CN112346058A - Imaging method for improving signal-to-noise ratio of high-speed SAR platform based on continuous pulse coding - Google Patents
Imaging method for improving signal-to-noise ratio of high-speed SAR platform based on continuous pulse coding Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9004—SAR image acquisition techniques
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- G—PHYSICS
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- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
The invention discloses an imaging method for improving the signal-to-noise ratio of a high-speed SAR platform based on continuous pulse coding, which mainly solves the problem that the prior art cannot image on the high-speed SAR platform. The implementation scheme is as follows: designing a pulse train signal and repeating the pulse train signal; obtaining an original aliasing echo signal according to the transmitted pulse train signal; constructing a multi-element linear equation set according to the transmitted pulse train signal form: selecting a plurality of sub-equation sets with the same equation quantity from the multi-element linear equation set according to the determined step length, and solving the complete echo signal to obtain the echo signal after aliasing resolution; and uniformly grouping and superposing the unmixed and superposed echo signals in the same group, and carrying out SAR imaging on the superposed echo signals according to the equivalent pulse repetition frequency. The invention can improve the azimuth sampling rate, eliminate the azimuth spectrum aliasing of the echo, realize the imaging on a high-speed platform, and can be used for topographic mapping, ocean observation, disaster prediction, crop evaluation and celestial body observation.
Description
Technical Field
The invention belongs to the technical field of digital signal processing, and particularly relates to an imaging method for improving the signal-to-noise ratio of an image of a high-speed SAR platform, which can be used for topographic mapping, ocean observation, disaster prediction, crop evaluation and celestial body observation.
Background
The synthetic aperture radar SAR is a full-time and all-weather remote detection means and has the capability of imaging a target. The signal-to-noise ratio SNR of the radar image is one of important indicators for measuring the imaging quality of the radar image, and directly determines whether accurate target information can be obtained from the radar image. In military applications, battlefield reconnaissance, target identification, ground attack, etc., and in civilian applications, terrain mapping, ocean observation, disaster prediction, crop assessment, celestial observation, etc., are available.
Wang Shifei et al put forward a pulse coding theory in a radar pulse coding theory method and application [ J ] radar science report, 2019,8(1): 1-16. doi:10.12000/JR19023 ], and improve the signal-to-noise ratio of a radar image by improving the duty ratio of a transmitted signal. The method comprises the steps of converting a monopulse signal transmitted in an original pulse repetition period into a group of long pulse train signals containing a plurality of monopulses, resolving and processing aliasing echoes in each receiving window to recover complete echoes corresponding to the monopulse signals as much as possible, and finally performing coherent superposition on the recovered complete echoes to achieve the purpose of improving the signal-to-noise ratio of radar echoes. The method has the following defects:
the recovered multiple groups of complete echoes need to transmit overlong pulse signals, and the longer the transmitted signals are, the larger the pulse train repetition period is, namely the lower the pulse train repetition frequency is, so that the method applied to a high-speed SAR platform can cause aliasing of the azimuth frequency spectrum of the echoes due to the fact that the pulse train repetition frequency is not high enough according to the sampling theorem, and the imaging effect is poor.
Disclosure of Invention
The invention aims to provide an imaging method for improving the signal-to-noise ratio of a high-speed SAR platform based on continuous pulse coding aiming at the defects in the prior art so as to equivalently improve the azimuth sampling rate, eliminate the azimuth spectrum aliasing of echoes and improve the imaging effect.
The technical idea of the invention is as follows: the method comprises the steps of continuously transmitting pulse train signals by taking the length of a pulse train as a period, selecting receiving windows which are periodically arranged to solve aliasing echoes, taking complete echo signals recovered by each group as one-time slow sampling echoes of a radar, and accurately imaging a target while obtaining a high signal-to-noise ratio by a high-speed SAR platform.
According to the above thought, the implementation steps of the invention include the following:
(1) designing a pulse train signal, and repeatedly transmitting the pulse train signal, wherein the repetition period is the width of the pulse train signal, each pulse train signal comprises a plurality of single pulse signals, and gaps among the single pulse signals are receiving windows;
(2) simulating SAR echo signals according to the transmitted pulse train signals to obtain original aliasing echo signals;
(3) constructing a multi-element linear equation set according to the form of the transmitted pulse train signal: where L is an observation matrix of each receive window, X is a set of all complete echoes that need to be solved, and R is an aliased echo signal of each receive window;
(4) selecting a plurality of sub-equation sets with the same equation quantity from the multi-element linear equation set established in the step (3) according to the determined step length, and solving the set X of all complete echoes to obtain an echo signal after aliasing resolution;
(5) uniformly grouping and superposing the echo signals after unmixing and superposition in the same group, and carrying out SAR imaging on the superposed echo signals according to equivalent pulse repetition frequency PRF;
compared with the prior art, the invention has the following advantages:
1. equivalently improving the azimuth sampling rate, eliminating the azimuth spectrum aliasing of the echo, and being suitable for a high-speed platform
In the prior art, in order to improve the signal-to-noise ratio of a radar image, a series of single pulse coding signals are adopted, and a next pulse train can be transmitted only after the echo of the last sub-pulse in the current pulse train is received, namely the transmitting frequency of the pulse train cannot be too large, so that for a high-speed platform, the azimuth frequency spectrum of the high-speed platform is subjected to aliasing due to undersampling, and accurate imaging cannot be performed;
the invention adopts a continuous pulse coding method, the pulse train repetition period is the time width of the pulse train, namely, the next pulse train is transmitted after the echo of the last sub-pulse in the current pulse train is received; in addition, the invention equivalently converts a plurality of groups of complete echoes calculated in a pulse train repetition period into sampling echoes of the radar at different azimuth moments, equivalently improves the radar azimuth sampling frequency, simultaneously ensures the signal-to-noise ratio requirement of the SAR image, eliminates azimuth spectrum aliasing caused by undersampling, improves the SAR imaging effect, and can be applied to a high-speed platform.
2. High adaptability
Because the invention designs the pulse train signal composed of S, 0 and-S, for the platforms with different speeds, a plurality of groups of echoes calculated in a pulse train repetition period can be equivalent to the sampling echoes of the radar at different azimuth moments, and partial echoes can be subjected to coherent superposition to improve the signal-to-noise ratio of one-dimensional distance direction, so that the invention has strong adaptability, and can be applied to not only high-speed platforms but also low-speed platforms.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a schematic diagram of a continuous pulse encoded signal transmitted in the present invention;
FIG. 3 is a diagram of echoes corresponding to burst encoded signals in the present invention;
FIG. 4 is a block diagram of an echo signal according to the present invention;
FIG. 5 is a schematic diagram of echo azimuth spectral aliasing caused by application of the prior art to a high speed platform;
FIG. 6 is a schematic diagram of the echo azimuth spectrum of the present invention applied to a high-speed platform;
FIG. 7 is a diagram of conventional single pulse imaging results on a high-speed stage;
FIG. 8 is a schematic diagram of the imaging results of the present invention at a high speed stage.
Detailed Description
The following describes in detail specific embodiments and effects of the present invention with reference to the drawings.
Referring to fig. 1, the implementation steps of this example are as follows:
step 1, designing a pulse train signal and repeatedly transmitting the pulse train signal.
The pulse train signal designed by the embodiment is composed of S, 0 and S, wherein S is time width TPThe interval of the chirp signal is fixed to TPOr 2TPI.e. one or two receive windows; s is a phase which adds pi to S, 0 represents a time width TPThe receive window of (1). The pulse train signal has a plurality of groups of permutation and combination forms, the length is designed according to requirements, fig. 2 shows an example of the pulse train signal, and the pulse train signal is represented as follows: S0S0S00S00-S0-S0S00S00S 0S;
the radar repeatedly transmits the pulse train signal to the target with the time width of the pulse train as a period.
And 2, receiving the echo signal of the target scene by the radar.
Because the interval time of the single pulses in the transmitted pulse train signal is very short, the echo corresponding to each single pulse signal is subjected to aliasing, and because the radar adopts a single-channel mode, a target echo cannot be received when the signal is transmitted, part of the echo is shielded by the transmitted single pulse signal, so that the echo is not complete, and the echo signal received by the radar is an incomplete and aliased signal, as shown in fig. 3;
because the imaging processing cannot be directly performed by using the echo in the receiving window due to the imperfection and aliasing of the echo, the complete echo information corresponding to the monopulse needs to be recovered from the aliasing echo of each receiving window.
And 3, constructing a multi-element linear equation set according to the form of the transmitted pulse train signal.
(3a) Let X be the set of all complete echoes to be solved, and because the pitch angle of the beam is limited and the scene width of radar illumination is limited, the length of the scene echo corresponding to a single pulse is limited, i.e. the duration of the scene echo corresponding to a single pulse after reception is limited from the beginning is denoted as T, and N is defined as T/TPIs upwardly-directed integer value of, wherein TPFor the time width of the chirp signal, X is given by TPIs a unit, is divided into N segments and is marked as X ═ X1,X2...Xn...XN]TAs shown in FIG. 4, wherein XnFor the nth echo, N is equal to [1, N ]]；
(3b) The aliased echo signal of each receive window is denoted as R ═ R1,R2...Rm...RM]T，RmFor the aliased echo signal of the mth receive window, M ∈ [1, M]M is the total number of receiving windows, and for the signal example in step 1, M is 13 × nan, and nan is the number of pulse train signals transmitted to the radar in the azimuth direction;
(3c) and (3) obtaining an observation matrix L according to the echo length and the transmitted pulse train signal form:
wherein lmnRepresents whether the nth segment of echo X exists in the mth receiving windownIf present, according to XnTaking l as positive and negative of corresponding transmitted monopulsemnIs 1 or-1, if no echo X exists in the mth receiving windownThen l ismnThe value is 0, M is belonged to [1, M]，n∈[1,N]；
(3d) And constructing a linear equation system Y according to the aliasing echo signals R and the observation matrix L of each receiving window:
constructing a linear equation set Y to be expressed as LX-R without considering noise, solving the equation set to obtain a complete echo set X without noise,
when considering noise, a system of linear equations is constructed as: solving the equation set to obtain a complete echo set X under the condition of noise, and simultaneously obtaining the change condition of the noise so as to measure the improvement of the signal-to-noise ratio of the radar;
and 4, resolving a linear equation set of the sub-lines to obtain a complete target echo corresponding to the single pulse signal.
Because the interval of the pulses in each group in the pulse train signal is very small and is in the microsecond level, the echo signals of each sub-pulse in one pulse train repetition period can be assumed to be approximately the same, and the assumption provides possibility for resolving the complete scene echo corresponding to a single pulse from the aliasing echo;
(4a) selecting Q continuous equations from the linear equation set Y, forming a sub-linear equation set lx belonging to Y, which is recorded as Y, and solving x to obtain: x ═ lTl)-1lTr, where Q > ═ N, L is a submatrix extracted row-wise for L, the rank of L is equal to or greater than N, i.e. LTl is a reversible matrix, X is a certain complete echo, X belongs to X, and R is a subvector of R;
(4b) selecting K as a step length, using a sub-linear equation set Y as a reference, sequentially selecting Q continuous equations in the linear equation set Y to form other sub-linear equation sets until all the equations in Y are selected, solving X corresponding to each equation set, and further obtaining a complete echo set X after de-aliasing1Then x, i.e. the radar equivalent pulse repetition frequency PRF is 1/T1. In the selection of T1The PRF is required to be greater than the minimum azimuth sampling rate required by radar imaging.
And 5, carrying out SAR imaging processing on all the recovered complete echoes.
(5a) Arranging the solved complete echoes in sequence according to the corresponding receiving windows;
(5b) and uniformly grouping the arrayed echoes to enable each group to contain num complete echoes, and then performing coherent superposition on the num complete echoes in the same group. The step (4b) easily deduces that the equivalent pulse repetition frequency PRF after the packet superposition is 1/(num × T)1)；
Because the echo in the group is coherent superposition and the noise is incoherent superposition, theoretically, the more the number of the superposed echoes is, the more the signal-to-noise ratio is improved, but as can be known from an equivalent pulse repetition frequency formula, the more the number of the superposed echoes is, the lower the equivalent azimuth sampling rate of the radar is, the problem of spectrum aliasing caused by undersampling of the echo obtained by the high-speed platform radar after solving can be caused, and accurate SAR imaging cannot be performed, so that the number of the echo in the group cannot be too large in the actual imaging process, and the number num of the echo in the group needs to be flexibly selected under the condition of meeting the requirements.
The technical effects of the invention are further explained by simulation experiments as follows:
1. simulation conditions
Creating a target model with 3 points, and performing a simulation test on a computer by using MATLAB R2018b software, wherein SAR system simulation parameters are shown in tables 1, 2 and 3:
TABLE 1 SAR System simulation parameters 1
TABLE 2 SAR System simulation parameters 2
TABLE 3 SAR System simulation parameters 3
2. Emulated content
Simulation 1, simulating the azimuth spectrum of the echo by using the radar pulse coding theory and the applied method in the background art under the SAR system simulation parameters of table 1, and the result is shown in fig. 5.
Simulation 2, under the SAR system simulation parameters of table 1, the method of the present invention is used to simulate the azimuth spectrum of the echo, and the result is shown in fig. 6.
Simulation 3, under the SAR system simulation parameters of table 2, performing conventional single pulse imaging on the target, wherein the pulse repetition frequency is the equivalent pulse repetition frequency of the present invention that employs the parameters of table 3 for imaging, and the imaging result is shown in fig. 7.
Simulation 4, in the SAR system simulation parameters in table 3, the target is imaged by using the method of the present invention, and the imaging result is shown in fig. 8.
3. Analysis of simulation results
Comparing fig. 5 and fig. 6, it can be seen that when the method of the radar pulse coding theory and application in the background art is applied to a high-speed platform, the azimuth spectrum of the echo is aliased and cannot be used for SAR imaging, whereas when the method of the present invention is applied to a high-speed platform, the azimuth spectrum of the echo is not aliased and can be used for SAR imaging.
Comparing the imaging result graphs of fig. 7 and fig. 8, it can be seen that the image noise in fig. 8 is significantly reduced, and the imaging quality is significantly better than that in fig. 7, which shows that the present invention not only effectively improves the signal-to-noise ratio of the SAR image, but also solves the imaging problem of the high-speed SAR platform.
Claims (5)
1. An imaging method for improving the signal-to-noise ratio of a high-speed SAR platform based on continuous pulse coding is characterized by comprising the following steps:
(1) designing a pulse train signal, and repeatedly transmitting the pulse train signal, wherein the repetition period is the width of the pulse train signal, each pulse train signal comprises a plurality of single pulse signals, and gaps among the single pulse signals are receiving windows;
(2) simulating SAR echo signals according to the transmitted pulse train signals to obtain original aliasing echo signals;
(3) constructing a multi-element linear equation set according to the form of the transmitted pulse train signal: where L is an observation matrix of each receive window, X is a set of all complete echoes that need to be solved, and R is an aliased echo signal of each receive window;
(4) selecting a plurality of sub-equation sets with the same equation quantity from the multi-element linear equation set established in the step (3) according to the determined step length, and solving the set X of all complete echoes to obtain an echo signal after aliasing resolution;
(5) and uniformly grouping and superposing the unmixed echo signals in the same group, and carrying out SAR imaging on the superposed echo signals according to the equivalent pulse repetition frequency PRF.
2. The method of claim 1, wherein the burst signal designed in (1) is a burst consisting of S, 0, -S, wherein S is a time width TPThe interval of the chirp signal is fixed to TPOr 2TPI.e. one or two receive windows; s is a phase which adds pi to S, 0 represents a time width TPThe receive window of (a); the radar repeatedly transmits the pulse train signal with the time width of the pulse train as a period.
3. The method of claim 1, wherein (3) the system of multivariate linear equations is constructed from the form of the transmitted burst signal by:
3a) let X be the set of all complete echoes to be solved, the duration of the scene echo corresponding to a single pulse after the scene echo is received from the beginning is T, and N is defined as T/TPIs upwardly-directed integer value of, wherein TPFor the time width of the chirp signal, X is given by TPIs a unit, is divided into N segments and is marked as X ═ X1,X2...Xn...XN]TWherein X isnFor the nth echo, N is equal to [1, N ]]；
3b) The aliased echo signal of each receive window is denoted as R ═ R1,R2...Rm...RM]T，RmFor the aliased echo signal of the mth receive window, M ∈ [1, M]M is the total number of receiving windows;
3c) and (3) obtaining an observation matrix L according to the echo length and the transmitted pulse train signal form:
element L in LmnRepresents whether the nth segment of echo X exists in the mth receiving windown，m∈[1,M]，n∈[1,N]If present, according to XnThe positive and negative of the corresponding transmitting single pulse are respectively 1 or-1, if the m-th receiving window has no echo XnIf so, the value is 0,
under the condition of not considering noise, a linear equation set LX ═ R, denoted as equation set Y, can be constructed to solve the complete echo set X, and when considering noise, the real receiving window signal model should be: LX + N-R can obtain the change situation of noise while carrying out echo calculation, thereby measuring the improvement of the signal-to-noise ratio of the radar.
4. The method according to claim 1, wherein a plurality of sub-equation sets with the same number are selected in (4) to obtain the de-aliased echo signal, and the following is implemented:
4a) selecting Q continuous equations from the linear equation set Y, forming a sub-linear equation set lx belonging to Y, which is recorded as Y, and solving x to obtain: x ═ lTl)-1lTr, where Q > ═ N, L is a submatrix extracted row-wise for L, the rank of L is equal to or greater than N, i.e. LTl is a reversible matrix, X is some complete echo, X ∈ X, R is the subvector of R;
4b) and selecting K as a step length, taking the equation set Y as a reference, sequentially selecting Q continuous equations in Y to form other sub-linear equation sets until all the equations in Y are selected, and solving X corresponding to each equation set to further obtain a complete echo set X after solution and aliasing.
5. The method of claim 1, wherein the equivalent pulse repetition frequency PRF of (5) is determined by grouping the echoes into groups, i.e., the number of echoes num and the distribution period T of the reception window1The product of (a) and (b) is obtained by taking the reciprocal.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113111758A (en) * | 2021-04-06 | 2021-07-13 | 中山大学 | SAR image ship target identification method based on pulse neural network |
| CN114428229A (en) * | 2022-01-02 | 2022-05-03 | 西安电子科技大学 | Signal-to-noise ratio improving method for pulse coding radar with any time interval |
| CN114488151A (en) * | 2022-04-08 | 2022-05-13 | 中国科学院空天信息创新研究院 | Active and passive combined detection method, device, equipment and medium for observation ship |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3339895A1 (en) * | 2016-12-22 | 2018-06-27 | Airbus Defence and Space GmbH | Multiple input multiple output, mimo, radar system |
| CN109782284A (en) * | 2019-03-15 | 2019-05-21 | 中国科学院电子学研究所 | A method of the synchronous interference SAR of Long baselines is realized based on pulse code |
| CN109946654A (en) * | 2019-01-30 | 2019-06-28 | 西安电子科技大学 | Radar array element-pulse code and processing method |
| CN110261851A (en) * | 2019-03-15 | 2019-09-20 | 中国科学院电子学研究所 | A method of full-polarization SAR is realized based on pulse code |
| CN110412570A (en) * | 2018-10-19 | 2019-11-05 | 西安电子科技大学 | HRWS-SAR imaging method based on space impulse phase code |
-
2020
- 2020-10-30 CN CN202011190783.6A patent/CN112346058B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3339895A1 (en) * | 2016-12-22 | 2018-06-27 | Airbus Defence and Space GmbH | Multiple input multiple output, mimo, radar system |
| CN110412570A (en) * | 2018-10-19 | 2019-11-05 | 西安电子科技大学 | HRWS-SAR imaging method based on space impulse phase code |
| CN109946654A (en) * | 2019-01-30 | 2019-06-28 | 西安电子科技大学 | Radar array element-pulse code and processing method |
| CN109782284A (en) * | 2019-03-15 | 2019-05-21 | 中国科学院电子学研究所 | A method of the synchronous interference SAR of Long baselines is realized based on pulse code |
| CN110261851A (en) * | 2019-03-15 | 2019-09-20 | 中国科学院电子学研究所 | A method of full-polarization SAR is realized based on pulse code |
Non-Patent Citations (3)
| Title |
|---|
| LUPENG GUO等: "Inter-pulse Phase Coding For MIMO-SAR Imaging", 《2019 6TH ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR)》 * |
| YAPENG HE等: "Frequency-Coded Pulse Radar Imaging via Compressive Sensing", 《IEEE》 * |
| 王岩飞等: "雷达编码脉冲理论方法及应用", 《雷达学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113111758A (en) * | 2021-04-06 | 2021-07-13 | 中山大学 | SAR image ship target identification method based on pulse neural network |
| CN113111758B (en) * | 2021-04-06 | 2024-01-12 | 中山大学 | SAR image ship target recognition method based on impulse neural network |
| CN114428229A (en) * | 2022-01-02 | 2022-05-03 | 西安电子科技大学 | Signal-to-noise ratio improving method for pulse coding radar with any time interval |
| CN114488151A (en) * | 2022-04-08 | 2022-05-13 | 中国科学院空天信息创新研究院 | Active and passive combined detection method, device, equipment and medium for observation ship |
| CN114488151B (en) * | 2022-04-08 | 2022-06-24 | 中国科学院空天信息创新研究院 | Active and passive combined detection method, device, equipment and medium for observation ship |
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