CN110501708B - Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method - Google Patents

Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method Download PDF

Info

Publication number
CN110501708B
CN110501708B CN201910806544.XA CN201910806544A CN110501708B CN 110501708 B CN110501708 B CN 110501708B CN 201910806544 A CN201910806544 A CN 201910806544A CN 110501708 B CN110501708 B CN 110501708B
Authority
CN
China
Prior art keywords
azimuth
calculating
fuzzy
antenna
area
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910806544.XA
Other languages
Chinese (zh)
Other versions
CN110501708A (en
Inventor
陈杰
王亚敏
杨威
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beihang University
Original Assignee
Beihang University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beihang University filed Critical Beihang University
Priority to CN201910806544.XA priority Critical patent/CN110501708B/en
Publication of CN110501708A publication Critical patent/CN110501708A/en
Application granted granted Critical
Publication of CN110501708B publication Critical patent/CN110501708B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Abstract

The invention relates to the technical field of signal processing, in particular to a multi-channel spaceborne TOPSAR azimuth ambiguity analysis method, which comprises the following steps: acquiring antenna and system parameters; calculating the multi-channel TOPSAR azimuth processing signal bandwidth according to the antenna and system parameters; dividing the azimuth scanning angle into N parts, and calculating the Doppler center frequency corresponding to each azimuth scanning angle; and calculating the corresponding azimuth ambiguity of each azimuth scanning angle by using the parameters and the obtained result to obtain the azimuth ambiguities corresponding to the N azimuth scanning angles respectively. The invention can accurately calculate the azimuth ambiguity under different azimuth beam rotation angles, optimize the overall design of the system and lay a foundation for the subsequent TOPSAR data processing.

Description

Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method
Technical Field
The invention relates to the technical field of signal processing, in particular to a multi-channel spaceborne TOPSAR azimuth ambiguity analysis method.
Background
The satellite-borne Synthetic Aperture Radar (SAR) belongs to a microwave active imaging radar, and can be widely applied to the fields of environmental monitoring, natural disaster assessment, agriculture, forestry and the like by means of the characteristic that the SAR can be observed on the ground all day long and all weather without being influenced by weather and climate.
With the continuous improvement of the space-to-ground observation requirement, the high-resolution wide swath SAR imaging becomes one of the main development directions of the satellite-borne SAR. The TOPSAR mode can simultaneously inhibit the problems of scallop effect, azimuth fuzzy change and the like of ScanSAR (scanning) mode images because all targets can be irradiated by azimuth beams equally, and can effectively solve the contradiction between the wide swath and high resolution by combining a multi-channel technology. However, due to the antenna beam rotation scanning, the conventional method for analyzing the Azimuth Ambiguity to Signal Ratio (AASR) of the multi-channel space-borne SAR stripe mode is not applicable. The orientation ambiguity analysis can optimize the system design and lay a foundation for the subsequent TOPSAR imaging and application.
Disclosure of Invention
The invention aims to provide a method suitable for multi-channel satellite-borne TOPSAR (top-down synthetic aperture radar) azimuth ambiguity analysis, aiming at the problem that the traditional multi-channel strip SAR azimuth ambiguity analysis method is not applicable due to the rotation of multi-channel satellite-borne TOPSAR mode antenna beams.
In order to achieve the purpose, the invention provides a multi-channel spaceborne TOPSAR azimuth ambiguity analysis method, which comprises the following steps:
s1, obtaining antenna and system parameters;
s2, calculating the multi-channel TOPSAR azimuth processing signal bandwidth according to the antenna and system parameters;
s3, dividing the azimuth scanning angle into N parts, and calculating the Doppler center frequency corresponding to each azimuth scanning angle;
s4, aiming at an azimuth scanning angle, calculating a transfer function matrix of each receiving channel and a compensation matrix in a corresponding main lobe area;
s5, calculating the azimuth off-axis angle corresponding to each fuzzy area and each non-fuzzy area by combining the Doppler center frequency corresponding to the azimuth scanning angle;
s6, calculating antenna directional diagrams corresponding to the transmitting antenna and the receiving antenna according to the azimuth off-axis angles corresponding to the fuzzy areas and the non-fuzzy areas;
s7, processing signal bandwidth according to the antenna directional diagram and the azimuth direction, and calculating the sum of energy in a non-fuzzy area;
s8, calculating the sum of energy in the fuzzy area according to the antenna directional diagram, the transfer function matrix and the compensation matrix in the corresponding main lobe area;
s9, calculating the azimuth ambiguity according to the energy sum of the non-fuzzy region and the fuzzy region;
s10, executing the above steps S4 to S9 for each azimuth scanning angle, and calculating azimuth ambiguities corresponding to the N azimuth scanning angles.
Preferably, the antenna and system parameters obtained in step S1 include: pulse repetition frequency fprfVelocity V of satellitesDoppler center frequency fdThe number of receiving channels K, the distance between adjacent phase centers of the receiving channels d, and the length L of the transmitting antennaTLength L of receiving antennaRSignal wavelength λ, satellite altitude H, earth radius RgAzimuthal resolution ρaDistance to satellite dwell time T in one subbanddAzimuth scanning angle
Figure GDA0002897344450000021
Simulated central time satellite arrivalDistance R between objectsst。
Preferably, the calculating the azimuth direction processing signal bandwidth in step S2 includes:
s2-1, calculating the distance between the equivalent rotation point and the satellite according to the antenna and the system parameters;
s2-2, calculating a mixing degree factor according to the distance between the equivalent rotation point and the satellite;
and S2-3, calculating the multi-channel TOPSAR azimuth processing bandwidth according to the mixing factor.
Preferably, the calculating the doppler center frequency corresponding to each azimuth scanning angle in step S3 includes:
s3-1, scanning the whole azimuth by the angle
Figure GDA0002897344450000036
Dividing the direction of the object to be scanned into N parts, and calculating the interval of the scanning angles of two adjacent parts of directions;
s3-2, calculating a central squint angle corresponding to each azimuth scanning angle according to the interval of two adjacent azimuth scanning angles;
s3-3, according to the central oblique angle corresponding to each azimuth scanning angle
Figure GDA0002897344450000037
The corresponding doppler center frequency is calculated.
Preferably, in step S4, for one azimuth scanning angle, the number of single-sided azimuth ambiguity regions corresponding to each receiving channel is set to be NsinThe total number of fuzzy areas is Nam＝K·NsinThe sum of the total number of the fuzzy areas and the non-fuzzy areas is Num 2Nam+ K; the step of calculating the transfer function matrix of the receiving channel and the compensation matrix in the corresponding main lobe area comprises the following steps:
s4-1, calculating the azimuth time delay error of each receiving channel compared with the central receiving channel;
s4-2, calculating transfer functions in all fuzzy areas of different non-fuzzy receiving channels according to the azimuth time delay error to obtain corresponding transfer function matrixes;
and S4-3, calculating a compensation matrix in the corresponding main lobe region according to the transfer function matrix.
Preferably, in step S4-1, for the receiving channel k, the expression of the azimuth time delay compared to the central receiving channel is Tdelay(k)＝kd/VsThe corresponding azimuth time delay error is expressed as
Figure GDA0002897344450000031
Wherein the content of the first and second substances,
Figure GDA0002897344450000032
Figure GDA0002897344450000033
representing a rounding down.
Preferably, in step S4-2, when the transfer functions in all the fuzzy areas corresponding to different non-fuzzy receiving channels k are calculated, the expression of the transfer function is:
Figure GDA0002897344450000034
wherein i 1,2., Num;
the expression of the corresponding transfer function matrix is:
Figure GDA0002897344450000035
in step S4-3, when calculating the compensation matrix in the corresponding main lobe region, inverting the corresponding part of the main lobe in the transfer function matrix, where the expression is:
Figure GDA0002897344450000041
preferably, the calculating of the antenna patterns corresponding to the transmitting antenna and the receiving antenna in step S6 includes:
s6-1, calculating the energy corresponding to each azimuth off-axis angle of the transmitting antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area;
s6-2, calculating the energy corresponding to each azimuth off-axis angle of the receiving antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area;
and S6-3, obtaining antenna directional diagrams corresponding to the transmitting antenna and the receiving antenna according to the energy corresponding to the off-axis angles of the transmitting antenna and the receiving antenna in each direction.
Preferably, in the step S7, the calculating the sum of the non-blur area energies includes:
s7-1, processing the signal bandwidth according to the azimuth to obtain the effective azimuth calculation point number corresponding to the non-fuzzy area; integrating the obtained antenna directional patterns into a one-dimensional form;
s7-2, according to the effective azimuth calculation point number corresponding to the non-fuzzy area, extracting the corresponding signal amplitude in the effective bandwidth in the antenna directional diagram in a one-dimensional form, and calculating the energy sum of the non-fuzzy area.
Preferably, the calculating of the sum of the blur area energies in step S8 includes:
s8-1, obtaining a fuzzy area signal reconstruction filtering function according to the transfer function matrix of each receiving channel and the compensation matrix in the corresponding main lobe area;
s8-2, reconstructing a fuzzy area signal according to the fuzzy area signal reconstruction filtering function and the antenna directional diagram;
and S8-3, according to the effective azimuth calculation points corresponding to the non-fuzzy region, extracting the corresponding signal amplitude in the effective bandwidth in the reconstructed fuzzy region signal, and calculating the energy sum of the fuzzy region.
The technical scheme of the invention has the following advantages:
(1) and (5) practicability. The method provided by the invention is different from the traditional multi-channel spaceborne stripe SAR model azimuth ambiguity calculation, can calculate the azimuth ambiguity corresponding to each rotation angle respectively, and is beneficial to the optimization design of the system.
(2) High efficiency. The method provided by the invention realizes the segmented calculation by dividing the azimuth beam scanning angle, avoids taking a ground observation target as a division object, and is simple to realize and high in efficiency.
(3) And (4) universality. The method provided by the invention can be equally suitable for a satellite-borne SAR beam bunching mode and a sliding beam bunching mode, and has strong universality.
Drawings
Fig. 1 is a schematic diagram of a multi-channel spaceborne toposar azimuth ambiguity analysis method in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Example one
As shown in fig. 1, the method for analyzing the bearing ambiguity of a multi-channel spaceborne toposar provided by the embodiment of the present invention includes the following steps:
and S1, acquiring the antenna and system parameters of the SAR system.
The antenna and system parameters of the SAR system are determined by the overall design or actual system, and preferably include: pulse repetition frequency fprfVelocity V of satellitesDoppler center frequency fdThe number of receiving channels (i.e. the number of receiving antennas) K, the distance between adjacent phase centers of the receiving channels is d, and the length L of the transmitting antennaTLength L of receiving antennaRSignal wavelength λ, satellite altitude H, earth radius RgAzimuthal resolution ρaThe distance is towards the satellite residence time T in a certain sub-banddAzimuth scanning angle
Figure GDA0002897344450000051
Simulating the distance R between the satellite at the central moment and the targetst. The satellite is the SAR systemThe satellite of (1).
S2, calculating the multi-channel TOPSAR azimuth processing signal bandwidth B according to the antenna and system parametersa。
Azimuth processing signal bandwidth BaMay be determined by a mixedness factor and an azimuthal resolution ρaAnd (4) calculating. In toposar, the mixedness factor is defined as the ratio of the distance between the equivalent rotation point to the satellite and the distance between the equivalent rotation point to the target.
Preferably, the step S2 of calculating the azimuth processing signal bandwidth includes the following steps:
and S2-1, calculating the distance between the equivalent rotation point and the satellite according to the antenna and the system parameters.
For simplifying analysis, the azimuth antenna is set to work in a front side view mode, and the distance R between an equivalent rotation point and a satellitersMay be determined by the dwell time T in the antenna and system parametersdSatellite velocity VsAnd azimuth scanning angle
Figure GDA0002897344450000061
And calculating, wherein the expression is as follows:
Figure GDA0002897344450000062
and S2-2, calculating a mixing degree factor according to the distance between the equivalent rotation point and the satellite.
By definition, the distance R between the satellite and the target can be simulated from the central momentstAnd calculating a mixing degree factor gamma according to the distance between the equivalent rotation point and the satellite:
γ＝Rrs/(Rrs+Rst)。
and S2-3, calculating the multi-channel TOPSAR azimuth processing bandwidth according to the mixing factor gamma.
Since the azimuth beam rotates, the TOPSAR azimuth processing bandwidth BaFrom the corresponding azimuthal resolution ρaAnd obtaining the strip mode azimuth processing bandwidth and a mixing factor gamma, which specifically comprises the following steps:
Ba＝VsRg/(Rg+Rst)/(ρaγ)。
wherein the expression of the strip mode azimuth processing bandwidth is B'a＝VsRg/(Rg+Rst)/ρa。
And S3, dividing the azimuth scanning angle into N parts, and calculating the Doppler center frequency corresponding to each azimuth scanning angle according to the antenna and the system parameters.
Preferably, after dividing the azimuth scanning angle into N parts due to the rotation of the azimuth beam, the doppler center frequencies corresponding to the time of the centers of the N parts of azimuth scanning angles are calculated respectively. Further, for the convenience of analysis, it is desirable that N be an odd number.
Specifically, the step S3 of calculating the doppler center frequency corresponding to each azimuth scanning angle includes the following steps:
s3-1, scanning the whole azimuth by the angle
Figure GDA0002897344450000063
Dividing the azimuth angle into N parts, calculating the interval of the scanning angles of two adjacent divided azimuth angles, and expressing the interval as
Figure GDA0002897344450000071
S3-2, calculating the central squint angle corresponding to each azimuth scanning angle after division according to the interval of two adjacent azimuth scanning angles, wherein the expression of the central squint angle is
Figure GDA0002897344450000072
n＝-(N-1)/2,...,0,....(N-1)/2；
S3-3, according to the central oblique angle corresponding to each azimuth scanning angle
Figure GDA0002897344450000073
Calculating the corresponding Doppler center frequency according to the expression
Figure GDA0002897344450000074
Scanning for each azimuthAngle, from its central perspective
Figure GDA0002897344450000075
And respectively calculating the azimuth ambiguities corresponding to each azimuth scanning angle as a center.
And S4, aiming at one azimuth scanning angle, calculating a corresponding transfer function matrix of each receiving channel and a corresponding compensation matrix in the main lobe area.
Scanning angle in the first direction
Figure GDA0002897344450000076
The description is given for the sake of example. Setting the number of the single-side azimuth fuzzy areas corresponding to each receiving channel as NsinThe total number of fuzzy areas is Nam＝K·NsinThe sum of the total number of the fuzzy areas and the non-fuzzy areas is Num 2NamAnd + K, the transfer function matrix of the receiving channel is related to the distance between centers of adjacent phases, the number of azimuth ambiguity areas, the number of receiving channels and the like.
Specifically, the calculating the transfer function matrix of the receiving channel and the compensation matrix in the corresponding main lobe region includes:
and S4-1, calculating the azimuth time delay and the corresponding azimuth time delay error of each receiving channel compared with the central receiving channel.
For the receive channel k, the expression of the azimuth time delay compared to the center receive channel is Tdelay(k)＝kd/VsThe corresponding azimuth time delay error is expressed as
Figure GDA0002897344450000077
Wherein the content of the first and second substances,
Figure GDA0002897344450000078
Figure GDA0002897344450000079
representing a rounding down.
S4-2, calculating transfer functions in all fuzzy areas of different non-fuzzy receiving channels according to the azimuth time delay errors to obtain corresponding transfer function matrixes.
The transfer function in all the fuzzy regions corresponding to different non-fuzzy receiving channels k can be expressed as:
Figure GDA00028973444500000710
wherein i 1,2., Num;
the corresponding transfer function matrix can be expressed as:
Figure GDA0002897344450000081
and S4-3, calculating a compensation matrix in the corresponding main lobe region according to the transfer function matrix.
The compensation matrix in the main lobe region, that is, the filter matrix in the main lobe region, is obtained by inverting the corresponding part of the main lobe in the transfer function matrix, and the expression is:
Figure GDA0002897344450000082
and S5, calculating the azimuth off-axis angle corresponding to each fuzzy area and each non-fuzzy area by combining the Doppler center frequency corresponding to the azimuth scanning angle.
Further, when the azimuth off-axis angle corresponding to each fuzzy region and each non-fuzzy region is calculated, the frequency of each fuzzy region and each non-fuzzy region is firstly calculated, then the azimuth off-axis angle is calculated according to the corresponding frequency, and two conditions can be divided according to the parity of the receiving channel number K:
(1) k is an odd number
Taking the number of energy superposition points in a fuzzy area as Nz(for convenience of analysis, take NzOdd), the frequency interval calculated within one pulse repetition frequency is Fint＝fprf/NzThe resulting frequency sequence in one pulse repetition period is Fp(ii)＝Fint·mm+Fdn(for the first part orientation scanAngle of rotation
Figure GDA0002897344450000083
I.e. Fp(ii)＝Fint·mm+Fd1) The Doppler center frequency corresponding to the azimuth scanning angle is correlated, wherein mm is a frequency division sequence and the range is (N)z-1)/2,...,(Nz-1)/2), ii corresponding to the range (1, 2.., N)z) Then the frequency range calculated in all the blurred and non-blurred regions is Fre (i, ii) ═ Fp(ii)+(i-Nam-(K-1)/2-1)·fprfWherein the value ranges of i and ii are the same as above, and the corresponding azimuth off-axis angle is A through inverse calculation of the frequency rangengle(i,ii)＝asin(-Fre(i,ii)·λ/(2Vs) The azimuth off-axis angle corresponding to the simulation center moment is A)mid＝asin(-fd·λ/2Vs)。
(2) K is an even number
Taking the number of energy superposition points in a fuzzy area as Nz(conveniently, N is extractedzOdd), the frequency interval calculated within one pulse repetition frequency is Fint＝fprf/NzThe frequency sequence obtained in one pulse repetition period is Fp(ii)＝Fint·mm+Fdn(scanning angle for first part orientation
Figure GDA0002897344450000091
I.e. Fp(ii)＝Fint·mm+Fd1) Where mm is a frequency dividing sequence, range (0.5.., N.)z-0.5), ii corresponds to the range (1, 2.., N)z) Then the frequency range calculated in all the blurred and non-blurred regions is Fre (i, ii) ═ Fp(ii)+(i-Nam-(K-1)/2-1)·fprfWherein the value ranges of i and ii are the same as above, and the corresponding azimuth off-axis angle is A through inverse calculation of the frequency rangengle(i,ii)＝asin(-Fre(i,ii)·λ/(2Vs) The azimuth off-axis angle corresponding to the simulation center moment is A)mid＝asin(-fd·λ/2Vs)。
And S6, calculating antenna directional diagrams corresponding to the transmitting antenna and the receiving antenna according to the azimuth off-axis angles corresponding to the fuzzy areas and the non-fuzzy areas obtained in the step S5.
The antenna directional patterns of the transmitting antenna and the receiving antenna are in a sinc function form, and the energy of the antenna directional patterns corresponding to all azimuth off-axis angles is calculated in the step.
Preferably, the step of calculating the antenna patterns corresponding to the transmitting antenna and the receiving antenna in step S6 includes:
s6-1, calculating the energy corresponding to each azimuth off-axis angle of the transmitting antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area, wherein the expression is as follows:
Figure GDA0002897344450000092
s6-2, calculating the energy corresponding to each azimuth off-axis angle of the receiving antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area, wherein the expression is as follows:
Figure GDA0002897344450000093
s6-3, calculating the sum of the transmitting energy and the receiving energy corresponding to each calculation point according to the energy corresponding to each azimuth off-axis angle of the transmitting antenna and the receiving antenna, and obtaining the antenna directional diagram corresponding to the transmitting antenna and the receiving antenna, wherein the expression is as follows:
EA(i,ii)＝TA(i,ii)·RA(i,ii)。
and S7, calculating the sum of the energy of the non-fuzzy area according to the antenna directional diagram obtained in the step S6 and the azimuth processing signal bandwidth obtained in the step S2.
And (4) summing the energy of the non-fuzzy areas, namely, computing the sum of the energy of the main lobe. Preferably, the calculating of the sum of the non-blurred region energies in step S7 includes:
s7-1, processing the signal bandwidth according to the azimuth to obtain the effective azimuth calculation point number corresponding to the non-fuzzy area, the expression is
Figure GDA0002897344450000101
Figure GDA0002897344450000102
Representing a rounding down. For convenience of subsequent description, the antenna pattern corresponding to the two-dimensional non-ambiguity region obtained in step S6 is integrated into a one-dimensional form, which is expressed as:
EA1(p)＝[EA(Nam,1),EA(Nam+1,1),...EA(Nam+K,1),EA(Nam,2),...,EA(Nam+K,Nz)]
wherein p is 1,2z，EA1And (p) the antenna directional diagram corresponding to the non-fuzzy area in a one-dimensional form is shown.
S7-2, according to the effective azimuth calculation point number corresponding to the non-fuzzy area, extracting the corresponding signal amplitude in the effective bandwidth in the antenna directional diagram in a one-dimensional form, and calculating the energy sum of the non-fuzzy area.
When N is presentz_valIf the number is odd, keeping the value unchanged; when N is presentz_valWhen the number is even, adding 1 to the value to obtain the effective azimuth calculation point number corresponding to the new non-fuzzy area, namely updating Nz_valLet N stand forz_val＝Nz_val+ 1; corresponding signal amplitude EA within the effective bandwidth1In part (p), the expression is:
EA2(q)＝EA1((NzK-Nz_val)/2+1,...,(NzK+Nz_val)/2+1)；
wherein q is 1,2z_val，EA2And (q) extracting the antenna directional diagram in the one-dimensional form to obtain a corresponding antenna directional diagram in the effective bandwidth of the non-fuzzy area.
The total energy corresponding to the main lobe, i.e. the sum of the energies of the non-blurred regions, is:
Figure GDA0002897344450000103
and S8, calculating the sum of the energy in the fuzzy area according to the antenna directional diagram, the transfer function matrix and the compensation matrix in the corresponding main lobe area.
Preferably, the calculating of the sum of the blur area energies in step S8 includes:
and S8-1, obtaining a fuzzy area signal reconstruction filtering function according to the transfer function matrix of each receiving channel and the compensation matrix in the corresponding main lobe area.
Specifically, the left and right fuzzy areas are calculated respectively, and the reconstruction signal of the left fuzzy area is:
Figure GDA0002897344450000111
wherein the number of the jj unilateral fuzzy areas is (jj ═ 1,2.., N)am) And mm represents the number of channels, namely, a fuzzy area signal corresponding to a channel in each non-fuzzy area is reconstructed, and the value range is (mm ═ 1,2.., K).
The corresponding right ambiguity region reconstruction signal is:
Figure GDA0002897344450000112
wherein jj, mm means as defined above.
And S8-2, reconstructing the fuzzy area signal according to the fuzzy area signal reconstruction filtering function and the antenna directional diagram. The method comprises the following specific steps:
Figure GDA0002897344450000113
wherein mm 1,2, the page, K, pp value range and mm are relevant, are: pp ═ N (mm-1)z+1,(mm-1)Nz+2,...,mmNzAnd the reconstructed fuzzy area signal obtained by traversing all the values along with mm is EAA (p), wherein p is 1,2z。
And S8-3, according to the effective azimuth calculation points corresponding to the non-fuzzy region, extracting the corresponding signal amplitude in the effective bandwidth in the reconstructed fuzzy region signal, and calculating the energy sum of the fuzzy region.
Effective azimuth calculation points corresponding to fuzzy region and effective azimuth calculation points corresponding to non-fuzzy regionAlso, N can be utilizedz_valAnd (6) performing calculation. The corresponding signal amplitude within the effective bandwidth is a portion of eaa (p), and the expression is:
EAA2(q)＝EAA((NzK-Nz_val)/2+1,...,(NzK+Nz_val)/2+1)；
wherein q is 1,2z_val，EAA2And (q) extracting the corresponding antenna directional diagram in the effective bandwidth of the reconstructed fuzzy area signal.
The sum of the energy of the fuzzy area is:
Figure GDA0002897344450000114
and S9, calculating the azimuth ambiguity according to the energy sum of the non-fuzzy region and the energy sum of the fuzzy region.
In the step, the azimuth ambiguity of the azimuth scanning angle is calculated according to the energy sum of the non-fuzzy region and the energy sum of the fuzzy region obtained in the step, and the azimuth ambiguity calculation formula is as follows:
AASR(n)＝10*lg(EAm/Em)。
s10, executing the above steps S4 to S9 for each azimuth scanning angle, and calculating azimuth ambiguities corresponding to the N azimuth scanning angles.
And repeating the steps S4 to S9, and respectively calculating the corresponding azimuth ambiguity of each azimuth scanning angle, namely completing the calculation of the multi-channel satellite-borne TOPSAR azimuth ambiguity corresponding to each scanning angle, wherein the calculation result can be used for optimizing the system design.
The multi-channel satellite-borne TOPSAR azimuth ambiguity calculation method is obtained by combining the characteristics of the TOPSAR mode antenna azimuth rotation scanning on the basis of multi-channel signal reconstruction, can accurately calculate the azimuth ambiguity under different azimuth beam rotation angles, optimizes the overall design of a system, and lays a foundation for subsequent TOPSAR data processing.
Example two
The second embodiment is basically the same as the first embodiment, and the same parts are not described again, except that:
in step S1, acquiring antenna and system parameters includes: f. ofprf＝1300Hz，Vs＝7500m/s，fd＝0，K＝2，λ＝0.03m，d＝4.1m，LT＝8.2m，LR＝4.1m，H＝852000m，Rg＝6371140m，ρa＝12.3m，Td＝42.73s，
Figure GDA0002897344450000121
Rst＝881357m。
In step S2, the bandwidth of the multi-channel TOPSAR azimuth processing signal is calculated according to the antenna and system parameters, the mixing factor is 0.3332, and the bandwidth B of the azimuth processing signal is calculatedaIs 1615 Hz.
In step S3, the azimuth scanning angle is divided into N, and for the sake of analysis, N is 101.
In step S4, for one azimuth scanning angle, a transfer function matrix of each receiving channel and a compensation matrix in a corresponding main lobe region are calculated, and the number of single-side azimuth ambiguity regions corresponding to each receiving channel is NsinThe total number of fuzzy areas is Nam＝K·NsinThe sum of the total number of the fuzzy areas and the non-fuzzy areas is Num 2Nam+K，Nsin＝10,Nam＝20,Num＝42。
In step S5, the azimuth off-axis angle corresponding to each of the blurred region and the non-blurred region is calculated, where K is an even number when K is 2, and the number of energy superposition points in one blurred region is taken as N in the case of the (2) th casez，Nz＝101。
In step S7, the sum of the energy of the non-fuzzy region is calculated, and the effective direction calculation point number corresponding to the non-fuzzy region is obtained according to the direction processing signal bandwidth, where the expression is
Figure GDA0002897344450000131
Calculating to obtain Nz_val108, even, and N in the following analysisz_val109, and the sum of the energies in the main lobe is calculated as Em＝84.6424。
In step S8, according to the antenna pattern and the transfer function matrixCorresponding to the compensation matrix in the main lobe area, calculating the energy sum of the fuzzy area and EAm＝0.67。
In step S9, the azimuth ambiguity is calculated from the sum of the non-blur region energies and the sum of the blur region energies, and aasr (n) is calculated to be-21.0151 dB.
In step S10, the above steps S4 to S9 are repeated, and the azimuth ambiguities corresponding to all the azimuth N azimuth scanning angle ranges are calculated. And finally obtaining the azimuth ambiguities AASR (N) approximately equal to-21.0151 dB calculated in all the small azimuth scanning angles with the number of N being 101, namely, the AASR differences corresponding to each refined azimuth scanning angle are not large.
To illustrate the effectiveness of the present invention, the following target simulation experiments were performed, with some simulation parameters of the examples shown in table 1 and the results calculated as above.
Table 1 example partial simulation parameters
Figure GDA0002897344450000132
Figure GDA0002897344450000141
From the calculation results, it can be seen that the azimuth beam scanning does not affect the azimuth ambiguity calculation in the TOPSAR mode, and the azimuth ambiguities corresponding to the respective scanning angles do not differ much. The above results illustrate the correctness and effectiveness of the method provided by the invention for calculating the multi-channel spaceborne TOPSAR azimuth ambiguity.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (4)

1. A multi-channel spaceborne TOPSAR azimuth ambiguity analysis method is characterized by comprising the following steps:
s1, obtaining antenna and system parameters;
s2, calculating the multi-channel TOPSAR azimuth processing signal bandwidth according to the antenna and system parameters;
s3, dividing the azimuth scanning angle into N parts, and calculating the Doppler center frequency corresponding to each azimuth scanning angle;
s4, aiming at an azimuth scanning angle, calculating a transfer function matrix of each receiving channel and a compensation matrix in a corresponding main lobe area;
s5, calculating the azimuth off-axis angle corresponding to each fuzzy area and each non-fuzzy area by combining the Doppler center frequency corresponding to the azimuth scanning angle;
s6, calculating antenna directional diagrams corresponding to the transmitting antenna and the receiving antenna according to the azimuth off-axis angles corresponding to the fuzzy areas and the non-fuzzy areas;
s7, processing signal bandwidth according to the antenna directional diagram and the azimuth direction, and calculating the sum of energy in a non-fuzzy area;
s8, calculating the sum of energy in the fuzzy area according to the antenna directional diagram, the transfer function matrix and the compensation matrix in the corresponding main lobe area;
s9, calculating the azimuth ambiguity according to the energy sum of the non-fuzzy region and the fuzzy region;
s10, executing the steps S4 to S9 for each azimuth scanning angle, and calculating azimuth ambiguity corresponding to the N azimuth scanning angles;
wherein, the antenna and system parameters obtained in step S1 include: pulse repetition frequency fprfVelocity V of satellitesDoppler center frequency fdThe number of receiving channels K, the distance between adjacent phase centers of the receiving channels d, and the length L of the transmitting antennaTLength L of receiving antennaRSignal wavelength λ, satellite altitude H, earth radius RgAzimuthal resolution ρaDistance to satellite dwell time T in one subbanddAzimuth broomAngle tracing
Figure FDA0002897344440000011
Simulating the distance R between the satellite at the central moment and the targetst；
The calculating of the azimuth direction processing signal bandwidth in step S2 includes:
s2-1, calculating the distance between the equivalent rotation point and the satellite according to the antenna and the system parameters;
s2-2, calculating a mixing degree factor according to the distance between the equivalent rotation point and the satellite;
s2-3, calculating the multi-channel TOPSAR azimuth processing bandwidth according to the mixing factor;
the step S3 of calculating the doppler center frequency corresponding to each azimuth scanning angle includes:
s3-1, scanning the whole azimuth by the angle
Figure FDA0002897344440000024
Dividing the direction of the object to be scanned into N parts, and calculating the interval of the scanning angles of two adjacent parts of directions;
s3-2, calculating a central squint angle corresponding to each azimuth scanning angle according to the interval of two adjacent azimuth scanning angles;
s3-3, according to the central oblique angle corresponding to each azimuth scanning angle
Figure FDA0002897344440000025
Calculating the corresponding Doppler center frequency;
in step S4, for an azimuth scanning angle, the number of single-sided azimuth ambiguity regions corresponding to each receiving channel is set to be NsinThe total number of fuzzy areas is Nam＝K·NsinThe sum of the total number of the fuzzy areas and the non-fuzzy areas is Num 2Nam+ K; the step of calculating the transfer function matrix of the receiving channel and the compensation matrix in the corresponding main lobe area comprises the following steps:
s4-1, calculating the azimuth time delay error of each receiving channel compared with the central receiving channel;
s4-2, calculating transfer functions in all fuzzy areas of different non-fuzzy receiving channels according to the azimuth time delay error to obtain corresponding transfer function matrixes;
s4-3, calculating a compensation matrix in the corresponding main lobe region according to the transfer function matrix;
in the step S4-1, for the receiving channel k, the expression of the azimuth time delay is T compared with the central receiving channeldelay(k)＝kd/VsThe corresponding azimuth time delay error is expressed as
Figure FDA0002897344440000021
Wherein the content of the first and second substances,
Figure FDA0002897344440000022
Figure FDA0002897344440000023
represents rounding down;
in step S4-2, when the transfer functions in all the fuzzy areas corresponding to different non-fuzzy receiving channels k are calculated, the expression of the transfer function is:
Figure FDA0002897344440000031
wherein i 1,2., Num;
the expression of the corresponding transfer function matrix is:
Figure FDA0002897344440000032
in step S4-3, when calculating the compensation matrix in the corresponding main lobe region, inverting the corresponding part of the main lobe in the transfer function matrix, where the expression is:
Figure FDA0002897344440000033
2. the method of claim 1, wherein the step S6 of calculating the antenna patterns corresponding to the transmitting antenna and the receiving antenna comprises:
s6-1, calculating the energy corresponding to each azimuth off-axis angle of the transmitting antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area;
s6-2, calculating the energy corresponding to each azimuth off-axis angle of the receiving antenna according to the sinc function and the azimuth off-axis angles corresponding to each fuzzy area and each non-fuzzy area;
and S6-3, obtaining antenna directional diagrams corresponding to the transmitting antenna and the receiving antenna according to the energy corresponding to the off-axis angles of the transmitting antenna and the receiving antenna in each direction.
3. The method according to claim 2, wherein in the step S7, the calculating the sum of the energies of the non-blur areas comprises:
s7-1, processing the signal bandwidth according to the azimuth to obtain the effective azimuth calculation point number corresponding to the non-fuzzy area; integrating the obtained antenna directional patterns into a one-dimensional form;
s7-2, according to the effective azimuth calculation point number corresponding to the non-fuzzy area, extracting the corresponding signal amplitude in the effective bandwidth in the antenna directional diagram in a one-dimensional form, and calculating the energy sum of the non-fuzzy area.
4. The method according to claim 3, wherein the step S8 of calculating the sum of the fuzzy area energies comprises:
s8-1, obtaining a fuzzy area signal reconstruction filtering function according to the transfer function matrix of each receiving channel and the compensation matrix in the corresponding main lobe area;
s8-2, reconstructing a fuzzy area signal according to the fuzzy area signal reconstruction filtering function and the antenna directional diagram;
and S8-3, according to the effective azimuth calculation points corresponding to the non-fuzzy region, extracting the corresponding signal amplitude in the effective bandwidth in the reconstructed fuzzy region signal, and calculating the energy sum of the fuzzy region.
CN201910806544.XA 2019-08-29 2019-08-29 Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method Active CN110501708B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910806544.XA CN110501708B (en) 2019-08-29 2019-08-29 Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910806544.XA CN110501708B (en) 2019-08-29 2019-08-29 Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method

Publications (2)

Publication Number Publication Date
CN110501708A CN110501708A (en) 2019-11-26
CN110501708B true CN110501708B (en) 2021-03-30

Family

ID=68590447

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910806544.XA Active CN110501708B (en) 2019-08-29 2019-08-29 Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method

Country Status (1)

Country Link
CN (1) CN110501708B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111273234B (en) * 2020-01-06 2021-12-24 内蒙古工业大学 Signal receiving and transmitting method based on synthetic aperture radar system
CN117233765B (en) * 2023-11-16 2024-02-27 中国科学院空天信息创新研究院 Satellite-borne SAR distance ambiguity suppression method based on receiving-transmitting pointing separation

Family Cites Families (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5294933A (en) * 1993-01-29 1994-03-15 Westinghouse Electric Corp. Wideband radar system utilizing adaptive interference canceler
CN101957449B (en) * 2010-04-06 2011-06-01 北京航空航天大学 Optimization method for azimuth ambiguity in space-borne TOPSAR mode
CN102967861B (en) * 2012-10-17 2014-02-12 中国人民解放军国防科学技术大学 Terrain observation by progressive scans synthetic aperture radar (TOPSAR) system parameter engineering design method
US9335410B2 (en) * 2013-02-19 2016-05-10 Mitsubishi Electric Research Laboratories, Inc. System and method for multiple spotlight synthetic radar imaging using random beam steering
CN103728618B (en) * 2014-01-16 2015-12-30 中国科学院电子学研究所 The satellite-borne SAR system implementation method of a kind of high resolving power, wide swath
CN104020456B (en) * 2014-06-18 2016-08-24 中国科学院电子学研究所 A kind of based on many special aobvious some linear array imaging radar system amplitude and phase error correction methods
EP3177941A4 (en) * 2014-08-08 2018-04-25 Urthecast Corp. Apparatus and methods for quad-polarized synthetic aperture radar
CN104898119B (en) * 2015-05-19 2018-08-24 北京航空航天大学 A kind of moving target parameter estimation method based on correlation function
CN106569189B (en) * 2016-10-31 2019-04-09 北京空间飞行器总体设计部 A kind of high resolution SAR satellite distance fuzziness method for analyzing performance
CN107015223B (en) * 2017-03-07 2020-01-21 中国科学院电子学研究所 Synthetic aperture radar azimuth signal reconstruction method and device
CN108008381B (en) * 2017-06-09 2019-01-01 北京航空航天大学 A kind of target bearing side lobe suppression method and device based on angles of azimuth SAR image
CN107976674A (en) * 2017-10-31 2018-05-01 西安空间无线电技术研究所 The PRF systems of selection of dualbeam SAR obscured based on top optimization direction a kind of and system
CN108267736B (en) * 2017-12-20 2019-11-29 西安空间无线电技术研究所 A kind of GEO SAR staring imaging mode orientation fuzziness determines method
CN108196253B (en) * 2017-12-27 2019-09-20 北京航空航天大学 A kind of azimuth ambiguity suppression method for synthetic aperture radar
CN108279404B (en) * 2018-01-22 2021-06-08 西安电子科技大学 Two-channel SAR phase error correction method based on spatial spectrum estimation
CN108845318B (en) * 2018-05-31 2022-04-15 南京航空航天大学 Satellite-borne high-resolution wide-range imaging method based on Relax algorithm
CN109061640B (en) * 2018-07-02 2022-06-21 南京信息工程大学 Azimuth fuzzy suppression method for forward-orbit interference SAR ocean current inversion
CN109669184B (en) * 2019-02-25 2021-04-20 电子科技大学 Synthetic aperture radar azimuth ambiguity elimination method based on full convolution network

Also Published As

Publication number Publication date
CN110501708A (en) 2019-11-26

Similar Documents

Publication Publication Date Title
CN107229048B (en) High-resolution wide-range SAR moving target speed estimation and imaging method
Zhang et al. Fast inverse-scattering reconstruction for airborne high-squint radar imagery based on Doppler centroid compensation
CN106970386A (en) A kind of optimization method of RADOP beam sharpening
CN102346249B (en) Implementation method for wide swath earth observation step scanning mode of synthetic aperture radar
Sun et al. Beam steering SAR data processing by a generalized PFA
CN110632594B (en) Long-wavelength spaceborne SAR imaging method
Xiong et al. New applications of omega-K algorithm for SAR data processing using effective wavelength at high squint
CN110501708B (en) Multi-channel spaceborne TOPSAR azimuth ambiguity analysis method
CN114545411B (en) Polar coordinate format multimode high-resolution SAR imaging method based on engineering realization
CN104316924A (en) Autofocus motion compensation method of airborne ultra-high resolution SAR (Synthetic Aperture Radar) back projection image
CN109270528B (en) One-station fixed type double-station SAR imaging method based on full-analytic distance model
CN103235305B (en) Spaceborne ultrahigh-resolution sliding bunching SAR (synthetic aperture radar) imaging method
CN105676190B (en) A kind of method and apparatus of correction synthetic aperture radar echo data
CN112198509B (en) Directional spectrum inverse filtering reconstruction method for multichannel spaceborne SAR on-board real-time processing
CN114201891B (en) Method for configuring base line and phase center between multiple channels of antenna azimuth
EP3534178B1 (en) Radar apparatus with antenna array and method for source location using a two-dimensional antenna array
Zuo et al. Unified coordinate system algorithm for terahertz video-SAR image formation
CN108535726A (en) ISAR imaging methods based on power power Fourier transformation
CN102928839B (en) Full-aperture imaging method for multi-channel wave beam-pointing synthetic aperture radar (SAR)
CN113484859B (en) Two-dimensional super-resolution radar imaging method based on fusion technology
CN110133646B (en) NLCS imaging-based multi-channel two-pulse clutter cancellation method for bistatic forward-looking SAR
Deng et al. A processing framework for airborne microwave photonic SAR with resolution up to 0.03 m: motion estimation and compensation
CN103076608B (en) Contour-enhanced beaming-type synthetic aperture radar imaging method
CN115236671B (en) Sequential SAR image moving target recovery method based on null wave beam construction
CN104008270A (en) Multichannel reconstruction method and device for periodical non-uniform sampling SAR (synthetic aperture radar) signals

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant