CN101685159A - Method for constructing spaceborne SAR signal high precision phase-keeping imaging processing platform - Google Patents
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Abstract
The present invention provides a method for constructing spaceborne SAR signal high precision phase-keeping imaging processing platform, comprising the following steps: 1) solving the spaceborne SAR data imaging processing parameters; 2) reading spaceborne SAR echo data in frame and storing in the form of two dimension complex array; 3) performing Fast Fourier Transform in the oriental direction;4) carrying out Doppler centroid circular shifting in the range-Doppler domain; 5) signal interpolating in range-Dopper domain; 6) performing Fast Fourier Transform in the distance direction; 7) performing distance migration correction and compression on data in wave-number domain, finishing focusing in distance direction and compensating residual complex constant phase terms; 8) performing FastInverse Fourier Transform in the distance direction; 9) focusing in oriental direction in range-Dopper domain and compensating residual complex constant phase terms; and 10) performing Fast Inverse Fourier Transform in the oriental direction and compensating linear phase error caused by circular shifting. The method can fast and flexibly finish the phase keeping-imaging processing of SAR signal.
Description
(I) technical field
The invention belongs to the field of Radar signal processing, relates to a method for constructing a high-precision phase-preserving imaging processing platform of a satellite-borne Synthetic Aperture Radar (SAR) signal, and particularly relates to a method for processing a satellite-borne SAR signal with high-precision phase information (phase preservation) based on a Chirp Scaling (CS) imaging processing algorithm.
(II) background of the invention
Synthetic Aperture Radar (SAR) satellite system technology has developed very rapidly in recent years. The SAR satellite is not limited by factors such as weather, geography, time and the like, can realize all-weather earth observation tasks in all seasons, and has certain penetration capacity, so that the SAR satellite is widely applied to aspects such as military reconnaissance, resource detection, ocean observation, ecological monitoring, quick rescue and the like.
The traditional SAR system has the imaging detection capability of two-dimensional high resolution, namely the slant range direction high resolution is obtained by utilizing a wide band signal, and the azimuth direction high resolution is obtained by utilizing a synthetic aperture signal processing method. Since the ground target area is a three-dimensional scene, conventional SAR imaging systems actually map three-dimensional space onto a two-dimensional slope plane. In order to obtain elevation information of a ground scene, the elevation information needs to be realized by interferometric synthetic aperture radar (InSAR) technology. The InSAR technology utilizes two spatially separated radars to perform independent two-dimensional imaging on the same target area, and then utilizes a phase interference processing technology to extract Elevation information so as to generate a high-precision Digital Elevation Model (DEM).
The InSAR concept was proposed and gradually developed in the early 70's of the 20 th century. The method obviously expands the application field of SAR imaging information, can acquire high-precision three-dimensional terrain information, can monitor small changes on the earth surface, has the time resolution of repeated monitoring up to several days, and can generate a high-precision and high-reliability global DEM database. In addition, the satellite-borne InSAR system can be used for researching the change condition of the surface features under extreme environments, such as the glacier change of south and north poles; and can also be used for detecting disastrous surface deformation, such as earthquake, volcanic eruption, landslide and the like. Therefore, the inssar height measurement technology is more and more highly emphasized by various high-tech countries, and is one of the current "hot" research directions in the field of microwave remote sensing.
The nature of the InSAR technology is that the interference phase information is used for inverting the elevation information of the earth surface through signal processing, so that the phase information (phase retention) is important for InSAR processing in the SAR imaging process. In the process of generating a Single Look Complex (SLC) image by SAR imaging processing, the degree of distortion of image phase information directly affects the elevation measurement accuracy of the InSAR system. In fact, the core of the InSAR processing flow is a series of operations performed around how to acquire accurate phase information, and the SAR imaging processing is used as the basis of the whole InSAR processing flow, the phase-preserving performance of the imaging processing directly affects the effect of subsequent interference processing, and the accuracy of phase maintenance directly affects the final InSAR height measurement accuracy. In summary, in the SAR imaging processing flow, it is very important to maintain the phase information of the target.
In order to realize the InSAR altimetry technology, two spatially separated radar antennas are required to observe the same target area, but in order to ensure the altitude measurement accuracy, the distance between the two radar antennas (called the base length) must be large enough. Especially for the satellite-borne InSAR system, a longer baseline is needed due to the long radar range. In the practical engineering application, the satellite-borne InSAR has various working modes, such as repeated orbit interference (such as ERS-1/2 satellite of European space agency), multi-station radar single-pass interference (such as space plane mapping plan SRTM of NASA (national space administration), TanDEM-X distributed satellite-borne interference SAR and other systems of the German space administration). In order to improve the temporal coherence of radar signals, a distributed space-borne interferometric SAR system, which is currently the best mode of operation, has become one of the research "hot spots" in the technical field of InSAR systems (as shown in fig. 1). However, the distributed spaceborne interference SAR system based on the multi-station radar has the problems of high complexity and high data processing difficulty, and particularly how to accurately maintain target phase information in the SAR imaging processing becomes one of the difficult problems of the technical research. The phase-preserving imaging processing method provided by the invention can realize high-precision phase-preserving imaging processing of the satellite-borne SAR signal in the InSAR working mode, and is particularly suitable for high-precision phase-preserving imaging processing of the SAR signal in the distributed satellite-borne InSAR working mode.
The process flow of InSAR can be roughly divided into the following steps (as shown in fig. 2): (1) the method comprises the following steps of imaging processing (2), image registration (3), image interference (4), phase unwrapping (5) and elevation inversion (6) geometric correction. The SAR imaging processing is the first step of the InSAR processing flow and is also the basis of the whole InSAR processing flow, and the phase retention performance of the SAR imaging processing has very important influence on the final InSAR processing effect. The existing spaceborne SAR imaging processing algorithm mainly comprises the following steps: a range-doppler (RD) algorithm, a time-frequency domain hybrid correlation algorithm, a Chirp Scaling (CS) algorithm, a wave number domain (Ω -K) algorithm, etc. The range-Doppler algorithm is the first imaging processing algorithm applied to the satellite-borne SAR signal, and the time domain-frequency domain hybrid correlation algorithm is an improved algorithm thereof. The two algorithms have the advantages of simple flow and easy implementation, but the two algorithms also have the defects of small depth of Focus (Focus depth) and poor accuracy of Range Cell Migration Compensation (RCMC), and are only suitable for imaging processing of medium-low resolution spaceborne SAR signals. In the nineties of the twentieth century, as the resolution of the satellite-borne SAR system is improved, the CS algorithm and the omega-K algorithm are successively appeared. The two algorithms can accurately compensate range migration and echo Doppler phases of the satellite-borne SAR signals, and have the advantages of large focusing depth and high processing precision. However, the existing satellite-borne SAR imaging algorithms all use the premise that the focusing effect of the SAR image is not affected, and different degrees of simplification and approximation processing exist in the algorithm derivation processing process, so that the compensation of the phase is not complete enough, and the generated SLC image has residual phase error. The influence of the residual phase errors on the SAR image focusing effect can be ignored, but the residual phase errors directly influence InSAR processing, so that the final height measurement accuracy is poor. Wherein the residual phase term having the greatest influence is a constant phase term and a linear phase term; and the residual phase error of the high-order term above the second order is very small, the influence on the high precision of InSAR measurement is relatively small, and the influence can be ignored in engineering. Aiming at the problem that the special requirements of InSAR processing on the phase-preserving performance are not fully considered in the existing satellite-borne SAR imaging algorithm, the invention provides a high-precision phase-preserving imaging processing method and platform of a satellite-borne SAR signal on the basis of deep analysis of the phase-preserving performance of the SAR imaging processing algorithm.
The method and the device perform deep analysis aiming at the phase-preserving performance requirement of the first-step imaging processing in the InSAR processing flow, and perform corresponding compensation processing aiming at the residual phase error by improving the phase compensation factor and the processing flow of the Chirp Scaling (CS) imaging algorithm. The residual phase error in the imaging process mainly comprises two parts, wherein the first part is the phase error introduced by the SAR signal through an all-pass phase correction network and comprises a quadratic phase term with opposite signs and a constant phase term; the second part is mainly caused by frequency domain circular shift, and the phase error introduced by the frequency domain circular shift is a linear phase error according to the corresponding mapping relation between the frequency domain and the time domain. The two parts are the neglected phases in the traditional imaging processing process, and in order to improve the phase maintaining precision after the imaging processing, the invention compensates the phases of the two parts in the processing process.
By adding the signal processing steps, the residual phase error of the satellite-borne SAR signal in the whole imaging processing flow can be accurately compensated, particularly, the residual complex constant phase item and the linear phase item can be accurately compensated, the azimuth phase compensation factor is dynamically updated along a range gate, the phase maintaining precision is further improved, and the high-precision phase-maintaining imaging processing (phase-maintaining imaging processing for short) of the SAR signal is realized, so that the phase maintaining problem of the imaging algorithm in InSAR processing is effectively solved, the pressure of phase error index distribution in the subsequent InSAR processing steps is relieved, and a good technical foundation is laid for realizing a high-precision satellite-borne InSAR three-dimensional terrain measurement practical system.
Disclosure of the invention
1. The purpose is as follows: the invention aims to provide a construction method of a high-precision phase-preserving imaging processing platform of a satellite-borne SAR signal, overcomes the defects of the prior art, and is an imaging processing method of the satellite-borne SAR signal, which accurately preserves phase information and is invented on the basis of a classical CS imaging processing algorithm. The method compensates the phase error of the radar signal introduced by the radar system all-pass phase network in the time domain, and simultaneously compensates the linear phase error introduced by frequency domain translation in the time domain, and has high phase maintaining precision. By analysis, the method can be used for rapidly and flexibly finishing the phase-preserving imaging processing of the SAR signal.
2. The technical scheme is as follows: the space-borne SAR acquires the high-resolution in the direction of slope through transmitting a chirp signal and a pulse compression technology, acquires the high-resolution in the direction of azimuth through a synthetic aperture technology, and the direction processing process can be equivalently regarded as the pulse compression of the chirp signal. Therefore, in order to better describe the method, first, an expression of the chirp signal compressed by the all-pass phase correction network is described.
The SAR echo data has a chirp characteristic in both the range direction and the azimuth direction, and is analyzed here by taking the range direction as an example. Let the mathematical expression of the amplitude normalized distance direction signal with rectangular envelope be:
τ is the distance forward time, τpB is the pulse width of the distance direction signal, B is the frequency modulation slope of the signal, wherein B is Bw/τpAnd rect (-) is a rectangular window.
For compressing the frequency modulated signal, the signal may be passed through an all-pass phase correction network, where the amplitude-phase characteristics of the all-pass phase correction network (see fig. 3) are:
the impulse response of the all-pass phase correction network is obtained by the formula (2),
by variable substitution, h (τ) can be found to be:
the expression of the chirp signal after passing through the all-pass correction network is:
wherein,representing a convolution.
Formula (5) indicates that: after the linear frequency modulation signal is compressed through the all-pass phase correction network, a secondary phase term with opposite sign and a constant phase term exist in the phase of the linear frequency modulation signal. Considering the short duration of the compressed chirp signal, the phase error introduced by the quadratic phase term is very small and therefore negligible, while the constant phase term needs to be compensated for in the processing.
The invention relates to a construction method of a high-precision phase-preserving imaging processing platform of a satellite-borne SAR signal, which comprises the following specific operation steps:
the method comprises the following steps: solving imaging processing parameters of the satellite-borne SAR data specifically comprises the following steps: wavefront slope distance R_minSignal sampling rate fsSignal bandwidth BwPulse width τpPulse repetition frequency fprfDoppler center frequency fdDoppler frequency modulation fRWorking wavelength lambda, satellite speed V, azimuth antenna length D and azimuth signal frame number NaDistance direction and distance gate number NrAnd the speed of light c.
The imaging processing parameters involved in the step are parameters necessary for SAR signal imaging processing, and can be provided in satellite-borne SAR raw data at home and abroad at present.
The specific operation flow is as follows:
(1) reading satellite auxiliary data such as a satellite auxiliary data header, an auxiliary data file and the like;
(2) correctly acquiring parameters required by satellite data imaging according to the explanation of the related auxiliary file;
step two: and reading in satellite-borne SAR echo data according to frames, and storing the data in a form of a two-dimensional complex array.
The condition for implementing the step is that the satellite-borne SAR echo data (as shown in fig. 4) is correctly read and stored, and is stored in a two-dimensional data form, and the satellite-borne SAR echo data is large in volume, so that a memory needs to be dynamically allocated under a normal condition. Meanwhile, the satellite-borne SAR signals are orthogonal signals, and data are stored according to a complex type in order to improve processing efficiency.
The expression stored in the two-dimensional array by the signal is as follows:
δ represents the target backscattering coefficient.
t represents azimuth time with a sampling interval of 1/fprf。
Tau represents the fast time of the distance and the sampling interval is 1/fs。
Wa(t) represents the azimuth antenna directivity function,in simulation
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θa(t) indicates an azimuth off-axis angle, θAλ/D denotes the azimuth beamwidth.
b＝Bw/τpRepresenting the chirp rate of the signal.
λ represents the operating wavelength.
The specific operation flow is as follows:
(1) matching a file header of the satellite effective data;
(2) number of frames N according to azimuth signalaDoor number N of distance directionrOpening up a memory space;
(3) reading in data in sequence according to frames, and correctly storing the data in the opened memory space in a two-dimensional complex array form;
step three: a fast discrete fourier transform is performed along the azimuth direction.
The implementation condition of this step is to accurately implement the transformation of the azimuth direction from the time domain to the frequency domain, and usually, in order to ensure the accuracy, this step is implemented by using a discrete digital signal processing method.
After the operation of this step is completed, the expression of the signal is:
wherein f represents the azimuth frequency with a sampling interval of fprf/NaAnd R represents the slope distance as a function of the distance gate.
The specific operation flow is as follows:
(1) starting from a first range gate, carrying out fast discrete Fourier transform on data stored in a memory of the range gate;
(2) storing the converted data in a storage space corresponding to the memory address of the original range gate data;
(3) repeating the operations (1) and (2) until the Nth steprAnd performing the data azimuth discrete Fourier transform in the range gate.
Step four: a circular shift of the doppler center frequency is performed in the range-doppler domain.
Due to the adoption of discrete signal processing, the signal spectrum repeatedly appears with the pulse repetition frequency as a period, and the spectrum needs to be circularly shifted for the convenience of subsequent processing. The condition for implementing this step is to precisely move the doppler center frequency to the middle position of the memory address occupied by the data, as shown in fig. 5, and it is especially important to correctly obtain the value of the doppler center frequency.
The specific operation steps are as follows:
(1) obtaining a pulse repetition frequency f from ephemeris parametersprfDoppler center frequency fdAnd azimuth signal frame number NaTo further improve the accuracy, the Doppler center frequency f can be adjusted by using a clutter locking methoddHigh accuracy estimation is performed.
(2) According to pulse repetition frequency fprfAnd Doppler center frequency fdThe number of circumferential shifts required for the calculation, N ═ f (f)prf-fd)/fprf·NaSince it is a digital signal, it is necessary to round N, i.e., N ═ fprf-fd)/fprf·Na]Therein []Representing a rounding operation.
(3) Starting from the first range gate, performing circular shift of Doppler center frequency, and moving data to the right by N address spaces;
(4) storing the shifted data in a storage space corresponding to the memory address of the original range gate data;
(5) repeating the operations (1) and (2) until the Nth steprThe data shift within the individual range gates is complete. Step five: and (5) performing distance-Doppler domain signal interpolation processing.
The condition of this step is that the time domain interpolation processing is performed on the range-doppler domain signal data along the range gate, and the space-variant characteristic of the SAR signal is eliminated, as shown in fig. 6.
In the range-doppler domain by an interpolation factor used to correct for the space-variant characteristic,
φcs(τ，f；Rref)＝exp{-j·π·br(f；Rref)Cs(f)[τ-τref(f)]2}(8)
wherein R isrefAnd
respectively representing the slope distance at the reference slope distance and the equivalent slope angle.
τref(f)＝Rref[1+Cs(f)]
Phi is thencsAnd S1After multiplying (tau, f; R), the interpolation result is,
the specific operation steps are as follows:
(1) opening up the internal memory to NrFor storing interpolation factors.
(2) An interpolation factor for the first frame is constructed.
(3) Carrying out point-to-point multiplication on the first frame interpolation factor and the first frame data to finish NrAnd performing secondary complex multiplication, and storing the result in a storage space corresponding to the memory address of the first frame data, namely covering the original data.
(4) And constructing the next frame interpolation factor, and storing the next frame interpolation factor in the storage space corresponding to the original memory address, namely covering the previous frame interpolation factor.
(5) Repeating the steps (2) to (4) until the Nth step is finishedaAnd (4) operation of frame data.
Step six: a fast discrete fourier transform is performed along the distance direction.
The implementation condition of this step is to accurately implement the transformation from the distance to the time domain to the frequency domain, and usually, in order to ensure the accuracy, this step is implemented by using a discrete digital signal processing method.
The expression of the signal after the distance conversion to the time domain and the frequency domain is completed is as follows:
wherein f isrIndicating the range-wise frequency.
The specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier transform on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address of the original data;
(3) repeating the operations (1) and (2) until the Nth stepaThe data distance of the frame is transformed to discrete fourier transform.
Step seven: and performing range migration correction and compression on the data in a wave number domain, finishing focusing processing of the distance upwards, and compensating a residual complex constant phase term.
The implementation condition of the step is that the distance migration correction track is accurately compensated, and meanwhile, the phase error introduced by data through the all-pass phase correction network is compensated, wherein the amplitude of the all-pass phase correction network is 1, and the phase characteristics are as follows:
the specific operation steps are as follows:
(1) opening up the internal memory to Na×NrAnd the complex space is used for storing the distance-oriented two-dimensional all-pass phase correction network.
(2) Sequentially constructing distance phase correction network data corresponding to each frame of data until constructing the Nth frameaAnd correcting the network data in the distance direction corresponding to the frame data to complete the construction of the distance direction two-dimensional all-pass phase correction network.
(3) The first frame data of the distance phase correction network and the first frame data of the wave number domain are multiplied point to point, and N is completedrAnd performing secondary complex multiplication, and storing the result in a storage space corresponding to the memory address of the first frame data in the wave number domain, namely covering the original data.
(4) Repeating the step (3) until the Nth step is finishedaAnd processing frame data.
Step eight: an inverse fast discrete fourier transform is performed along the distance direction.
The implementation condition of this step is to accurately implement the transformation from the frequency domain to the time domain, and usually, in order to ensure the accuracy, this step is implemented by using a discrete digital signal processing method.
The distance direction processing is completed, and the signal expression is,
wherein,
representing the distance-compressed distance envelope.
The specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier inverse transformation on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address where the original data is located;
(3) repeating the operations (1) and (2) until the Nth stepaThe data distance of the frame is inverse discrete fourier transformed.
Step nine: and completing the azimuth focusing process in the range-Doppler domain, and compensating the residual complex constant phase term.
This step is performed on the condition that the focusing process on the azimuth signal is completed by a method of dynamically updating the azimuth phase compensation factor along the range gate while compensating for the phase error introduced by the data through the all-pass phase correction network. The azimuth all-pass phase network is a two-dimensional correction network, the amplitude of the two-dimensional correction network is 1, and the phase characteristics are as follows:
wherein,
indicating the slope distance as a function of distance from the door.
The specific operation steps are as follows:
(1) opening up the internal memory to Na×NrAnd the complex space is used for storing the azimuth two-dimensional all-pass phase correction network.
(2) Constructing azimuth phase correction network data corresponding to each range gate data until constructing the Nth range gate datarAnd (4) the azimuth phase correction network data corresponding to the data gate completes the construction of an azimuth two-dimensional all-pass phase correction network. It should be noted that, in order to improve the accuracy, the doppler parameter of each range gate needs to be estimated by an adaptive estimation method, the azimuth phase compensation factors corresponding to different range gates are dynamically updated, and the accurate construction of the azimuth two-dimensional all-pass phase correction network is completed.
(3) Point-to-point multiplying the first range gate data of the azimuth phase correction network and the first range gate data of the range-Doppler domain to complete NaAnd performing secondary complex multiplication, and storing the result in a storage space corresponding to the memory address where the first range gate data of the range-Doppler domain is located, namely covering the original data.
(4) Repeating the step (3) until the Nth step is finishedrAnd (4) processing data of each range gate.
Step ten: an inverse fast discrete fourier transform is performed in the azimuth direction and the linear phase error is compensated.
The condition for implementing the step is to accurately realize the transformation of the azimuth direction from the frequency domain to the time domain, and usually, in order to ensure the precision, a method of inverse fast Fourier transform in discrete digital signal processing is adopted to transform the azimuth direction signal from the frequency domain to the time domain. In order to compensate for the phase error introduced by the frequency circular shift, each range gate of the time domain signal generated after transformation is multiplied by the same linear phase correction factor function, and the expression is as follows:
Ф_linear(t)＝exp{-2π·(N·fprf/Na)·t}(14)
in the formula, t represents the fast time direction, and the finally obtained processing result is:
wherein, Wac(t) represents the envelope of the directional function of the azimuth antenna after it has been changed.
The specific operation steps are as follows:
(1) starting from the first range gate data, performing fast inverse discrete Fourier transform on the data stored in the memory;
(2) compensating for an azimuthally-upward residual linear phase;
(3) storing the converted data in the address of the memory where the original data is located;
(4) repeating the operations (1) to (3) until the Nth steprThe data processing of the individual range gates is completed.
3. The advantages and the effects are as follows:
the construction method of the satellite-borne SAR signal high-precision phase-preserving imaging processing platform has the advantages that:
(1) on the basis of the CS imaging algorithm, the SAR signal imaging processing flow is improved, the absolute phase precision of the generated SAR complex image is well ensured, and the method has the advantage of high phase precision.
(2) The invention effectively improves the phase holding precision of the SAR image by compensating the phase error introduced when the SAR signal is compressed by the all-pass phase correction network in the time domain.
(3) According to the time domain-frequency domain mapping relation of the signals, the phase error introduced by frequency domain circular shift is well compensated in the time domain by adding the linear phase correction factor, and the method has the characteristics of flexible operation and high processing precision.
(4) The invention effectively ensures the consistency of the SAR image phase precision in the whole imaging area range by a method of updating the azimuth phase compensation factor along the range gate in the range-Doppler domain.
(5) The processing flow of the invention has the advantages of simple structure and modular operation, is beneficial to the transplantation of processing modules among different processing platforms, realizes the optimal utilization of resources and has better universality and practicability.
(IV) description of the drawings
Fig. 1 is a schematic diagram of satellite-borne distributed satellite SAR interferometric height measurement.
Fig. 2 is a flow chart of on-board InSAR signal processing.
Fig. 3 is a schematic diagram of the amplitude-phase characteristics of the frequency domain of the all-pass phase network.
Fig. 4 is a schematic diagram illustrating storage of satellite-borne SAR echo data.
Figure 5 is a diagram of a doppler center frequency circular shift.
Fig. 6 is a schematic diagram of signal interpolation in the range-doppler domain.
FIG. 7 is a flowchart of a high-precision phase-preserving imaging processing method of a satellite-borne SAR signal.
Fig. 8 is a comparison of the results of phase error analysis after the imaging process.
The symbols in the figures are as follows:
in FIG. 3, ω represents angular frequency, BpRepresenting the signal processor bandwidth.
In FIG. 4, R_minRepresenting the wave front distance, namely the skew distance corresponding to the first distance gate; r_jRepresents the pitch, N, corresponding to the jth range gateaNumber of frames representing azimuth signal, NrDistance of representationThe number of the separation distance doors.
In FIG. 5, f denotes the instantaneous Doppler frequency, f0Representing the Doppler center frequency, fprfIndicating the pulse repetition frequency.
In fig. 6, the dotted line indicates the result after re-interpolation.
(V) detailed description of the preferred embodiments
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Fig. 1 is a schematic diagram of satellite-borne distributed satellite SAR interferometric height measurement, which has become one of research "hotspots" in the technical field of InSAR systems as a best working mode at present.
Fig. 2 is a flow chart of on-board InSAR signal processing. The process flow can be roughly divided into the following steps: (1) the method comprises the following steps of imaging processing (2), image registration (3), image interference (4), phase unwrapping (5) and elevation inversion (6) geometric correction.
Fig. 3 is a schematic diagram of the amplitude-phase characteristics of the frequency domain of the all-pass phase network, which is used for compressing the frequency-modulated signal.
The invention mainly aims at the problem that the phase precision of the satellite-borne SAR signal processing is difficult to maintain, and provides a high-precision phase-preserving imaging processing method and a high-precision phase-preserving imaging processing platform for the satellite-borne SAR signal.
The invention can be realized on a microcomputer, and can also be integrated in hardware equipment based on a Digital Signal Processor (DSP) to realize high-speed real-time processing. The implementation environment of this example is a common microcomputer, in which a Central Processing Unit (CPU) is pentium (r)4, a CPU master frequency is 3.0GHz, a hard disk storage space is 80GB, an internal memory (internal memory) is 2GB, and a display device is a 17-inch liquid crystal display.
The invention relates to a construction method of a high-precision phase-preserving imaging processing platform of a satellite-borne SAR signal, which comprises the following specific operation steps:
the method comprises the following steps: solving satellite data imaging processing parameters, comprising: wavefront slope distance R_min630176.000m, signal sampling rate fs125.0MHz, signal bandwidth Bw110.0MHz, pulse width τp20.0 mus, pulse repetition frequency fprf3200.0Hz Doppler center frequency fd17Hz Doppler frequency fR5707Hz/s, working wavelength λ 0.03m, satellite velocity V7662 m/s, azimuth antenna length D7.5 m, and azimuth frame number Na2048, the number of distance sampling points Nr8192, the speed of light c is 299792458 m/s.
The implementation conditions of the step are as follows: the necessary parameters needed in the imaging operation need to be acquired through a satellite data file header, in general, the imaging processing parameters are provided by domestic and foreign standard SAR signal data, and in order to further improve the processing precision, some important parameters can be subjected to self-adaptive estimation processing, such as Doppler center frequency fdAnd Doppler frequency fRAnd the like.
Step two: and reading in satellite-borne SAR echo data according to frames, and storing the data in a form of a two-dimensional complex array.
As shown in fig. 4, this step is carried out under the conditions: the satellite-borne SAR echo data are correctly read in, and the satellite-borne SAR system adopts two orthogonal signals to acquire data, so that the data can be stored in a two-dimensional complex data form for convenient processing. Meanwhile, since the data volume of the satellite-borne SAR echo is usually large, dynamic allocation of a memory is usually required to improve efficiency. The expression of the signals stored in the two-dimensional array is shown as follows:
wherein,
δ represents the target backscattering coefficient, and δ is 1 in the simulation process.
t represents azimuth time with a sampling interval of 1/fprf＝312.5μs。
Tau represents the fast time of the distance and the sampling interval is 1/fs＝8.0ns
Wa (t) shows directional antenna directivity function in simulation
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θa(t) indicates an azimuth off-axis angle, θAAnd λ/D0.004 rad represents the azimuth beam width.
b＝Bw/τpThe signal chirp rate is expressed as 5.5e12 Hz/s.
λ ═ 0.03m denotes the operating wavelength.
And c is 299792458m/s to represent the speed of light.
The specific operation flow is as follows:
(1) matching a file header of the satellite effective data;
(2) number of frames N according to azimuth signala2048, distance gate number NrOpening up a memory space for 8192;
(3) reading in data in sequence according to frames, and correctly storing the data in the opened memory space in a two-dimensional complex array form;
step three: fast discrete Fourier transform along azimuth direction
The conditions for this step are as follows: the method can accurately realize the transformation of the azimuth direction from a time domain to a frequency domain, generally adopts a discrete digital signal processing method to complete the step in order to ensure the precision, and can adopt different range gates to perform parallel processing in order to improve the processing efficiency. After the operation of this step is completed, the expression of the signal is shown as follows:
wherein f represents the azimuth frequency with a sampling interval of fprf/NaR denotes the slope distance as a function of the range gate at 1.5625 Hz.
The specific operation flow is as follows:
(1) starting from a first range gate, carrying out fast discrete Fourier transform on data stored in a memory of the range gate;
(2) storing the converted data in a storage space corresponding to the memory address of the original range gate data;
(3) repeating the operations (1) and (2) until the Nth steprThe data orientation within 8192 range gates is finished by discrete Fourier transform.
Step four: circular shift of Doppler center frequency
As shown in fig. 5, the conditions for this step are as follows: for each range gate data, the Doppler center frequency is accurately moved to the middle position of the memory address occupied by the range gate data, so that the method has the advantages of being more convenient in subsequent operation and reducing address shift operation.
The specific operation steps are as follows:
(1) obtaining a pulse repetition frequency f from ephemeris parametersprf3200Hz Doppler center frequency fd17Hz and azimuth signal frame number Na2048, the doppler center frequency f can be further improved by using a clutter locking methoddHigh accuracy estimation is performed.
(2) According to pulse repetition frequency fprfAnd Doppler center frequency fdThe number of circumferential shifts required for the calculation, N ═ f (f)prf-fd)/fprf·NaSince it is a digital signal, it is necessary to round N, i.e., N ═ fprf-fd)/fprf·Na]2037, wherein [ ·]Representing a rounding operation.
(3) Starting from the first range gate, performing circular shift of Doppler center frequency, and moving data to the right by N-2037 address spaces;
(4) storing the shifted data in a storage space corresponding to the memory address of the original range gate data;
(5) repeating the operations (1) and (2) until the Nth steprShifting of data within 8192 range gates is complete.
Step five: and (5) performing distance-Doppler domain signal interpolation processing.
As shown in fig. 6, this step is carried out under the conditions: the space-variant characteristic of the SAR signal is eliminated by carrying out time domain interpolation processing on the range-Doppler domain signal data along a range gate, the principle is that a linear frequency modulation signal related to the frequency modulation rate is multiplied by the range-direction frequency modulation signal, and the expression of the frequency modulation signal is shown as the following formula:
φcs(τ，f；Rref)＝exp{-j·π·br(f；Rref)Cs(f)[τ-τref(f)]2}(8)
wherein R isref634413.2m and
the slope distance at the reference slope distance and the equivalent slope angle, respectively.
τref(f)＝Rref[1+Cs(f)]
After multiplication, the result is still a frequency modulated signal, but the chirp rate and the phase center are changed,
the specific operation steps are as follows:
(1) opening up the internal memory to Nr8192 complex space for storing interpolation factors.
(2) An interpolation factor for the first frame is constructed.
(3) Carrying out point-to-point multiplication on the first frame interpolation factor and the first frame data to finish NrAnd (5) when the number of the complex multiplications is 8192, storing the result in the memory position of the first frame data, and covering the original data.
(4) And constructing the next frame interpolation factor, and storing the next frame interpolation factor in the storage space corresponding to the original memory address, namely covering the previous frame interpolation factor.
(5) Repeating the steps (2) to (4) until the Nth step is finishedaOperation for 2048 frames of data.
Step six: a fast discrete fourier transform is performed along the distance direction.
The conditions for this step are as follows: the transformation of the distance from the time domain to the frequency domain is accurately realized, and usually, in order to ensure the precision, a discrete digital signal processing method is adopted to complete the step. The expression of the signal after the distance conversion into the time domain and the frequency domain is completed is shown as the following formula:
wherein f isrRepresenting the range-wise frequency with a sampling interval fs/Nr＝15.25KHz
The specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier transform on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address where the original data is located;
(3) repeating the operations (1) and (2) until the Nth stepaThe data distance of 2048 frames is transformed to discrete fourier transform.
Step seven: and performing range migration correction and compression on the data in a wave number domain, finishing focusing processing of the distance upwards, and compensating a residual complex constant phase term. The method specifically comprises the following steps of enabling the two-bit data to pass through an all-pass phase correction network along the azimuth direction, compensating range migration and completing range compression, wherein the all-pass phase correction network is a two-dimensional correction network, the amplitude of the all-pass phase correction network is 1, and the phase characteristics are as follows:
the specific operation steps are as follows:
(1) opening up the internal memory to Na×NrThe space is a complex space of 2048 × 8192 size, and is used for storing a distance two-dimensional all-pass phase correction network.
(2) Sequentially constructing distance phase correction network data corresponding to each frame of data until constructing the Nth frameaAnd correcting the network data in the distance direction corresponding to the frame data to complete the construction of the distance direction two-dimensional all-pass phase correction network.
(3) Directing the distance to a first frame data of a phase correction network and a first of a wavenumber domainMultiplying frame data point to complete NrAnd (4) when the complex multiplication is 8192 times, storing the result in a storage space corresponding to the memory address of the first frame data in the wave number domain, namely covering the original data.
(4) Repeating the step (3) until the Nth step is finishedaProcessing of 2048 frames of data.
Step eight: an inverse fast discrete fourier transform is performed along the distance direction.
The implementation condition of this step is to accurately implement the transformation from the frequency domain to the time domain, and usually, in order to ensure the accuracy, this step is implemented by using a discrete digital signal processing method. After this step, the distance direction processing is completed, and the signal expression is as follows:
wherein,representing the distance-compressed distance envelope.
The specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier inverse transformation on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address where the original data is located;
(3) repeating the operations (1) and (2) until the Nth stepaThe data distance of 2048 frames is completed to the inverse discrete fourier transform.
Step nine: and completing the azimuth focusing process in the range-Doppler domain, and compensating the residual complex constant phase term.
This step is performed on the condition that the focusing process on the azimuth signal is completed by a method of dynamically updating the azimuth phase compensation factor along the range gate while compensating for the phase error introduced by the data through the all-pass phase correction network. The method comprises the following steps of enabling two-dimensional data to pass through an all-pass phase correction network along a range gate to complete azimuth focusing processing and residual error processing, wherein the all-pass phase correction network is a two-dimensional correction network, the amplitude of the all-pass phase correction network is 1, and phase characteristics are as follows:
wherein,
indicating the slope distance as a function of distance from the door.
The specific operation steps are as follows:
(1) opening up the internal memory to Na×NrThe space is a complex space with the size of 2048 multiplied by 8192 and is used for storing the azimuth two-dimensional all-pass phase correction network.
(2) Constructing azimuth phase correction network data corresponding to each range gate data until constructing the Nth range gate datarAnd (5) completing the construction of the azimuth two-dimensional all-pass phase correction network according to the azimuth phase correction network data corresponding to 8192 data gates. It should be noted that, in order to improve the accuracy, the doppler parameter of each range gate needs to be estimated by an adaptive estimation method, and the azimuth phase compensation factors corresponding to different range gates are dynamically updated, so as to complete the precise construction of the azimuth phase correction network.
(3) Point-to-point multiplying the first range gate data of the azimuth phase correction network and the first range gate data of the range-Doppler domain to complete Na2048 times of complex multiplication, and storing the result in a storage space corresponding to the memory address where the first range gate data of the range-doppler domain is located, namely, covering the original data.
(4) Repeating the step (3) until the Nth step is finishedr8192 range gate data processing.
Step ten: an inverse fast discrete fourier transform is performed in the azimuth direction and the linear phase error is compensated.
The implementation condition of this step is to accurately implement the transformation of the azimuth from the frequency domain to the time domain, and usually to ensure the accuracy, this step is implemented by using a discrete digital signal processing method, and at the same time, the phase error introduced by the circular shift is compensated. The specific method is that the signal is subjected to fast discrete Fourier inverse transform along the range gate, and the data after inverse transform is multiplied by the same linear phase correction factor function along each range gate so as to correct the phase error introduced by frequency circular shift, as shown in the following:
Ф_linear(t)＝exp{-2π·(N·fprf/Na)·t}(14)
wherein (N.f)prf/Na) 3182.8125, the final result is:
the specific operation steps are as follows:
(1) starting from the first range gate data, performing fast inverse discrete Fourier transform on the data stored in the memory;
(2) compensating for an azimuthally-upward residual linear phase;
(3) storing the converted data in a storage space corresponding to the memory address where the original data is located;
(4) repeating the operations (1) to (3) until the Nth steprThe data orientation of 8192 range gates is completed to the inverse discrete fourier transform.
After the final imaging treatment, the theoretical ideal phase of the target can be obtained as
The subsequent InSAR interferometric height measurement processing can be completed by utilizing the phase.
In order to better illustrate the effectiveness and superiority of the method, the invention carries out a signal simulation experiment, and the result verifies the effectiveness of the method. Table 1 shows simulation parameters and imaging processing parameters, and in order to verify the accuracy of the phase-preserving processing, the echo data simulation is performed using 9 marked points in a 3 × 3 point matrix (with an interval of 100mx100 m). The phase results after the imaging process are given in table 2 and the phase error variation results are given in table 3.
TABLE 1 simulation parameters and imaging processing parameters
Table 2 phase results after imaging processing
(Note: the above theoretical phases are all converted to-pi to + pi, i.e., -180 degrees to +180 degrees)
TABLE 3 comparison of phase error analysis results after imaging processing
The simulation result shows that the method is obviously superior to the traditional imaging processing method, and the phase retention characteristic is greatly improved. The method well retains the phase information of the target in the imaging processing flow, particularly can effectively compensate the phase error introduced by the signal passing through the all-pass phase network and the linear phase error introduced by the frequency circumferential shift in the signal processing, and adopts a method for dynamically updating the azimuth phase compensation factor along the range gate, thereby further reducing the phase error and improving the precision of maintaining the phase information of the target. Therefore, the method can well complete the phase-preserving imaging processing and lay a foundation for InSAR height measurement processing.
FIG. 7 is a flowchart of a high-precision phase-preserving imaging processing method of a satellite-borne SAR signal.
Fig. 8 is a comparison of the results of phase error analysis after the imaging process.
Practice proves that: the method can quickly and flexibly complete the phase-preserving imaging processing of the SAR signal.
Claims (1)
1. A construction method of a satellite-borne SAR signal high-precision phase-preserving imaging processing platform is characterized by comprising the following steps: the method comprises the following specific steps:
the method comprises the following steps: solving imaging processing parameters of the satellite-borne SAR data specifically comprises the following steps: wavefront slope distance R_minSignal sampling rate fsSignal bandwidth BwPulse width τpPulse repetition frequency fprfDoppler center frequency fdDoppler frequency modulation fRWorking wavelength lambda, satellite speed V, azimuth antenna length D and azimuth signal frame number NaDistance direction and distance gate number NrThe speed of light c;
the specific operation flow is as follows:
(1) reading in a satellite auxiliary data header and an auxiliary data file;
(2) correctly acquiring parameters required by satellite data imaging according to the explanation of the related auxiliary file;
step two: reading in satellite-borne SAR echo data according to frames, and storing the data in a form of a two-dimensional complex array;
the implementation condition of the step is that the satellite-borne SAR echo data is read and stored correctly and is stored in a two-dimensional data form; the method comprises the steps that due to the fact that the satellite-borne SAR echo data volume is large, a memory needs to be dynamically allocated, and in consideration of the fact that satellite-borne SAR signals are orthogonal signals, data are stored according to a plurality of types;
the expression stored in the two-dimensional array by the signal is as follows:
δ represents the target backscattering coefficient;
t represents azimuth time with a sampling interval of 1/fprf；
Tau represents the fast time of the distance and the sampling interval is 1/fs；
Wa(t) shows the directional antenna directivity function in the azimuth, in the simulation
θa(t) indicates an azimuth off-axis angle, θAλ/D denotes azimuth beam width;
representing a transmit pulse envelope;
b＝Bw/τprepresenting the signal chirp rate;
λ represents the operating wavelength;
the specific operation flow is as follows:
(1) matching a file header of the satellite effective data;
(2) number of frames N according to azimuth signalaDoor number N of distance directionrOpening up a memory space;
(3) reading in data in sequence according to frames, and correctly storing the data in the opened memory space in a two-dimensional complex array form;
step three: performing fast discrete Fourier transform along the azimuth direction;
the implementation condition of the step is that the conversion of the azimuth direction from a time domain to a frequency domain is accurately realized, and in order to ensure the precision, the step is completed by adopting a discrete digital signal processing method;
after the operation of this step is completed, the expression of the signal is:
wherein f represents the azimuth frequency with a sampling interval of fprf/NaR represents the slope distance as a function of the distance gate;
the specific operation flow is as follows:
(1) starting from a first range gate, carrying out fast discrete Fourier transform on data stored in a memory of the range gate;
(2) storing the converted data in a storage space corresponding to the memory address of the original range gate data;
(3) repeating the operations (1) and (2) until the Nth steprThe data azimuth direction discrete Fourier transform in the range gate is completed;
step four: performing circular shift of Doppler center frequency in a range-Doppler domain;
the implementation condition of the step is that the Doppler center frequency is accurately moved to the middle position of the memory address occupied by the data, and particularly the numerical value of the Doppler center frequency is correctly acquired;
the specific operation steps are as follows:
(1) obtaining a pulse repetition frequency f from ephemeris parametersprfDoppler center frequency fdAnd azimuth signal frame number NaTo further improve the accuracy, the Doppler center frequency f can be adjusted by using a clutter locking methoddCarrying out high-precision estimation;
(2) according to pulse repetition frequency fprfAnd Doppler center frequency fdThe number of circumferential shifts required for the calculation, N ═ f (f)prf-fd)/fprf·NaSince it is a digital signal, it is necessary to round N, i.e., N ═ fprf-fd)/fprf·Na]Therein []Representing a rounding operation;
(3) starting from the first range gate, performing circular shift of Doppler center frequency, and moving data to the right by N address spaces;
(4) storing the shifted data in a storage space corresponding to the memory address of the original range gate data;
(5) repeating the operations (1) and (2) until the Nth steprCompleting data shift in the range gate;
step five: distance-Doppler domain signal interpolation processing;
the implementation condition of the step is that the time domain interpolation processing is carried out on the range-Doppler domain signal data along the range gate, the space-variant characteristic of the SAR signal is eliminated,
in the range-doppler domain by an interpolation factor used to correct for the space-variant characteristic,
φcs(τ，f；Rref)＝exp{-j·π·br(f；Rref)Cs(f)[τ-τref(f)]2} (8)
wherein R isrefAnd
respectively representing the slope distance and the equivalent slope angle at the reference slope distance;
τref(f)＝Rref[1+Cs(f)]
phi is thencsAnd S1After multiplying (tau, f; R), the interpolation result is,
the specific operation steps are as follows:
(1) opening up the internal memory to NrThe complex space for storing interpolation factors;
(2) constructing an interpolation factor for the first frame;
(3) carrying out point-to-point multiplication on the first frame interpolation factor and the first frame data to finish NrPerforming secondary complex multiplication, and storing the result in a storage space corresponding to the memory address of the first frame data, namely covering the original data;
(4) constructing a next frame interpolation factor, storing the next frame interpolation factor in a storage space corresponding to the original memory address, namely covering the previous frame interpolation factor;
(5) repeating the steps (2) to (4) until the Nth step is finishedaAn operation of frame data;
step six: performing fast discrete Fourier transform along the distance direction;
the implementation condition of the step is that the distance is accurately transformed from a time domain to a frequency domain, and in order to ensure the precision, the step is completed by adopting a discrete digital signal processing method;
the expression of the signal after the distance conversion to the time domain and the frequency domain is completed is as follows:
wherein f isrRepresents the range-wise frequency;
the specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier transform on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address of the original data;
(3) repeating the operations (1) and (2) until the Nth stepaThe data distance of the frame is completed by discrete Fourier transform;
step seven: performing range migration correction and compression on the data in a wave number domain, finishing focusing processing of a distance direction, and compensating a residual complex constant phase term;
the implementation condition of the step is that the distance migration correction track is accurately compensated, and meanwhile, the phase error introduced by data through the all-pass phase correction network is compensated, wherein the amplitude of the all-pass phase correction network is 1, and the phase characteristics are as follows:
the specific operation steps are as follows:
(1) opening up the internal memory to Na×NrThe complex space is used for storing a distance direction two-dimensional all-pass phase correction network;
(2) sequentially constructing distance phase correction network data corresponding to each frame of data until constructing the Nth frameaCorrecting network data in a distance direction corresponding to the frame data to complete the construction of a distance direction two-dimensional all-pass phase correction network;
(3) the first frame data of the distance phase correction network and the first frame data of the wave number domain are multiplied point to point, and N is completedrPerforming secondary complex multiplication, and storing the result in a storage space corresponding to the memory address of the first frame data in the wave number domain, namely covering the original data;
(4) repeating the step (3) until the Nth step is finishedaProcessing frame data;
step eight: performing fast inverse discrete Fourier transform along the distance direction;
the implementation condition of the step is that the conversion from the frequency domain to the time domain is accurately realized, and in order to ensure the precision, the step is completed by adopting a discrete digital signal processing method;
the distance direction processing is completed, and the signal expression is,
wherein,
representing the distance direction envelope after the distance compression;
the specific operation steps are as follows:
(1) starting from the first frame data, carrying out fast discrete Fourier inverse transformation on the data stored in the memory;
(2) storing the converted data in a storage space corresponding to the memory address where the original data is located;
(3) repeating the operations (1) and (2) until the Nth stepaCompleting the inverse discrete Fourier transform of the data distance of the frame;
step nine: completing the focusing processing in the direction of the range-Doppler domain, and compensating the residual complex constant phase term;
the implementation condition of the step is that the focusing processing of the azimuth signal is completed by a method of dynamically updating the azimuth phase compensation factor along the range gate, and meanwhile, the phase error introduced by data through the all-pass phase correction network is compensated; the azimuth all-pass phase network is a two-dimensional correction network, the amplitude of the two-dimensional correction network is 1, and the phase characteristics are as follows:
wherein,
represents the slope distance as a function of distance gate;
the specific operation steps are as follows:
(1) opening up the internal memory to Na×NrThe complex space is used for storing the azimuth two-dimensional all-pass phase correction network;
(2) constructing azimuth phase correction network data corresponding to each range gate data until constructing the Nth range gate datarThe azimuth phase correction network data corresponding to each data gate completes the construction of an azimuth two-dimensional all-pass phase correction network; in order to improve the precision, the Doppler parameters of each range gate need to be estimated by a self-adaptive estimation method, the azimuth phase compensation factors corresponding to different range gates are dynamically updated, and the precise construction of an azimuth two-dimensional all-pass phase correction network is completed;
(3) point-to-point multiplying the first range gate data of the azimuth phase correction network and the first range gate data of the range-Doppler domain to complete NaThe second complex multiplication, storing the result in the memory space corresponding to the memory address of the first range gate data of the range-Doppler domain, namely covering the original data;
(4) repeating the step (3) until the Nth step is finishedrProcessing the data of each range gate;
step ten: performing fast inverse discrete Fourier transform along the azimuth direction and compensating a linear phase error;
the implementation condition of the step is that the conversion of the azimuth direction from the frequency domain to the time domain is accurately realized, and in order to ensure the precision, an inverse fast Fourier transform method in discrete digital signal processing is adopted to convert the azimuth direction signal from the frequency domain to the time domain; in order to compensate for the phase error introduced by the frequency circular shift, each range gate of the time domain signal generated after transformation is multiplied by the same linear phase correction factor function, and the expression is as follows:
Φ_linear(t)＝exp{-2π·(N·fprf/Na)·t} (14)
in the formula, t represents the fast time direction, and the finally obtained processing result is:
wherein, Wac(t) representing an envelope after the directional function of the azimuth antenna is changed;
the specific operation steps are as follows:
(1) starting from the first range gate data, performing fast inverse discrete Fourier transform on the data stored in the memory;
(2) compensating for an azimuthally-upward residual linear phase;
(3) storing the converted data in the address of the memory where the original data is located;
(4) repeating the operations (1) to (3) until the Nth steprThe data processing of the individual range gates is completed.
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Application publication date: 20100331 Assignee: Shanghai Spaceflight Institute of TT&C And Telecommunication Assignor: BEIHANG University Contract record no.: X2021990000219 Denomination of invention: Construction method of high precision phase preserving imaging processing platform for Spaceborne SAR signal Granted publication date: 20110525 License type: Common License Record date: 20210413 |