CN113203998B - ISAR translation compensation and imaging method, system, medium and device - Google Patents
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Abstract
The invention provides an ISAR (inverse synthetic aperture radar) translation compensation and imaging method, a system, a medium and equipment, which comprise the following steps: step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals; step 2: performing generalized keystone transformation on the baseband signals and simultaneously completing linear distance walk correction and non-uniform signal reconstruction; and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term; and 4, step 4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase; and 5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform. The invention can process translation compensation and ISAR imaging under random PRF, thereby obtaining high-resolution ISAR images, and the proposed algorithm does not involve any nonlinear operation, and can obtain near-optimal performance under the environment of low signal-to-noise ratio.
Description
Technical Field
The invention relates to the technical field of radar signal processing, in particular to an ISAR (inverse synthetic aperture radar) translation compensation and imaging method, system, medium and equipment. And more particularly, to an ISAR translational compensation and imaging method based on random pulse repetition frequency.
Background
Compared with a Synthetic Aperture Radar (SAR) system which is mainly used for acquiring two-dimensional high-resolution imaging of a static scene, an Inverse Synthetic Aperture Radar (ISAR) system can complete two-dimensional high-resolution imaging of a non-cooperative target so as to acquire detailed information of an interested moving target, including motion information, shape, structure, size and the like, and is one of important means for effective target observation and national defense construction.
The relative motion between the target and the radar can be divided into a translation part and a rotation part, wherein the translation part does not contribute to imaging and needs to be accurately compensated; the latter is the basis for imaging and as such needs to be properly processed to obtain well focused ISAR images. Therefore, in order to acquire a two-dimensional high-resolution image of a non-cooperative target, ISAR (inverse synthetic aperture radar) translational compensation is firstly required to be completed, and the ISAR translational compensation comprises two steps of envelope alignment and initial phase correction, and envelope walking and phase walking caused by translational motion between the target and a radar are respectively solved. For envelope alignment, a related scholars have proposed a plurality of schemes, and typical methods include an envelope correlation method, a minimum entropy method, a global envelope alignment method and the like; these methods have high performance at high signal-to-noise ratios (SNR), but are susceptible to noise and envelope hopping. For initial phase correction, typical methods include phase gradient self-focusing, eigen-point method, etc.; the algorithm can effectively remove phase errors caused by the translation part, and also has higher requirement on SNR. In order to improve stability, methods of combined envelope alignment and initial phase correction are proposed, for example, a full-dimensional search scheme based on a particle swarm algorithm is proposed, the algorithm finishes estimation of translation parameters by extracting phase history caused by translation and combining image quality evaluation indexes, and therefore translation compensation is finished. This class is robust to noise but has a high computational complexity.
Although the conventional ISAR technology based on the uniform Pulse Repetition Frequency (PRF) is relatively mature, with the development of the electromagnetic interference technology, the requirements of the actual system for interference resistance, resolution and the like are further improved. The random/agile PRF signal is used as a transmitting signal, which is beneficial to solving the problem of distance ambiguity, improving the azimuth resolution, enhancing the anti-interference performance and the like. However, in the PRF-agile radar system, for non-cooperative target ISAR imaging, the target may be defocused seriously by imaging using the conventional translation compensation algorithm and imaging algorithm. For the problem, the traditional non-uniform sampling theory can perform signal reconstruction processing along the slow time dimension at each distance frequency point by using a traditional non-uniform signal reconstruction method, but the method needs to perform non-uniform signal reconstruction at each distance frequency point, so the calculation complexity is relatively high. In addition, if the target is a fast target, doppler blurring of the target occurs, further increasing the difficulty of signal processing. Therefore, under the condition that the signal sampling of the target is non-uniform, the ISAR imaging of the target with Doppler blurring and low SNR is a key problem with relatively small computational complexity.
Disclosure of Invention
In view of the shortcomings in the prior art, it is an object of the present invention to provide an ISAR translational compensation and imaging method, system, medium, and device.
The ISAR translation compensation and imaging method provided by the invention comprises the following steps:
step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
step 2: performing generalized keystone transformation on the baseband signals and simultaneously completing linear distance walk correction and non-uniform signal reconstruction;
and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
and 4, step 4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
and 5: and finishing the final ISAR imaging result by utilizing two-dimensional Fourier transform.
Preferably, the expression of the generalized keystone transformation in step 2 is:
(f r +f c )(m+r m )＝f c m′
in the formula: f. of r 、f c 、m、r m And m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, r m A random slow time indication and a new uniform slow time indication.
Preferably, the doppler blur compensation function in step 3 is:
in the formula: m amb Represents a Doppler ambiguity number; j is an imaginary unit.
Preferably, the acceleration phase compensation function in step 4 is:
wherein,
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
According to the ISAR translation compensation and imaging system provided by the invention, the ISAR translation compensation and imaging system comprises:
module M1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
module M2: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
module M3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
module M4: constructing an acceleration phase function to compensate the residual distance bending and the quadratic Doppler phase;
module M5: and finishing a final ISAR imaging result by utilizing two-dimensional Fourier transform.
Preferably, the expression of the generalized keystone transformation in the module M2 is:
(f r +f c )(m+r m )＝f c m′
in the formula: f. of r 、f c 、m、r m And m' is distance frequency variable, carrier frequency, uniform dispersion slow time indication, r m A random slow time indication and a new uniform slow time indication.
Preferably, the doppler blur compensation function in the module M3 is:
in the formula: m amb Representing a Doppler ambiguity number; j is an imaginary unit.
Preferably, the acceleration phase compensation function in the module M4 is:
wherein,
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
According to the present invention, a computer-readable storage medium is provided, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method as described above.
According to the invention, the ISAR translation compensation and imaging device comprises: a controller;
the controller comprises the computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the ISAR translational compensation and imaging method; alternatively, the controller comprises the ISAR translation compensation and imaging system.
Compared with the prior art, the invention has the following beneficial effects:
(1) the invention can process translation compensation and ISAR imaging under random PRF, thereby obtaining high-resolution ISAR images;
(2) compared with the traditional non-uniform signal reconstruction algorithm, the calculation amount of the algorithm is small;
(3) the GKT and the matched filtering processing of the algorithm belong to linear transformation and do not involve any nonlinear operation, so that the near-optimal performance can be obtained in the low signal-to-noise ratio (SNR) environment.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of an ISAR translational compensation and imaging method at a random Pulse Repetition Frequency (PRF) according to the present invention;
FIG. 2 is a diagram of an ISAR observation geometric model;
FIG. 3 is a diagram of a simulated model of scattering points of an aircraft;
FIG. 4 is a diagram of imaging results of a conventional ISAR translational compensation method;
fig. 5 is a diagram of an imaging result of the proposed ISAR translation compensation method.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Example (b):
the invention provides an ISAR (inverse synthetic aperture radar) translation compensation and imaging method under random pulse repetition frequency, as shown in figure 1, which specifically comprises the following steps:
the method comprises the following steps: ISAR echo modeling under random PRF.
For a random PRF sampled radar system, the non-uniform sampling slow time at this time is represented as:
t m ＝(m+r m )T…………(1)
in the formula, t m ＝mT+r m T represents a slow time variable, m is a discrete slow time indicator, r m Representing a random slow time indication, T is the pulse repetition period of the geometric mean.
According to the ISAR observation model shown in FIG. 2, any scattering point P (x) on the target k ,y k ) The instantaneous slope to the radar is:
in the formula,
representing the slant of the translation part, R 0 、v r And a r Respectively, initial slope distance, radial speed and radial acceleration; r is a radical of hydrogen k And theta 0 Respectively representing the polar diameter and the polar angle of the scattering point; ω represents the rotational angular velocity. Considering that the ISAR rotation angle of the target is relatively small during the coherent integration time, equation (2) can be approximated according to a first-order Taylor expansion
After distance compression, the distance frequency domain signal corresponding to the kth scattering point of the target is as follows:
in the formula, f r Representing a frequency variable, f c Is the spur frequency and B is the signal bandwidth.
Step two: the proposed ISAR translation compensation and imaging scheme based on generalized KT and matched filtering.
(1) For Doppler blurred echo signals, and formula (1) is brought into formula (4), which can be simplified as follows:
in the formula, v 0 Representing the base band velocity, M amb Indicating the doppler ambiguity number and lambda the signal wavelength. Further simplifying the formula (5), we can obtain:
(2) utilizing Generalized KT (GKT) transformation to simultaneously complete azimuth non-uniform signal reconstruction and eliminate linear coupling between distance and azimuth, wherein the GKT is defined as the following form:
(f r +f c )(m+r m )＝f c m′…………(7)
in the formula, m' is a transformed uniform sampling slow time variable. By bringing formula (7) into formula (6), it is possible to obtain:
the generalized KT transformation operation can be realized by sinc interpolation, and can also be realized by adopting rapid algorithms such as cubic spline interpolation or scale transformation. It should be noted that this step may be performed simultaneously for linear distance ambulatory correction and for off-range unit correction.
(3) And constructing a Doppler fuzzy compensation term to eliminate the influence of Doppler fuzzy.
To eliminate r in formula (8) m The influence caused by the method needs to estimate the Doppler fuzzy number; from the derivation result in equation (8), the following matched filter function is set, namely:
in the formula,
representing searchesThe number of doppler ambiguities. Multiplying formula (8) by formula (9), when
Then, therefore, equation (8) becomes:
as can be seen, the Doppler ambiguity term is effectively removed.
(4) And constructing a phase compensation term and eliminating the phase term related to the translational acceleration.
From the results of equation (10), the following compensation function is constructed:
in the formula,
is the searched radial acceleration. Multiplying formula (10) by formula (11) when
The result after compensation is:
it can be observed that the coupling of the range frequency domain and the azimuth time has been completely solved after the acceleration effect compensation in the translational component.
(5) Range-doppler (RD) imaging processing.
After compensating the acceleration influence in the translation component, firstly performing Inverse Fast Fourier Transform (IFFT) along the distance dimension to obtain:
in the formula, t r Indicating the distance fast time, T p Is the signal pulse width. At the moment, the signals positioned in the same distance unit are completely corrected; and then the whole imaging process can be completed by the position FFT:
the whole imaging process can be summarized in the following form:
wherein, FFT m′ And
respectively representing the fast Fourier transform along the azimuth time and the inverse fast Fourier transform along the distance frequency domain;
the GKT transformation of equation (7) is shown.
The effects of the present invention can be further illustrated by the following simulations:
(1) simulation conditions
The simulation experiment platform parameters are given in table 1, and the implementation steps of this example were performed on a MATLAB2016 simulation platform.
TABLE 1 simulation parameters Table
| Parameter(s) | Numerical value |
| Carrier frequency | 10GHz |
| Mean value of pulse repetition frequency | 571.4Hz |
| Distance bandwidth | 200MHz |
| Distance sampling frequency | 300MHz |
| Duration of pulse | 40μs |
| Accumulation time | 0.512s |
| Number of distance sampling points | 256 |
| Number of azimuth sampling points | 256 |
(2) Emulated content
This section presents the results of the simulation process to verify the proposed algorithm. The rotation angular speed of the airplane target is 0.06rad/s, the translation speed is 25m/s, and the translation acceleration is 5m/s 2 SNR was set to 10dB and the scattering point model is shown in FIG. 3.
FIG. 3 is a simulated model of the scattering points of an aircraft target. FIG. 4(a) is a distance envelope after a distance pulse pressure; FIG. 4(b) is the result of RD imaging without translational compensation; fig. 4(c) shows the result of envelope alignment based on the conventional envelope correlation method; FIG. 4(d) is the result of RD imaging after translational compensation based on the envelope correlation method and the feature point;
FIG. 4(e) is the result of distance walk correction of conventional KT; fig. 4(f) is an imaging result based on a conventional RD algorithm; FIG. 5(a) is a distance envelope graph of GKT, and FIG. 5(b) is a search graph of search Doppler ambiguity number and search translational acceleration; fig. 5(c) is an RD imaging result of the proposed method.
Fig. 4(a) and (b) show the distance envelope and RD imaging results, respectively, without translational compensation, and a significant envelope walk phenomenon can be observed, in which case the RD imaging results are also almost completely defocused; FIG. 4(e) shows a conventional KT with envelope walk-corrected, where the envelope is mostly aligned but some migration is still present; and 4(f) is an imaging result based on a traditional RD imaging algorithm on the basis of traditional KT, at the moment, FT is directly adopted for the non-uniformly sampled echo signals, the scattering points of the target cannot be effectively focused, and only a rough outline of the band can be observed. FIG. 5 is the processing result of the proposed method, and it can be observed from FIG. 5(a) that the validity of the proposed GKT (the translational acceleration has been compensated), FIG. 5(b) is the curves of the searched acceleration and Doppler ambiguity number, the Doppler ambiguity number is 3 from the point of minimum entropy value, and the searched acceleration is 4.99m/s 2 (ii) a Fig. 5(c) shows the final imaging result after the proposed method solves the translation compensation, and a well-focused ISAR imaging result can be observed.
In conclusion, the simulation experiment verifies the correctness, the effectiveness and the reliability of the method.
It is known to those skilled in the art that, in addition to implementing the system, apparatus and its various modules provided by the present invention in pure computer readable program code, the system, apparatus and its various modules provided by the present invention can be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like by completely programming the method steps. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description has described specific embodiments of the present invention. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (4)
1. An ISAR translation compensation and imaging method, comprising:
step 1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
and 2, step: performing linear distance walk correction and non-uniform signal reconstruction on the baseband signals by adopting generalized keystone transformation;
and step 3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
and 4, step 4: constructing an acceleration phase compensation function to compensate the residual distance bending and the quadratic Doppler phase;
and 5: finishing a final ISAR imaging result by utilizing two-dimensional Fourier transform;
the expression of the generalized keystone transformation in the step 2 is as follows:
(f r +f c )(m+r m )＝f c m′
in the formula: f. of r 、f c 、m、r m And m' is a distance frequency variable, a carrier frequency, a uniform dispersion slow time indication, a random slow time indication and a new uniform slow time indication, respectively;
the Doppler fuzzy compensation function in the step 3 is as follows:
in the formula: m is a group of amb Represents a Doppler ambiguity number; j is an imaginary unit;
the acceleration phase compensation function in the step 4 is as follows:
wherein,
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
2. An ISAR translational compensation and imaging system, comprising:
module M1: distance compression and lower frequency modulation processing are carried out on radar echoes, and the radar echoes are converted into baseband signals;
module M2: performing generalized keystone transformation on the baseband signals and simultaneously completing linear distance walk correction and non-uniform signal reconstruction;
module M3: constructing a Doppler fuzzy compensation function, and compensating the Doppler fuzzy term;
module M4: constructing an acceleration phase compensation function to compensate the residual distance bending and the quadratic Doppler phase;
module M5: finishing a final ISAR imaging result by utilizing two-dimensional Fourier transform;
the expression of the generalized keystone transformation in the module M2 is:
(f r +f c )(m+r m )＝f c m′
in the formula: f. of r 、f c 、m、r m And m' is a distance frequency variable, a carrier frequency, a uniform dispersion slow time indication, a random slow time indication and a new uniform slow time indication, respectively;
the doppler blur compensation function in the module M3 is:
in the formula: m amb Represents a Doppler ambiguity number; j is an imaginary unit;
the acceleration phase compensation function in the module M4 is:
wherein,
represents the searched acceleration; c is the speed of light; t is the pulse repetition period of the geometric mean.
3. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method as claimed in claim 1.
4. An ISAR translational compensation and imaging device, comprising: a controller;
the controller comprising a computer readable storage medium of claim 3 having a computer program stored thereon which, when executed by a processor, performs the steps of the ISAR translational compensation and imaging method of claim 1; alternatively, the controller comprises the ISAR translation compensation and imaging system of claim 2.
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