

Specifically, the linear frequency modulation reference signal H _ref (t) is combined with the internal calibration response signal Pulse compression is performed to obtain the internal calibration pulse pressure signal y _cal (t) as

Among them, fft is the Fourier transform symbol; ifft is the inverse Fourier transform symbol; conj is the complex conjugate symbol.

The variable subscript i _cal corresponding to the amplitude peak value of the signal y _cal (t) is i _cal =|max(y _cal (t))| _i , where i is the subscript corresponding to the variable. Then the delay amount of the delay compensation is Δ _cal =i _cal -N _rr /2, where N _rr is as described above.

The internal calibration response signal Pre-padded with zeros to the number of pulse compression processing points NN _p in the range direction. Further, the delay amount of the delay compensation is used as the subscript starting position of the internal calibration response signal after pre-padded with zeros, and the internal calibration reference signal after the delay amount Δ _cal compensation is obtained as follows:

in, for The starting position of the signal variable subscript; for The variable subscript final position of the signal.

In one embodiment of the present invention, the linear frequency modulation reference signal H _ref (t) and the internal calibration response signal Pulse compression is performed to obtain an internally calibrated pulse pressure signal y _cal (t).

The variable subscript corresponding to the amplitude peak value of the internal calibration pulse pressure signal y _cal (t) is i _cal =|max(y _cal (t))| _i =6468, and the delay amount of the delay compensation is Δ _cal =i _cal -N _rr /2=468, wherein N _rr is as described above.

The internal calibration response signal The pre-padded zeros are added to the number of pulse compression processing points NN _p in the range direction, NN _p being as described above. Further, the delay is used as the subscript starting position of the internal calibration response signal after the pre-padded zeros, and the internal calibration reference signal after the delay amount Δ _cal compensation is obtained as follows:

S4, performing double polynomial fitting of least squares and orthogonal polynomial on the internal calibration reference signal to obtain a second fitting polynomial of amplitude and phase.

The amplitude and phase numerical curves of the internal calibration reference signal obtained in step S3 are obtained, and polynomial fitting is performed respectively. The polynomial fitting can be, for example, a double fitting of least squares and orthogonal polynomials. After the polynomial fitting, the second fitting polynomial of amplitude and the second fitting polynomial of phase are obtained.

FIG. 2 is a flow chart of performing polynomial fitting on an internal calibration reference signal according to an embodiment of the present invention.

Referring to FIG. 2 , performing polynomial fitting on the internal calibration reference signal includes the following sub-steps:

S41, acquiring the amplitude and phase value curves to be fitted from the internal calibration reference signal.

The internal calibration reference signal obtained in step S3 has completed the delay compensation of the internal calibration response signal, so the amplitude value curve can be directly read, and its average is taken and inverted to obtain the amplitude value curve to be fitted. The phase value curve of the internal calibration reference signal obtained after step S3 is directly read as the phase value curve to be fitted.

Specifically, for the internal calibration reference signal in step S3, the mean value of its amplitude value curve is taken and inverted to obtain the amplitude value curve to be fitted: for:

Where, _Nrr is as mentioned above; _ti is The variable subscript of the signal, where i is the number of points and takes values of 1, 2, ..., N _rr .

Accordingly, the phase value curve to be fitted is for:

In one embodiment of the present invention, the amplitude value curve of the internal calibration reference signal in step S3 is directly read, its average is taken and inverted to obtain the amplitude value curve to be fitted:

FIG. 5 is an amplitude value curve to be fitted according to an embodiment of the present invention.

At the same time, the phase value curve of the internal calibration reference signal is directly read to obtain the phase value curve to be fitted.

FIG. 6 is a phase value curve to be fitted according to an embodiment of the present invention.

S42, performing least squares polynomial fitting on the amplitude and phase numerical curves to be fitted according to the initial fitting order, to obtain preliminary fitting polynomials of amplitude and phase.

Specifically, the amplitude and phase numerical curves to be fitted are fitted as follows:

in, are the least square fitting coefficients of amplitude and phase respectively; n ₀ is the initial fitting order; They are the preliminary fitting polynomial for amplitude and the preliminary fitting polynomial for phase respectively.

In addition, let the amplitude least squares fitting coefficient matrix and the phase least squares fitting coefficient matrix be expressed as Defined as:

In one embodiment of the present invention, the amplitude value curve to be fitted as shown in FIG5 is subjected to least squares polynomial fitting to obtain a preliminary amplitude fitting polynomial as follows:

Among them, the initial fitting order n ₀ is 10, and its least squares fitting coefficient matrix for

Similarly, the phase numerical curve to be fitted shown in FIG6 is fitted by least squares polynomial fitting to obtain the initial phase fitting polynomial:

Among them, the initial fitting order n ₀ is 10, and its least squares fitting coefficient matrix for

S43, obtaining the square error of the preliminary fitting polynomial of the amplitude and phase, and judging whether the fitting result is not greater than the preset square error: if the fitting result is not greater than the preset square error, the fitting accuracy requirement is met; otherwise, increasing the fitting order until the increased square error can still meet the fitting accuracy requirement, and obtaining the highest fittable order and the first fitting polynomial of the amplitude and phase;

Specifically, the square errors of the amplitude and phase preliminary fitting polynomials obtained in step S42 are respectively

Where, NN _r is as described above; are the amplitude and phase numerical curves to be fitted, Preliminary fitting polynomials for amplitude and phase, respectively, are the squared amplitude and phase errors.

The preset square error may include, for example, an amplitude preset square error and a phase preset square error. The amplitude preset square error may be, for example, 3.3×10 ⁻¹⁰ , and the phase preset square error may be, for example, 1.5×10 ⁻⁹ . The preset square error may be set as required, and the present invention does not impose any specific limitation.

Increasing the fitting order will increase the square error. Specifically, it is judged whether the fitting result is not greater than the preset square error. For example, if the square error of the amplitude of the fitting is D≤3.3× ^10-10 , and the square error of the phase of the fitting is D≤1.5× ^10-9 , then the fitting error requirement is met. At this time, the first fitting polynomial of the amplitude and phase is the preliminary fitting polynomial of the amplitude and phase obtained in step S42; otherwise, return to step S42, increase the fitting order, and continue to perform the least squares polynomial fitting until the increased square error meets the fitting accuracy requirement, and the first fitting polynomial of the amplitude and phase is obtained, which is expressed as and At this time, the amplitude and phase first fitting polynomial is different from the amplitude and phase preliminary fitting polynomial obtained in step S42.

In one embodiment of the present invention, the least squares errors of the amplitude preliminary fitting polynomial and the phase preliminary fitting polynomial are calculated as follows:

From the above, it can be seen that the fitting results all meet the preset square error requirements of amplitude and phase. At this time, the highest fitting order is 10, and the first-order fitting polynomials of amplitude and phase are obtained. At this time, the first-order fitting polynomials of amplitude and phase are equivalent to the preliminary fitting polynomials of amplitude and phase obtained in step S42.

S44, performing orthogonal polynomial fitting on the amplitude and phase first fitting polynomials respectively according to the highest fittable order to obtain amplitude and phase orthogonal fitting polynomials.

Specifically, the first fitting polynomials of amplitude and phase are fitted as:

in, are the orthogonal fitting coefficients of amplitude and phase respectively; t is the time; n is the highest fitting order; are orthogonal fitting polynomials for amplitude and phase respectively; _Pi (t) is the orthogonal basis function, _Pi (t) is:

In addition, let the amplitude orthogonal fitting coefficient matrix and the phase orthogonal fitting coefficient matrix be expressed as Defined as:

In one embodiment of the present invention, the amplitude obtained in step S43 is first fitted with a polynomial The numerical curve of is fitted with an orthogonal polynomial, and the amplitude orthogonal fitting polynomial is obtained as follows:

Among them, the highest fitting order n is 10, _Pi (t) is the orthogonal basis function, and the orthogonal fitting coefficient matrix is for:

The first phase polynomial fitted to the phase obtained in step S43 is The numerical curve of is fitted with an orthogonal polynomial, and the phase orthogonal fitting polynomial is obtained as follows:

Among them, the highest fitting order n is 10, _Pi (t) is the orthogonal basis function, and the orthogonal fitting coefficient matrix is for:

S45, optimizing the coefficients of the amplitude and phase orthogonal fitting polynomials respectively to form second-order fitting polynomials of amplitude and phase.

The coefficient optimization may include, for example:

The high-order coefficients whose values in the amplitude orthogonal fitting polynomial are close to zero are truncated, and the low-order coefficients with larger values and effective values are taken to form the second amplitude fitting polynomial;

The high-order coefficients whose values in the phase orthogonal fitting polynomial are close to zero are truncated, and the low-order coefficients with larger values and effective values are taken, and the first-order coefficients and the second-order coefficients are set to zero to form the second-order fitting polynomial of the phase.

Specifically, in the magnitude orthogonal polynomial coefficient matrix In the process, the coefficients whose values are less than the first preset value are truncated to obtain the amplitude orthogonal polynomial coefficient matrix for:

The first preset value may be, for example, 0.1. The first preset value may be set as required, and the present invention does not impose any specific limitation thereto.

The corresponding amplitude is the second fitting polynomial for:

Specifically, in the phase orthogonal polynomial coefficient matrix In the above example, the first-order coefficients and the second-order coefficients are set to zero, and the coefficients whose values are less than the second preset value are truncated to obtain the phase orthogonal polynomial coefficient matrix. for:

The second preset value may be, for example, 0.02. The second preset value may be set as required, and the present invention does not impose any specific limitation thereto.

The corresponding phase second fitting polynomial for:

In one embodiment of the present invention, in the 10th order amplitude orthogonal polynomial coefficient matrix In the equation, the coefficients with values less than 0.1 are truncated to obtain the second-order amplitude orthogonal fitting polynomial for:

Wherein, referring to step S44, P _k (t) is defined as:

And, the amplitude orthogonal polynomial coefficient matrix for

In one embodiment of the present invention, in the phase orthogonal polynomial coefficient matrix In the equation, the first-order coefficients and the second-order coefficients are set to zero, and the coefficients with values less than 0.02 are truncated to obtain the sixth-order phase fitting orthogonal polynomial.

Wherein, referring to step S44, _Pi (t) is defined as:

And, the phase orthogonal polynomial coefficient matrix for

S5, based on the second fitting polynomial of the amplitude and phase, construct a polynomial constant model and fill the polynomial constant model with zeros in the center to obtain a range reference signal.

Specifically, the second fitting polynomial based on the amplitude and phase obtained in step S5 is Calculate the amplitude and phase polynomials respectively to obtain the amplitude constant polynomial A _fit (t) and the phase constant polynomial Construct the polynomial constant model h _fit (t) as:

The polynomial constant model h _fit (t) is centered, and zeros are padded on the left and right sides of h _fit (t) respectively. The number N _r of zeros padded on one side (left and right) is as described in step S1.

It can be obtained that the range reference signal H _fit (t) is:

In one embodiment of the present invention, for the second-order amplitude orthogonal polynomial and the 6th order phase quadrature polynomial Perform polynomial calculations respectively to obtain the amplitude constant polynomial A _fit (t) and the phase constant polynomial Correspondingly, the polynomial constant model h _fit (t) is obtained as:

in:

The number of zero padding _Nr is 8192 as described in S1, and the obtained range reference signal H _fit (t) is:

S6, dividing the SAR original data into scenes to obtain a scene of SAR original echo data, and filling the distance in the scene of SAR original echo data with zeros in the center of the data to form standard scene SAR echo data.

Step S6 includes the following sub-steps:

S61, reading SAR raw data, and sequentially arranging the range data along the azimuth direction to form a scene of SAR raw echo data;

S62, centering the range data in a scene of SAR original echo data, and padding the range data with zeros before and after to the number of range data processing points to form standard scene SAR echo data.

Specifically, a scene of SAR raw echo data is separated from the SAR.raw raw data as s(l _α ,j _β )

Where: l _α is the azimuth data; α is the number of sampling points in the azimuth direction; j _β is the range data; β is the number of sampling points in the range direction.

The range data j _β in the scene SAR echo data is filled with zeros at the center to the range data processing point number NN _r to form the standard scene SAR echo data:

In one embodiment of the present invention, a scene of SAR raw echo data is read from SAR.raw raw data as s(l _α , j _β ), wherein l _α is azimuth data, and the number of sampling points is α=18000; j _β is range data, and the number of sampling points is β=16384. NN _r is 28384 as described in S1.

Fill the range data j _β with zeros at the center to the range data processing point number NN _r , and the standard scene SAR echo data can be obtained as follows:

S7, performing range pulse compression on the standard scene SAR echo data and the range reference signal in sequence to obtain a range Doppler image.

Specifically, the range reference signal H _fit (t) obtained in step S6 and the standard scene SAR echo data s (l _α , j _k ) obtained in step S5 are sequentially subjected to range pulse compression to obtain a range Doppler image |I _fit (τ _α , r _k )|

|I(τ _α , r _k )|=|ifft(fft(S(l _α , j _k ))×conj(fft(H _fit (t))))|

Among them, fft is the Fourier transform symbol; ifft is the inverse Fourier transform symbol; conj is the complex conjugate symbol.

In one embodiment of the present invention, the range reference signal H _fit (t) and the standard scene SAR echo data s (l _α , j _k ) are sequentially subjected to range pulse compression to obtain a range Doppler image |I _fit (τ _α , r _k )|.

|I _fit (τ _α , r _k )|=|ifft(fft(S(l _α , j _k ))×conj(fft(H _fit (t))))|

In the embodiment of the present invention, there is no strict sequence of steps. For example, operations S1, S2, and S6 can be executed in parallel, and operations S5 and S6 can also be executed in parallel. The present invention does not limit the specific sequence of steps.

The SAR.raw raw data of the embodiment of the present invention includes multiple ground corner reflector signals, so the multiple ground corner reflector signals are pulse compressed in the range Doppler image |I _fit (τ _α , r _k )|, and the technical effect of the method of the present invention is explained with the actual SAR echo raw data results containing the ground corner reflector target.

Fig. 7 is a range Doppler image of a ground corner reflector (#3-15503) according to an embodiment of the present invention. Fig. 8 is a range Doppler image of a ground corner reflector (#4-16160) according to an embodiment of the present invention.

Referring to FIG. 7 , the distance Doppler image of the ground corner reflector #3-15503 obtained by the method according to the present invention is: Its peak value is

Referring to FIG8 , the distance Doppler image of the ground corner reflector #4-16160 obtained by the method according to the present invention is: Its peak value is

In addition, in order to compare the pulse compression effect, the linear frequency modulation reference signal H _ref (t) obtained in step S1 and the standard scene SAR echo data s (l _α , j _k ) obtained in step S6 are directly subjected to range pulse compression in sequence to obtain the reference range Doppler image |I _ref (τ _α , r _k )|:

|I _ref (τ _α , r _k )|=|ifft(fft(S(l _α , j _k ))×conj(fft(H _ref (t))))|

From the above formula, we can get the reference distance Doppler image of the ground corner reflector #3-15503: And, the reference range Doppler image of the ground corner reflector #4-16160 is:

Therefore, for the ground corner reflector #3-15503, taking H _fit (t) as the reference function, the obtained range Doppler image peak is Expand along the distance And, taking H _ref (t) as the reference function, the range Doppler image peak is obtained Expand along the distance

In addition, the ideal point target responds to pulse compression with the linear frequency modulation reference signal H _ref (t) as the point target:

|I _ideal (t)|=|ifft(fft(H _ref (t))×conj(fft(H _ref (t))))|

From the above formula, it can be obtained that the peak value of the ideal point target response along the distance direction is |I _ideal (14192-20: 14192+20)|.

Table 1 gives a comparison of the pulse compression effects under the conditions of the embodiments, wherein for each ground corner reflector, three range Doppler images of the present invention, the reference range Doppler image and the ideal point target response are used as comparisons to test the pulse compression results of the ground corner reflector of the method described in the present invention.

Table 1

9 is a comparison result of the pulse compression effect with the ideal point target response for a ground corner reflector (#3-15503) using the range reference signal H _fit (t) and the linear frequency modulation reference signal H _ref (t) according to an embodiment of the present invention as matching functions.

Moreover, the range Doppler images obtained in Figures 7 and 8 are both three-dimensional images, and their range expansion functions are represented by taking 20 sampling points on the left and right sides of the peak position. In order to facilitate the observation of the comparison effect, Figures 9 and 10 in this application are both images of the peak range expansion function formed by taking 3 sampling points on the left and right sides of the peak position, and the images are both one-dimensional images.

The short dashed line image in FIG9 is a pulse compression effect using the range reference signal H _fit (t) of the present invention as a matching function, and its peak value along the range expansion function is:

The long dashed line image in FIG9 is the pulse compression effect with the linear frequency modulation reference signal H _ref (t) as the matching function, and its peak value along the distance expansion function is:

The solid line image in FIG9 is the pulse compression effect of the ideal point target response, and its peak value along the distance expansion function is |I _ideal (14192-3:14192+3)|.

FIG10 is a comparison result of the pulse compression effect with the ideal point target response for the ground corner reflector (#4-16160) using the range reference signal H _fit (t) and the linear frequency modulation reference signal H _ref (t) of an embodiment of the present invention as matching functions, wherein:

The short dashed line image in FIG10 is a pulse compression effect using the range reference signal H _fit (t) of the present invention as a matching function, and its peak value along the range expansion function is:

The long dashed line image in FIG10 is the pulse compression effect with the linear frequency modulation reference signal H _ref (t) as the matching function, and its peak value expansion function along the distance direction is:

The solid line image in FIG10 is the pulse compression effect of the ideal point target response, and its peak value along the range expansion function is |I _ideal (14192-3:14192+3)|.

Referring to Figures 9 and 10, the range reference signal H _fit (t) and the linear frequency modulation reference signal H _ref (t) are matching functions. When compared with the range Doppler images obtained after range pulse compression of the actual SAR echo data containing a ground corner reflector target, it can be seen that the pulse compression result of the range reference signal H _fit (t) of the ground corner reflector is closer to the ideal point target response effect.

In an embodiment of the present invention, the transmission pulse time width of the SAR linear frequency modulation signal is normalized to facilitate the selection of the polynomial fitting coefficient; the internal calibration response signal with a time delay is moved forward to the origin to achieve the node distribution of the polynomial fitting starting from the origin; the amplitude and phase numerical curves of the internal calibration reference signal are double fitted by least squares and orthogonal polynomials to construct a range reference signal. The SAR range reference signal constructed by the present invention fits the inherent nonlinear component of the SAR internal calibration response signal, while suppressing random spurious and crosstalk. The present invention overcomes the peak offset, main lobe broadening and side lobe rise of the simple low-order polynomial numerical fitting model after pulse compression, and can meet the numerical stability and accuracy requirements of the SAR range matching function. After pulse compression testing with actual SAR echo data containing ground corner reflector targets, the results are close to the ideal point target response effect.

Fig. 11 schematically shows a block diagram of a SAR range reference signal processing device according to an embodiment of the present invention. The device can execute the above-mentioned SAR range reference signal processing method.

As shown in FIG. 11 , the SAR range reference signal processing device 300 according to the embodiment of the present invention may include, for example, a first generating module 310 , a second generating module 320 , a first constructing module 330 , a double fitting module 340 , a second constructing module 350 , a third generating module 360 and a third constructing module 370 .

The first generating module 310 is used to perform time normalization on the SAR transmission pulse width to obtain a SAR linear frequency modulation signal, and to fill the SAR linear frequency modulation signal with zeros to the range pulse compression processing points to generate a linear frequency modulation reference signal;

The second generating module 320 is used to extract the SAR internal calibration loop sample data, obtain the initial internal calibration loop response signal, pre-fill the initial internal calibration loop response signal with zeros to the number of range pulse compression processing points, and perform mean processing to generate the internal calibration response signal;

A first construction module 330 is used to perform pulse compression on the linear frequency modulation reference signal and the internal calibration response signal to obtain an internal calibration pulse compression signal, and to perform pre-zero padding and delay compensation on the internal calibration response signal to construct an internal calibration reference signal;

A double fitting module 340 is used to perform polynomial fitting on the internal calibration reference signal to obtain a second-order fitting polynomial for amplitude and a second-order fitting polynomial for phase;

A second construction module 350 is used to construct a polynomial constant model according to the second fitting polynomial of the amplitude and phase, and fill the polynomial constant model with zeros in the middle to obtain a range reference signal;

The third generation module 360 is used to divide the SAR raw data into scenes to obtain a scene of SAR raw echo data, and fill the distance data in the scene of SAR raw data with zeros in sequence to form standard scene SAR echo data;

The third construction module 370 is used to perform range pulse compression on the standard scene SAR echo data and the range reference signal in sequence to construct a range Doppler image.

It should be noted that the implementation method of the SAR range reference signal processing device part is similar to the implementation method of the SAR range reference signal processing method part, and the technical effects achieved are also similar. For specific details, please refer to the implementation method part of the above-mentioned SAR range reference signal processing method, which will not be repeated here.

The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. a SAR range reference signal processing method, is characterized in that, comprising: Carrying out time normalization to the SAR emission pulse width to obtain a SAR chirp signal, and filling the center of the SAR chirp signal with zeros to the number of pulse compression processing points in the range direction to obtain a chirp reference signal; Extract the sample data of the SAR internal calibration loop from the SAR raw data, obtain the initial internal calibration loop response signal, fill it with zeros in front of it to the number of range pulse compression processing points, and complete the mean value processing to obtain the internal calibration response signal; Performing pulse compression on the chirp reference signal and the internal calibration response signal to obtain an internal calibration pulse pressure signal, subtracting the peak position of the internal calibration pulse pressure signal from the ideal pulse pressure position of the chirp signal to obtain a time delay, performing pre-zero padding on the internal calibration response signal, completing time delay compensation, and constructing an internal calibration reference signal; Carrying out double polynomial fitting of least squares and orthogonal polynomials to the internal calibration reference signal to obtain a second double fitting polynomial of magnitude and phase; Based on the second-fold fitting polynomial of the amplitude and phase, a polynomial constant value model is constructed and the polynomial constant value model is centered and filled with zeros to obtain a range reference signal; Split the original SAR data into one scene to obtain the original SAR echo data of one scene, and fill the distance data in the original SAR data of one scene with zeros in order to form the SAR echo data of the standard scene; Sequentially performing range pulse compression on the standard scene SAR echo data and the range reference signal to obtain a range Doppler image; Wherein, the double polynomial fitting of the least squares and orthogonal polynomials on the internal calibration reference signal includes: Obtain the magnitude and phase numerical curves to be fitted from the internal calibration reference signal; According to the initial fitting order, the magnitude and phase numerical curves to be fitted are respectively subjected to least squares polynomial fitting to obtain a preliminary fitting polynomial of magnitude and phase; Calculate the square error of the preliminary fitting polynomial of the amplitude and phase, and judge whether the fitting result is not greater than the preset square error: if the fitting result is not greater than the preset square error, then the fitting accuracy requirement is met; otherwise, the fitting order is increased until the increased square error can still meet the fitting accuracy requirement, and the highest fitting order is obtained, as well as the first re-fitting polynomial of the amplitude and phase; According to the highest fitable order, perform orthogonal polynomial fitting on the amplitude and phase first re-fitting polynomials, respectively, to obtain amplitude and phase orthogonal fitting polynomials; The coefficients of the amplitude and phase quadrature fitting polynomials are respectively optimized to form a second-order fitting polynomial of amplitude and phase. 2. The SAR range-to-reference signal processing method according to claim 1, wherein said time normalization is carried out to the SAR emission pulse width, and obtaining the SAR chirp signal comprises: The SAR chirp signal is constructed as: Wherein, B is the SAR system bandwidth; T is the transmission pulse width; t is the time, its time step Δt=2/(T·Samp), Samp is the sampling frequency, and the number of sampling points N _rr =T·Samp of the chirp signal h _ref (t). 3. The SAR range reference signal processing method according to claim 1, wherein the SAR internal calibration loop sample data comprises: transmitting internal calibration sample data, receiving internal calibration sample data and public internal calibration sample data. 4. The SAR range-to-reference signal processing method according to claim 1, wherein said internal calibration response signal is pre-filled with zeros, and completion of delay compensation includes: Wherein, the preceding zero padding includes: prepending the internal calibration response signal, padding the rear side of the internal calibration response signal to the number of pulse compression processing points in the range direction; Wherein, the completion of the delay compensation includes: subtracting the subscript variable value corresponding to the peak value of the internal calibration pulse pressure signal, subtracting the ideal pulse pressure position of the chirp signal as a delay amount, using the delay amount as the subscript starting position of the internal calibration response signal that has been zero-filled before, moving the internal calibration response signal that has been zero-filled before the front, padding the internal calibration response signal with zeros at the rear side, and the number of zero padding is the delay amount, and the ideal pulse pressure position is 1/2 of the number of sampling points. 5. The SAR range-to-reference signal processing method according to claim 1, wherein said carrying out least squares polynomial fitting to said magnitude to be fitted and phase numerical curve respectively comprises: The amplitude and phase numerical curves to be fitted are fitted as: in, are the least square fitting coefficients of amplitude and phase respectively; t is the time; n ₀ is the initial fitting order, are the magnitude preliminary fitting polynomial and the phase preliminary fitting polynomial, respectively. 6. The SAR range-oriented reference signal processing method according to claim 1, wherein said carrying out orthogonal polynomial fitting respectively to said amplitude and phase first heavy fitting polynomial comprises: Fit the magnitude and phase first-fit polynomials to: in, are the orthogonal fitting coefficients of the amplitude and phase respectively; t is the moment; n is the highest fitting order; are the amplitude and phase orthogonal fitting polynomials; P _i (t) is the orthogonal basis function, and P _i (t) is: 7. The SAR range-to-reference signal processing method according to claim 1, wherein said coefficient optimization comprises: Perform truncation processing on the high-order coefficients whose coefficient values tend to zero in the amplitude orthogonal fitting polynomial, and take the relatively large and effective low-order coefficients to form the second-fold amplitude fitting polynomial; Perform truncation processing on the high-order coefficients whose coefficient values tend to be zero in the phase quadrature fitting polynomial, take the larger and effective lower-order coefficients and set the first-order coefficients and second-order coefficients to zero to form the second phase fitting polynomial. 8. The SAR range-direction reference signal processing method according to claim 1, wherein the SAR original data is divided into scenes to obtain a scene of SAR original echo data, and the distance data in the scene of SAR original echo data is centered with zeros to form a standard scene SAR echo data comprising: Read the original SAR data, and arrange the range data along the azimuth direction to form a scene of SAR original echo data; Centering the range data in the original SAR echo data of one scene, padding the range data with zeros up to the number of range echo data processing points to form the standard scene SAR echo data. 9. A SAR range reference signal processing device, characterized in that, comprising: The first generating module is used to time-normalize the SAR transmission pulse width to obtain a SAR chirp signal, and center zero-fill the SAR chirp signal to the range pulse compression processing points to generate a chirp reference signal; The second generation module is used to extract the sample data of the SAR internal calibration loop, obtain the initial internal calibration loop response signal, pre-fill the initial internal calibration loop response signal with zeros to the range pulse compression processing points, and complete the mean value processing to generate the internal calibration response signal; The first building block is used to perform pulse compression on the chirp reference signal and the internal calibration response signal to obtain an internal calibration pulse pressure signal, and perform pre-zero padding on the internal calibration response signal to complete time delay compensation, and construct an internal calibration reference signal; The double fitting module is used to perform double polynomial fitting of least squares and orthogonal polynomials on the internal calibration reference signal to obtain a second double fitting polynomial of amplitude and phase; The second building block is used for second re-fitting polynomials according to the amplitude and phase, constructing a polynomial constant value model and centering the polynomial constant value model to obtain a range reference signal; The third generation module is used to divide the SAR original data into scenes to obtain the original SAR echo data of one scene, and fill the distance data in the original SAR data of one scene with zeros in order to form the SAR echo data of the standard scene; The third building block is used to sequentially perform range pulse compression on the standard scene SAR echo data and the range reference signal to construct a range Doppler image; Wherein, the double fitting module is specifically used for: Obtain the magnitude and phase numerical curves to be fitted from the internal calibration reference signal; According to the initial fitting order, the magnitude and phase numerical curves to be fitted are respectively subjected to least squares polynomial fitting to obtain a preliminary fitting polynomial of magnitude and phase; Calculate the square error of the preliminary fitting polynomial of the amplitude and phase, and judge whether the fitting result is not greater than the preset square error: if the fitting result is not greater than the preset square error, then the fitting accuracy requirement is met; otherwise, the fitting order is increased until the increased square error can still meet the fitting accuracy requirement, and the highest fitting order is obtained, as well as the first re-fitting polynomial of the amplitude and phase; According to the highest fitable order, perform orthogonal polynomial fitting on the amplitude and phase first re-fitting polynomials, respectively, to obtain amplitude and phase orthogonal fitting polynomials; The coefficients of the amplitude and phase quadrature fitting polynomials are respectively optimized to form a second-order fitting polynomial of amplitude and phase.