KR100650518B1 - A specifying method and system for settling position of pru - Google Patents

Abstract

A method and a system for specifying the position of PRU(position reference unit) is provided to precisely specify position information of the position reference unit under a water level. The position of an antenna is measured, and the position of a signal transceiver is specified by using distance information between the antenna and the signal transceiver and posture information of a buoy(102). The distance between the signal transceiver and a signal receiving member is measured. The specifying step and the measuring step are repeated while the buoy is moved to at least three points. The position of a PRU(104) is trigonometrically measured based on the position information and the distance information. An error of the measured PRU position is eliminated.

Description

A SPECIFYING METHOD AND SYSTEM FOR SETTLING POSITION OF PRU}

1 is a schematic diagram for explaining specifying a dropping point of a PRU according to a preferred embodiment of the present invention.

2 is a view for explaining a specific configuration of the buoy shown in FIG.

FIG. 3 is a diagram for describing a detailed configuration of the PRU shown in FIG. 1.

4 is a block diagram illustrating a system for specifying a destination point of a PRU according to a preferred embodiment of the present invention.

5 is a view for explaining a change in the relative position of the GPS antenna and the signal transmitting means according to the buoy posture.

6 is a diagram for explaining triangulation of a PRU by multi-point positioning of buoys.

7 is a block diagram illustrating a propagation process of a position error.

FIG. 8 is a view for explaining an example of position error caused by DOP. FIG. 8A shows a good DOP, and FIG. 8B shows a bad DOP.

The present invention relates to an element technology for LBL, which is a system for specifying a position in the water based on three or more underwater acoustic distance measurement reference points. The present invention relates to a method and system for specifying a location of a PRU that measures a distance to a PRU equipped with signal receiving means, calculates an absolute position of a location reference point (PRU) by triangulation, and eliminates errors to specify a precise location.

The Long-Base Line (LBL) system measures at least three distances between the PRU (Position Reference Unit) and the signal transmission means attached to the buoy, etc. It refers to a system that specifies the location of signal transmission means through a technique. In order to use the LBL system, the position of the position reference point (PRU) needs to be known exactly. There are three conventional methods for knowing the position reference point (PRU).

First, after surveying the input position using the GPS in the vessel, it is a method to specify the position by fixing the pile (pile) to the sea floor vertically downward. Alternatively, assuming that the buoy is floating and the position reference point (PRU) is vertically downward, a method of specifying the horizontal position of the buoy as the horizontal position of the position reference point may be used. In addition, for large-scale operations such as oil well development, the use of equipment such as ultra short baseline (USBL) or super short baseline (SSBL) on board ships and GPS can be used to specify the location of the subsurface location reference point (PRU).

However, the method for knowing the position reference point (PRU) according to the conventional method described above, in the case of the first method, if the pile fixed to the sea bottom is not located exactly vertically below the ship which is the measurement point, the error of the position reference point (PRU) may be There is a problem that occurs up to m or more, and if you want to change the position of the position reference point, since the new pile must be fixed to the bottom continuously, additional cost is still required. In addition, in the case of the buoy-based method, since the buoy's motion is generated by the blue, many errors must be included in specifying the exact position of the position reference point (PRU), and the ultra short baseline (USBL) or SSBL ( Equipment such as super short baseline is very expensive, has a short base, accommodates relatively large errors, and is not easily available.

The present invention has been proposed to solve the problems of the prior art, and aims to precisely specify the position information of a position control point (PRU) under water when configuring an LBL system.

According to the present invention, the method for specifying the position of a PRU is characterized by (a) measuring the position of an antenna to specify the position of an under-sleep PRU equipped with a signal receiving means using a buoy on the surface equipped with an antenna and a signal transmitting means. (B) specifying the position of the signal transmitting means using length information between the antenna and the signal transmitting means and buoy posture information, (c) measuring the distance between the signal transmitting means and the signal receiving means, (d (B) repeating steps (b) and (c) while moving the buoy at least three points; (e) location information of the signal transmitting means at least three points and distance information of the signal transmitting means and the signal receiving means. Triangulating the position of the PRU based on the step of removing the error from the measured PRU position.

In this case, step (e) includes (e1) estimating a distance between any signal transmission means and a PRU, (e2) obtaining a location of the PRU using a least squares estimation method, and (e3) obtaining the location of the PRU. If the difference between the PRU and the previously obtained PRU is greater than the predetermined error limit, the obtained PRU is substituted into the step (e1), and the steps (e2) and (e3) are repeated. It is preferable to include calculating the position as a result. Also, in step (f), it is preferable to use the optimum smoother to remove the error, and in one embodiment, such an optimum smoother uses an extended Kalman filter as the front filter and a fixed interval optimal using the linearized Kalman filter as the rear filter. There may be a smoother.

The system for specifying the position of the under-sleep PRU equipped with the signal receiving means using the buoy on the surface equipped with the signal transmitting means according to the present invention includes a position measuring unit for measuring the position of the buoy, and an inclination for measuring the posture of the buoy. Measuring means having a measuring unit, analysis means for specifying the position of the signal transmitting means at least three points or more based on the positional information and attitude information input from the measuring means, positional information of the signal transmitting means at least three points and And a calculation means for triangulating the position of the PRU based on the distance information between the signal transmission means and the signal reception means measured at least three points, and removing the error from the measured PRU position.

At this time, it is preferable that the position measuring part uses RTK-DGPS, and it is preferable that the inclination measuring part is an attitude measuring sensor.

Further, the calculating means includes a distance converting unit for calculating a distance between the signal transmitting means and the signal receiving means at least three points, the distance information calculated by the distance converting unit, and the positional information of the signal transmitting means at least three points or more. It is preferable to have a triangulation operation unit for triangulating the position of the PRU by using an indirect feedback least squares estimation method, and an error removal unit for eliminating an error using an optimal smoother at the position of the measured PRU. Such calculation means may further include an error analysis unit for analyzing the positional error of the PRU with the known position information of the PRU.

The present invention is equipped with a real-time Kinematic Differential Global Positioning System (RTK-DGPS) processing equipment, which is a precision satellite navigation system, buoys located on the water surface, and the kinematic conditions between the GPS antenna and the signal transmission means are inclinometer and azimuth system, etc. Through precise measurement through to determine the position of the signal transmission means in and out 3cm. The sound signal transmitting means mounted on the buoy thus designed is moved to three or more positions on the surface of the water to measure the distance to the PRU, and then triangulate the position of the PRU. Since the position result of the geodetic PRU includes an error derived from an acoustic signal and a buoy's motion due to a wave, such an error is eliminated by using an optimal smoothing technique to remove the position error. The present invention provides a mechanism and method that can precisely specify the location of the PRU.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the following embodiments are provided to those skilled in the art to fully understand the present invention, and may be modified in various forms, and the scope of the present invention is described in the following embodiments. It is not limited.

(Example)

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a schematic diagram for explaining specifying a dropping point of a PRU according to a preferred embodiment of the present invention. Referring to FIG. 1, a system for specifying a dropping point of a PRU includes a host computer 100, a buoy 102 connected by wire to the host computer 100, and a PRU 104 located at the sea bottom. The buoy 102 moves more than three points from the water surface as shown in FIG. 1 and measures the distance to the PRU 104 at the bottom. The host computer 100 then determines the absolute position of the PRU 104 using a triangulation technique based on the measured distance information between the buoy 102 and the PRU 104 and the location information of the buoy 102. However, in the case of using the acoustic signal, since the position information of the geodetic PRU includes an error in the acoustic signal due to the error and the buoy motion caused by the blue wave, the precise position of the PRU 104 may be specified through the error elimination process. It becomes possible.

2 is a view for explaining a specific configuration of the buoy shown in FIG. 2, the buoy 102 is connected to a GPS antenna 200 and a GPS antenna 200 for receiving a carrier phase correction signal from a GPS satellite, a lighthouse at a port, or a DGPS correction station on a coast, and receives position compensation information. The analog signal is collected by collecting the RTK-DGPS board 204, the posture sensor 202 for measuring the position of the buoy, and the RTK-DGPS board 204 and the posture measuring sensor 202. DSP (206) for converting (absolute position and azimuth angle of GPS antenna, horizontal yaw and longitudinal angle of buoy, etc.) into digital signal and analyzing it according to the digital measurement signal and user setting condition to calculate absolute position of signal transmission means And a signal transmitter 210 for mounting an acoustic signal to the PRU 104 at the bottom of the buoy, and a battery 208. The signal transmitting unit 210 may be implemented by a pinger.

FIG. 3 is a diagram for describing a detailed configuration of the PRU shown in FIG. 1. The PRU 104 is disposed as a location reference point at a specific location under the water or at the bottom. This PRU 104 is composed of a weight (300) as a center of gravity and the signal receiving means 302 as shown in FIG. The signal receiving means 302 may be implemented as a transceiver, and preferably includes a signal amplifier.

As described above, the position specifying system of the PRU according to the present invention uses the GPS antenna 200 mounted on the buoy, as shown in FIG. 5, between the GPS antenna 200 and the signal transmitting means 210. By precisely measuring the kinematic conditions through an inclinometer, azimuth system, etc., the position of the signal transmission means 210 is precisely measured. In addition, the buoy 102 on which the signal transmission means 210 is mounted is moved to three or more positions on the water surface to measure the distance to the PRU. Distance measurement to the PRU is performed by the signal transmitting means 210 when the signal transmitting means 210 emits an acoustic signal underwater, and the signal receiving means 302 receives it and transmits it to the host computer 100 again. The host computer 100 uses a signal between the signal transmitting means 210 and the signal receiving means 302 at three or more points, and based on the time information between the two signals, The distance information between the signal receiving means 302 is extracted. The host computer 100 then triangulates the location of the PRU based on the distance information. Since the position result of the geodetic PRU includes errors derived from the acoustic signal and the buoy's motion due to the blue wave, it is necessary to remove these errors by using an optimal smoothing technique to remove such position errors.

Hereinafter, a location specifying system of the PRU according to the present invention and a location specifying method performed therein will be described in more detail.

4 is a block diagram illustrating a system for specifying a destination point of a PRU according to a preferred embodiment of the present invention. The fall point specifying system of the PRU includes a measuring means 400, an analyzing means 410, and a calculating means 420.

First, the measuring means 400 is mounted to the buoy 102, and consists of a position measuring unit 402 and the inclination measuring unit 404, the position measuring unit 402 is the GPS antenna 200 and RTK- of FIG. The DGPS board 204 may be implemented, and the tilt measurement unit 404 may be implemented by the posture measurement sensor 202. The position measuring unit 402 sends the latitude, longitude, altitude information and nose angle information to the analyzing means 410 in real time, and the inclination measuring unit 404 sends the information about the buoy's posture to the analyzing means 410 in real time. Will be entered.

Next, the analysis means 410 is also attached to the buoy 102, and consists of an A / D conversion unit 412, a posture analysis unit 414, and a position analysis unit 416. The A / D converter 412, the attitude analyzer 414, and the position analyzer 416 may be implemented by the DSP 206 of FIG. 2. The A / D converter 412 functions to convert analog signals sent from the position measuring unit 402 and the tilt measuring unit 404 of the measuring unit 400 into digital signals. The posture analyzing unit 414 and the position analyzing unit 416 calculate buoys, that is, positional information of the signal transmitting unit, in consideration of posture buoy information based on the information transmitted from the A / D converter 412. Since buoys move at three or more points for triangulation, the position information calculation is repeated several times for each point.

The computing means 420 is implemented by the host computer 100 of FIG. 1, and includes a distance calculator 422, a triangulation calculator 424, an error remover 426, and an error analyzer 428. . The distance conversion unit 422 is based on the time information until the signal emitted from the signal transmitting means 210 of the buoy 102 to the signal receiving means 302 of the PRU 104, the signal transmitting means 210 ) And the distance information between the signal receiving means 302 is extracted. The triangulation calculation unit 424 is a signal transmitting means at three or more positions input from the position analysis unit 416 and the distance information between the signal transmitting means and the signal receiving means at three or more positions inputted from the distance converting unit 422. Triangulate the location of the PRU using the location information. The error remover 426 removes the error component of the sound signal and the error component due to the blue wave by using an optimal smoothing technique, and the error analyzer 428 analyzes the error according to the measurement position of the buoy on the surface of the water. .

In this case, the triangulation performed by the triangulation calculator 424 uses a least square method using an indirect feedback state variable. 6 is a view for explaining triangulation of a PRU by multi-point positioning of buoys. The calculation process of triangulation using least square method using indirect feedback state variables is as follows.

The relationship between the distance measurement value between the PRU and the signal transmission means and the PRU is as follows.

[x _i y _i z _i ] ^T : Position of the i th PRU in the Cartesian coordinate system

u = [x _u y _u z _u ] ^T : Position of signal transmission means in Cartesian coordinate system

The distance information measured by the PRU and the signal transmission means is a measurement including noise. When the distance measurement value is accurate in the three-dimensional space, the position between the three position reference points and the signal transmission means is squared on both sides of Equation 1, and the sides are arranged to obtain a closed solution. In general, however, closed-circuit solutions cannot be obtained because the distance measurements contain errors. In order to reduce the error included in the measured values, more than four measured values may be used. In this case, the least squares estimation method using a line of sight vector may be used to obtain a position. In the present invention, this is modeled as "ρ _i = r _i + v". Where ρ _i denotes the distance information obtained in the i th performance, r denotes the distance between the position reference point (PRU) and the i th transmission means position that does not include the actual error, and v denotes random noise. In the present invention, a method of ignoring an error included in a measurement value, calculating a location using a least square estimator (LSE), and then removing the error component by indirectly feedbacking the calculated location information. Use

에서 ρ_i를 테일러 급수로 전개하면 다음과 같다.The location of the location control point (PRU) estimated in the previous step

Expanding ρ _i to the Taylor series at

는

을 이용하여 계산된 PRU와 신호 송신수단 사이의 거리이며, 수학식 2에서 2차항 이상을 무시하고 n개의 신호 송신수단의 위치에 대하여 전개하면 다음과 같은 선형화된 측정식을 얻을 수 있다.here

Is

It is the distance between the PRU and the signal transmitting means calculated using the equation, and the linearized measurement equation can be obtained by ignoring the quadratic term or more in Equation 2 and expanding the position of the n signal transmitting means.

Where h _i is the gaze vector between the position of the i-th signal transmission means and the PRU and is as follows.

Using Equation 3, the position of the position reference point can be obtained as follows, and this process is repeatedly performed to improve the accuracy.

The location of the location reference point PRU may be specified by the indirect feedback least squares estimation described above. However, due to the limitation of the least-squares estimation method, since a large amount of error still remains in the calculated position of the reference point (PRU), the present invention allows the specification of the position reference point (PRU) more accurately by using an optimal smoothing technique.

The position information obtained by the least-squares estimation method by the random error component included in the distance measurement process still includes the error component, which is assumed to be a random walk process. Therefore, the position error due to the random error can be plotted as shown in FIG.

The system is represented by the equation of continuous time differential equation (6).

Here, x, y and z are positional errors in the respective X, Y and Z directions.

In order to apply the above differential equation to the optimum smoother, it is expressed as a discrete time differential equation.

In addition, the observation model for the LBL system can be configured as follows. The observation formula subtracts the position information obtained through triangulation of the position estimated by the system, and removes the position error compensation process by multiplying the smoother gain. Rough As described above, the distance relation between the position reference point (PRU) and the i-th signal transmitting means is expressed by Equation 1 below.

는 i-번째 음향 송신수단 위치와 위치기준점(PRU)의 거리를 수학식 6을 이용하여 추정한 결과이다. 그리고 H_i는 관측식을 구성하는 i-번째 신호 송신수단 위치에 관한 수학식 3에서 얻은 행벡터를 의미하고, 마지막 V는 관측식에 포함된 백색 가우시안(Gaussian) 잡음을 의미한다.Where ρ _i is the distance of the position reference point (PRU) measured from the position of the i-th transmission means,

Is a result of estimating the distance between the i-th sound transmitting means position and the position reference point (PRU) using Equation 6. H _i denotes a row vector obtained from Equation 3 regarding the position of the i-th signal transmitter constituting the observation equation, and the last V denotes white Gaussian noise included in the observation equation.

In the present invention, the LBL system modeled as described above is used to specify the exact position of the PRU through the process of filtering out the position error using the smoothing algorithm described below.

Smoothing technique in the present invention can be summarized as follows.

The basic concept of smoothing is to use state variable estimation at any point in time t _{k up} to subsequent measurements. The following two equations represent the difference between a Kalman filter and a smoother.

Here, Z _k = {z ₁ , z ₁ , ..., z ₁ } means all measurements up to the kth.

를 추정하기 위하여 이후의 측정치를 사용하기 때문에 실시간으로 스무딩 기법을 적용하기는 사실상 불가능하나, 본 발명과 같이 먼저 거리 정보를 계측한 후 PRU의 위치 정보를 후처리하여 얻는 경우 상기 수학식 10과 같은 구성이 가능하고, 이를 이용하면 추정 정밀도가 향상된다. 따라서 본 발명에서 사용할 고정 구간 스무더에 관한 내용을 아래와 같이 기술한다.In equation (10)

It is virtually impossible to apply the smoothing technique in real time because the following measurement values are used to estimate. However, when the distance information of the PRU is measured after the distance information is first obtained, as shown in Equation 10, It is possible to configure, and using this improves the estimation accuracy. Therefore, a description of the fixed section smoother to be used in the present invention as follows.

In the present invention, the system related to the position error of the PRU's position specifying system is considered as a linear system. However, since the distance relation between the PRU and the signal transmitting means is nonlinear, the following indirect feedback nonlinear smoothing technique is used.

Among the various methods of implementing the smoother, the present invention takes a method consisting of two filters, a forward filter and a backward filter, as an embodiment, and the final smoothed using the outputs of the two filters. An optimum smoother having a structure for calculating the state variable estimate is described as follows. Since the position-specific system is a nonlinear system, a general extended Kalman Filter algorithm is used as a front filter, and a linearized Kalman filter algorithm is used as a linearization reference point based on the position information calculated by the front filter. The result is described as follows.

The forward filter to be used for nonlinear smoothing uses the result as it is because the filter variable of the Extended Kalman filter is implemented as a state variable error. The rear filter is used to correct the error of the state variable and the result is as follows.

를 노미널(nominal) 상태 변수 x_n과 교란된(perturbed) 양

로 분리하여 정리한 것이다. 만일, 수학식 11에서, x_n(τ)로 전방 필터 결과인

를 사용하고, 수학식 13을 이용하여 정리하면 다음과 같이

에 대한 식을 얻을 수 있다.here,

Is the amount perturbed with the nominal state variable x _n

It is separated and organized as. In Equation (11), x _n (τ) is the forward filter result.

If you use the following equation (13),

You can get the expression for.

The propagation for the covariance matrix is

는 전방 필터의 추정치를 기준 궤적으로 사용할 때, 다음과 같이 나타낼 수 있다.The update by the measurement can be obtained by using the relationship between the front filter and the rear filter at the time of the measurement. In particular, it should be noted that the rear filter uses the estimate of the front filter as a reference trajectory for linearization. Updated estimate of the back filter

When using the estimated value of the forward filter as a reference trajectory, can be expressed as follows.

는 상태변수에서 교란 값으로 우리가 사용할 후방 필터의 필터 상태변수를 나타낸다.here

Denotes the filter state variable of the rear filter we will use as a disturbance value in the state variable.

Equation 14 can be arranged as follows using Equation 15.

이다.here,

to be.

에 대한 관계식을 유도하면 다음과 같다.From the above equation

If we derive the relation for,

The update equation for the covariance matrix of the state variable uses Equation 18.

The algorithm for the derived rear filters is as follows.

를 추정한 후 이 결과를 전방 필터 추정치인

와 결합하는 스무딩 알고리즘은 다음과 같다.In the same way as above

After estimating the

The smoothing algorithm combined with

이다.here

to be.

For reference, the linearized Kalman filter and the extended Kalman filter used in the present invention are as follows.

The linearized Kalman filter is used when a reference trajectory is given to estimate the state variables of a nonlinear system.

Assume the system and measurement model is as follows.

를 추정한 후 상태변수 추정치

는 다음과 같이 계산한다.Error from filter

Estimate of state variables

Calculate as

Initial conditions and assumptions:

Propagation:

Update: t = t ⁺ _k

here,

를 초기치로 하여 다음과 같이 생성한다.The extended Kalman filter does not have a reference trajectory used to linearize a nonlinear system in advance, but generates a reference trajectory using the estimated state variable using the filter. The system model and the measurement model of the nonlinear system are assumed to be given by Equations (24) and (25). In the Extended Kalman filter, the reference trajectory is generated using the k th measurement at t _k ≤ t <t _{k + 1} .

Create an initial value as follows.

에 대한 오차 추정치 δ

는 칼만 필터가 최적 필터이기에 0(zero)이 된다.State Variables Estimated Using the kth Measurement

Error estimate for δ

Is zero because the Kalman filter is an optimal filter.

Therefore, the propagation equation for the state variable error at t _k ≤ t <t _{k + 1} is as follows.

From the above equation, it can be seen that when the indirect feedback method is used in the extended Kalman filter algorithm, the propagation of the error is not necessary.

Initial Conditions and Assumptions:

Propagation: t ⁺ _k-1 ≤t <t ^- _k

here,

In other words, the extended Kalman filter derived so far has a structure very similar to the indirect feedback method used in nonlinear systems.

However, if the measurement point of the buoy on the water surface is actually poor, the error due to the geometric arrangement of the position reference point (PRU) and the signal transmission means mounted on the buoy is a main component of the error of the position-specific system provided by the present invention. A tool to analyze the dilution of precision (DOP) is described below.

FIG. 8 is a view for explaining an example of position error caused by DOP. FIG. 8A shows a good DOP, and FIG. 8B shows a bad DOP.

There can be various error factors of LBL. The error component according to the arrangement between the position reference point and the receiving means can be estimated as follows. For error analysis of LBL, covariance of error is derived. First, the measured value and the measurement error are as follows.

Therefore, the estimate of the location with noise is as follows.

If the mean of the noise is zero, the expected value of the position estimate is as follows.

Therefore, the covariance of the estimation error can be derived as follows using the above relationship.

If V = (H ^T H) ^-1 , position error, horizontal error, and vertical error due to the geometrical arrangement are obtained as follows.

In general, the above formula is referred to as the following terms.

That is, VDOP refers to the size of the position error component in the vertical direction according to the buoy's geometrical arrangement, HDOP refers to the position error component on the horizontal plane according to the buoy's geometrical arrangement, and PDOP refers to the size of the position error component in the three-dimensional space. . In other words, when measuring the distance to the PRU while moving the buoy, it is possible to increase the accuracy in specifying the position of the PRU by determining the measurement point so that the above-mentioned DOP as small as possible.

In the present invention, the location of the location reference point (PRU) of the LBL location specifying system is specified using the above-described process and method.

The location identification method and location identification system of the PRU according to the present invention enables the use of a mobile PRU using buoys, does not require additional pile installation cost for the installation of the PRU, and does not consider the point where the PRU falls off. After dropping in the sea, it is effective to obtain the exact location of the PRU. In addition, the present invention also provides an analysis tool of the error according to the measurement position of the buoy on the surface, thereby improving the position accuracy and reliability.

As mentioned above, although preferred embodiment of this invention was described in detail, this invention is not limited to the said embodiment, A various deformation | transformation by a person of ordinary skill in the art within the scope of the technical idea of this invention is carried out. This is possible.

Claims (9)

In the method of specifying the position of the sub-sleep PRU equipped with the signal receiving means using the buoy on the surface equipped with the antenna and the signal transmitting means, (a) measuring the position of the antenna; (b) specifying a position of the signal transmission means using length information between the antenna and the signal transmission means and attitude information of the buoy; (c) measuring a distance between the signal transmitting means and the signal receiving means; (d) repeating steps (b) and (c) while moving the buoy at least three points; (e) triangulating the position of the PRU based on the position information of the signal transmitting means and at least three points of distance information between the signal transmitting means and the signal receiving means; (f) removing the error in the surveyed PRU location. The method of claim 1, wherein the antenna is a GPS antenna. The method of claim 1, wherein step (e) (e1) estimating the distance between any signal transmitting means and the PRU; (e2) finding a location of the PRU using least squares estimation; (e3) If the difference between the position of the obtained PRU and the position of the previously obtained PRU is larger than the predetermined error limit, the positions of the obtained PRU are substituted into step (e1), and the steps (e2) and (e3) are repeated, and the predetermined error Calculating a position of the obtained PRU as a result when the limit is smaller than the limit. 2. The method of claim 1, wherein in step (f), the removal of errors uses an optimum smoother. In the system for specifying the position of the sub-sleep PRU equipped with the signal receiving means using the buoy on the surface equipped with the signal transmitting means, Measuring means having a position measuring unit for measuring the position of the buoy and an inclination measuring unit measuring the posture of the buoy; Analysis means for specifying the position of the signal transmitting means at least three points or more based on the positional information and the attitude information inputted from the measuring means; Triangulate the position of the PRU based on the positional information of the signal transmitting means at least three points and the distance information between the signal transmitting means and the signal receiving means measured at at least three points, and error in the measured PRU position. Position specifying system, characterized in that it comprises a calculation means for removing. The position specifying system according to claim 5, wherein the position measuring unit is an RTK-DGPS device. The position specifying system according to claim 5, wherein the inclination measuring unit is a posture measuring sensor. The method of claim 5, wherein the calculating means, A distance converting unit for calculating a distance between the signal transmitting means and the signal receiving means at least three points; A triangulation calculator configured to triangulate the position of the PRU using an indirect feedback least-squares estimation method based on the distance information calculated by the distance calculator and the position information of the signal transmitting means at least three points; And an error removal unit for canceling an error using an optimum smoother at the surveyed PRU location. The position specifying system according to claim 8, wherein the calculating means further comprises an error analyzing unit which analyzes a position error of the PRU having known position information of the PRU.

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