CN110988874A - ISAR imaging method for complex moving target - Google Patents
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Abstract
The invention relates to an ISAR imaging method of a complex moving target, which comprises the following steps: acquiring radar echo signals of scattering points of a target to be detected in each distance unit; modeling the radar echo signal into a cubic phase signal after pulse compression processing and motion compensation; performing parameter estimation on the cubic phase signal by adopting a non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function to obtain an estimated parameter; updating the radar echo signal of a scattering point in each distance unit according to the pre-estimated parameters; and obtaining an ISAR image of the target to be detected according to the updated radar echo signal. According to the method, NIM-CRQCRD is adopted to carry out parameter estimation on the cubic phase signal, and the parameter estimation can be realized only by adopting fast Fourier transform, so that the calculation process is greatly simplified, and the anti-noise performance of the method can be effectively improved.
Description
Technical Field
The invention belongs to the technical field of inverse synthetic aperture radar imaging, and particularly relates to an ISAR imaging method for a complex moving target.
Background
Synthetic Aperture Radar (SAR) is one of the most common imaging radars, and is usually mounted on a moving platform such as an airplane or a satellite to image the ground as a stationary target. The antenna aperture synthesis method has the essence that a huge and effective antenna aperture is equivalently synthesized in the azimuth direction through the relative motion between the radar and a target, so that the limitation of the real aperture antenna of the radar on the azimuth resolution is broken through, and a new step is taken by the radar imaging technology. Inverse Synthetic Aperture Radar (ISAR) is another Radar imaging technology developed on the basis of SAR, and aims to solve the imaging problem of a moving target. ISAR is mostly placed at a fixed position to image a moving target, mainly performs two-dimensional imaging on a non-cooperative target, and has important application value in strategic defense, anti-satellite, tactical weapons and radar astronomy.
In the course of ISAR development, many excellent ISAR imaging algorithms emerge, wherein a traditional Range-Doppler (RD) imaging method is the ISAR imaging method which is the most commonly applied and has the smallest operation amount, and the method has the implicit assumption that the Doppler frequency shift of a target echo signal in an observation time is kept unchanged. For a complex moving target, the target speed changes with time in the observation time, so that the target echo signal is time-varying in the doppler dimension, and therefore, the conventional RD imaging method is not suitable for ISAR imaging of the complex moving target. Based on the above problems, an imaging method using Range-Instantaneous Doppler (RID) for a complicated moving object has been proposed.
Regarding the imaging method of RID, the currently common algorithms include a Cubic Phase Function (CPF), a higher-Order Ambiguity Function-Integrated Cubic Phase Function (HAF-ICPF), a local polynomial Wigner distribution (LWD), and an algorithm based on a Generalized variable Fourier Transform (GSCFT), but the above algorithms have low noise immunity, and the use of a Non-uniform Fourier Transform (NUFFT) in the calculation process complicates the calculation process, so that it is necessary to provide an ISAR imaging method with simple calculation method and good noise immunity.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides an ISAR imaging method for a complex moving object. The technical problem to be solved by the invention is realized by the following technical scheme:
the invention provides an ISAR imaging method of a complex moving target, which comprises the following steps:
acquiring radar echo signals of scattering points of a target to be detected in each distance unit;
modeling the radar echo signal into a cubic phase signal after pulse compression processing and motion compensation;
performing parameter estimation on the cubic phase signal by adopting a non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function to obtain an estimated parameter;
updating the radar echo signal of a scattering point in each distance unit according to the pre-estimated parameters;
and obtaining an ISAR image of the target to be detected according to the updated radar echo signal.
In one embodiment of the present invention, the cubic phase signal is,
where L denotes the L-th distance unit and L denotes the total distance unitNumber, tmDenotes the slow time, P denotes the number of scattering points in the l-th range bin, ApRepresenting the amplitude, phi, of the radar echo signal at the p-th scattering pointp,1Representing the center frequency, phi, of the radar echo signal at the p-th scattering pointp,2Frequency modulation, phi, of the radar echo signal representing the p-th scattering pointp,3Second harmonic frequency, z (t), of radar echo signal representing the p-th scattering pointm) Representing complex white gaussian noise.
In one embodiment of the present invention, the estimated parameters include: a frequency modulation rate estimate, a secondary frequency modulation rate estimate, a center frequency estimate, and an amplitude estimate.
In an embodiment of the present invention, performing parameter estimation on the cubic phase signal by using non-uniform sampling integral type correction modulation frequency-chirp rate distribution to obtain an estimated parameter, includes:
processing the cubic phase signal by using a non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function to obtain a modulation rate estimation value and a quadratic modulation rate estimation value of the radar echo signal of the scattering point;
and performing Doppler compensation on the cubic phase signal according to the frequency modulation rate estimated value and the secondary frequency modulation rate estimated value to obtain a center frequency estimated value and an amplitude estimated value of the radar echo signal of the scattering point.
In an embodiment of the present invention, the processing of performing non-uniform sampling integration type correction on a modulation frequency-quadratic modulation frequency distribution function on the cubic phase signal to obtain a modulation frequency estimation value and a quadratic modulation frequency estimation value of a radar echo signal of the scattering point includes:
processing the cubic phase signal by adopting an instantaneous autocorrelation function to obtain an estimation model of the radar echo signal of the scattering point,
the instantaneous autocorrelation function is such that,
the estimation model is a model of,
wherein, taumRepresenting the delay variable as a non-uniform sample, α and
both represent a constant time delay and are,
represents the cross terms generated after the autocorrelation function processing,
representing a noise term generated after the autocorrelation function processing;
eliminating nonlinear coupling between slow time and delay variables of the estimation model;
performing fast Fourier transform on the estimation model after cancellation non-linear coupling to obtain an estimation model Fourier transform equation;
carrying out non-coherent accumulation on the estimation model Fourier transform equation to obtain the non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function;
and carrying out non-uniform sampling integral type correction modulation frequency-secondary modulation frequency distribution function processing on the cubic phase signal, and obtaining the modulation rate estimation value and the secondary modulation rate estimation value by adopting a peak value detection technology.
In an embodiment of the present invention, performing doppler compensation on the cubic phase signal according to the frequency modulation estimated value and the second frequency modulation estimated value to obtain a center frequency estimated value and an amplitude estimated value of the radar echo signal of the scattering point, including:
use of
Doppler compensation is carried out on the cubic phase signal, and the cubic phase after the Doppler compensation is carried outPerforming fast Fourier transform on the signal to obtain the estimated value of the center frequency and the estimated value of the amplitude,
the calculation formula of the center frequency estimated value and the amplitude estimated value is as follows,
wherein the content of the first and second substances,
an estimated frequency modulation value of the radar echo signal of the p-th scattering point is represented,
a quadratic frequency estimate representing the radar echo signal for the p-th scattering point,
an amplitude estimate of the radar return signal representing the p-th scattering point,
the center frequency of the radar echo signal of the p-th scattering point is shown, D' represents the peak amplitude obtained after the fast Fourier transform is carried out on the Doppler compensated cubic phase signal,
indicating a slow time tmThe frequency of the corresponding frequency domain is,
and the number of sampling points of the radar echo signals is represented.
In one embodiment of the present invention, eliminating the non-linear coupling between the slow time and delay variables of the estimation model comprises:
performing Keystone transformation on the estimation model to eliminate nonlinear coupling between slow time and delay variables of the estimation model, wherein,
the Keystone transform function is as follows,
the estimation model after eliminating the non-linear coupling is,
wherein, tnRepresenting a variable scale time, h representing a variable scale factor,
represents the cross terms after the Keystone transformation,
representing the noise term after the Keystone transform.
In an embodiment of the present invention, performing fast fourier transform on the estimation model after canceling the nonlinear coupling to obtain an estimation model fourier transform equation, includes:
performing first fast Fourier transform on the estimation model after cancellation except the nonlinear coupling along a variable scale time axis to obtain a first Fourier transform equation,
wherein the content of the first and second substances,
expressed as a scaled time tnThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the first fast fourier transform,
representing the generation of a noise term after a first fast fourier transform;
performing a second fast Fourier transform on the first Fourier transform equation along the time delay variable axis to obtain an estimation model Fourier transform equation,
wherein the content of the first and second substances,
representing a time-delay variable τmThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the second fast fourier transform,
representing the noise term generated after the second fast fourier transform.
In an embodiment of the present invention, performing non-coherent accumulation on the estimation model fourier transform equation to obtain the non-uniform sampling integral type modified modulation frequency-quadric modulation frequency distribution function includes:
constant time delay of Fourier transform equation of the estimation model
Non-coherent accumulation is carried out on results obtained by taking different values to obtain a non-uniform sampling integral type correction modulation frequency-secondary modulation frequency distribution function as,
in an embodiment of the present invention, the processing of performing non-uniform sampling integral type correction on a modulation frequency-secondary modulation frequency distribution function on the cubic phase signal, and obtaining the estimated modulation frequency value and the estimated secondary modulation frequency value by using a peak detection technique includes:
determining a center frequency estimate and an amplitude estimate of the radar echo signal at the scattering point according to the following equations,
wherein the content of the first and second substances,
an estimated frequency modulation value of the radar echo signal of the p-th scattering point is represented,
a quadratic frequency estimate representing the radar echo signal for the p-th scattering point,
representing the cubic phase signal s for the l-th range celll(tm) And (4) carrying out non-uniform sampling integral type correction frequency-secondary frequency modulation distribution function processing on the result.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function is adopted to carry out parameter estimation on the cubic phase signal, so that NUFFT (non-uniform Fourier transform) is avoided in the parameter estimation process, the parameter estimation can be realized only by adopting fast Fourier transform, the calculation process is greatly simplified, and meanwhile, the noise resistance of the method can be effectively improved by adopting a mode of combining non-coherent accumulation and coherent accumulation.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic diagram of an ISAR imaging model of a complex moving object according to an embodiment of the present invention;
FIG. 2 is a flowchart of an ISAR imaging method for a complex moving object according to an embodiment of the present invention;
FIG. 3 is a graph of an output SNR provided by an embodiment of the present invention
A graph of variation results;
FIGS. 4-6 are graphs of simulation results of anti-noise performance provided by embodiments of the present invention;
7-10 are graphs of cross term suppression performance simulation results provided by embodiments of the present invention;
11-14 are graphs of simulation results of ISAR imaging based on M-CRQCRD provided by embodiments of the present invention;
fig. 15-18 are graphs of simulation results of the ISAR imaging based on NIM-CRQCRD according to the embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined object, the following describes in detail an ISAR imaging method for a complex moving object according to the present invention with reference to the accompanying drawings and the detailed description.
The foregoing and other technical matters, features and effects of the present invention will be apparent from the following detailed description of the embodiments, which is to be read in connection with the accompanying drawings. The technical means and effects of the present invention adopted to achieve the predetermined purpose can be more deeply and specifically understood through the description of the specific embodiments, however, the attached drawings are provided for reference and description only and are not used for limiting the technical scheme of the present invention.
Example one
Referring to fig. 1, fig. 1 is a schematic diagram of an ISAR imaging model of a complex moving object according to an embodiment of the present invention, where a center O of a cartesian coordinate system XYZ is a target rotation center, a vector R represents a unit vector in a line of sight (LOS) direction, and v is a unit vectorrRepresenting the translational component of the object motion and the vector W representing the rotational component of the object motion, where the vector W can be decomposed into components W parallel to the vector RRAnd perpendicular to the vectorComponent W of Re，WRAnd WeIn (1) only WeContributes to ISAR imaging, therefore, WeReferred to as the effective rotation vector.
Scattering point p (x)p,yp,zp) For any scattering point on a moving object, vector rpAs a direction vector from the center point O to the scattering point p, the translational component v is taken into accountrThen, its radial movement velocity is vr+(rp×We) R, x and x represent the outer product and the inner product, respectively, and the Doppler frequency of the scattering point p can be obtained from the radial motion velocity,
where lambda represents the wavelength of the radar transmitted signal and, for complex moving objects,
wherein v is0Initial velocity, a, representing the translational component0Representing the initial velocity, gamma, of the translational component0Jerk representing a translational component, a represents a rotational velocity vector WeB represents a rotational velocity vector WeK represents a rotational velocity vector WeThe third order of (a).
Referring to fig. 2, fig. 2 is a flowchart of an ISAR imaging method for a complex moving object according to an embodiment of the present invention, where as shown in the figure, the ISAR imaging method for a complex moving object according to the embodiment includes:
s1: acquiring radar echo signals of scattering points of a target to be detected in each distance unit;
the distance units are divided according to the distance resolution of the radar, and in the radar image, when two targets are located at the same azimuth but different from the radar in distance, the minimum distance between the two targets and the radar is the distance resolution. It is generally defined that the distance between two targets is the distance resolution when the falling edge of the echo pulse of a closer target just coincides with the rising edge of the echo of a farther target, as the limit of the resolution.
S2: modeling the radar echo signal into a cubic phase signal after pulse compression processing and motion compensation;
assuming that the radar transmits a chirp signal, the radar echo signal of the scattering point p is processed by down-conversion and pulse compression,
where t denotes the fast time, tmRepresents the slow time, δpRepresenting the amplitude of the signal, B representing the bandwidth of the transmitted signal, c representing the speed of light, z (t)m) Representing complex white Gaussian noise, R (t)m) Is shown at tmThe distance from the scattering point p to the radar, at the moment, is expressed as,
wherein R isp(t0) Is shown at an initial time t0The distance of the scattering point p from the radar.
If the number of scattering points in the first distance unit is P, then the cubic phase signal is modeled after the equation (3) is subjected to motion compensation,
wherein L represents the L-th range bin, L represents the total range bin number, tmDenotes the slow time, P denotes the number of scattering points in the l-th range bin, ApRepresenting the amplitude, phi, of the radar echo signal at the p-th scattering pointp,1Representing the center frequency, phi, of the radar echo signal at the p-th scattering pointp,2Frequency modulation, phi, of the radar echo signal representing the p-th scattering pointp,3Second harmonic frequency, z (t), of radar echo signal representing the p-th scattering pointm) Watch (A)Showing complex white gaussian noise.
As can be seen from equations (5) and (6), doppler spread is caused by the existence of the modulation frequency (CR) and the Quadratic modulation frequency (QCR) in the Cubic Phase Signals (CPS), so that the conventional RD method is no longer applicable, and in order to obtain ISAR imaging with good focusing, parameter estimation needs to be performed on the CPS.
S3: performing parameter estimation on the cubic phase signal by adopting a Non-uniform sampled Integrated modulated Chirp Rate-Quadratic frequency modulation (NIM-CRQCRD) Distribution function to obtain an estimated parameter;
wherein the pre-estimated parameters include: a frequency modulation rate estimate, a secondary frequency modulation rate estimate, a center frequency estimate, and an amplitude estimate.
Specifically, the method comprises the following steps:
s31: carrying out NIM-CRQCRD function processing on the cubic phase signal to obtain a frequency modulation rate estimation value and a secondary frequency modulation rate estimation value of the radar echo signal of the scattering point;
in this embodiment, the S31 includes the following steps:
(1) processing the cubic phase signal by adopting an instantaneous autocorrelation function to obtain an estimation model of the radar echo signal of the scattering point, wherein,
the instantaneous autocorrelation function is such that,
wherein, taumRepresenting a time delay variable, α and
both represent a constant time delay.
Substituting equation (5) into equation (7) to obtain the estimation model,
wherein the content of the first and second substances,
represents the cross terms generated after the autocorrelation function processing,
representing the noise term generated after the autocorrelation function processing.
(2) Eliminating nonlinear coupling between slow time and delay variables of the estimation model;
specifically, Keystone transformation is carried out on the estimation model, and slow time t in an exponential term of a formula (8) is eliminatedmAnd a delay variable τmAnd a non-linear coupling therebetween, wherein,
the Keystone transform function is as follows,
wherein, tnRepresenting the time of scaling and h representing the scaling factor.
Substituting equation (9) into equation (8) to obtain an estimation model after eliminating nonlinear coupling,
wherein the content of the first and second substances,
represents the cross terms after the Keystone transformation,
representing the noise term after the Keystone transform.
(3) Performing fast Fourier transform on the estimation model after cancellation non-linear coupling to obtain an estimation model Fourier transform equation;
specifically, the method comprises the following steps:
a. along the scale-variable time axis t for equation (10)nPerforming a first fast Fourier transform to obtain a first Fourier transform equation,
wherein the content of the first and second substances,
expressed as a scaled time tnThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the first fast fourier transform,
representing the generation of a noise term after a first fast fourier transform;
b. along the delay variable axis tau for equation (11)mPerforming a second fast Fourier transform to obtain an estimation model Fourier transform equation,
wherein the content of the first and second substances,
representing a time-delay variable τmThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the second fast fourier transform,
representing the noise term generated after the second fast fourier transform.
(4) Performing non-coherent accumulation on the estimation model Fourier transform equation to obtain the NIM-CRQCRD function;
specifically, the method comprises the following steps:
constant in equation (12)Time delay
Taking the results obtained by different values to carry out non-coherent accumulation to obtain the NIM-CRQCRD function as,
from equation (13), it can be seen that the scattering point P (P ═ 1,2.. P) is (Φ ·)p,2,φp,3There is a unique peak at/h).
(5) Processing the cubic phase signal by an NIM-CRQCRD function, obtaining the estimated frequency modulation value and the estimated secondary frequency modulation value by adopting a peak value detection technology,
wherein the content of the first and second substances,
an estimated frequency modulation value of the radar echo signal of the p-th scattering point is represented,
a quadratic frequency estimate representing the radar echo signal for the p-th scattering point,
representing the cubic phase signal s for the l-th range celll(tm) And (5) carrying out NIM-CRQCRD function processing on the result.
S32: and performing Doppler compensation on the cubic phase signal according to the frequency modulation rate estimated value and the secondary frequency modulation rate estimated value to obtain a center frequency estimated value and an amplitude estimated value of the radar echo signal of the scattering point.
Specifically, the method comprises the following steps:
use of
Performing Doppler compensation on the cubic phase signal, performing fast Fourier transform on the cubic phase signal after the Doppler compensation to obtain the central frequency estimated value and the amplitude estimated value,
the calculation formula of the center frequency estimated value and the amplitude estimated value is as follows,
wherein the content of the first and second substances,
an amplitude estimate of the radar return signal representing the p-th scattering point,
the center frequency of the radar echo signal of the p-th scattering point is shown, D' represents the peak amplitude obtained after the fast Fourier transform is carried out on the Doppler compensated cubic phase signal,
indicating a slow time tmThe frequency of the corresponding frequency domain is,
and the number of sampling points of the radar echo signals is represented.
S4: updating the radar echo signal of a scattering point in each distance unit according to the pre-estimated parameters;
specifically, the method comprises the following steps:
subtracting the p-th scattering point from which the estimated parameter has been obtained from equation (5) according to the following equation until the residual energy of the cubic phase signal is less than an energy threshold,
in this embodiment, the energy threshold is 5% of the energy of the original signal.
And (4) repeating the steps to update the radar echo signals of scattering points in each range unit by taking l as l + 1.
S5: and obtaining an ISAR image of the target to be detected according to the updated radar echo signal.
Obtaining ISAR image of the target to be measured by using the updated radar echo signal and adopting the range-instantaneous-Doppler imaging technology of parameter estimation
In the ISAR imaging method for the complex moving target, the NIM-CRQCRD is adopted to carry out parameter estimation on the CPS, so that NUFFT (non-uniform Fourier transform) is avoided in the parameter estimation process, the parameter estimation can be realized only by adopting fast Fourier transform, the calculation process is greatly simplified, and meanwhile, the noise resistance of the method can be effectively improved by adopting a mode of combining non-coherent accumulation and coherent accumulation.
Example two
The present embodiment is a simulation experiment of the ISAR imaging method of the complex moving object in the first embodiment.
The simulation parameters are as follows: considering a signal with a single-component CPS, the signal contains zero-mean white Gaussian noise, the effective length N of the signal is 256, and the sampling rate FsIs 256Hz, A1＝1，φ1,1＝10Hz，φ1,2＝12Hz/s，φ1,3＝16Hz/s2。
Assuming constant time delay for non-coherent accumulation in NIM-CRQCRD
The number of (I) is set to 1, and it can be known from formula (8) that when I is 1, NIM-CRQCRD is equivalent to Modified Chirp-Quadratic Chirp distribution (M-CRQCRD), and the noise threshold of M-CRQCRD is-5 dB, so that the input signal-to-noise ratio is-5 dB, the constant delay α is set to 1, and the variable scale factor h is 1, the constant delay is set to
Preferably in the range of [ -0.5:0.5 [)]Please refer to fig. 3, fig. 3 shows an embodiment of the present inventionEmbodiments provide an output signal-to-noise ratio
The results of the change are plotted, which are the results of 300 monte carlo tests, and as can be seen from the results in the graph,
the results obtained are very slightly different and all are clearly better than
The average obtained result is about 1dB higher, so that the method can be used for the treatment of the cancer
Within a range of (2) selecting a constant time delay
The value of (a).
The simulation parameters are as follows, all signal parameters are the same as those in simulation 1, the constant time delay α is 1, the variable scale factor h is 1, and the input signal-to-noise ratio range is set to be [ -10:0]dB, 100 tests are performed for each input snr, see fig. 4-6, where fig. 4 is a graph of input-output snr results, fig. 5 is a graph of rms error of CR estimates, and fig. 6 is a graph of rms error of QCR estimates. As can be seen from equation (13), if the delay is constant, the delay is constant
The peak value position of the self term is not changed, and the noise term has randomness, so that the peak value position is not fixed at one point, and after the formula (14), the increment of the peak amplitude of the noise term is smaller than that of the self term, so that the noise resistance of the NIM-CRQCRD is improved. As can be seen from FIG. 4, when the value of I is set to 2, 4, 8, 16, the noise-resistant threshold of NIM-CRQCRD is-6 dB, -7dB, -8dB, -9dB, respectively, and the simulation result proves that the noise-resistant performance of NIM-CRQCRD is better than that of M-CRQCRD, and the input signal-to-noise ratio is lowerUnder the condition, accurate estimation values of CR and QCR can still be obtained, and the anti-noise performance of the QCR is improved along with the increase of the I value.
The simulation parameters are as follows: consider a signal having two CPS identified by Au1 and Au2, respectively, with zero mean white Gaussian noise. The effective length N of the signal is 256 and the sampling rate FsIs 256Hz, A1＝1，φ1,1＝-120Hz，φ1,2＝-30Hz/s，φ1,3＝-80Hz/s2，A2＝1，φ2,1＝100Hz，φ2,2＝30Hz/s，φ2,3＝64Hz/s2The constant delay α is 1, the scaling factor h is 1, and the input signal-to-noise ratio is set to 0 dB.
Referring to fig. 7-10, fig. 7-10 are graphs of simulation results of cross term suppression performance under different values of I provided by an embodiment of the present invention, where I is 2 in fig. 7, I is 4 in fig. 8, I is 8 in fig. 9, and I is 16 in fig. 10. From fig. 7-fig. 10, it can be seen that the simulation result is not affected by the value of I, and only the energy of the self items Au1 and Au2 is accumulated in the presence of the multi-component CPS, and (phi) can be obtained by the peak detection technique1,2,φ1,3) Is estimated as
(φ2,2,φ2,3) Is estimated value of
And the energy of the cross terms is not accumulated like the self terms, so that the parameter estimation of Au1 and Au2 is not influenced. Simulation results prove that the cross term inhibition performance of the NIM-CRQCRD is not influenced by the value of I, and the effect is as good as that of the M-CRQCRD.
In practical application, different from the current simulation parameter, the CPS amplitude is often different, so that a weak self term may be submerged by a strong cross term, and in this case, the CLEAN technology is generally used to solve the problem.
The simulation verification proves that the NIM-CRQCRD has better anti-noise performance and cross term inhibition performance. The complex moving object ISAR imaging method of the present invention based on NIM-CRQCRD will be validated in the following simulations.
The ship is imaged in the simulation experiment, and the unit vector of radar LOS is
The carrier frequency of the radar is 5GHz, the bandwidth of a transmitted signal is 100MHz, the wavelength of the transmitted signal is 0.06m, the pulse repetition period is 256Hz, the effective pulse number is 256, the sampling rate is 100MHz, and the motion parameters of the ship are shown in Table 1.
TABLE 1 Ship motion parameters
| Speed of rotation | Acceleration of a vehicle | Acceleration rate | |
| Translation parameter | 30m/s | 2m/s2 | 2m/s3 |
| Component of rotation parameter X axis | 0.03rad/s | 0.02rad/s2 | 0.01rad/s3 |
| Component of rotation parameter Y axis | 0.01rad/s | 0.02rad/s2 | 0.01rad/s3 |
| Component of rotation parameter Z axis | 0.02rad/s | 0.01rad/s2 | 0.01rad/s3 |
The signal-to-noise ratio is set to [ -6: -9] dB, please refer to fig. 11-18, where fig. 11-14 are graphs of simulation results of ISAR imaging based on M-CRQCRD according to an embodiment of the present invention, and fig. 15-18 are graphs of simulation results of ISAR imaging based on NIM-CRQCRD according to an embodiment of the present invention, where the results are normalized. Entropy can be used as a parameter for measuring the imaging quality of ISAR, see table 2, where table 2 is the entropy of each image in fig. 11-18. As can be seen from fig. 11-14, in an environment with a low signal-to-noise ratio, the ISAR imaging based on M-CRQCRD is poor in quality, and especially when the signal-to-noise ratio is-8 dB and-9 dB, the ISAR imaging algorithm based on M-CRQCRD has completely failed, so that the shape of the ship is submerged in the pseudo-scattering points. As can be seen from fig. 15-18, the ISAR imaging algorithm based on NIM-CRQCRD has no influence on ISAR imaging quality in low signal-to-noise ratio environment, and still can obtain images with good focusing, which is also confirmed by the results in table 2. The simulation result proves the effectiveness of the NIM-CRQCRD-based complex moving object ISAR imaging algorithm in a low signal-to-noise ratio environment.
TABLE 2 entropy of ISAR imaging based on M-CRQCRD and NIM-CRQCRD at different input signal-to-noise ratios
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. An ISAR imaging method of a complex moving object, comprising:
acquiring radar echo signals of scattering points of a target to be detected in each distance unit;
modeling the radar echo signal into a cubic phase signal after pulse compression processing and motion compensation;
performing parameter estimation on the cubic phase signal by adopting a non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function to obtain an estimated parameter;
updating the radar echo signal of a scattering point in each distance unit according to the pre-estimated parameters;
and obtaining an ISAR image of the target to be detected according to the updated radar echo signal.
2. The method of claim 1, wherein the cubic phase signal is,
wherein L represents the L-th range bin, L represents the total range bin number, tmDenotes the slow time, P denotes the number of scattering points in the l-th range bin, ApRepresenting the amplitude, phi, of the radar echo signal at the p-th scattering pointp,1Representing the center frequency, phi, of the radar echo signal at the p-th scattering pointp,2Frequency modulation, phi, of the radar echo signal representing the p-th scattering pointp,3Second harmonic frequency, z (t), of radar echo signal representing the p-th scattering pointm) Representing complex white gaussian noise.
3. The method of claim 1, wherein the pre-estimated parameters comprise: a frequency modulation rate estimate, a secondary frequency modulation rate estimate, a center frequency estimate, and an amplitude estimate.
4. The method of claim 3, wherein performing a parameter estimation on the cubic phase signal using a non-uniform sampling integral type modified modulation frequency-chirp distribution to obtain an estimated parameter comprises:
processing the cubic phase signal by using a non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function to obtain a modulation rate estimation value and a quadratic modulation rate estimation value of the radar echo signal of the scattering point;
and performing Doppler compensation on the cubic phase signal according to the frequency modulation rate estimated value and the secondary frequency modulation rate estimated value to obtain a center frequency estimated value and an amplitude estimated value of the radar echo signal of the scattering point.
5. The method according to claim 4, wherein the processing of the non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function on the cubic phase signal to obtain the estimated modulation frequency value and the estimated quadratic modulation frequency value of the radar echo signal of the scattering point comprises:
processing the cubic phase signal by adopting an instantaneous autocorrelation function to obtain an estimation model of the radar echo signal of the scattering point,
the instantaneous autocorrelation function is such that,
the estimation model is a model of,
wherein, taumRepresenting the delay variable as a non-uniform sample, α and
both represent a constant time delay and are,
represents the cross terms generated after the autocorrelation function processing,
representing a noise term generated after the autocorrelation function processing;
eliminating nonlinear coupling between slow time and delay variables of the estimation model;
performing fast Fourier transform on the estimation model after cancellation non-linear coupling to obtain an estimation model Fourier transform equation;
carrying out non-coherent accumulation on the estimation model Fourier transform equation to obtain the non-uniform sampling integral type correction modulation frequency-quadratic modulation frequency distribution function;
and carrying out non-uniform sampling integral type correction modulation frequency-secondary modulation frequency distribution function processing on the cubic phase signal, and obtaining the modulation rate estimation value and the secondary modulation rate estimation value by adopting a peak value detection technology.
6. The method of claim 4, wherein performing Doppler compensation on the cubic phase signal according to the frequency modulation frequency estimation value and the quadratic modulation frequency estimation value to obtain a center frequency estimation value and an amplitude estimation value of the radar echo signal of the scattering point, comprises:
use of
Performing Doppler compensation on the cubic phase signal, performing fast Fourier transform on the cubic phase signal after the Doppler compensation to obtain the central frequency estimated value and the amplitude estimated value,
the calculation formula of the center frequency estimated value and the amplitude estimated value is as follows,
wherein the content of the first and second substances,
an estimated frequency modulation value of the radar echo signal of the p-th scattering point is represented,
a quadratic frequency estimate representing the radar echo signal for the p-th scattering point,
an amplitude estimate of the radar return signal representing the p-th scattering point,
the center frequency of the radar echo signal of the p-th scattering point is shown, D' represents the peak amplitude obtained after the fast Fourier transform is carried out on the Doppler compensated cubic phase signal,
indicating a slow time tmThe frequency of the corresponding frequency domain is,
and the number of sampling points of the radar echo signals is represented.
7. The method of claim 5, wherein eliminating non-linear coupling between slow time and delay variables of the estimation model comprises:
performing Keystone transformation on the estimation model to eliminate nonlinear coupling between slow time and delay variables of the estimation model, wherein,
the Keystone transform function is as follows,
the estimation model after eliminating the non-linear coupling is,
wherein, tnRepresenting a variable scale time, h representing a variable scale factor,
represents the cross terms after the Keystone transformation,
representing the noise term after the Keystone transform.
8. The method of claim 7, wherein performing a fast fourier transform on the estimation model after canceling the non-linear coupling to obtain an estimation model fourier transform equation comprises:
performing first fast Fourier transform on the estimation model after cancellation except the nonlinear coupling along a variable scale time axis to obtain a first Fourier transform equation,
wherein the content of the first and second substances,
expressed as a scaled time tnThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the first fast fourier transform,
to representGenerating a noise item after the first fast Fourier transform;
performing a second fast Fourier transform on the first Fourier transform equation along the time delay variable axis to obtain an estimation model Fourier transform equation,
wherein the content of the first and second substances,
representing a time-delay variable τmThe frequency of the corresponding frequency domain is,
representing the cross terms generated after the second fast fourier transform,
representing the noise term generated after the second fast fourier transform.
9. The method of claim 8, wherein non-coherent accumulation of the estimation model fourier transform equation to obtain the non-uniform sampling integral type modified modulation frequency-quadric modulation frequency distribution function comprises:
constant time delay of Fourier transform equation of the estimation model
Non-coherent accumulation is carried out on results obtained by taking different values to obtain a non-uniform sampling integral type correction modulation frequency-secondary modulation frequency distribution function as,
10. the method of claim 9, wherein the processing of the non-uniform sampling integral type modified modulation frequency-quadratic modulation frequency distribution function on the cubic phase signal, and obtaining the estimated modulation frequency value and the estimated quadratic modulation frequency value by using a peak detection technique comprises:
determining a center frequency estimate and an amplitude estimate of the radar echo signal at the scattering point according to the following equations,
wherein the content of the first and second substances,
an estimated frequency modulation value of the radar echo signal of the p-th scattering point is represented,
a quadratic frequency estimate representing the radar echo signal for the p-th scattering point,
representing the cubic phase signal s for the l-th range celll(tm) And (4) carrying out non-uniform sampling integral type correction frequency-secondary frequency modulation distribution function processing on the result.
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