CN110308448B - Method for enhancing two-dimensional image of inverse synthetic aperture radar - Google Patents
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Abstract
The invention provides a method for enhancing a two-dimensional image of an inverse synthetic aperture radar, which belongs to the field of radar signal processing. According to the invention, the signal is processed through the high-order coupling Duffing oscillator and the 6 th-order Gaussian function, the signal-to-noise ratio of the processed signal spectrum function is about 3dB higher than that of the signal spectrum function obtained by directly utilizing Fourier transform, and the signal-to-noise ratio of the ISAR two-dimensional image can be improved by about 3dB by respectively processing the ISAR fast-time dimensional signal and the ISAR slow-time dimensional signal through the method.
Description
Technical Field
The invention relates to a method for enhancing an Inverse Synthetic Aperture Radar (ISAR) two-dimensional image, belonging to the field of radar signal processing.
Background
One of the most common implementations for Inverse Synthetic Aperture Radar (ISAR) two-dimensional range-doppler (R-D) imaging algorithms that employ broadband chirp (LFM) signals is formed by the following steps: keystone transform eliminates range walk, range image pulse compression, phase focusing, and azimuthal Fourier transform.
In the case of a relatively low imaging signal-to-noise ratio, the following two problems may occur: firstly, the signal-to-noise ratio of the distance image after pulse compression is low, and a special display point cannot be found for phase focusing; secondly, even if phase focusing is performed, the signal-to-noise ratio of the ISAR two-dimensional image after the azimuth Fourier transform is low, and the target cannot be well distinguished. Therefore, at low signal-to-noise ratio, the ISAR image needs to be enhanced to resolve the target feature well.
For the enhancement of the ISAR image, two methods can be used, wherein one method is to carry out image denoising, edge detection and the like on the imaging result by using an image processing method; secondly, the signal-to-noise ratio is improved in the imaging process. The first method has a problem that the ISAR two-dimensional image cannot be obtained due to a low signal-to-noise ratio in an imaging link, and therefore, the image processing of the ISAR two-dimensional image has no significance. Therefore, the rational approach is the second. At present, the main idea of improving the signal-to-noise ratio in the imaging process is to use various methods to perform accurate motion compensation, align the envelope of echoes and accurately focus the phase, but these methods only avoid the signal-to-noise ratio loss caused by the defocusing of the two-dimensional image of the radar and cannot really improve the signal-to-noise ratio of the radar imaging. At present, no method is used for improving the signal-to-noise ratio of the ISAR two-dimensional image, so that a new method needs to be provided for solving the problem.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the method for enhancing the two-dimensional image of the inverse synthetic aperture radar, which can improve the imaging signal-to-noise ratio of the radar and enhance the imaging performance of the ISAR under the low signal-to-noise ratio.
In order to achieve the above purpose, the invention adopts the following technical scheme: a method for enhancing a two-dimensional image of an inverse synthetic aperture radar comprises the following steps:
step 7, carrying out phase focusing on the range profile signals obtained in the step 6;
step 9, performing Fourier transform on the signal matrix obtained in the step 8 in a slow time dimension, and then solving a mode;
and 10, adjusting the amplitude of the signal obtained in the step 9 according to a 6-order Gaussian function to obtain an enhanced two-dimensional image of the inverse synthetic aperture radar.
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the baseband signal is represented as:
in the formula (I), the compound is shown in the specification,
for the baseband signal, i represents the number of scattering points of the target, m represents the number of pulses, AiThe p (.) function represents the complex envelope of the signal, which is the scattering intensity of the scattering point of the object,
for fast time variables, tmAs a slow time variable, Ri(tm) Is tmThe distance between the scattering point of the ith target and the radar at the moment, c is the speed of light, fcIs the carrier frequency, and j is the imaginary unit.
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the baseband frequency domain signal is:
wherein f is the frequency of the baseband signal; p (f) is a spectral function of the complex envelope of the baseband signal, Ri0Is the initial distance, v, of the ith scattering point from the radariIs the initial velocity of the ith scattering point.
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the keystone transformation is performed on the baseband frequency domain signal matrix in step 3, and specifically, the keystone transformation is performed on the baseband frequency domain signal matrix by:
let a new time variable τm：
Substituting the above formula into baseband frequency domain signal formula (4) to obtain time scale converted signal Sr(f,τm) Comprises the following steps:
the method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the coupled oscillator system is the coupling of two high-order Duffing oscillators.
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the coupling of the two high-order Duffing oscillators is specifically expressed as the following first-order ordinary differential equation system:
in the formula, x1And y1Two state variables, x, of the first Duffing oscillator, respectively2And y2Two state variables of the second Duffing oscillator respectively,
are each x1And y1The time derivative of (a);
are each x2And y2The time derivative of (a); alpha is the damping coefficient of Duffing oscillator, k is the coupling coefficient of linear restoring force between oscillators, q is the coupling coefficient of nonlinear restoring force between oscillators, beta is the amplitude of periodic driving force, t is time, s (t) is the input signal to be processed, for each row of the baseband frequency domain signal matrix processed in step 3, the output of the coupled Duffing oscillator system is the oscillator state variationDifference in amount: x is the number of1-x2。
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the 6 th order gaussian function is:
in the formula (I), the compound is shown in the specification,
wherein x is a function argument whose value is an integer and the range is: 0-N/2, wherein N is the number of sampling points of each echo; a 1-a 6, b 1-b 6 and c 1-c 6 are constant parameters of a6 th order Gaussian function respectively.
The method for enhancing the two-dimensional image of the inverse synthetic aperture radar is characterized in that the signal amplitude adjusting method comprises the following steps: and comparing each line of the target range profile with the value of the 6-order Gaussian function after even symmetry continuation one by one, and performing equal-proportion amplification to obtain the target range profile after signal amplitude adjustment.
The invention has the beneficial effects that: the signal is processed by the high-order coupling Duffing oscillator and the 6 th-order Gaussian function, the signal-to-noise ratio of the processed signal spectrum function is about 3dB higher than that of the signal spectrum function obtained by directly utilizing Fourier transform, and the signal-to-noise ratio of the ISAR two-dimensional image can be improved by about 3dB by respectively processing the ISAR fast-time dimensional signal and the ISAR slow-time dimensional signal through the method.
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FIG. 1 is an algorithmic flow diagram of an embodiment of the present invention;
FIG. 2 is a sinusoidal waveform with a natural frequency of 15 Hz;
FIG. 3 is a signal waveform of FIG. 2 after Gaussian white noise is superimposed on a sinusoidal waveform;
FIG. 4 is an output waveform of the signal of FIG. 3 after being processed by a coupling Duffing oscillator;
FIG. 5 is a spectrum obtained by Fourier transforming the signal of FIG. 3;
FIG. 6 is a spectrum obtained by Fourier transforming the signal of FIG. 4;
FIG. 7 is a spectrum obtained by Fourier transforming the signal of FIG. 2;
FIG. 8 is a waveform diagram of a6 th order Gaussian function;
FIG. 9 is a graph of the amplitude adjusted spectral function of FIG. 6;
FIG. 10 is a target geometry for a simulation example;
FIG. 11 is an ISAR image obtained by a simulation example using a common R-D imaging algorithm;
FIG. 12 is an ISAR image obtained by the method of the present invention in a simulation example;
FIG. 13 is a three-dimensional view of FIG. 11;
fig. 14 is a three-dimensional view of fig. 12.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a method for enhancing a two-dimensional image of an inverse synthetic aperture radar includes the steps of:
the baseband signal of the radar target echo signal after the carrier frequency is removed by frequency mixing can be written as follows:
in the formula, i represents the sequence number of the scattering point of the target; m represents a pulse number; a. theiIs the scattering intensity of the scattering point of the target; a p (.) function represents the complex envelope of the signal;
is a fast time variable; t is tmIs a slow time variable; ri(tm) Is tmThe distance between the ith target scattering point and the radar at the moment; c is the speed of light; f. ofcIs the carrier frequency, and j is the imaginary unit.
the baseband frequency domain signal obtained by performing fourier transform on the mixed baseband signal in the fast time dimension is represented as:
wherein f is the frequency of the baseband signal; p (f) is a spectral function of the complex envelope of the baseband signal.
The distance from the ith target scattering point to the radar is retained by the following term:
Ri(tm)＝Ri0+vitm (3)
in the formula, Ri0The initial distance of the ith scattering point from the radar; v. ofiIs the initial velocity of the ith scattering point.
Substituting the above equation into baseband frequency domain signal expression (2) can obtain:
the second phase term of the above equation contains the doppler frequency, but the doppler frequency varies with f, and the keystone transform can be used to eliminate this effect.
for the Keystone transform, a new time variable may be specified:
let a new time variable τm：
Substituting the above formula into the baseband frequency domain signal formula (4) to obtain the signal S after time scale conversionr(f,τm) Comprises the following steps:
as can be seen from the above equation, the keystone transform eliminates the coupling of the doppler frequency and the baseband signal frequency f by using the linear coordinate transform, and corrects the range walk of the target. As the keystone transformation is linear transformation of a time coordinate, the statistical property of the Gaussian white noise is unchanged after the Keystone transformation.
the coupled oscillator system is the coupling of two high-order Duffing (Duffing) oscillators, and is specifically expressed as the following first-order ordinary differential equation set:
in the formula, x1And y1Two state variables, x, of the first Duffing oscillator, respectively2And y2Two state variables of the second Duffing oscillator respectively,
are each x1And y1The time derivative of (a);
are each x2And y2The time derivative of (a); alpha is the damping coefficient of Duffing vibrators, k is the coupling coefficient of linear restoring force between vibrators, q is the coupling coefficient of nonlinear restoring force between vibrators, beta is the amplitude of periodic driving force, and t is timeAnd s (t) is the input signal to be processed, which is, in the embodiment of the present invention, each row of the matrix of M × N baseband frequency domain signals processed in step 3. In this embodiment, oscillator parameters are respectively: α ═ 10, k ═ 1.5, q ═ 0.01, β ═ 0.01; the initial value of the oscillator state variable may be arbitrarily selected. The ordinary differential equation set can be solved by a fixed step length four-order Runge-Kutta method, and the output of the coupled Duffing oscillator system is the difference value of oscillator state variables: x is the number of1-x2And 3, performing keystone transformation on the baseband frequency domain signal matrix, and then processing and outputting the signal through a coupling oscillator system. Through the processing, the signal-to-noise ratio of the baseband frequency domain signal is improved by about 3 dB;
to illustrate the effect of the coupled Duffing oscillator system, fig. 2 simulates a sine wave waveform with a frequency of 15Hz and an amplitude of 0.02, and the fourier transform of this signal is shown in fig. 7, from which it can be seen that the frequency of the signal is 15 Hz. The waveform of the signal superimposed with white gaussian noise is shown in fig. 3, and it can be seen from fig. 3 that the signal is completely buried by the noise. The signal of fig. 3 is input into the coupled Duffing oscillator system shown in the formula (7), and the output waveform of the oscillator system is shown in fig. 4. Fig. 5 is the result of a fourier transform of the signal of fig. 3, in which the frequency of the 15Hz signal is not effectively discerned. Fig. 6 is the result of a fourier transform of the signal of fig. 4, in which the frequency of the 15Hz signal can be clearly discerned.
And 5, carrying out inverse Fourier transform on the baseband frequency domain signal matrix with the signal-to-noise ratio improved in the step 4 in a fast time dimension, and carrying out modulo on the result of the inverse Fourier transform to obtain a target range profile.
The distance obtained at this time appears to be an exponential curve type waveform, the appearance of which is similar to that shown in fig. 6; the target distance obtained at this time is in the form of an exponential curve accumulated toward the center, which is not favorable for direct observation, so that the exponential curve is further processed to flatten the waveform of the exponential curve, which is convenient for direct observation as in the case of a normal distance.
in the formula (I), the compound is shown in the specification,
wherein x is a function argument whose value is an integer and the range is: 0-N/2, wherein N is the number of sampling points of each echo; a 1-a 6, b 1-b 6 and c 1-c 6 are constant parameters of a6 th order Gaussian function respectively. The function is extended even symmetrically to obtain a complete 6 th order gaussian function waveform as shown in fig. 8.
The signal amplitude adjusting method comprises the following steps: and (4) comparing each line of the target range profile obtained in the step (5) with the value of the complete 6-order Gaussian function after even symmetry continuation one by one, and performing equal-proportion amplification to obtain a target range profile after signal amplitude adjustment. For example, if the value of the target range image is 0.12, and the corresponding value of the 6 th order Gaussian function is 0.1, and the value of the 6 th order Gaussian function is doubled to 1, then the signal value should be scaled to 1.2. Similarly, if the signal value is 0.12, corresponding to a value of 0.15 for a6 th order Gaussian function, and the value of the 6 th order Gaussian function is doubled to 1, the signal value should be proportionally multiplied to 0.8. By the method, the exponential type target range profile can be flattened into the waveform of the normal target range profile, and direct observation is facilitated.
Fig. 9 is the amplitude adjusted waveform of fig. 6. Comparing fig. 9 and fig. 5, it can be seen that the spectral line of the 15Hz sinusoidal signal in the spectrum function of the signal processed by the coupling Duffing oscillator is highlighted, and the spectral line resolution has about 3dB enhancement effect, which corresponds to about 3dB enhancement of the signal-to-noise ratio.
The target range profile which can be directly observed can be obtained through the steps, and the signal-to-noise ratio of the target range profile is improved by about 3 dB. The performance of a subsequent phase focusing algorithm is related to the signal-to-noise ratio of the target range profile, and the higher the signal-to-noise ratio is, the more accurate the phase focusing is, so that the signal-to-noise ratio of the target range profile is improved to positively influence the subsequent phase focusing;
step 7, carrying out phase focusing on the range profile signals obtained in the step 6;
step 9, performing Fourier transform on the signal matrix obtained in the step 8 in a slow time dimension, and then solving a mode;
and 10, adjusting the signal amplitude of the signal matrix obtained in the step 9 according to the method in the step 6. After adjustment, the ISAR two-dimensional image with improved signal-to-noise ratio can be obtained.
Example 1: FIG. 10 shows a target geometry of a simulation example of the method of the present invention. The simulation is a flying target 50 kilometers away from the radar, and the motion parameters of the target are as follows: the initial radial speed is-100 m/s (moving towards the radar) and the rotational speed around the geometric centre is 4 deg./s. The radar parameters are: the radar transmits an LFM pulse string, the pulse width is 5 mu s, the bandwidth is 500MHz, the carrier frequency is 10GHz, the number of fast time sampling points is 1000, the pulse repetition period is 500 mu s, the imaging time is 0.1s, 200 echoes are totally obtained, and the signal-to-noise ratio of the echoes is set to be-30 dB.
FIG. 11 is an ISAR image obtained by a simulation example using a conventional R-D imaging algorithm.
FIG. 12 is an ISAR image obtained by the method of the present invention according to a simulation example, and it can be seen from comparison with FIG. 11 that the imaging signal-to-noise ratio is improved.
Fig. 13 is a three-dimensional view of fig. 11.
FIG. 14 is a three-dimensional graph of FIG. 12, comparing FIG. 13, showing the improvement in signal-to-noise ratio of the scattering sites of the object.
In summary, the following steps: by the high-order coupling Duffing oscillator and the 6 th-order Gaussian function provided by the invention, ISAR fast time dimension signals and ISAR slow time dimension signals are respectively processed, and the signal-to-noise ratio of an ISAR two-dimensional image can be improved by about 3 dB.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A method for enhancing a two-dimensional image of an inverse synthetic aperture radar is characterized by comprising the following steps:
step 1, when the inverse synthetic aperture radar transmits a broadband linear frequency modulation pulse train signal, mixing a target echo signal received by the inverse synthetic aperture radar, and removing a carrier frequency to obtain a baseband signal;
step 2, carrying out Fourier transform on the baseband signals in a fast time dimension to obtain baseband frequency domain signals and form a baseband frequency domain signal matrix;
step 3, performing keystone transformation on the baseband frequency domain signal matrix;
step 4, processing the baseband frequency domain signal matrix processed in the step 3 through a coupling oscillator system in a fast time dimension;
step 5, performing inverse Fourier transform on the baseband frequency domain signal matrix with the signal-to-noise ratio improved in the step 4 in a fast time dimension, and then performing modulus calculation to obtain a target range profile;
step 6, adjusting the amplitude of the target range profile signal obtained in the step 5 according to a 6-order Gaussian function;
step 7, carrying out phase focusing on the range profile signals obtained in the step 6;
step 8, processing the distance image signal matrix obtained in the step 7 after phase focusing through a coupling oscillator system in a slow time dimension;
step 9, performing Fourier transform on the signal matrix obtained in the step 8 in a slow time dimension, and then solving a mode;
and 10, adjusting the amplitude of the signal obtained in the step 9 according to a 6-order Gaussian function to obtain an enhanced two-dimensional image of the inverse synthetic aperture radar.
2. The method of enhancing an inverse synthetic aperture radar two-dimensional image according to claim 1, wherein the baseband signal is represented as:
in the formula (I), the compound is shown in the specification,
for the baseband signal, i represents the number of scattering points of the target, m represents the number of pulses, AiThe p (.) function represents the complex envelope of the signal, which is the scattering intensity of the scattering point of the object,
for fast time variables, tmAs a slow time variable, Ri(tm) Is tmThe distance between the scattering point of the ith target and the radar at the moment, c is the speed of light, fcIs the carrier frequency, and j is the imaginary unit.
3. The method of claim 2, wherein the baseband frequency domain signal is:
wherein f is the frequency of the baseband signal; p (f) is a spectral function of the complex envelope of the baseband signal, Ri0Is the initial distance, v, of the ith scattering point from the radariIs the initial velocity of the ith scattering point.
4. The method for enhancing two-dimensional image of inverse synthetic aperture radar according to claim 3, wherein the keystone transform is performed on the baseband frequency domain signal matrix in step 3, specifically:
let a new time variable τm：
Substituting the above formula into baseband frequency domain signal formula (4) to obtain time scale converted signal Sr(f,τm) Comprises the following steps:
5. the method for enhancing two-dimensional image of inverse synthetic aperture radar as claimed in claim 1, wherein said coupled oscillator system is a coupling of two high-order Duffing oscillators.
6. The method for enhancing two-dimensional image of inverse synthetic aperture radar according to claim 5, wherein the coupling of the two high-order Duffing oscillators is specifically expressed as the following system of first-order ordinary differential equations:
in the formula, x1And y1Two state variables, x, of the first Duffing oscillator, respectively2And y2Two state variables of the second Duffing oscillator respectively,
are each x1And y1The time derivative of (a);
are each x2And y2The time derivative of (a); α is a damping coefficient of the Duffing oscillator, k is a coupling coefficient of linear restoring force between oscillators, q is a coupling coefficient of nonlinear restoring force between oscillators, β is an amplitude of a periodic driving force, t is time, s (t) is an input signal to be processed, and for each row of the baseband frequency domain signal matrix processed in step 3, an output of the coupled Duffing oscillator system is a difference value of state variables of the oscillators: x is the number of1-x2。
7. The method of claim 1, wherein the 6 th order gaussian function is:
in the formula (I), the compound is shown in the specification,
wherein x is a function argument whose value is an integer and the range is: 0-N/2, wherein N is the number of sampling points of each echo; a 1-a 6, b 1-b 6 and c 1-c 6 are constant parameters of a6 th order Gaussian function respectively.
8. The method for enhancing two-dimensional image of inverse synthetic aperture radar according to claim 1, wherein the signal amplitude adjusting method comprises: and comparing each line of the target range profile with the value of the 6-order Gaussian function after even symmetry continuation one by one, and performing equal-proportion amplification to obtain the target range profile after signal amplitude adjustment.
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