KR102202622B1 - Apparatus and Method for Improving Target Detection Accuracy - Google Patents

Abstract

Disclosed are a device for improving an accuracy of detecting a target and a method thereof. The present invention includes: an image forming unit which acquires a detection signal reflected from a target and forms an initial target image using raw data regarding the detection signal; a target-of-interest image extracting unit which selects at least one target of interest from the initial target image, and generates at least one segmented image including each of the at least one interest target; and an image synthesizing unit which generates a final target image by synthesizing a target image processor for estimating a residual phase error of each of the at least one segmented image and compensating for the residual phase error and the at least one segmented image for which the residual phase error is compensated, thereby improving the accuracy of detection.

Description

Apparatus and Method for Improving Target Detection Accuracy}

The present invention relates to an apparatus and method for improving target detection accuracy. More specifically, the present invention relates to a target detection accuracy improving apparatus and method for generating an image for detecting a target with improved accuracy by dividing an image formed from raw data and synthesizing the generated divided image again.

The content described in this section merely provides background information on the present embodiment and does not constitute the prior art.

Unlike general radars, the composite aperture radar refers to a radar that generates and provides 3D image information about an object on the ground by using a detection signal transmitted from a radar reflected from an object located on the ground. The main use of the composite aperture radar is to obtain a long aperture with high crossrange resolution by using the radar mounted on the vehicle, and this composite aperture radar has a great effect on changes in weather and day and night. Do not receive. Therefore, synthetic aperture radars are being used for surveillance and reconnaissance on the sea, day and night.

In general, in the process of collecting a signal to form a wide area composite aperture radar image, if the payload on which the radar is mounted is vibrated severely, the composite aperture formed from the collected signal varies by region, so the composite aperture There is a technical need to improve the quality of the entire radar image area.

Conventionally, in the image processing method for evenly improving the image quality of a composite aperture radar image over a wide area, it is impossible to improve the image quality in the case of a composite aperture radar image over a wide area in the azimuth direction, and the geometric relationship between the radar and the terrain. There is a problem in that whether or not an image processing method for improving the image quality of a composite aperture radar image can be applied varies according to a squint angle of.

The present invention forms an image from raw data obtained from a detection signal reflected from a target so as to increase the probability of detection and identification of a target, and divides and generates the formed image using a target of interest with a strong side lobe signal It is to provide a target detection accuracy improvement apparatus and method for generating an image with improved detection accuracy by estimating and compensating for a phase error of each of at least one divided image.

In order to achieve the above object, the apparatus for improving accuracy of target detection according to an embodiment of the present invention obtains a detection signal reflected from the target, and forms an initial target image using raw data related to the detection signal. Part, a target-of-interest image extractor for selecting at least one target of interest from the initial target image and generating at least one segmented image including each of the at least one target of interest, and a residual phase of each of the at least one segmented image A target image processing unit of interest for estimating an error and compensating for the residual phase error, and an image synthesizing unit for generating a final target image by synthesizing at least one divided image for which the residual phase error is compensated.

In order to achieve the above object, a method for improving target detection accuracy by a computing device according to another embodiment of the present invention acquires a detection signal reflected from the target, and uses raw data on the detection signal to obtain an initial target. Forming an image, selecting at least one target of interest from the initial target image, generating at least one segmented image including each of the at least one target of interest, a residual phase of each of the at least one segmented image It may include estimating an error, compensating for the residual phase error, and generating a final target image by synthesizing the at least one divided image.

In order to achieve another object of the present invention, the method for improving target detection accuracy of the present invention can provide a storage medium in which a computer-readable program is recorded for execution in a computer.

According to the embodiment of the present invention as described above, the phase error is calculated based on signals having a strong side lobe influence on the target of interest required for estimating the phase error, rather than the phase error of the entire image from the aircraft radar image acquired in the ground and sea environments. Because of the extraction, the accuracy of error estimation is improved and the probability of target detection and identification increases.

In addition, according to an embodiment of the present invention, since the characteristics of the target are reflected when the residual phase error is estimated, the influence of the side lobe of the target of interest generated in various directions may be reduced.

The effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a block diagram schematically illustrating a configuration of an apparatus for improving target detection accuracy according to an embodiment of the present invention.
2 is a block diagram showing in detail the configuration of an image forming unit according to an embodiment of the present invention.
3 is a block diagram showing a detailed configuration of a target image extracting unit according to an embodiment of the present invention.
4 is a block diagram showing in detail the configuration of a target image processing unit according to an embodiment of the present invention.
5 is a block diagram showing a detailed configuration of an apparatus for improving target detection accuracy according to another embodiment of the present invention.
6 is a flowchart illustrating a method of improving target detection accuracy according to an embodiment of the present invention.
7 is a flowchart specifically illustrating a method of improving target detection accuracy according to another embodiment of the present invention.
8 is a flowchart specifically illustrating a method of estimating and compensating a residual phase error of each of a plurality of divided images according to an embodiment of the present invention.
9 is a diagram illustrating in detail a method of improving target detection accuracy according to an embodiment of the present invention.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the implementation of the present invention, reference should be made to the accompanying drawings illustrating preferred embodiments of the present invention and the contents described in the accompanying drawings.

Hereinafter, the present invention will be described in detail by describing a preferred embodiment of the present invention with reference to the accompanying drawings. However, the present invention may be implemented in various different forms, and is not limited to the described embodiments. Further, in order to clearly describe the present invention, parts not related to the description are omitted, and the same reference numerals in the drawings indicate the same members.

Throughout the specification, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components unless specifically stated to the contrary. In addition, terms such as “... unit”, “... unit”, “module”, and “block” described in the specification mean units that process at least one function or operation, which is hardware, software, or hardware. And software.

Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In addition, in describing the present invention, when it is determined that a detailed description of a related known configuration or function may obscure the subject matter of the present invention, a detailed description thereof may be omitted.

Hereinafter, a configuration of an apparatus and method for improving detection accuracy using a side leaf according to an embodiment of the present invention will be described in detail with reference to the related drawings.

1 is a block diagram schematically illustrating a configuration of an apparatus for improving target detection accuracy according to an embodiment of the present invention.

Referring to FIG. 1, an apparatus 10 for improving accuracy of target detection according to an embodiment of the present invention includes an image forming unit 100, a target image extracting unit 200, a target image processing unit 300, and an image synthesis. It may include a unit 400. The apparatus 10 for improving detection accuracy using a side lobe according to an embodiment of the present invention may omit some components or additionally include other components among various components exemplarily illustrated in FIG. 1.

The apparatus 10 for improving detection accuracy using a side lobe according to an embodiment of the present invention moves by mounting a radar and transmits image data from a payload equipped with a radar such as an artificial satellite, a flying vehicle, or an unmanned aerial vehicle using a beam every time it moves. It can be received, and it is a small area but high resolution by adjusting the strip mode for a standard image of medium resolution, a scan mode for wide area observation of low resolution, or by adjusting the antenna beam to illuminate the continuously imaged area. Raw data may be obtained from the transmitted image data using a spotlight mode capable of obtaining an image of. However, the above-described example is only an example for explaining an embodiment of the present invention, and is not limited thereto.

The image forming unit 100 according to an embodiment of the present invention may acquire a detection signal reflected from a target and form an initial target image using raw data related to the detection signal.

The above-described detection signal may be a signal received from an antenna mounted on an aircraft or satellite, and the above-described detection signal is a marine target, a target such as a building with a large area and a large radar cross section (Radar Cross Section, RCS). It may include a signal reflected from the sea clutter, such as.

In addition, the above-described detection signal may be a chirp signal. The chirp signal may represent a signal having a time-frequency characteristic in which a frequency constantly changes over time.

The above-described raw data may represent data for obtaining a radar image.

The image forming unit 100 according to an embodiment of the present invention resets the squint angle value to generate an initial target image using raw data related to the detection signal, and performs preprocessing to reduce unnecessary data for compensation and side lobe reduction. It can perform a function, and can form an initial target image by interpolating and compressing the preprocessed data.

The image forming unit 100 according to an embodiment of the present invention receives a signal for detecting a target through two I/Q channels, an in-phase channel and a quadrature-phase channel. It is possible to perform a pre-processing function to reduce the side lobe of the beam by removing unnecessary Doppler bandwidth and shaking motion compensation for generating a radar image for the received I/Q type radar raw data, and interpolating the pre-processed data. And compression to form a radar image.

A detailed method of forming the above-described initial target image will be described with reference to FIG. 2.

2 is a block diagram showing in detail the configuration of an image forming unit according to an embodiment of the present invention.

Referring to FIG. 2, the image forming unit 100 according to an embodiment of the present invention may include a reset unit 110, a preprocessor 120, and an image generation unit 130.

The reset unit 110 according to an embodiment of the present invention resets the squint angle value of the raw data related to the received signal.

Here, the squint angle refers to an angle between an axis in which the beam of an antenna mounted on an aircraft or satellite is directed toward a target and an axis in which the antenna is directed perpendicular to the ground.

In general, when the target moves, the radar signal received from the target includes a phase error due to the movement of the target, and the radar image is blurred. The above-described phenomenon is because the radar image is affected by the phase error caused by the Doppler effect caused by the movement of the target. Here, the change of the squint angle changes the Doppler Centroid. The Doppler center frequency refers to the Doppler frequency corresponding to the center of the beam emitted by the radar sensor, and the Doppler frequency in the aircraft radar image refers to the frequency domain in the flight direction of the aircraft radar image.

Therefore, since the quality of the radar image is changed by the squint angle value, the distance and azimuth interpolation axis required for the radar image formation process must be redefined by resetting the squint angle value.

If there is a phenomenon in which the position of the target is moved in the distance direction or in the azimuth direction due to the Doppler characteristic according to the movement of the vehicle, the surrounding clutter signal is removed and the squint angle is recalculated using the curve fitting method to determine the distance and Orientation interpolation axis can be redefined. Here, in the curve fitting method, the signal from which the surrounding clutter signal has been removed is sampled and data is obtained. For this sampled data, the distance and orientation interpolation axis can be redefined by calculating a function for the squint angle.

The preprocessor 120 according to an embodiment of the present invention performs a preprocessing function of reducing unnecessary data for vibration compensation and side lobe reduction based on the recalculated squint angle.

The motion compensation method described above is a method of compensating the motion by estimating the velocity and acceleration in each direction of a payload equipped with a radar such as an artificial satellite, an aircraft, or an unmanned aerial vehicle. The method may be a method of shifting the phase of each radar sample according to motion in space, but is not limited thereto.

The preprocessor 120 according to an embodiment of the present invention may reduce unnecessary data for side lobe reduction by deramping the raw data whose motion is compensated by the above-described method, but is not limited thereto. .

The above-described deramping processing method may be a method of directly coupling a reflection chirp signal corresponding to a received signal with a transmission chirp signal corresponding to a transmission signal. The above-described deramping processing method can be used as an advantage in terms of data amount and processing time for obtaining a high-resolution image.

The preprocessor 120 according to an embodiment of the present invention may sample deramped raw data of a received signal in order to reduce a side lobe of a beam by removing an unnecessary Doppler bandwidth. The above-described sampling interval may be determined according to a preset time interval.

The image generator 130 according to an embodiment of the present invention may generate an initial target image by interpolating the preprocessed data in a distance direction and a direction direction based on a redefined distance and azimuth direction interpolation axis and then compressing it. .

The image generator 130 according to another embodiment of the present invention may generate an initial target image using the pre-processed data using a radar image forming algorithm.

As the above-described radar image forming algorithm, a Polar Format Algorithm (PFA) or Range Migration Algorithm (RMA) technique may be applied.

A Range Migration Algorithm (RMA) technique that performs One-dimensional Spectrum Interpolation as the above-described radar formation algorithm according to another embodiment of the present invention may be applied. The RMA described above performs 2D Fourier transform of the reflected signal reflected from the target, performs 2D matched filtering, performs 1D spectral interpolation at a downrange frequency, and performs 2D Fourier transform. It may represent a technique of forming a radar image by performing inverse FT.

Accordingly, the image generation unit 130 according to another embodiment of the present invention generates an interpolated signal by interpolating from raw data in a distance direction by applying the above-described RMA technique, and converts the interpolated signal in a distance direction. Can be compressed. In addition, it is possible to perform interpolation and compression in the azimuth direction using the above-described RMA technique.

An initial target image may be generated by using the data compressed in the above-described distance direction and direction direction.

3 is a block diagram showing a detailed configuration of a target image extracting unit according to an embodiment of the present invention.

Referring to FIG. 3, the target image extracting unit 200 according to an embodiment of the present invention may include a target target extracting unit 210 and an image splitting unit 220.

The target image extracting unit 200 according to an embodiment of the present invention selects at least one target of interest from the initial target image, and generates at least one segmented image including each of the at least one target of interest.

The target of interest extraction unit 210 according to an embodiment of the present invention may select a region of interest (ROI) that is a target of interest necessary for estimating a residual phase error.

Here, ROI refers to a region of interest, and may refer to a region including an image of a target to be detected or identified within the input image.

The image segmentation unit 220 according to an embodiment of the present invention may segment an initial target image based on a target of interest.

The image segmentation unit 220 according to an embodiment of the present invention divides the initial target image into images including overlaps so as to include each of the at least one target of interest selected by the above-described target of interest extraction unit 210, One split image can be created.

4 is a block diagram showing in detail the configuration of a target image processing unit according to an embodiment of the present invention.

The target image processing unit 300 may include a phase error estimation processing unit 310 and a phase error compensation processing unit 320.

The target image processing unit 300 according to an embodiment of the present invention estimates a residual phase error of each of at least one divided image and compensates for the residual phase error of each of the at least one divided image estimated for the phase error. At least one divided image may be generated.

The phase error estimation processing unit 310 according to an embodiment of the present invention calculates the absolute value of the signal strength of the data cells in which the side lobe signal included in the data cell of at least one divided image is concentrated, and calculates each of the calculated data. Extracts the location of the cell with the maximum signal strength value in the azimuth direction for each data cell in the distance direction from the absolute signal strength value of the data contained in the cell, and the location of the cell in the azimuth direction based on the cell with the maximum signal strength value It is possible to create row data by shifting and estimate the residual phase error of the row data.

In addition, the phase error estimation processing unit 310 calculates the absolute value of the signal strength of the data cells in which the side lobe signals included in the data cells of at least one divided image are concentrated, and the signals of the data included in each of the calculated data cells For each data cell in the azimuth direction from the intensity absolute value, the location of the cell with the maximum signal strength value in the distance direction is extracted, and column data is created by moving the location of the cell in the distance direction based on the cell with the maximum signal strength value. , The residual phase error of the thermal data may be estimated, and an error estimation method is not limited thereto.

Here, the residual phase error is a phase error that exists after motion compensation is considered. Residual phase errors from various causes, such as uncompensated sensor motion or atmospheric effects, result in deterioration of image quality. Accordingly, the phase error that is not compensated may be compensated by the phase error estimation processing unit 310 and the phase error compensation processing unit 320.

The phase error estimation processing unit 310 according to an embodiment of the present invention applies a phase gradient autofocus technique to obtain a phase component to be compensated by estimating and integrating a differential value of a phase error from an image out of focus. Thus, the residual phase error of the row data of each of the at least one divided image may be estimated.

The residual phase error of the row data of each of the at least one segmented image may be estimated using Linear Unbiased Minimum Variance (LUMV) corresponding to the Phase Gradient Autofocus method described above.

Specifically, the above-described phase gradient autofocus (PGA) technique selects a range bin with the largest signal size for each range bin, shifts to the origin corresponding to the center of the image, and then uses an appropriate window to estimate phase compensation. It shows a technique for removing unnecessary data and estimating the phase error from the removed data.

However, the method of estimating the phase error of a divided image by applying the phase gradient autofocus (PGA) technique described above is only an example for explaining an embodiment of the present invention, and is not limited thereto, and the phase error of the divided image Various methods of estimation can be applied.

The phase error compensation processor 320 according to an embodiment of the present invention may compensate and process a residual phase error estimated from row data of each of at least one divided image.

The phase error compensation processing unit 320 according to an embodiment of the present invention removes a linear component that may cause an effect of moving a target from the estimated residual phase error, and performs phase compensation for each of at least one row data. At least one phase error compensated data may be generated.

The phase error compensation processing unit 320 according to an embodiment of the present invention may extract a linear component that may cause an effect of moving a target from the estimated residual phase error by approximating it using a polyfit (Polynomial Fitting) technique, and then removing it. have.

Here, since the Polyfit (Polynomial Fitting) technique is a widely known technique, a detailed description thereof will be omitted.

The phase error compensation processing unit 320 according to an embodiment of the present invention may generate at least one phase error compensation data for which a residual phase error is compensated by performing phase error compensation for each of at least one row data.

Here, the residual phase error compensation can compensate the residual phase error of each of at least one data by using the integration of the phase error estimated by the linear unbiased minimum variance (LUMV) from which the above-described linear component is removed. , But is not limited thereto.

The phase error compensation processing unit 320 according to an embodiment of the present invention reconverts the phase-compensated data region into a phase-compensated initial target image, moves the data that has been moved relative to the target of interest to an initial position, and removes the overlap. Make it the initial segmented image size.

The phase error compensation processor 320 according to an embodiment of the present invention may generate an initial target image phase-compensated for a phase-compensated data region using a radar image forming algorithm. As a radar image forming algorithm, a Polar Format Algorithm (PFA) or a Range Migration Algorithm (RMA) technique may be applied, but is not limited thereto.

Since the detailed method of generating the radar image described above has been described above, a detailed description will be omitted.

The image synthesizer 400 according to an embodiment of the present invention may generate a final target image by synthesizing the divided images.

For example, if K targets of interest (K is a natural number greater than 1) are selected and K split images are generated based on the target of interest, the target image processing unit 300 repeats phase error estimation and compensation K times. Thus, K split images in which phase errors are compensated may be generated.

Accordingly, the image synthesizer 400 according to an embodiment of the present invention may synthesize K divided images and display them as a final target image. That is, the target detection accuracy improvement apparatus 10 according to an embodiment of the present invention can obtain a final target image with improved accuracy by synthesizing a total of K divided images from the detection signal reflected from the target through the above-described process. have.

The apparatus 10 for improving target detection accuracy according to another embodiment of the present invention may further include a display unit (not shown in the drawing). The above-described display unit may display the final target image synthesized by the image synthesizing unit 400 to provide to the user. That is, the display unit according to an embodiment of the present invention may display a final target image with improved accuracy of the initial target image formed by the image forming unit 100 and provide it to the user.

5 is a block diagram showing in detail a configuration of an apparatus for improving accuracy of target detection according to another embodiment of the present invention.

Referring to FIG. 5, a target detection accuracy improvement apparatus 20 according to another embodiment of the present invention includes an image processing unit 100, an interest target selection unit 210, an image segmentation unit 220, and a phase error estimation processing unit. 310, a phase error compensation processing unit 320, an image synthesizing unit 400, and a main control unit 500 may be included.

The image processing unit 100 according to an embodiment of the present invention includes a reset unit 110 and a preprocessor 120 included in the apparatus 10 for improving accuracy of target detection according to another embodiment of the present invention shown in FIG. 2. ) And an image restoration unit 130.

For example, the interest target extraction unit 210 and the image segmentation unit 220 included in the target detection accuracy improving device 20 according to another embodiment of the present invention shown in FIG. 3 are devices for improving target detection accuracy. In response to the target image extraction unit 200 of (10), the phase error estimation processing unit 310 and the phase error compensation processing unit 320 correspond to the target image processing unit 300 of the target detection accuracy improving device 10 Can be.

In the target detection accuracy improving apparatus 20, the main control unit 500 may collect raw data, transmit or receive divided data from which the raw data is divided, and control a process of improving detection accuracy using a side lobe.

Up to now, an apparatus for improving accuracy of target detection according to an embodiment of the present invention has been described with reference to FIGS. 1 to 5. However, it is intended to clarify that the division of the constituent units illustrated in FIGS. 1 to 5 is merely divided by the main functions that each constituent unit is responsible for. That is, two or more constituent parts may be combined into one constituent part, or one constituent part may be divided into two or more for each more subdivided function. In addition, each of the components may additionally perform some or all of the functions of other components in addition to its own main function, and some of the main functions of each component are in charge of other components. Of course, it can also be performed.

6 is a flowchart illustrating a method of improving target detection accuracy according to an embodiment of the present invention.

The method for improving target detection accuracy may be performed by a computing device and operates in the same manner as the apparatus for improving target detection accuracy.

Referring to FIG. 6, the computing device acquires a detection signal reflected from a target, and forms an initial target image by using raw data about the detection signal (S610).

The above-described raw data may represent data for obtaining a radar image.

The computing device selects at least one target of interest from the initial target image, and generates at least one segmented image including each of the at least one target of interest (S620).

The above-described target of interest refers to a region of interest, and may refer to a region including an image of a target to be detected or identified within an input image.

The computing device estimates a residual phase error of each of the at least one segmented image and compensates for the residual phase error (S630).

A method of estimating and compensating the residual phase error of each of the at least one divided image described above will be described later in FIG. 8.

The computing device synthesizes at least one segmented image to generate a final target image (s640).

The computing device according to an embodiment of the present invention may generate an initial target image and a final target image from an ROI extracted by performing a radar image forming algorithm.

As the radar image forming algorithm according to an embodiment of the present invention, a Range Migration Algorithm (RMA) performing one-dimensional spectrum interpolation may be used, but is not limited thereto.

7 is a flowchart specifically illustrating a method of improving target detection accuracy according to another embodiment of the present invention.

Referring to FIG. 7, the computing device acquires a detection signal reflected from a target, and generates raw data for the detection signal (S701).

If a phenomenon in which the target position is moved from the raw data occurs, the computing device removes the surrounding clutter signal and recalculates the squint angle using a curve fitting method (s702).

The computing device performs a pre-processing process, which is a process of compensating for the swing motion and reducing the side lobes and data based on the recalculated squint angle (s703).

The computing device according to an embodiment of the present invention may perform vibration compensation on the acquired raw data, and deramping the vibration-compensated raw data to generate the deramped raw data. The computing device can reduce the side lobe of the beam by removing unnecessary Doppler bandwidth.

The computing device generates an initial target image using the compressed data by interpolating the above-described raw data in a distance direction and an azimuth direction (S704).

The computing device according to an embodiment of the present invention may apply a Polar Format Algorithm (PFA) and a Range Migration Algorithm (RMA) technique as a radar image forming algorithm.

The computing device selects a target of interest from the initial target image (S705).

The computing device divides the image around the selected target of interest (S706).

The computing device estimates the residual phase error in the image segmented around the target of interest (s707).

Here, the method of estimating the residual phase error is to estimate the residual phase error by applying a phase gradient autofocus technique that calculates the phase component to be compensated by estimating and integrating the differential value of the phase error from the out of focus image. It can, but is not limited to this.

The computing device compensates for the estimated phase error (s708).

Here, the method of compensating for the estimated phase error can compensate for the residual phase error of each of at least one data by integrating the phase error estimated by the Linear Unbiased Minimum Variance (LUMV), but is limited thereto. It is not.

A detailed method of estimating the phase error and compensating for the phase error will be described later in FIG. 8.

The computing device may iteratively perform phase error estimation and compensation as many as the number of targets of interest.

For example, the ROI is a total of K (K is a natural number greater than 1), and if ROI (k) is selected as the target of interest, phase error estimation and compensation are performed repeatedly until the value of k becomes the same as the value of K. can do. Where k=1,2,... ,K.

The computing device compares and determines whether k is a value greater than K (s709).

As a result of the determination, if k is equal to or less than K, the computing device according to an embodiment of the present invention may repeat the above-described process to estimate and compensate for the phase error by k+1th number, and repeat the above-described process. If k is greater than K, the computing device estimates and compensates for a phase error of a total of K divided images (s709).

The computing device may synthesize a total of K divided images obtained by estimating and compensating for the trauma error (s710).

The computing device may generate the final target image (s711).

The computing device according to another embodiment of the present invention may display a high-resolution radar image representing image data from which a target is detected, generated by the above-described method, and provide it to a user.

8 is a flowchart specifically illustrating a method of estimating and compensating a residual phase error of each of a plurality of divided images according to an embodiment of the present invention.

Referring to FIG. 8, the computing device sets a reference to a location of an ROI as a target of interest as the center of a divided image (s810).

The computing device extracts a location of a cell having a maximum value by searching for a cell location in an azimuth direction for all cells in the distance direction based on the target center of interest (S820).

The computing device makes the cell having the maximum value into one row by moving the position of the cell in the azimuth direction with respect to the center of the target of interest (S830).

The computing device converts the data into a region for estimating the residual phase error in order to apply the autofocus technique (S840).

The computing device estimates a residual phase error of the transformed data (s850). Since the above-described method of estimating the residual phase error has been described above, a detailed description will be omitted.

The computing device approximates and extracts a linear component that may cause an effect of moving a target among the estimated residual phase errors based on Polyfit (Polynomial Fitting), and then removes it (s860).

The computing device compensates for the estimated residual phase error (s870). Since the above-described method of compensating for the estimated residual phase error has been described above, a detailed description will be omitted.

The computing device converts the phase-compensated data region into a radar image region (s880).

The computing device moves the data cells that have moved relative to the target of interest to the initial position, and then removes the overlap to make the size of the initial segmented image (s990).

The above-described method of processing an image formed from raw data into a plurality of divided images is repeatedly performed as many as the number of divided images.

9 is a diagram illustrating in detail a phase error estimation processing unit according to an embodiment of the present invention.

Referring to FIG. 9, a case in which there are three targets of interest (ROI) is illustrated, but the above-described example is only an example for describing an embodiment of the present invention, and is not limited thereto, and the number of targets of interest may vary. have.

The phase error estimation processing unit 310 according to an embodiment of the present invention may estimate a phase error of each of the SubImg_1 910, SubImg_2, and SubImg_3 images, which are images divided by the target image extracting unit 200, of interest.

Specifically, a method of estimating the phase error of the SubImg_1 (910) image will be described.

Here, when the SubImg_1 (910) image is converted into a data region, it may be expressed as SubImg_1(m,n) 920.

Here, SubImg_1(m,n) 920 is all cells in the distance direction based on the target of interest, n=1,2,... Search for ,N in the azimuth direction to find the position in the azimuth direction with the maximum signal strength. Where m=1,2,... ,M. Further, M is the size of data in the direction of the segmented image, and N is the size of data in the direction of distance of the segmented image.

For each cell, the data corresponding to the maximum value position is moved to the same position as the target of interest reference to form an equivalent row (930).

For example, SubImg_1(m,n) 920 is a first cell 921, a second cell 922, a third cell 923, a fourth cell 924, a fifth cell 925, and It is possible to have data in which the side lobe signals of the 6 cells 926 are concentrated.

Here, assuming that the cell having the maximum signal strength is the fourth cell 924, the first cell 921 moves three cells in the opposite direction from the current position, and the second cell 922 moves in the opposite direction from the current position. 2 cells are moved, the third cell 923 moves one cell in the opposite direction from the current position, and the fifth cell 925 moves one cell in the azimuth direction from the current position, and the sixth cell 926 Moves two cells from the current position in the azimuth direction to create a row 931 having the same position as the fourth cell 924.

The phase error estimation processing unit 310 according to an embodiment of the present invention estimates a residual phase error using an autofocus technique by extracting row data of a target of interest after making equal rows.

Here, the autofocus technique may be a phase gradient autofocus technique.

If each of SubImg_2 and SubImg_3 is repeatedly performed in the same process, it is possible to estimate the phase using the data of the target of interest reflecting the characteristics of the side lobe.

Even if all the components constituting the embodiments of the present invention described above are described as being combined into one or operating in combination, the present invention is not necessarily limited to these embodiments. That is, as long as it is within the scope of the object of the present invention, one or more of the components may be selectively combined and operated. In addition, although all of the components can be implemented as one independent hardware, a program module that performs some or all functions combined in one or more hardware by selectively combining some or all of the components. It may be implemented as a computer program having In addition, such a computer program is stored in a computer readable media such as a USB memory, a CD disk, a flash memory, etc., and is read and executed by a computer, thereby implementing an embodiment of the present invention. The recording medium of the computer program may include a magnetic recording medium or an optical recording medium.

The above description is merely illustrative of the technical idea of the present invention, and those of ordinary skill in the technical field to which the present invention belongs can make various modifications, changes, and substitutions within the scope not departing from the essential characteristics of the present invention. will be. Accordingly, the embodiments disclosed in the present invention and the accompanying drawings are not intended to limit the technical idea of the present invention, but to explain, and the scope of the technical idea of the present invention is not limited by these embodiments and the accompanying drawings. . The scope of protection of the present invention should be interpreted by the following claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present invention.

10: Device for improving detection accuracy using side lobes
100: image forming unit
200: interest target image extraction unit
300: target image processing unit of interest
400: image synthesis unit

Claims (13)

In the device for improving the detection accuracy of the target,
An image forming unit that obtains a detection signal reflected from the target and forms an initial target image using raw data related to the detection signal;
A target-of-interest image extraction unit selecting at least one target of interest from the initial target image and generating at least one segmented image including each of the at least one target of interest;
A target image processing unit for estimating a residual phase error of each of the at least one divided image and compensating for the residual phase error; And
Including; an image synthesizing unit for generating a final target image by synthesizing the at least one divided image compensated for the residual phase error,
The target image processing unit of interest may include a phase error estimation processing unit for estimating and processing a residual phase error in each of the at least one divided image; And a phase error compensation processing unit that compensates and processes the estimated residual phase error.
The phase error estimation processing unit extracts a location of a cell having a maximum signal strength value from among data cells in which a side lobe signal included in the data cell of the at least one divided image is concentrated, and the cell having the maximum signal strength An apparatus for improving target detection accuracy to create row data by moving a position of an azimuth direction data cell based on, and to estimate a residual phase error of the row data. The method of claim 1,
The detection signal is a signal received from an antenna mounted on an aircraft or satellite, and the raw data is data for obtaining a radar image. The method of claim 1,
The image forming unit,
A reset unit for resetting the squint angle from the raw data;
A pre-processing unit performing a pre-processing function of reducing unnecessary data from the raw data in order to compensate for the swing motion and reduce the side lobe around the reset squint angle; And
And an image generator configured to generate an initial target image by interpolating and compressing the preprocessed raw data in a distance direction and an azimuth direction. The method of claim 1,
The target image extraction unit of interest,
A target of interest selecting unit for selecting at least one region of interest (ROI) from the initial target image; And
And an image segmentation unit configured to generate at least one segmented image by dividing the initial target image into images including an overlap so as to include each of the at least one target of interest. delete delete The method of claim 1,
The phase error compensation processing unit,
From the estimated residual phase error, a linear component that may cause the effect of moving the target is extracted and removed, the residual phase error is compensated, and the phase-compensated data area is re-converted into an image to remove the overlap. An apparatus for improving accuracy of target detection, characterized in that making the size of an initial divided image. The method of claim 1,
The phase error estimation processing unit,
Since the position of the side lobe of the target of interest (ROI) is moved, the accuracy of the phase error estimation can be improved by estimating the residual phase error reflecting the characteristics of the target of interest, and the phase error of the row data is A device for improving target detection accuracy, comprising estimating a differential value and estimating a phase component to be compensated by integrating a differential value of the estimated phase error. In the method for improving target detection accuracy by a computing device,
Obtaining a detection signal reflected from the target, and forming an initial target image using raw data about the detection signal;
Selecting at least one target of interest from the initial target image and generating at least one segmented image including each of the at least one target of interest;
Estimating a residual phase error of each of the at least one divided image and compensating for the residual phase error; And
Including; synthesizing the at least one divided image to generate a final target image; and
The step of estimating and compensating for the residual phase error of each of the at least one divided image may include calculating an absolute value of data in which a side lobe signal included in a data cell of the at least one divided image is concentrated, and the calculated Extracting a position of a maximum value cell in an azimuth direction with respect to each data cell in a distance direction from the absolute values of data included in each data cell; Moving the cell having the maximum value in an azimuth direction based on the center of the target of interest; Estimating a residual phase error by transforming the data into a region for estimating the residual phase error; Removing a linear component that may cause an effect of moving a target from the estimated phase error; Compensating for an estimated phase error from which the linear component has been removed; Re-converting the phase-compensated data region into an image to move the data that has been moved relative to the target of interest to an initial position; And removing the overlap of the image to obtain an initial segmented image size. The method of claim 9,
Forming the initial target image from the raw data,
Resetting the squint angle from the raw data;
Performing a preprocessing function of reducing unnecessary data for vibration compensation and side lobe reduction around the reset squint angle; And
And interpolating the pre-processed data in a distance direction and an azimuth direction and then compressing the preprocessed data to form an initial target image. The method of claim 9,
Generating the at least one divided image may include:
Selecting at least one region of interest (ROI) from the initial target image; And
And generating at least one segmented image by dividing the initial target image into an image including an overlap so as to include each of the at least one target of interest. delete A computer-readable recording medium storing a program for executing the method for improving the target detection accuracy according to any one of claims 9 to 11 through execution by a processor.

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