KR101703773B1 - Method for acquiring radar image using serveillance radar and System thereof - Google Patents

Abstract

The present invention relates to a radar image processing technology, more specifically, to a method for obtaining a radar image and a system thereof, which apply an inverse synthetic aperture radar (ISAR) image obtaining technology, applied to an estimation radar, also to a detection radar generally used and arranged.

Description

Technical Field [0001] The present invention relates to a radar image acquisition method using a navigation radar,

The present invention relates to a radar image processing technique, and more particularly, to an inverse synthetic aperture radar (ISAR) image acquisition technique applied to a tracking radar for a commonly used and arranged detection radar And a system therefor.

Due to changes in domestic and international military and / or security environments, conflicts are increasingly unpredictable and unpredictable. These changes have emphasized the importance of information, and radar, which has the advantage of being observable in all situations, such as weather and daylight, is central to the development of military information and communication technology.

Radar is used in many ways in target recognition due to its ability to detect targets regardless of weather conditions or daytime nighttime. In addition, the technology to recognize the target quickly is recognized as a very important factor in the performance of modern warfare, and this technology has a crucial influence on the survival possibility of the fighter and the missile.

Due to the improved technology of the radar, the target recognition technology has made a lot of progress. In particular, since the 1990s, radar signal processing technology has undergone a lot of development. Currently, it continues to develop around highly integrated radar system and digital signal processing technology. Radar-based target recognition techniques are generally divided into two areas: cooperative recognition and non-cooperative target recognition.

Cooperative recognition technology using information from other systems such as GPS (Global Positioning System) in the target recognition technology is effective in many ways but it is not appropriate because it provides information to the enemy system as well as the enemy. Therefore, non-coordinated target recognition technology, which is limited to the system of the allied group, is appropriate in the military sense.

More sophisticated data on non-coordinated target recognition techniques and scattering characteristics of targets are essential for the design of radars and are currently being applied in advanced countries. Research on advanced countries' research institutes is focused on high resolution signal processing methods such as CNR (Complex Natural Resonance) analysis of received scattered electromagnetic waves, various HRRP (High Resolution Range Profile) acquisition techniques, scattering point extraction, and ISAR Inverse Synthetic Aperture Radar (SAR), Synthetic Aperture Radar (SAR) imaging, or Time-Frequency Analysis (2-D) methods are used to analyze the scattering mechanism of a target or apply it to target recognition.

In general, High Resolution Range Profile (HRRP) or Inverse Synthetic Aperture Radar (ISAR) images are images obtained from fixed radar such as tracking radar or multi-function radar. These techniques are applied to a rotating radar Technological examples are hard to find because of military security reasons, and there are not many related research examples. In 2009, the Naval Reserch Laboratory of U.S. has been working on acquiring ISAR images from a rotating radar. When acquiring ISAR images for multiple targets, it is difficult to separate the dwell time for each target, and in general ISAR images are difficult to obtain continuously updated images Therefore, we have been studying ISAR image acquisition in rotating radar.

According to this study, when an ISAR image is acquired from a rotating transmitting / receiving antenna, it can be updated to a new image every time the antenna rotates and it is easy to distinguish the time zone in which radar observes each target for multiple targets There are advantages.

However, unlike a conventional tracking radar that uses a sufficient number of pulses to obtain an ISAR image, a rotating Doppler spectrum is acquired in each range-bin using a limited pulse in a radar, it is difficult to acquire an image in a cross range direction.

To solve this problem, the US Naval Reserch Laboratory group used adaptive Doppler spectrum estimation to estimate the Gabor basis set from the received signal when the number of pulses was sufficient, . Assuming that the antenna stopped momentarily when the pulse signal transmitted by the radar received the target, the power spectral density of each received signal was assumed to be constant by the rotation of the radar.

In order to predict the Doppler spectrum, a Kalman filter is used. The Kalman filter uses past data and current data to reduce the noise of the current data from past data information, . FIG. 1 shows the result of obtaining the ISAR image according to the resolution level using the adaptive Doppler spectrum estimation technique proposed in this study.

There is also a case study of the ISAR image obtained from the 2008 Defense Research and Development Canada group by briefly introducing the design of the radar mounted on the plane and measuring the ISAR image of the target on sea level. In this study, ISAR images are obtained by compensating for the motion of the target before acquiring the ISAR image and compensating for the relative movement of the target by the radar mounted on the airplane. A diagram showing this concept is shown in Fig.

Other researches in the field of radar signal processing have developed most algorithms for SAR and ISAR in advanced countries, and most of the algorithms for acquiring two - dimensional images are almost completed. It is known to be used in the current military radar system by combining it with Automatic Target Recognition (ATR). Motion compensation techniques for ISAR images for moving targets and motion compensation techniques for radar signals have also been completed and developed steadily.

In particular, high resolution methods have been studied and applied in order to enhance the classification performance of a target in a one-dimensional and two-dimensional signal processing method. The radar has a tracking radar to acquire an image of the target and a detection radar to determine the position of the target. Unlike a detection radar that detects a target in all directions while rotating 360 degrees, the tracking radar is aimed only at a designated target, radiating the beam and tracking the target by measuring the scattering wave, which acquires the ISAR image from the signal obtained while tracking the target .

The tracking radar acquires the ISAR image from continuous and sufficient data because it tracks the signal from the target for a certain amount of time, whereas the detection radar has a short time to look at the target while the signal obtained from the target is rotated periodically There is a difference in obtaining ISAR image from this.

Therefore, unlike a tracking radar that uses information contained in all pulse signals when acquiring ISAR images, a rotating search radar requires a process of selecting a pulse containing information of the target and a process of processing a signal obtained from a small pulse . In addition, it is necessary to carry out a study on a new compensation process for the rotational movement of the target obtained at each antenna rotation.

1. Korean Registered Patent No. 10-1001612 (December, 2010) 2. Korean Registered Patent No. 10-1081894 (November 3, 2011)

1. ISAR Image Formation of Rear Tracking Vehicle Radar with Pulse-Phase Error Compensation Kang, Byung-Soo, Kang, Byoung-Soo, ) pp.97-103 2. ISANG Cross-Range Scaling for Maneuvering Target Kang, Byoung-Soo, Journal of the Korea Electromagnetic Engineering Society Vol. 25, No. 10, 1062p ~ 1068p, 2014

The present invention has been proposed in order to solve the problem according to the above background art, and it is an object of the present invention to provide a radar image acquiring method and a radar image acquiring method for applying an inverse synthetic aperture radar (ISAR) The purpose of the system is to provide.

It is another object of the present invention to provide a radar image acquisition method and system thereof for acquiring an image using a navigation radar simply by software update.

The present invention provides a radar image acquiring method for applying an inverse synthetic aperture radar (ISAR) image acquisition technique applied to a tracking radar to a detection radar in order to achieve the above-described problems.

The radar image acquiring method includes:

(a) receiving multiple target information and radar system specification information;

(b) generating a received signal of the search radar using the multi-target information and the radar system specification information;

(c) classifying the received signal for each target of the multiple target; And

(d) acquiring a radar image for each target using an image acquisition technique using a scattering point distance difference or data generation using image scattering information and an image acquisition technique.

In this case, the step (C) may include: obtaining multi-target original data having the received signal; Extracting mountain points from the multi-target data and converting the mountain points into high-resolution data; Extracting and storing characteristics of lines generated by the motion of each target from the high-resolution data using a Hough-transform technique; And classifying all of the scattering points by a target using the characteristics of the straight lines, and classifying the data in the original data according to a target.

(여기서, s(v, w)는 탐색 레이더의 수신신호이고, v는 시간을 나타내는 파라미터이며, w는 광대역 주파수에 대해 주파수를 나타내는 파라미터이며, G_v는 안테나의 이득이며, A_k와 R_vk는 각각 산란점의 산란강도와 탐색 레이더간 거리이고, K는 표적을 이루는 산란점의 수이고, c는 빛의 속도이며, f_w는 주파수 샘플이고, u(v)는 탐색 레이더가 바라보는 방향에 따라 표적이 보이면 1의 값을 가지고 보이지 않으면 0의 값을 갖는다)에 의해 생성되는 것을 특징으로 할 수 있다.Further, the received signal of the search radar is expressed by the following equation

Where v is a parameter representing the time, w is a parameter representing the frequency with respect to the wideband frequency, G _v is the gain of the antenna, A _k and R _vk Is the scattering intensity of the scattering point and the distance between the search radars, K is the number of scattering points forming the target, c is the speed of light, f _w is the frequency sample, u (v) is the direction And a value of 0 if the target is not seen with a value of 1).

In addition, the image acquiring method using the above-mentioned scattering point distance difference is performed by using the relationship between the mountain ranges of the scattering points obtained at the two observations of the pair of search radars and the respective degrees of rotation according to the degree of rotation And the interval between the scattering points is determined.

In addition, the data generation and image acquisition technique using the scattering point information generates a received signal in an invisible region using the scattering point information of the target extracted from the obtained received signal, and generates an inverse synthetic aperture (ISAR) And compensates the received signal by a Radar motion compensation technique to acquire an image.

Also, the scattering point information is generated by extracting a one-dimensional scattering point using the number of scattering points after estimating the number of scattering points using a compression sensing technique.

In addition, the received signal in the invisible region may include a velocity in an unobserved region between a first observed region first observed by a pair of search radars spaced a certain distance and a second observed region second observed, The position information and the scattering intensity of scattering points estimated using the acceleration relation are estimated by substituting the scattering intensity into a signal model based on GTD (generalized triangular decomposition).

In addition, the ISAR motion compensation scheme may be a stage-by-stage approach based on a minimum entropy method.

In this case, the SSA technique includes distance alignment to compensate for the entropy of the sum of the two adjacent distance profiles to a minimum, and distance profile to compensate for phase errors still remaining after the distance alignment, so that the entropy of the entire ISAR image is minimized. And a phase correction for adding a phase to the output signal.

On the other hand, another embodiment of the present invention is a radar image acquisition system including a search radar for tracking a target and a signal processing device for receiving a received signal from the search radar and generating an ISAR (Inverse Synthetic Aperture Radar) System can be provided.

The signal processing apparatus includes a reception signal generation module that receives multi-target information and radar system specification information, and generates a reception signal of the search radar using the multi-target information and the radar system specification information; A classifier for classifying the received signal for each target of the multiple targets; And a generation unit that acquires a radar image for each target using an image acquisition technique using a scattering point distance difference or a data generation and image acquisition technique using scattering point information.

According to the present invention, it is possible to acquire an image of a target only by software update through an image acquisition technique using a search radar having a higher penetration rate than a tracking radar, and to use the radar to detect and identify the target, It is expected to contribute.

Another advantage of the present invention is that it can be used for forming a radar image by using a limited signal in the existing tracking radar situation, and can be used as signal processing techniques in other fields.

FIG. 1 shows an example of a result obtained by obtaining an ISAR (Inverse Synthetic Aperture Radar) image according to a resolution level using a general adaptive Doppler spectrum estimation technique.
2 is an example of a target detection result screen in a general SAR image.
3 is a flowchart illustrating a process of acquiring an image in a search radar according to an embodiment of the present invention.
FIG. 4 is a flow chart showing in detail sub-step S330 of sorting each target from the received signals for the multiple targets shown in FIG.
Fig. 5 is a conceptual diagram for easy understanding of Fig.
FIGS. 6A and 6B are conceptual diagrams illustrating a factor for determining a difference in scattering point distance of a target in a search radar according to the first technique of step S340 shown in FIG. 3. FIG.
FIG. 7 is a conceptual diagram for explaining a relationship between a vertical distance (distance) of a scattering point and a scattering point distance difference in a search radar.
8A and 8B are views showing an example of target image acquisition using the difference in scattering point distance for a 7-point target.
FIG. 9 is a flowchart illustrating a process of generating data and acquiring an image using scattering point information according to a second technique of step S350 shown in FIG.
10 is a conceptual diagram schematically showing the flowchart shown in FIG.
FIG. 11 is a flowchart showing the scattering point extraction step (S910) shown in FIG. 9 in more detail.
FIG. 12 is a flow chart showing in more detail the antenna gain compensation step (S920) shown in FIG.
FIG. 13 is a flow chart showing the concept of the stage-by-stage approach (SSA) technique shown in FIG.
14 is a configuration diagram of a radar image acquisition system for acquiring images in a search radar according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout.

3 is a flowchart illustrating a process of acquiring an image in a search radar according to an embodiment of the present invention. Referring to FIG. 3, after inputting multiple target information and radar specification information (i.e., search radar specification information), a signal model of a search radar based on geometric theory of diffraction (GTD) And generates a reception signal of the search radar (steps S310 and S320).

Here, s (v, w) denotes a received signal of the search radar, v is a parameter indicating time, w is a parameter indicating a frequency with respect to a wideband frequency, and G _v denotes an antenna gain. A _k and R _vk denote the scattering intensity and scattering distance of the scattering point, respectively. K represents the number of scattering points forming the target, c represents the speed of light, and f _w represents a frequency sample. Finally, u (v) has a value of 1 if the target is seen according to the direction in which the search radar is looking, or 0 if it is not visible.

Thereafter, the received signal of the obtained search radar does not contain only the signal for one target, but the signals for the various targets are mixed. Therefore, a process of classifying the received signal for each target is performed from this signal (step S330). This will be described later with reference to FIG.

3, after the multiple target classification is completed, a radar image acquisition process for each target is applied (steps S340, S350, S360). Here we propose two techniques. The first technique uses an image acquisition technique using a difference in scattering point distance, and uses the fact that the interval between scattering points is determined by the cross range of each scattering point in the next rotation (step S340). Figures 6 and 7 illustrate schematically this first technique. The understanding will be described later.

3, the second technique is a data generation and image acquisition technique using scattering point information, and generates a received signal in an invisible region using scattering point information of a target extracted from the obtained received signal, And an ISAR (Inverse Synthetic Aperture Radar) motion compensation method of the tracking radar to compensate the ISAR (step S350).

FIG. 4 is a flow chart showing a detailed step S330 of sorting each target from the received signals for the multiple targets shown in FIG. 3 according to the first embodiment of the present invention. Referring to FIG. 4, the classification of the received signal is largely divided into four steps.

In a navigation radar, you are usually in a situation where you are observing multiple targets. Therefore, it is necessary to classify the signals for multiple targets for each target. In a first step, a received signal obtained through a search radar for a situation in which multiple targets exist is represented by the presence of multiple target data in one data (step S410). do.

In the second step, the received data is converted into data having high-resolution information by scattering point extraction (step S420). As a third step, the change of the position information of the scattering points is stored using a Hough-transform technique (step S430). Hough transform is a technique of extracting features of straight lines formed in image data by transferring a straight line formed in arbitrary image data to a new domain of the distance and slope of the straight line. Applying the Hough-transform technique to the high-resolution data obtained from the scattering point extraction in the second step, we can extract the characteristics of the straight lines generated by the motion of each target, and can characterize the multiple target through this.

The extracted scattering point has a characteristic that it is placed on the same path (straight line in the case of Hough-transform) for each target, and information of the extracted scattering point can be classified by each target using this characteristic (step S440).

Fig. 5 is a conceptual diagram for easy understanding of Fig. Referring to FIG. 5, scattering points 520 are extracted from original data 510, position information 530 of scattering points is extracted, peak detection 540 is performed from the position information using a hypotransform And data 550 classified according to the target is generated.

6A and 6B are conceptual diagrams showing a factor for determining the difference in scattering point distance of the target in the search radar according to the first technique of step S340 shown in FIG. 3, and FIG. 7 is a graph showing the vertical distance (cross range) and the distance between the scattering points.

6A, 6B and 7, the first technique is a technique of obtaining a radar image from a scatter signal of a target obtained in two rotation observations without a process of estimating a received signal. 6A and 6B, the order of the first rotation and the second rotation is generated by using the first search radar 610-1 and the second search radar 610-2.

At this time, it can be observed that as the degree of rotation is changed in the situation where the first and second search radars 610-1 and 610-2 observe the target, the difference of the gap between the scattering points changes, This is the difference caused by the cross range.

The relationship between the scattering points and the cross range of each scattering point is shown in FIG. FIG. 7 is a conceptual diagram for explaining a relationship between a vertical distance (distance) of a scattering point and a scattering point distance difference in a search radar.

Using the parameters shown in FIG. 7, the relationship between the scattering points according to the cross-range of the scattering points (c1, c2, c3) and the order of rotation is shown in Equation (2). Using equation (2), the distance between each scattering point is calculated from the range profile obtained in the first rotation and the second rotation, and the cross-range of all points of the mountain is calculated from the variation of these intervals .

7, c2 is the cross-range distance of the second scattering point, d is the down-range distance between the scattering points,? Is the incident beam direction in the first rotation, In the direction of the incident beam.

In the above equation, only the scattering point c2 is defined, but similarly, c1 and c3 are also defined.

8A and 8B are views showing an example of target image acquisition using the difference in scattering point distance for a 7-point target. In particular, FIG. 8A is a signal composed of a received signal obtained for one target as described in FIGS. FIG. 8B also simulates the radar image of the air vehicle shown as an example.

FIG. 9 is a flowchart showing a process of generating data and acquiring an image using scattering point information according to a second technique of step S350 shown in FIG. 3. FIG. 10 is a conceptual diagram schematically showing the flowchart shown in FIG. to be. In addition, the second technique estimates the received signal of the non-target area and makes it equal to the received signal obtained from the tracking radar, and acquires the image by applying the motion compensation technique used in the existing tracking radar.

9, an antenna gain compensation process (step S920), a received signal estimation process in an unobserved area (step S930), and an ISAR (Inverse Synthetic Aperture Radar) motion compensation (Step S940).

As a first step, the scattering points (1010 in FIG. 10) of the target are extracted through the one-dimensional scattering point extraction technique to obtain a received signal at a time when no target is observed. At this time, if noise is mixed in the received signal, it becomes difficult to grasp the accurate number of scattering points of the target. Accordingly, first, the number of scattering points is estimated as shown in FIG. 11 using a compressed sensing technique, and a scattering point of the target is extracted through one-dimensional scattering point extraction (step S910).

Then, in the tracking radar, the beam is steered according to the movement of the target so that the target exists at the center of the beam. On the other hand, since the search radar rotates irrespective of the position or movement of the target, have. Therefore, the gain of the beam varies in the corresponding direction depending on the position of the target in the beam. Therefore, it is solved through the antenna gain compensation process (1020 in FIG. 10) as shown in FIG. 12 (step S920).

9, after completion of the antenna gain compensation process, the positions of the scattering points in the invisible region using the scattering point positions in each range profile obtained in the scattering point extracting process (1030 ) (Step S930). First, the average velocity of the target is obtained by using the scattering point position information in the first and second observed regions. Through the velocity and acceleration relation, the acceleration in the unobserved region between the two observed regions is obtained, and the position of the accurate target in the second observed region is grasped. This position is the position relative to the target position in the first observed region.

Secondly, the velocity in the first and second observed regions of each scattering point is obtained, and it is substituted into the positional change equation for acceleration movement to estimate the positions of the scattering points in the unobserved region. The position information of the scattering point obtained in this way and the previously obtained scattering intensity are substituted into a signal model based on GTD (Generalized Triangular Decomposition) to estimate a received signal in an unobserved region.

If a received signal similar to the signal of the tracking radar is obtained through the above process, finally the ISAR image (1040 in FIG. 10) is acquired using the existing ISAR motion compensation technique (step S940). The motion compensation scheme uses a stage-by-stage approach (SSA) based on a minimum entropy method.

FIG. 11 is a flowchart showing the scattering point extraction step (S910) shown in FIG. 9 in more detail. Referring to FIG. 11, some bursts (pulse radars) transmit a plurality of pulse signals, and receive a pulse signal corresponding to a target and returning information about the target. In this case, (Step S1110), estimates the number of scattering points (step S1120), and extracts a scattering point of the target for each burst through one-dimensional scattering point extraction (step S1120) Step S1130).

FIG. 12 is a flow chart showing in more detail the antenna gain compensation step (S920) shown in FIG. Referring to FIG. 12, the maximum value of the scattering intensity obtained from all the range profiles is obtained for each scattering point (step S1210). Next, respective scaling factors are obtained in order to make the scattering intensity of each scattering point in each range profile to the maximum values obtained previously (step S1220).

The scaling factor of each scattering point is averaged in the obtained range profile to finally average the scaling factor of the corresponding range profile (step S1230). Finally, the antenna gain compensation process is completed by multiplying the corresponding signal (step S1240).

FIG. 13 is a flow chart showing the concept of the stage-by-stage approach (SSA) technique shown in FIG. Referring to FIG. 13, the SSA technique includes a range alignment process (step S1320) and a phase adjustment process (step S1330). Of course, there is a data decompression process (step S1310) before the distance alignment process, and a process of compressing the ISAR image (step S13410) after the phase correction process.

The distance alignment process (step S1320) compensates for the movement of the scattering points to a different range bin according to the movement of the target. The entropy of the sum of the sizes of the two adjacent range profiles is minimized To compensate.

The phase correction process is performed to compensate for the remaining phase errors after the distance alignment, and phase is added to each range profile so that the entropy of the entire ISAR image is minimized. If both distance alignment and phase correction are performed, the final ISAR image is acquired.

14 is a configuration diagram of a radar image acquisition system for acquiring images in a search radar according to an embodiment of the present invention. 14, there is provided a navigation radar 1410 for tracking a target 10, a signal processing device 1420 for receiving an incoming signal from the search radar 1410 and generating an ISAR image, and the like.

The search radar 1410 may include a first search radar and a second search radar disposed at a predetermined interval from the first search radar. Of course, more than one pair of search radars may be constructed.

The signal processing unit 1420 includes a reception signal generation module 1421 that receives the multiple target information and the radar system specification information and generates a reception signal of the search radar using the multiple target information and the radar system specification information, A classification unit 1423 for classifying the received signals for each target of the target, a radar image for each target using the image acquisition technique using the scatter point-to-target distance difference or the data generation and image acquisition technique using the scatter point information A generation unit 1425, and an image processing unit 1427 for processing and storing and / or displaying the obtained radar image.

The terms " part, "" unit," " module, "and the like, which are described in the specification, refer to a unit that processes at least one function or operation, and may be implemented by hardware or software or a combination of hardware and software.

10: Target
1410: Radar
1420: Signal processing device
1421: Receive signal generation module
1423:
1425:
1427:

Claims (9)

(a) receiving multiple target information and radar system specification information;
(b) generating a received signal of a search radar that detects a target in all directions while rotating 360 degrees using the multi-target information and the radar system specification information;
(c) classifying the received signal for each target of the multiple target; And
(d) acquiring a radar image for each target using an image acquisition technique using a scattering point distance difference or data generation using image scattering point information and an image acquisition technique,
The step (c)
Obtaining multi-target original data having the received signal;
Extracting mountain points from the multi-target data and converting the mountain points into high-resolution data;
Extracting and storing characteristics of lines generated by the motion of each target from the high-resolution data using a Hough-transform technique; And
Classifying all the scattering points by a target using the characteristics of the straight lines, and classifying data in the original data according to a target. delete The method according to claim 1,
The received signal of the search radar is expressed by Equation

Where v is a parameter representing the time, w is a parameter representing the frequency with respect to the wideband frequency, G _v is the gain of the antenna, A _k and R _vk Is the scattering intensity of the scattering point and the distance between the search radars, K is the number of scattering points forming the target, c is the speed of light, f _w is the frequency sample, u (v) is the direction And a value of 0 if the target is not visible and a value of 1 if the target is not visible.
The method according to claim 1,
The image acquiring method using the above-described scattering point distance difference is performed by using the relationship between the mountain ranges of the scattering points obtained from the two observations of the pair of search radars and the respective mountain ranges according to the degree of rotation, And the distance between the scattering points is determined.
The method according to claim 1,
The data generation and image acquisition technique using the scattering point information generates a received signal in an invisible region using the scattering point information of the target extracted from the obtained received signal and generates an inverse synthetic aperture radar (ISAR) And compensating the received signal by a motion compensation technique to obtain an image.
6. The method of claim 5,
Wherein the scattering point information is generated by estimating the number of scattering points using a compression sensing technique and then extracting a one-dimensional scattering point using the number of scattering points.
6. The method of claim 5,
The received signal in the invisible region is a velocity and acceleration relationship in an unobserved region between a first observed region first observed by a pair of search radars spaced a certain distance and a second observed region second observed, And estimating the position information and the scattering intensity of the scattering points estimated using the generalized triangular decomposition (GTD) based signal model.
6. The method of claim 5,
The ISAR motion compensation scheme is a SSA (stage-by-stage approach) based on a minimum entropy method,
The SSA scheme includes distance alignment to compensate for entropy of the sum of the magnitudes of two adjacent distance profiles to a minimum and phase to each distance profile so that entropy of the entire ISAR image is minimized to compensate for phase errors still remaining after the distance alignment. And a phase correction unit that adds the phase correction to the radar image.
1. A radar image acquisition system comprising: a navigation radar that rotates 360 degrees and detects a target in all directions; and a signal processing device that receives and processes a received signal from the navigation radar to generate an ISAR (Inverse Synthetic Aperture Radar)
The signal processing apparatus includes:
A received signal generation module that receives multiple target information and radar system specification information and generates a received signal of the search radar using the multiple target information and the radar system specification information;
A classifier for classifying the received signal for each target of the multiple targets; And
And a generation unit for acquiring a radar image for each target using an image acquisition technique using a scattering point distance difference or a data generation and image acquisition technique using scattering point information,
Wherein,
Acquiring multi-target original data having the received signal, extracting mountain points from the multi-target data, converting the multi-target data into high-resolution data, and extracting high-resolution data from the high-resolution data using the Hough- Extracts and stores the characteristics of the straight lines generated by the movement of the search radar, classifies all the scattering points according to the target using the characteristics of the straight lines, and classifies the data in the original data according to the target. Radar image acquisition system using.

Images