KR102363929B1 - Method of estimating position for SAR motion compensation, apparatus for estimating position for SAR motion compensation, and computer program for the method - Google Patents

Abstract

The present invention relates to a method for estimating a position for SAR motion compensation, a device for estimating a position and a computer program stored in a recording medium to perform the method. The method for estimating the position of a radar for obtaining an SAR image comprises the steps of: obtaining the state variables of the radar; calculating the estimated position of the radar using an estimation model including the preset gain coefficient of the radar based on the state variables; converting the estimation model and the estimated position into a Laplace area and substituting the estimated position of the Laplace area for the estimation model of the Laplace area to calculate an attenuation coefficient of the Laplace area for the estimated position; and estimating the position of the radar using the attenuation coefficient, wherein the state variables include the position data and velocity data of the radar. Provided are a method for estimating a position, a device for estimating a position and a computer program stored in a recording medium to perform the method.

Description

A position estimating method for SAR motion compensation, a position estimating apparatus, and a computer program stored in a recording medium for executing the method }

Embodiments of the present invention relate to a position estimation method for SAR fluctuation compensation, a position estimation apparatus, and a computer program stored in a recording medium for executing the method.

In general, SAR (synthetic aperture radar) oscillation compensation uses position information of a navigation sensor mounted on a platform (eg, aircraft or satellite) or radar. Such a navigation sensor is mainly composed of an inertial measurement unit (IMU) and a global positioning system (GPS), and the combined system is called an embedded GPS and IMU (EGI).

Although it is possible to perform SAR fluctuation compensation through the radar position information output from the EGI, there is an error in the output of the EGI due to the sensor error of the IMU and the GPS, making it difficult to accurately compensate the SAR fluctuation. As a solution to this problem, a method of using the result of integrating the velocity output of the EGI rather than using the position information of the radar directly is widely used. In this case, by integrating the speed, it is possible to attenuate the error of noise and discontinuity included in the EGI output, and it exhibits better vibration compensation performance than using the position information of the radar directly.

However, when only velocity integration is performed without using location information of the radar, since observability of a location is not secured, a linear error or a Wiener process error may occur. When SAR fluctuation compensation is performed with information including such an error, position distortion and resolution degradation of the final SAR image may occur.

An object of the present invention is to provide a position estimation method for SAR fluctuation compensation, a position estimation apparatus, and a computer program stored in a recording medium for executing the method. However, these problems are exemplary, and the scope of the present invention is not limited thereto.

According to one aspect of the present invention, in a method of estimating a position of a radar for acquiring a SAR image, the step of acquiring a state variable of the radar, an estimation model including a preset gain factor of the radar based on the state variable calculating the estimated position of the radar using There is provided a position estimation method comprising the steps of calculating an attenuation coefficient of , and estimating the position of the radar using the attenuation coefficient, wherein the state variable includes position data and velocity data of the radar.

The gain factor may be expressed as a matrix including two rows and two columns.

The estimation model may include a constant velocity equation and an error attenuation equation of the radar in 3D space.

The calculating of the estimated position of the radar may include calculating the estimated position by substituting the state variable into the estimated model.

Calculating the attenuation coefficient of the Laplace domain includes converting the equation of the estimation model into the Laplace domain, converting the equation of the estimated position into the Laplace domain, and converting the equation of the estimated position of the Laplace domain into the Laplace domain Calculating the estimated position equation of the Laplace region including the attenuation coefficient by substituting it into the equation of the estimated model, and calculating the attenuation coefficient with an equation for each parameter of the gain coefficient with respect to the estimated position equation. can do.

The attenuation coefficient may include a first attenuation coefficient and a second attenuation coefficient, the first attenuation coefficient may attenuate the position error of the radar, and the second attenuation coefficient may attenuate the speed error of the radar.

According to one aspect of the present invention, there is provided a computer program stored in a recording medium for executing the above-described method using a computer.

According to one aspect of the present invention, there is provided an apparatus for estimating a position of a radar for acquiring an SAR image, comprising a processor, wherein the processor acquires a state variable of the radar, and a preset of the radar based on the state variable calculating the estimated position of the radar using an estimation model including a gain factor, converting the estimated model and the estimated position into a Laplace domain, and substituting the estimated position of the Laplace domain into the estimated model of the Laplace domain, Calculating the attenuation coefficient of the Laplace region with respect to the estimated position, estimating the position of the radar using the attenuation coefficient, the state variable including position data and velocity data of the radar, a position estimation apparatus is provided .

The gain factor may be expressed as a matrix including two rows and two columns.

The estimation model may include a constant velocity equation and an error attenuation equation of the radar in 3D space.

The processor may calculate the estimated position by substituting the state variable into the estimation model.

The attenuation coefficient is calculated as a formula for each parameter of the gain factor with respect to the estimated position equation of the Laplace region, and the estimated position equation is obtained by substituting the equation of the estimated position of the Laplace region into the equation of the estimated model of the Laplace region. can be calculated.

The attenuation coefficient may include a first attenuation coefficient and a second attenuation coefficient, the first attenuation coefficient may attenuate the position error of the radar, and the second attenuation coefficient may attenuate the speed error of the radar.

Other aspects, features and advantages other than those described above will become apparent from the following detailed description, claims and drawings for carrying out the invention.

According to an embodiment of the present invention made as described above, a method for estimating a position of a radar capable of effectively performing SAR fluctuation compensation by attenuating an error of radar position information, a position estimating apparatus, and a recording medium to execute the method A stored computer program may be implemented. Of course, the scope of the present invention is not limited by these effects.

1 is a diagram for explaining the configuration and operation of a location estimation apparatus according to an embodiment of the present invention.
2 is a diagram for explaining a configuration of a processor of a location estimation apparatus according to an embodiment of the present invention.
3 is a flowchart illustrating a location estimation method according to an embodiment of the present invention.
4 and 5 are diagrams for explaining an effect of a location estimation method according to an embodiment of the present invention.

Since the present invention can apply various transformations and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. Effects and features of the present invention, and a method for achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various forms.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, and when described with reference to the drawings, the same or corresponding components are given the same reference numerals, and the overlapping description thereof will be omitted. .

In the following embodiments, terms such as first, second, etc. are used for the purpose of distinguishing one component from another without limiting the meaning. And singular expressions include plural expressions unless the context clearly dictates otherwise. In addition, the terms include or have means that a feature or element described in the specification is present, and does not exclude the possibility that one or more other features or elements may be added.

In the drawings, the size of the components may be exaggerated or reduced for convenience of description. For example, since the size and thickness of each component shown in the drawings are arbitrarily indicated for convenience of description, the present invention is not necessarily limited to the illustrated bar.

In the following embodiments, when it is said that a part such as a region, component, part, block or module is on or on another part, not only when it is directly on the other part, but also another region, component, part in the middle , blocks or modules are included. And when a region, component, part, block or module is connected, it is not only when the region, component, part, block or module is directly connected, but also another region in the middle of the region, component, part, block or module. , includes cases in which components, units, blocks or modules are interposed and indirectly connected.

Hereinafter, various embodiments of the present invention will be described in detail with reference to the accompanying drawings in order to enable those of ordinary skill in the art to easily practice the present invention.

FIG. 1 is a diagram for explaining the configuration and operation of a location estimation apparatus according to an embodiment of the present invention, and FIG. 2 is a diagram for explaining a processor configuration of a location estimation apparatus according to an embodiment of the present invention.

First, referring to FIG. 1 , an apparatus 100 for estimating a location according to an embodiment of the present invention may include a memory 110 , a processor 120 , a communication module 130 , and an input/output interface 140 . However, the present invention is not limited thereto, and the location estimation apparatus 100 may further include other components or some components may be omitted. Some components of the location estimation apparatus 100 may be divided into a plurality of devices, or a plurality of components may be merged into one device.

The location estimation apparatus 100 according to an embodiment of the present invention may be provided in the radar. For example, the location estimation apparatus 100 may be mounted on a radar of an aircraft or a satellite. However, the present invention is not limited thereto. Also, the location estimation apparatus 100 may receive location information of the radar output from an embedded GPS and IMU (EGI) mounted on the radar. Also, the location estimation apparatus 100 may receive speed information of the radar output from an embedded GPS and IMU (EGI) mounted on the radar. For example, location information and speed information of the radar may be expressed as data on a three-dimensional coordinate axis.

The location estimation apparatus 100 according to an embodiment of the present invention may estimate the location of the radar based on location information of the radar output from an embedded GPS and IMU (EGI). For example, the location estimation apparatus 100 may more accurately estimate the location of the radar by attenuating an error in location information of the radar output from the embedded GPS and IMU (EGI). Also, the position estimating apparatus 100 may perform SAR fluctuation compensation using the estimated position of the radar. Alternatively, the position estimating apparatus 100 may transmit the estimated radar position to an external device to perform SAR fluctuation compensation.

The memory 110 is a computer-readable recording medium and may include a random access memory (RAM), a read only memory (ROM), and a permanent mass storage device such as a disk drive. In addition, program codes and data for controlling the location estimation apparatus 100 may be temporarily or permanently stored in the memory 110 .

The processor 120 obtains a state variable of the radar, calculates an estimated position of the radar using an estimation model including a preset gain factor of the radar based on the state variable, and converts the estimated model and the estimated position into a Laplace domain And, by substituting the estimated position of the Laplace region into the estimation model of the Laplace region, the attenuation coefficient of the Laplace region with respect to the estimated position can be calculated, and the position of the radar can be estimated using the attenuation coefficient. For example, the state variable may include position data and velocity data of the radar.

The communication module 130 may provide a function for communicating with an external device through a network. For example, a request generated by the processor 120 of the location estimation apparatus 100 according to a program code stored in a recording device such as the memory 110 is transmitted to an external device through a network under the control of the communication module 130 . can Conversely, a control signal, command, or file provided under the control of the processor of the external device may be received by the location estimation apparatus 100 through the communication module 130 through the network. For example, a control signal or command of an external device received through the communication module 130 may be transmitted to the processor 120 or the memory 110 .

The communication method is not limited, and not only a communication method using a communication network (eg, a mobile communication network, a wired Internet, a wireless Internet, a broadcasting network) that the network may include, but also short-range wireless communication between devices may be included. For example, the network includes a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a broadband network (BBN), the Internet, and the like. may include any one or more of the networks of Further, the network may include, but is not limited to, any one or more of a network topology including, but not limited to, a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, and the like. .

Also, the communication module 130 may communicate with an external device through a network. Although the communication method is not limited, the network may be a local area wireless network. For example, the network may be a Bluetooth (Bluetooth), BLE (Bluetooth Low Energy), or Wifi communication network.

Also, the location estimation apparatus 100 according to the present invention may include an input/output interface 140 . The input/output interface 140 may be a means for an interface with an input/output device. For example, the input device may include a device such as a keyboard or mouse, and the output device may include a device such as a display for displaying a communication session of an application. As another example, the input/output interface 140 may be a means for an interface with a device in which functions for input and output are integrated into one, such as a touch screen. As a more specific example, the processor 120 of the location estimation apparatus 100 processes the command of the computer program loaded in the memory 110, and the service screen or content configured using the data provided by the external server is displayed on the input/output interface ( 140) may be displayed on the display.

Also, in other embodiments, the location estimation apparatus 100 may include more components than those of FIG. 1 . For example, it may be implemented to include at least a portion of the above-described input/output device, or may further include other components such as a battery and charging device for supplying power to internal components, various sensors, and a database.

Hereinafter, the internal configuration of the processor 120 of the location estimation apparatus 100 according to an embodiment of the present invention will be described in detail with reference to FIG. 2 . For ease of understanding, it is assumed that the processor 120 to be described later is the processor 120 of the location estimation apparatus 100 illustrated in FIG. 1 .

The processor 120 of the position estimation apparatus 100 according to an embodiment of the present invention includes a state variable acquirer 121 , an estimated position calculator 122 , an attenuation coefficient calculator 123 , and a position estimator 124 . ) is included. According to some embodiments, components of the processor 120 may be selectively included in or excluded from the processor 120 . In addition, according to some embodiments, the components of the processor 120 may be separated or combined to express the functions of the processor 120 .

The processor 120 and components of the processor 120 may control the location estimation apparatus 100 to perform steps S110 to S140 included in the location estimation method of FIG. 3 . For example, the processor 120 and components of the processor 120 may be implemented to execute instructions according to the code of the operating system included in the memory 110 and the code of at least one program. Here, the components of the processor 120 are representations of different functions of the processor 120 that are performed by the processor 120 according to an instruction provided by a program code stored in the location estimation apparatus 100 . can The internal configuration and specific operation of the processor 120 will be described with reference to the flowchart of the position estimation method of FIG. 3 .

3 is a flowchart illustrating a location estimation method according to an embodiment of the present invention.

In step S110, the processor may obtain a state variable of the radar. For example, the state variable may include position data and velocity data of the radar. In addition, the position data and the velocity data may be expressed as data for a three-dimensional coordinate axis. For example, the processor may receive position data and velocity data of the radar from a navigation sensor mounted on the radar or an integrated navigation system (EGI).

In step S120, the processor may calculate an estimated position of the radar using an estimation model including a preset gain factor of the radar based on the state variable of the radar. For example, the state variable of the radar may be expressed as a constant velocity equation as in Equation (1).

<Equation 1>

는 3차원 공간에서 i번째 축에 대한 레이다의 상태 변수를 나타내고,

는 3차원 공간에서 i번째 축에 대한 시스템 행렬을 나타내며 수학식2와 같이 정의될 수 있다.here,

represents the state variable of the radar on the i-th axis in the three-dimensional space,

denotes a system matrix for the i-th axis in a three-dimensional space and may be defined as in Equation (2).

<Equation 2>

는 i번째 축의 레이다의 위치를 나타내고,

는 i번째 축의 레이다의 속도를 나타낸다.here,

represents the position of the radar on the i-th axis,

represents the speed of the radar on the i-th axis.

The estimation model according to an embodiment of the present invention may be designed as in Equation (3).

<Equation 3>

는

의 추정치를 나타내고,

은 이득 계수를 나타낸다. 또한,

는 i번째 축의 상태 변수 측정치를 나타내고,

는 i번째 축의 측정 행렬을 나타내며 수학식4와 같이 정의될 수 있다. 예컨대, '추정치'는 본 발명에 따른 상태 변수의 추정값을 나타내고, '측정치'는 레이다에 탑재된 항법 센서 또는 복합항법장치(EGI)에서 측정된 상태 변수의 측정값을 나타낸다.Here, in addition to Equations 1 and 2,

Is

represents an estimate of

is the gain factor. also,

represents the state variable measurement on the i-th axis,

denotes the measurement matrix of the i-th axis and may be defined as in Equation (4). For example, 'estimated value' represents an estimated value of a state variable according to the present invention, and 'measured value' represents a measured value of a state variable measured by a navigation sensor mounted on a radar or an EGI.

<Equation 4>

는 i번째 축에 대한 레이다의 위치 측정치를 나타내고,

는 i번째 축에 대한 레이다의 속도 측정치를 나타낸다. 예를 들어, 이득 계수는 수학식5와 같이 2개의 행과 2개의 열을 포함하는 행렬로 표현될 수 있다. here,

represents the position measurement of the radar with respect to the i-th axis,

is the radar speed measurement for the i-axis. For example, the gain factor may be expressed as a matrix including two rows and two columns as shown in Equation (5).

<Equation 5>

Here, l ₁ to l ₄ represent a component of a gain factor.

이고, 오차 감쇄 방정식은

을 나타낼 수 있다. 즉, 본 발명의 일 실시예에 따른 추정 모델은 3차원 공간에 대한 레이다의 등속 방정식과 오차 감쇄 방정식의 합으로 이루어질 수 있다.In an embodiment of the present invention, the estimation model may include a constant velocity equation and an error attenuation equation of the radar in a three-dimensional space. For example, in Equation 3, the constant velocity equation is

and the error attenuation equation is

can indicate That is, the estimation model according to an embodiment of the present invention may be formed of the sum of the constant velocity equation of the radar in the three-dimensional space and the error attenuation equation.

In an embodiment of the present invention, the processor may calculate the estimated position of the radar by substituting the state variable of the radar into the estimation model. For example, the processor may calculate the estimated position of the radar by applying the position measurement data and the velocity measurement data of the radar to the estimation model.

<Equation 6>

는 레이다의 추정 위치를 나타낸다.here,

indicates the estimated position of the radar.

In step S130, the processor may convert the estimated model and the estimated position into a Laplace domain, and substitute the estimated position of the Laplace domain into the estimated model of the Laplace domain to calculate an attenuation coefficient of the Laplace domain with respect to the estimated position.

For example, the estimation model of Equation 3 may be transformed into a Laplace domain as shown in Equation 7. Specifically, the process of transforming Equation 3 into the s-domain through the Laplace transform is as follows. The left side of Equation 3 is converted to sX(s), and the right side of Equation 3 is converted to (A-LC)X(s) + LY(s), and if summarized as an expression for X(s), It can be expressed as the formula of the first line of Equation 7. In addition, since Y(s) is a Laplace transform of the measured state variable, if expressed as an equation for position and velocity with reference to equation 4, equation 7 can be transformed into an s-domain with respect to position and velocity, and finally X(s) can be expressed as a function of the damping factor and position and velocity.

<Equation 7>

In addition, when the estimated position of Equation 6 is converted into a Laplace domain and substituted into Equation 7, the equation of the Laplace domain for the estimated position can be calculated as shown in Equation 8.

<Equation 8>

는 제1 감쇄 계수를 나타내고,

는 제2 감쇄 계수를 나타낸다. 즉, 수학식8은 감쇄 계수를 포함하는 라플라스 영역의 추정 위치 방정식을 나타낼 수 있다. 예를 들어, 감쇄 계수는 제1 감쇄 계수 및 제2 감쇄 계수를 포함할 수 있다. 또한, 제1 감쇄 계수는 레이다의 위치 오차를 감쇄하고, 제2 감쇄 계수는 레이다의 속도 오차를 감쇄할 수 있다. 예컨대, 수학식8은 레이다의 위치 오차가 제1 감쇄 계수에 의하여 감쇄되고, 레이다의 속도 오차가 제2 감쇄 계수에 의하여 감쇄되는 것을 나타낸다.here,

represents the first attenuation coefficient,

denotes the second attenuation coefficient. That is, Equation 8 may represent the estimated position equation of the Laplace region including the attenuation coefficient. For example, the attenuation coefficient may include a first attenuation coefficient and a second attenuation coefficient. In addition, the first attenuation coefficient may attenuate the position error of the radar, and the second attenuation coefficient may attenuate the speed error of the radar. For example, Equation 8 indicates that the position error of the radar is attenuated by the first attenuation coefficient, and the speed error of the radar is attenuated by the second attenuation coefficient.

In an embodiment of the present invention, the processor may calculate the attenuation coefficient by using an equation for each parameter of the gain coefficient with respect to the estimated position equation. For example, the processor may represent the attenuation coefficient using Equation 7, Equation 8, and Equation 5.

<Equation 9>

는 제1 감쇄 계수를 나타내고,

는 제2 감쇄 계수를 나타낸다. 또한, 제1 감쇄 계수 및 제2 감쇄 계수는 각각 이득 계수의 각 파라미터(l₁ 내지 l₄)에 대한 수식으로 표현될 수 있다.here,

represents the first attenuation coefficient,

denotes the second attenuation coefficient. In addition, each of the first attenuation coefficient and the second attenuation coefficient may be expressed as a formula for each parameter ( l ₁ to l ₄ ) of the gain factor.

In step S140, the processor may estimate the position of the radar using the attenuation coefficient. For example, referring to Equation 9, the processor according to an embodiment of the present invention adjusts the gain factor L of Equation 3 to obtain poles and zeros of dynamics for position and velocity errors. (zero) can be set to any desired value. Therefore, according to the present invention, the optimal SAR fluctuation compensation performance can be exhibited by the user setting an appropriate value according to the platform (eg, aircraft or satellite) environment and the autofocus algorithm condition.

The method for estimating position according to an embodiment of the present invention includes the steps of determining a first attenuation coefficient and a second attenuation coefficient of Equation 9, determining a gain factor using Equation 9 and Equation 5, Equation 3 The method may include estimating state variables (eg, position and velocity) of the radar using Equation 6, and outputting the estimated position of the radar using Equation (6). For example, the first attenuation coefficient and the second attenuation coefficient are transfer functions of the position and velocity errors, and the user can set the dynamics of the error output in an appropriate form according to the platform environment and autofocus algorithm conditions. Also, a gain factor that satisfies the first attenuation factor and the second attenuation factor set by the user may be set. In addition, the state variable of the radar can be estimated by applying the gain factor set through the above process to the estimation model of Equation (3). In addition, the estimated position of the radar output through Equation 6 may be used for SAR fluctuation compensation. However, the present invention is not limited thereto, and the order of the steps for estimating the location may be changed.

According to the present invention, there is an effect that more accurate SAR fluctuation compensation can be performed by correcting an error in a measurement position that occurs due to a sensor error of a conventional embedded GPS and IMU (EGI).

In addition, according to the present invention, by using the position information of the radar, an error that may occur when only speed integration is performed without using the position information of the radar does not occur. Therefore, according to the present invention, there is an effect of overcoming the position distortion and resolution degradation of the SAR image during SAR fluctuation compensation.

로 설정될 경우, 제1 감쇄 계수 및 제2 감쇄 계수는 수학식10과 같이 계산될 수 있다.In one embodiment of the present invention, each parameter of the gain factor is

When set to , the first attenuation coefficient and the second attenuation coefficient may be calculated as in Equation (10).

<Equation 10>

In this case, the cut-off frequency of the estimation model becomes w and is attenuated secondarily. According to the present invention, when autofocus is performed using a phase gradient autofocus (PGA) method, position errors in all frequency bands can be blocked by selecting an optimal w according to the PGA window condition. In addition, according to the present invention, it is possible to secure stability for all state variables, thereby preventing divergence of estimated positions due to bias. Accordingly, there is an effect of preventing position distortion and resolution degradation of the SAR image that may occur during SAR fluctuation compensation.

로 설정될 경우, 제1 감쇄 계수 및 제2 감쇄 계수는 수학식11과 같이 계산될 수 있다.In one embodiment of the present invention, each parameter of the gain factor is

When set to , the first attenuation coefficient and the second attenuation coefficient may be calculated as in Equation (11).

<Equation 11>

In this case, the estimated position of Equation (8) can be expressed as Equation (12).

<Equation 12>

Equation 12 shows the same result as the position estimation of the conventional velocity integration method. That is, it can be seen that the position estimation method of the present invention is a position estimation method that additionally performs error attenuation in addition to the position estimation of the conventional velocity integration method through setting of an attenuation coefficient.

In an embodiment of the present invention, each parameter of the gain factor may be set to a Kalman-bucy filter gain obtained by Algebraic Riccati Equation (ARE). In this case, the position estimation method of the present invention can show optimal performance for position and velocity errors having a Gaussian normal distribution.

4 and 5 are diagrams for explaining an effect of a location estimation method according to an embodiment of the present invention.

First, FIG. 4 shows the SAR image after SAR fluctuation compensation through the conventional velocity integration method of estimating the position of the radar. In addition, Figure 5 shows the SAR image after SAR fluctuation compensation through the position estimation of the radar according to the present invention.

In FIG. 4 , the position of the SAR image is distorted and the resolution is lowered, but in FIG. 5 , it can be seen that the position error of the SAR image is corrected and the resolution is not lowered compared to that of FIG. 4 .

The method for estimating position according to an embodiment of the present invention may attenuate errors of an output of an embedded GPS and IMU (EGI) up to a frequency band desired by a user by adjusting a gain coefficient of the estimation model. Therefore, according to the present invention, SAR fluctuation compensation for all frequency bands is possible in conjunction with the PGA technique. In addition, by ensuring the observability of the position, the convergence of the position error is ensured, and thus, it is possible to prevent the distortion of the position of the SAR image and the decrease in resolution, which are problems of the existing widely used velocity integration method.

The apparatus and/or system described above may be implemented as a hardware component, a software component, and/or a combination of the hardware component and the software component. The devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU). It may be implemented using one or more general purpose or special purpose computers, such as a logic unit, microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The software may include a computer program, code, instructions, or a combination of one or more thereof, which configures the processing device to operate as desired or, independently or collectively, the processing device can be ordered. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or apparatus, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with reference to the limited embodiments and drawings, various modifications and variations are possible from the above description by those skilled in the art. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

100: location estimation device
110: memory
120: processor
130: communication module
140: input/output interface

Claims (13)

A method for estimating a location of a radar for acquiring a SAR image, the method comprising:
obtaining a state variable of the radar;
calculating an estimated position of the radar using an estimation model including a preset gain factor of the radar based on the state variable;
converting the estimated model and the estimated position into a Laplace domain, and substituting the estimated position of the Laplace domain into the estimated model of the Laplace domain to calculate an attenuation coefficient of the Laplace domain with respect to the estimated position; and
estimating the position of the radar using the attenuation coefficient;
including,
The state variable includes position data and velocity data of the radar. According to claim 1,
wherein the gain factor is expressed as a matrix including two rows and two columns. According to claim 1,
The estimation model includes a constant velocity equation and an error attenuation equation of the radar in a three-dimensional space. According to claim 1,
The calculating of the estimated position of the radar may include calculating the estimated position by substituting the state variable into the estimation model. According to claim 1,
Calculating the attenuation coefficient of the Laplace region comprises:
transforming the equation of the estimation model into a Laplace domain;
transforming the equation of the estimated position into a Laplace domain;
calculating an estimated position equation of the Laplace region including an attenuation coefficient by substituting the equation of the estimated position of the Laplace region into the equation of the estimated model of the Laplace region; and
calculating the attenuation coefficient as a formula for each parameter of the gain coefficient with respect to the estimated position equation;
A method of estimating a location, comprising: According to claim 1,
The attenuation coefficient includes a first attenuation coefficient and a second attenuation coefficient,
The first attenuation coefficient attenuates the position error of the radar, and the second attenuation coefficient attenuates the speed error of the radar. A computer program stored in a recording medium for executing the method of any one of claims 1 to 6 using a computing device. In the radar position estimation apparatus for acquiring the SAR image,
processor; including;
The processor obtains a state variable of the radar, calculates an estimated position of the radar using an estimated model including a preset gain factor of the radar based on the state variable, the estimated model and the estimated position is converted into a Laplace domain, the estimated position of the Laplace domain is substituted into the estimated model of the Laplace domain, an attenuation coefficient of the Laplace domain for the estimated position is calculated, and the position of the radar is estimated using the attenuation factor and,
The state variable includes position data and velocity data of the radar. 9. The method of claim 8,
The gain factor is expressed as a matrix including two rows and two columns. 9. The method of claim 8,
The estimation model includes a constant velocity equation and an error attenuation equation of the radar with respect to a three-dimensional space. 9. The method of claim 8,
and the processor calculates the estimated position by substituting the state variable into the estimation model. 9. The method of claim 8,
The attenuation coefficient is calculated as a formula for each parameter of the gain coefficient with respect to the estimated position equation of the Laplace domain,
The estimated position equation is calculated by substituting the equation of the estimated position of the Laplace region into the equation of the estimated model of the Laplace region. 9. The method of claim 8,
The attenuation coefficient includes a first attenuation coefficient and a second attenuation coefficient,
The first attenuation coefficient attenuates the position error of the radar, and the second attenuation coefficient attenuates the speed error of the radar.

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