KR101016845B1 - Method of generating inverse synthetic aperture radar image for multiple targets flying in formation and apparatus thereof - Google Patents

Abstract

The present invention relates to a method and apparatus for generating a reverse synthetic aperture radar image for a flight in flight. According to the present invention, the method includes receiving a reflected wave scattered and reflected from a target, generating a flight trajectory of the target from a distance side view extracted from the reflected wave, selecting a pixel whose magnitude of the pixel value is larger than the reference value from the flight trajectory Extracting a flight trajectory, modeling the extracted flight trajectory as a polynomial, and aligning distance by adjusting a parameter included in the polynomial such that the estimated trajectory according to the polynomial approaches the extracted flight trajectory, the distance-aligned distance profile Compensating for the phase error and generating a reverse synthetic aperture radar image using the distance profile. According to the present invention, by modeling flight trajectories of a plurality of targets flying in flight polynomial, ISAR image can be obtained more accurately and quickly by performing distance alignment with respect to a plurality of targets accurately and quickly. As a result, it is expected to be used in various ways for military purposes on the battlefield.

ISAR, radar, distance profile, distance component, PSO, scattering circle, formation flight

Description

TECHNICAL OF GENERATING INVERSE SYNTHETIC APERTURE RADAR IMAGE FOR MULTIPLE TARGETS FLYING IN FORMATION AND APPARATUS THEREOF}

The present invention relates to a method and apparatus for generating a reverse synthetic aperture radar image, and more particularly, to a method for generating a reverse synthetic aperture radar image to which a new distance alignment method is applied to a flight flight target composed of a plurality of targets. Relates to a device.

Recently, a technology for an inverse synthetic aperture radar (hereinafter referred to as "ISAR") imaging system for obtaining a two-dimensional high resolution image of a moving target has been widely used. The down-range resolution of the ISAR image is determined by the bandwidth of the radar signal, and the cross-range resolution is determined by the relative rotational movement of the target and the radar. Due to the two-dimensional nature of these ISAR images, they are applied for many military purposes.

Radar images can be used to identify targets over long distances and such techniques are called non-cooperative target recognition (NCTR) or automatic target recognition (ATR). For this NCTR or ATR, a high resolution ISAR image must be obtained, but when the target moves, a phase error occurs due to the blurring of the radar image. The most commonly used method for obtaining ISAR images is the Range-Doppler algorithm. The most important steps in the Range-Doppler algorithm are between pulses for chirp radar systems and bursts for stepped-frequency radar systems. This is a reward for the translational motion that occurs in.

The fluctuation of the target object generally consists of translational and rotational motions, especially when the compensation for the translational motion is inadequate, the same scatterers range. in different positions on the profile, which causes the ISAR image to become very blurred.

Compensation for translational motion is largely divided into two stages: range alignment and phase adjustment. The distance alignment is to align the signals reflected from the same scattering source to be located at the same position in different distance side views, and the phase adjustment is a method of compensating the phase error due to the forced distance alignment.

In the case of the distance alignment algorithm according to the prior art, it is assumed that only one target exists in the radar beam. However, in the actual battlefield situation, most flight formations in which a plurality of targets move in the same direction and speed, and according to the prior art, multiple targets are captured in the radar beam so that reflected waves by multiple targets exist simultaneously in the received signal. do. In this case, since scattering waves caused by a plurality of targets generate constructive interference or destructive interference with each other, the accuracy of distance alignment is reduced or the distance alignment calculation time is greatly increased.

An object of the present invention is to provide a method and apparatus for generating an ISAR image to which a distance alignment method suitable for a plurality of targets in flight.

In addition, another object of the present invention is to provide a method and apparatus for generating an ISAR image capable of aligning distances to targets quickly and accurately even when the target has a long flight trajectory.

According to an embodiment of the present invention for solving this problem, in the method for generating a reverse synthetic aperture radar image for a target in flight, receiving a reflected wave scattered and reflected from the target, from the reflected wave Generating a flight trajectory of the target from the extracted distance side view, extracting a new flight trajectory by selecting a pixel whose magnitude of a pixel value is greater than a reference value from the flight trajectory, modeling the extracted flight trajectory by polynomial and And distance-aligning by adjusting a parameter included in the polynomial such that the estimated trajectory according to the polynomial approaches the extracted flight trajectory, and compensating a phase error of the distance-aligned distance side view, and using the distance side view. Generating a reverse synthetic aperture radar image.

The distance side view may include a distance component according to an observation angle of the radar.

In the extracting of the new flight trajectory, a pixel having a size greater than the reference value may be set to 1 and a pixel smaller than the reference value may be set to 0.

The polynomial can be expressed as follows.

Where M is the number of distance profiles and a _i is a parameter.

The parameter may be adjusted to maximize the number of pixels matched among the estimated trajectory according to the polynomial and the extracted flight trajectory.

The parameter is estimated through a particle swarm optimization (PSO) algorithm, and the PSO algorithm may be expressed by the following equation.

Where t is the number of generations, φ is the inertia weight, ρ ₁ = r ₁ c ₁ , ρ ₂ = r ₂ c ₂ , c ₁ , c ₂ > 1, c ₁ + c ₂ <4, r _i Is a random variable with a uniform distribution between 0 and 1.

Dividing the extracted flight trajectories into a plurality of sections, performing distance alignment using the estimated trajectories according to the polynomial with respect to the extracted flight trajectories included in each section, and distances overlapping neighboring sections The method may further include aligning the neighboring sections based on the side view.

According to another embodiment of the present invention, in the apparatus for generating a reverse synthetic aperture radar image for a target in flight, receiving a reflected wave scattered and reflected from the target, and the target from the distance side view extracted from the reflected wave A distance side view generation unit for generating a flight trajectory of a, extracting a new flight trajectory by selecting a pixel whose magnitude is greater than a reference value from the flight trajectory, modeling the extracted flight trajectory by a polynomial, and according to the polynomial A distance alignment unit for adjusting a parameter included in the polynomial so that the estimated trajectory is close to the extracted flight trajectory, a phase adjusting unit for compensating a phase error of the distance-aligned distance side view, and an inverse synthetic aperture surface using the distance side view It includes an image generator for generating a radar image.

By modeling the flight trajectories of multiple targets flying in flight in a polynomial manner, ISAR images can be obtained more precisely and quickly by performing distance alignment with multiple targets accurately and quickly. As a result, it is expected to be used in various ways for military purposes on the battlefield.

DETAILED DESCRIPTION Embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily practice the present invention.

First, an ISAR image will be described with reference to FIG. 1. 1 is an exemplary diagram illustrating the movement of a target to generate an ISAR image, and FIG. 2 is a diagram illustrating a scattering source generated from a target.

As shown in FIG. 1, the change in the observation angle caused by the relative movement of the target 100 away from the radar 200 is used to form an ISAR image. That is, the radar signal according to the change of the observation angle between the radar 200 and the target 100 is transmitted to the ISAR image generating apparatus 300, and the ISAR image generating apparatus 300 receives the ISAR image based on the received radar signal. Create Here, when the radar 200 emits a radar beam toward the target 100, the target 100 captured by the radar beam scatters the radar signal into a plurality of reflected waves. In this case, the target 100 captured by the radar beam is represented as an isotropic point scatterer on the 3D coordinate side as shown in FIG. 2.

Prior to describing the present invention, a Doppler algorithm for functionalizing the radar signal will be described. First, in the radar signal, the monostatic chirp waveform is most widely used because it has a high distance resolution. The transmitted chirp signal may be expressed as Equation 1 below.

일 경우 1이고, 그 밖의 범위에서는 0을 갖는 함수이다. Where r (t) is the signal transmitted at time t, A ₀ is the amplitude of the signal, and f ₀ Is the starting frequency and B is the bandwidth. τ is the pulse width, rect is

If 1, it is a function with 0 in other ranges.

Here, the received signal reflected from the scattering source may be represented by Equation 2 below.

A is the amplitude of the reflected signal and d ₀ is the delay time between the radar and the scattering source. In the case of a plurality of targets, the received signal g (t) can be expressed by Equation 3 below.

Where d _{k , n} represents the time delay between the radar and the nth scattering source of the target, N is the number of scattering circles, and K is the number of targets. The value of d _{k , n} can be calculated using the planar waveform approximation. In the Range-Doppler algorithm, the reflected signal is represented as a distance profile at a particular lateral angle, undergoes translational compensation, including distance alignment and phase adjustment, and then at each distance component (hereinafter referred to as "range bin"). Fast Fourier transform (FFT) is applied, a detailed description thereof will be described with reference to FIG.

3 is a flowchart of a Range-Doppler algorithm for generating an ISAR image. The Range-Doppler algorithm assumes that the relative angle of rotation between the target and radar is small and that scattering circles do not move to adjacent range bins for small angles of rotation. When the rotation angle is large, the interpolation is uniformly performed in the (frequency, angle) region by using a polar format, and a technique for obtaining a high resolution image is one of two-dimensional spectral estimation techniques. Multiple signal classification (MUSIC) techniques and the like can be used.

As shown in FIG. 3, the Range-Doppler algorithm consists of three stages: a range compression step S310, a translational motion compensation step S320, and an azimuth compression step S350. Lose.

The distance compression step S310 is a process of forming a distance side view representing the distribution of scattering circles at each observation angle. In this step, matched filtering using a wideband chirp signal or an inverse discrete Fourier transform (IDFT) using a step frequency signal is used. Distance resolution is determined by the bandwidth of the radar signal, expressed as c / 2B to be. Where c is the speed of light and B is the bandwidth. The distance side view shown in the right end of FIG. 3 may be represented by a plurality of range bins of reflected waves reflected from scattering sources at a particular observation angle.

The translational motion compensation step S320 is a process of compensating motion between pulses in the case of a chirp radar and bursts in the case of a step radar, and is divided into a distance alignment step S330 and a phase adjustment step S340. .

Finally, the vertical compression (S350) is a process of arranging the scattering circles in the vertical direction by using the difference in the Doppler frequencies of the scattering sources. Vertical resolution is affected by the viewing angle and is expressed as λ / 2Δθ. Where Δθ is the observation angle and λ is the wavelength. In the absence of translational compensation, the ISAR image is just a two-dimensional Fourier transform, and if the movement of the distance profiles due to the target's motion is not compensated for, the ISAR image will be seriously blurred. It demonstrates in more detail.

As shown in Figure 3, the translational motion compensation step (S320) is divided into a distance alignment step (S330) and a phase adjustment step (S340), the range alignment (range alignment) step (S330) is a step of aligning the distance side view , Phase adjustment step (S340) is a step for compensating for the relative phase error of the forcibly aligned distance side views.

If the target is stationary and only rotates, the signals reflected from the same scattering source will be at a fixed distance on the distance profile. However, because the target can move several range bins between pulses, the reflected signals will generally be in different locations at different distance profiles. Therefore, the distance side views must be aligned so that the signals reflected from the same scattering source are located at the same distance in all distance side views. However, when the distance side views are moved without any phase compensation, a phase error is generated. Therefore, the phase error should be compensated for each distance side view.

If the target's kinematic parameters are known correctly, translational compensation can be performed directly. However, since it is impossible to know these variables accurately, the relative travel distance and phase error for distance alignment cannot be accurately calculated. For this reason, techniques for distance alignment and phase adjustment are widely used without using motion variables.

In the distance sorting step S330, a cost function indicating similarity of distance side views, such as correlation and entropy, is widely used. Among many cost functions, the one-dimensional entropy cost function is known to be very efficient and robust to noise. This cost function (H _{Gm , Gm +1} ) is given by Equation 4 below.

In Equation 4, G _m (n) and G _{m +1} (n) represent m-th and (m + 1) -th distance profiles in the n-th range bin, N _p represents the total number of range bins, and σ Indicates the number of movements for distance alignment. In general, G _m (n) to minimize errors in distance alignment Instead, the mean of the first to mth distance profiles is used. According to Equation 1, alignment is performed by moving the (m + 1) th distance side view by the number of shifts σ minimizing the one-dimensional entropy cost functions H _{Gm and Gm +1} .

In the phase adjusting step S340, methods such as a maximum contrast method and a minimum entropy method are used. These techniques, like the distance alignment technique, are also applied without information on the motion of the target, and can be easily implemented by those skilled in the art, and thus detailed descriptions are omitted.

On the other hand, as described above, the distance alignment method of minimizing the entropy cost function according to Equation 4 is effective for generating an image for one target but is not suitable for generating an image for a plurality of targets.

4A illustrates a distance alignment result generated by applying a method of minimizing an entropy cost function for a single target, and FIG. 4B illustrates a distance alignment generated by applying a method of minimizing an entropy cost function for a plurality of targets. The results are shown.

4A relates to two distance profiles generated for one target, and the two distance profiles are strongly correlated with each other, and the distance alignment is accurately performed by a distance alignment method for minimizing entropy according to Equation 4. It can be seen that.

On the other hand, Figure 4b relates to the two distance side view generated for a plurality of targets, it can be seen that the value of the third range bin and the fifth range bin has increased dramatically due to the influence of other targets. That is, the values of the third range bin and the fifth range bin in the second distance side view (Range Profile 2) in FIG. 4B should be aligned to the fourth range bin and the sixth range bin in the first distance side view (Range Profile 1). Increasing the values to 6 and 7, respectively, resulted in inaccurate distance alignment. This result is due to constructive or destructive interference occurring between the reflected waves for a plurality of targets, and as shown in FIG. 4B, the value of the range bin increases during distance alignment. Therefore, in the case of one target, the entropy functions as an appropriate cost function because the neighboring distance profiles are similar, but in the case of a plurality of targets, the values of the neighboring range bins are not similar. Application to the target can be considered inappropriate.

Accordingly, an apparatus and a method for generating an ISAR image that can prevent incorrect distance alignment caused by a range bin having a high value when capturing a plurality of targets will be described with reference to FIGS. 5 through 10.

5 illustrates a configuration of an ISAR image generating apparatus according to an embodiment of the present invention.

As shown in FIG. 5, an ISAR image generating apparatus 300 according to an exemplary embodiment of the present invention includes a distance side view generator 310, a translational compensator 320, and an image generator 330.

The distance side view generator 310 receives the reflected waves scattered and reflected from the target, and generates a distance side view indicating the distribution of scattering circles. The distance side view includes a range bin for the target according to the viewing angle of the radar.

The translation compensation unit 320 compensates for the translation of the target, and includes a distance alignment unit 322 and a phase adjuster 324.

The distance alignment unit 322 extracts a new flight trajectory by selecting a pixel having a magnitude greater than a reference value from the flight trajectory, models the extracted flight trajectory as a polynomial, and estimates the trajectory according to the polynomial to the extracted flight. Adjust the parameters included in the polynomial to approximate the trajectory. The phase adjuster 324 compensates for the phase error of the distance-aligned distance side view.

The image generator 330 arranges scattering circles in a vertical direction, and generates an ISAR image using a distance side view.

Hereinafter, a distance alignment step according to an embodiment of the present invention will be described.

FIG. 6 is a flowchart illustrating a distance alignment method for a plurality of targets according to an exemplary embodiment of the present invention, and FIG. 7 is an exemplary view showing a plurality of targets in flight in formation.

First, as shown in FIG. 7, a distance side view as shown in FIG. 8A representing a distribution of scattering circles at each observation angle for a plurality of targets in flight, is formed (S610).

FIG. 8A illustrates a distance side view trajectory generated for multiple targets.

The distance side view trajectory shown in FIG. 8A shows the magnitude of the reflected wave reflected after the radar fires a radar pulse (or laser beam) to the target. In FIG. Shows the number of radar pulses fired toward the target (assuming 128 pulses in FIG. 6). In addition, the horizontal axis Down-Range Bin in Figure 8a represents the time it takes for the radar to receive the reflected wave after firing the radar pulse, which corresponds to the distance between the radar and the target. Therefore, it can be said that the distance side view trajectory shown in FIG. 8A corresponds to the flight trajectory of the target.

Also, the color of the distance side view trajectory represents the magnitude of the reflected wave, which is proportional to the pixel value of the distance side view trajectory image. Therefore, the measurement result of one radar pulse among the radar pulses shown in the distance side view trajectory shown in FIG. 8A is a distance side view shown in the right end of FIG. 3, where the magnitude of the reflected wave is the distance component ( range bin).

Then, select the η range bins having the highest pixel values in each distance side view, set the value to 1, and set the value to 0 for the other range bins to extract a new flight trajectory as shown in FIG. S620). FIG. 8B illustrates a flight trajectory of a target generated by extracting a range bin in which a pixel value is set to 1 in FIG. 8A. That is, in FIG. 8A, η range bins having a large pixel value are extracted for each cross-range bin.

Here, the value of η should be set to be appropriate for selecting a range bin corresponding to the scattering source. If the value of η is too large, the range bin with the smaller value is selected. If the value of η is too small, only the range bin with a few large values is selected. The extracted flight trajectory for each cross-range bin shown in FIG. 8B may be indicated by a solid line in the target region of FIG. 9.

9 is a view for explaining a cost function according to an embodiment of the present invention. As shown in FIG. 9, the center corresponds to the target region, and both sides of the target region correspond to a non-target region.

Then, the extracted flight trajectory of the target is modeled as a polynomial such as Equation 5 (S630). Equation 5 is a polynomial for estimating the extracted flight trajectory, and polynomial R (t) is a polynomial for the estimated trajectory.

In Equation 5, M is the number of distance side views and a _i is a parameter. R (t) is a real number and is set to an integer value close to the actual value. The function value of the polynomial R (t) varies according to the parameter a _i , and the estimated trajectory of the polynomial R (t) also varies.

In operation S640, the parameter a _i is adjusted to track the extracted flight trajectory according to the polynomial. To this end, the estimated trajectory according to the polynomial represented by the dotted line in FIG. 9 is moved in the direction of the target area. In FIG. 9, it is shown that the estimated trajectory is moved from the left to the right of the target area. Therefore, the estimated trajectory passes through the extracted flight trajectory. As the estimated trajectory coincides with the extracted flight trajectory, more pixels overlap between the estimated trajectory and the extracted flight trajectory.

In this case, the total sum of overlapping pixel values may be defined as a cost function, and a parameter a _i value for maximizing the cost function may be set. That is, if the sum of the pixel values is large, the polynomial shown in Equation 5 can be considered to be substantially identical to the extracted trajectory, and the distance alignment can be easily performed using the set parameter a _i value.

Here, it is effective to estimate the parameter a _i value through particle swarm optimization (PSO). PSO is a population-based probabilistic optimization technique that initializes entities called particles to random values and then velocity towards the local best and global best of each particle. Change to find the minimum and maximum cost functions and the entity providing them. The method of updating each particle is as shown in Equation 6 below.

)는 i번째 particle(

)에 더해져서 이 particle을 이동시킨다.Where t is the number of generations, φ is the inertia weight, ρ ₁ = r ₁ c ₁ , ρ ₂ = r ₂ c ₂ , c ₁ , c ₂ > 1, c ₁ + c ₂ <4, r _i Is a random variable with a uniform distribution between 0 and 1. The velocity vector obtained from Equation 6 is the velocity vector

) Is the i particle (

To move this particle.

On the other hand, the flight trajectory estimated by Equation 5 is difficult to exactly match the extracted distance side profile, and the distance alignment error may cause serious problems. In particular, as the flight time of the trajectory is long, the extracted distance side view trajectory is also long, so it is difficult to estimate the correct flight trajectory through Equation 5.

Therefore, in the embodiment of the present invention, as shown in FIG. 10, the extracted distance side view trajectory may be divided into several segments, and two neighboring segments may share one distance side view. 10 is a view for explaining a cost function divided into a plurality of compartments according to an embodiment of the present invention.

First, the flight trajectory is estimated through Equation 5 for each of the sections shown in FIG. 10, and the neighboring distance profiles are distance-aligned based on overlapping range profiles. In addition, estimating the flight trajectory in parallel according to each section can prevent the time delay because the same time as the method of estimating the entire flight trajectory by one polynomial is required.

Hereinafter, the ISAR image generated through the entropy minimization method according to the related art and the ISAR image generated through the embodiment of the present invention will be described with reference to FIGS. 11A through 11D.

FIG. 11A is an exemplary view illustrating distance alignment of a distance side view through an entropy minimization method, and FIG. 11B is an exemplary view illustrating distance alignment of a distance side view through an embodiment of the present invention. FIG. 11C is an exemplary view showing an ISAR image generated using FIG. 11A, and FIG. 11D is an exemplary view showing an ISAR image generated using FIG. 11B.

First, comparing FIG. 11A and FIG. 11B, it can be seen that FIG. 11A is less uniform in comparison with FIG. 11B and that both boundaries of the distance-aligned distance side view do not proceed correctly in a straight line shape. Accordingly, the ISAR image shown in FIG. 11C represents only pixels having a high pixel value and does not represent target pixels spreading through the image. On the other hand, the ISAR image shown in FIG. 11D can display the target more accurately and clearly by modeling the flight trajectory of the target by polynomial.

Thus, according to the embodiment of the present invention by modeling the flight trajectory of a plurality of targets flying in flight polynomial, ISAR image having a clearer and higher quality can be obtained by performing distance alignment accurately and quickly for a plurality of targets have.

Although the preferred embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements of those skilled in the art using the basic concepts of the present invention defined in the following claims are also provided. It belongs to the scope of rights.

1 is an exemplary diagram illustrating the movement of a target to generate an ISAR image.

2 is a diagram showing a scattering source generated from a target.

3 is a flowchart of a Range-Doppler algorithm for generating an ISAR image.

4A illustrates a distance alignment result generated by applying a method of minimizing an entropy cost function for one target.

4B illustrates the distance alignment results generated by applying a method of minimizing the entropy cost function for multiple targets.

5 illustrates a configuration of an ISAR image generating apparatus according to an embodiment of the present invention.

6 is a flowchart illustrating a distance alignment method for a plurality of targets according to an embodiment of the present invention.

7 is an exemplary view showing a plurality of targets in flight for formation.

FIG. 8A illustrates a distance side view trajectory generated for multiple targets.

FIG. 8B illustrates a flight trajectory of a target generated by extracting a range bin in which a pixel value is set to 1 in FIG. 8A.

9 is a view for explaining a cost function according to an embodiment of the present invention.

10 is a view for explaining a cost function divided into a plurality of compartments according to an embodiment of the present invention.

FIG. 11A is an exemplary view illustrating distance alignment of a distance side view through an entropy minimization method. FIG.

Figure 11b is an exemplary view showing the distance alignment of the distance side view through an embodiment of the present invention.

FIG. 11C is an exemplary diagram illustrating an ISAR image generated using FIG. 11A.

FIG. 11D is an exemplary diagram illustrating an ISAR image generated using FIG. 11B.

Claims (14)

A method for generating a reverse synthetic aperture radar image for a squadron in flight, Receiving reflected waves scattered and reflected from the target, Generating a flight trajectory of the target from a distance side view extracted from the reflected wave, Extracting a new flight trajectory by selecting a pixel having a magnitude greater than a reference value from the flight trajectory, Modeling the extracted flight trajectory as a polynomial, and adjusting distances by adjusting a parameter included in the polynomial such that the estimated trajectory according to the polynomial approaches the extracted flight trajectory, and Compensating the phase error of the distance-aligned distance side view, and generating a reverse synthetic aperture radar image using the distance side view. The method of claim 1, And the distance side view comprises a distance component according to an observation angle of the radar. The method of claim 1, Extracting a new flight trajectory, The pixel of which the size of the pixel value is greater than the reference value is set to 1, and the pixel smaller than the reference value is set to 0. The method of claim 3, Wherein the polynomial is represented as follows:

Where M is the number of distance profiles and a _i is a parameter. The method of claim 4, wherein And adjusting the parameter to maximize the number of pixels matched among the estimated trajectory and the extracted flight trajectory according to the polynomial. The method of claim 5, The parameter is estimated through a particle swarm optimization (PSO) algorithm, wherein the PSO algorithm is a method of generating a reverse synthetic aperture radar image, characterized by the following equation:

Where t is the number of generations, φ is the inertia weight, ρ ₁ = r ₁ c ₁ , ρ ₂ = r ₂ c ₂ , c ₁ , c ₂ > 1, c ₁ + c ₂ <4, r _i Is a random variable with a uniform distribution between 0 and 1. The method of claim 1, Dividing the extracted flight trajectory into a plurality of compartments, Performing distance alignment on the extracted flight trajectories included in each section by using the estimated trajectory according to the polynomial; and And arranging the neighboring sections based on a distance side view overlapping the neighboring section. An apparatus for generating a reverse synthetic aperture radar image for a flight in flight. A distance side view generation unit for receiving a reflected wave scattered and reflected from the target and generating a flight trajectory of the target from the distance side view extracted from the reflected wave, From the flight trajectory, a new flight trajectory is selected by selecting a pixel whose magnitude is larger than a reference value, the extracted flight trajectory is modeled as a polynomial, and the estimated trajectory according to the polynomial is close to the extracted flight trajectory. Distance alignment unit for adjusting the parameters included in the polynomial, A phase adjuster for compensating for the phase error of the distance-aligned distance profile, and And an image generator for generating a reverse synthetic aperture radar image using the distance side view. The method of claim 8, And the distance side view comprises a distance component according to an observation angle of the radar. The method of claim 8, The distance alignment unit, A reverse synthetic aperture radar image, wherein the new flight trajectory is extracted by setting a pixel value of a pixel having a size greater than the reference value to 1 and a pixel value of a pixel smaller than a reference value to 0. Device to generate. The method of claim 10, Wherein the polynomial is represented as follows:

Where M is the number of distance profiles and a _i is a parameter. The method of claim 11, And adjusting the parameter to maximize the number of pixels matched among the estimated trajectory and the extracted flight trajectory according to the polynomial. The method of claim 12, The parameter is estimated through a particle swarm optimization (PSO) algorithm, the PSO algorithm is an apparatus for generating a reverse synthetic aperture radar image, characterized by the following equation:

Where t is the number of generations, φ is the inertia weight, ρ ₁ = r ₁ c ₁ , ρ ₂ = r ₂ c ₂ , c ₁ , c ₂ > 1, c ₁ + c ₂ <4, r _i Is a random variable with a uniform distribution between 0 and 1. The method of claim 8, The distance alignment unit, The extracted flight trajectory is divided into a plurality of compartments, distance alignment is performed using the estimated trajectory according to the polynomial with respect to the extracted flight trajectories included in each compartment, and based on a distance side view overlapping the neighboring compartments. And aligning the neighboring sections with each other.

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