KR101760392B1 - Distributed mimo radar system and method of target position estimation thereof - Google Patents

Abstract

The present invention relates to a distributed MIMO radar system capable of estimating a precise target position by solving the nonlinearity problem of the TDOA information equation and a method of estimating its target position, Transmitter; And a plurality of receivers for receiving a signal transmitted from the plurality of transmitters and passing through a target and estimating a target position using Taylor linear approximation at an initial reference point of the target, A new target reference point that minimizes the absolute value of the equation based on the linear approximation error equation of the target position is updated to repeatedly perform the target position estimation by the Taylor linear approximation estimation technique.

Description

[0001] DISTRIBUTED MIMO RADAR SYSTEM AND METHOD OF TARGET POSITION ESTIMATION THEREOF [0002]

The present invention relates to a distributed MIMO radar system for estimating a target position in a distributed MIMO radar environment and a method for estimating a target position thereof.

A multi-input multi-output (MIMO) radar system can obtain a higher degree of freedom (DoF) than a conventional phased array radar (PAR) system using a plurality of transmitters and receivers. It has recently attracted attention from academia, showing the possibility of improving the performance of the radar system. Particularly, in the case of a distributed MIMO radar system, since a plurality of transmitters and receivers are distributedly arranged with respect to a target, it is suitable for target position estimation using spatial diversity.

Typical target estimation techniques (methods) of a conventional distributed MIMO radar system commonly use a method of estimating a target position using time difference of arrival (TDoA) information obtained from each receiver. At this time, since the equation provided by the TDoA information has a nonlinear characteristic, it is difficult to estimate the target position.

An example of the technique developed to solve the nonlinearity problem of the TDoA information is a Taylor linear approximation estimation method using a Taylor linear approximation of the TDoA information equation. In the case of the Taylor linear approximation estimation method, an initial value should be set at the Taylor approximation. If the initial value is close to the actual target, a precise target position estimation result can be obtained. Otherwise, Occurs.

In order to solve the nonlinearity problem of TDoA information, another target position estimation technique is to construct a linear TDoA equation by assuming that a propagation delay time between each transmitter and receiver is provided, and then a Least Square (LS) estimation There is an LS technique that estimates the position of a target through a technique. Since the LS method can overcome the limitations of the Taylor approximation method because it can estimate the position without setting initial values, it is difficult to see that the nonlinearity problem of TDoA information is fundamentally solved It is true.

It is an object of the present invention to provide a distributed MIMO radar system and a method of estimating a target position thereof by solving the nonlinearity problem of the TDOA information equation to estimate a precise target position.

In order to achieve the above object, a distributed MIMO radar system according to an embodiment of the present invention is a distributed MIMO radar system in which a plurality of transmitters, a target, and a plurality of receivers are distributedly arranged in a two-dimensional plane, A plurality of transmitters for transmitting a transmission signal; And a plurality of receivers for receiving a signal transmitted from the plurality of transmitters and passing through a target and estimating a target position using Taylor linear approximation at an initial reference point of the target, A new target reference point which minimizes the absolute value of the equation based on the linear approximation error equation of the target position is updated and the target position estimation by the Taylor linear approximation estimation technique is repeatedly performed a predetermined number of times.

In an embodiment of the present invention, each receiver can derive a new target reference point that makes the one-way function zero by calculating a partial derivative of the formula from the defined linear approximation error equation to the target reference point.

In one embodiment of the present invention, the estimated target position is characterized by being closer to an actual target as the number of iterations increases.

According to another aspect of the present invention, there is provided a method for estimating a target position of a distributed MIMO radar system, the method comprising: receiving a signal transmitted from a plurality of transmitters via a target; Estimating a target position by applying Taylor linear approximation to the received signal at an initial reference point of the target; Defining a linear approximation error equation of the estimated target position; Deriving and updating a new target reference point that minimizes the absolute value of the linear approximation error equation defined above; And repeatedly performing a target position estimation using the Taylor linear approximation estimation technique at the updated new target reference point.

In one embodiment of the present invention, the step of deriving the new target reference point may include calculating a partial derivative of a target reference point in an equation obtained by squaring the defined linear approximation error equation; And deriving a new target reference point that makes the calculated one-way function zero.

In an embodiment of the present invention, the target position estimation is repeatedly performed a predetermined number of times, and the estimated target position is closer to the actual target as the number of repetitions increases.

In one embodiment of the present invention, estimating the target position includes estimating a propagation delay time of a received signal using a maximum likelihood estimation technique; Deriving a linear approximation equation for the estimated propagation delay time using Taylor linear approximation at an initial reference point; Deriving a linear approximation equation of the derived propagation delay time as a determinant for all transmitters and receivers; And estimating a target position by applying a least squares estimation technique to the determinant of the derived linear approximation equation.

In the distributed MIMO radar system, a new target reference point is updated, and the Taylor approximation equation close to the position of the target is tracked through repetitive calculation, thereby providing a precise target position. Thus, TDoA information The nonlinearity problem of the equation can be solved.

1 is a configuration diagram of a distributed MIMO radar system according to an embodiment of the present invention;
FIG. 2 is a flowchart showing a method of estimating a target through repetitive calculation in a distributed MIMO radar system according to the present invention. FIG.
FIG. 3 is a diagram comparing the estimation results of the estimated mean square error (MSE) estimation technique of the conventional Taylor linear approximation estimation technique with the target estimation technique through the iterative calculation proposed in the present invention.

The embodiments of the present invention can be modified into various forms and the scope of the present invention should not be interpreted as being limited by the embodiments described below. All terms including technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

The present invention relates to a technique of estimating a position of a target using TDoA information in a distributed MIMO radar environment, and iteratively estimates Taylor approximation equation close to the position of the target, thereby providing a precise target position We propose a method to solve the nonlinearity problem of time difference of arrival (TDoA) information equation.

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

FIG. 1 is a schematic block diagram of a distributed MIMO radar system according to an embodiment of the present invention, and FIG. 2 is a flowchart illustrating a target estimation method using an iterative operation in a distributed MIMO radar system according to the present invention.

에 위치하고, 상기 N개의 수신기는

에 위치하며, 상기 표적은

에 각각 위치한다. 이후 기재 순서와 상관없이 k는 송신기의 색인을 지칭하고,

은 수신기의 색인을 지칭한다. Referring to FIG. 1, a distributed MIMO radar system according to the present invention includes M transmitters, N receivers, and targets randomly distributed in a two-dimensional plane. At this time, the M transmitters

And the N receivers are located at

, And the target

Respectively. Regardless of the order in which they appear, k refers to the index of the transmitter,

Quot; refers to the index of the receiver.

를 각각 표적으로 전송하면, 해당 신호는 표적을 경유하여 수신기에 도달한다(S10). 이때

번째 수신기에서 수신된 신호는 다음의 수학식 1과 같이 나타낼 수 있다. As shown in FIG. 2 in the above-described distributed configuration, when a plurality of transmitters are orthogonal to each other,

To the target, the corresponding signal reaches the receiver via the target (S10). At this time

Th receiver can be expressed by Equation (1). &Quot; (1) "

[Equation 1]

는 반송 주파수,

는 표적의 RCS(Radar Cross Section)에 비례하는 복소 진폭을 의미하고,

는

번째 수신기에서 발생하는 백색 가우시안(Zero Mean White Gaussian) 잡음을 의미한다. 상기 수학식 1에서

는 송신신호가 k번째 송신기로부터 표적을 경유하여

번째 수신기까지지 도달하는데 소요되는 전파 지연시간으로 다음의 수학식 2와 같이 나타낼 수 있다. here

Lt; RTI ID = 0.0 >

Means the complex amplitude proportional to the RCS (Radar Cross Section) of the target,

The

(Zero Mean White Gaussian) noise generated in the first receiver. In Equation (1)

Lt; RTI ID = 0.0 > k < / RTI >

Th receiver, and can be expressed by Equation (2) below.

&Quot; (2) "

Where c is the speed of light.

)을 추정하는 과정은 널리 알려져 있는 기본적인 기술이므로 본 발명에서는 이를 생략하고 MLE를 통해

가 추정되었고, 수학식 1에서 확인할 수 있는 백색 가우시안 잡음(

)으로 인한 추정 에러

가 발생하였다고 가정하고 진행한다(S11). 따라서, 추정된 전파 지연시간을

라고 정의하면 다음의 수학식 3과 같이 나타낼 수 있다. From Equation (1), the maximum likelihood estimation (MLE)

) Is a well-known basic technique. Therefore, in the present invention,

And the white Gaussian noise (1), which can be seen in Equation (1)

)

(S11). Therefore, the estimated propagation delay time is

Can be expressed as Equation (3). &Quot; (3) "

&Quot; (3) "

에서 테일러 선형 근사를 이용하여 수학식 4와 같이 상기 추정된 전파 지연시간(

)에 대한 선형 근사 방정식을 구한다.Since Equation (3) does not have the form of a linear equation for the positions x and y of the target, the position of the target can not be estimated by a general estimation technique. Therefore,

The estimated propagation delay time (t) is calculated using the Taylor linear approximation in Equation (4)

) Is obtained from the linear approximation equation.

&Quot; (4) "

,

및

는 수학식 3의 테일러 선형 근사 결과로 계산될 수 있으며 각각 수학식 5와 같다.In the linear approximate equation of the equation (4)

,

And

Can be calculated as the Taylor linear approximation result of Equation (3), and are expressed by Equation (5), respectively.

&Quot; (5) "

가 표적의 위치와 다를 경우 선형 근사 오차로 인하여 정밀한 추정이 불가능하다. Since Equation (4) is a linear equation, it is possible to perform target estimation using the existing estimation technique,

Is different from the position of the target, precise estimation is impossible due to the linear approximation error.

)의 선형 근사 방정식의 선형 근사 오차를 계산하고 오차를 최소화할 수 있는 새로운 기준점을 업데이트하여 반복 연산해줌으로써 표적의 위치를 추적하는 방안을 제안한다. 본 발명에서 제안하는 반복 연산 알고리즘은 도 2에 요약 명시된 과정 (S14~S19)을 따른다. Therefore, the present invention can be applied to the propagation delay time

We propose a method to track the position of a target by calculating the linear approximation error of the linear approximation equation of the linear approximation and updating the new reference point to minimize the error. The iterative calculation algorithm proposed in the present invention follows the procedures (S14 to S19) summarized in Fig.

로 설정될 수 있다. i번째 연산에서의 기준점을

라고 할 때, i번째 표적 위치 추정 결과를 얻기 위하여, 상기 수학식 4에 도시된 전파 지연시간 (

)의 선형 근사 방정식을 모든 송·수신기에 대하여 다음 수학식 6과 같이 행렬식으로 나타낸다.As shown in FIG. 2, first, the receiver sets an initial reference point (value) in order to update the reference point and repeat the calculation (S12). In one embodiment, the initial reference point (value)

Lt; / RTI > The reference point in the i-th operation

, To obtain the i-th target position estimation result, the propagation delay time (

) Is expressed by a matrix formula for all transmitters and receivers as shown in Equation (6). &Quot; (6) "

&Quot; (6) "

라고 할 때

이고,

이다. 또한 시스템 행렬

는 수학식 7과 같이 정의한다 (S13).In Equation (6)

When

ego,

to be. Also,

Is defined as Equation (7) (S13).

&Quot; (7) "

Therefore, by applying a Least Square (LS) estimation method to the determinant of the linear approximation equation shown in Equation (6), the estimation result of the i-th target position can be obtained as shown in Equation (8).

&Quot; (8) "

Next, it is checked whether i is greater than the number of repetitions of operation P (S15). If it is small, a linear approximation error is defined with respect to the estimation result of the i-th target position as shown in equation (9) .

&Quot; (9) "

를 찾기 위해, 아래의 수학식 10과 같이 상기 수학식 9를 제곱한 수식의

에 대한 편도함수를 계산하고, 그것을 0으로 만드는

를 찾는다.The absolute value of the linear approximation error equation defined by Equation (9) is minimized

The following equation (10) is used to find the equation

To calculate the one-way function for < RTI ID = 0.0 >

.

&Quot; (10) "

)을 다음 수학식 11과 같이 구한 후, 해당 기준점을 다음 연산을 위하여 업데이트한다(S16). That is, a new (i + 1) th reference point (

Is calculated as shown in the following Equation 11, and the corresponding reference point is updated for the next operation (S16).

&Quot; (11) "

를 얻을 수 있다(S17).Therefore, the present invention can obtain the estimated value of the target position closer to the actual target than before by performing the above-described operations (S13 to S14) using the (i + 1) th reference point obtained through the equation (11) If all of the P iterative operations are performed, the result of the target position estimation using the iterative calculation proposed in the present invention as shown in the following Equation (12)

(S17).

&Quot; (12) "

FIG. 3 is a graph showing a comparison of estimated mean square error (MSE) of the conventional iterative linear approximation estimation technique and the iterative operation estimation technique proposed in the present invention.

As shown in FIG. 3, the performance of the estimation result of the target position obtained through the iterative calculation and the estimation result of the target position obtained by the conventional Taylor linear approximation estimation technique depending on the initial reference value is compared In order to simulate the distance error between the initial reference value and the actual target versus the estimated result.

As can be seen from FIG. 3, as the initial reference value becomes farther away from the actual target, the conventional Taylor linear approximation estimation technique increases the distance error, whereas the iterative calculation estimation technique of the present invention shows that the distance error hardly increases have.

As described above, the present invention derives the estimation result of the target position using the Taylor linear approximation estimation technique at the initial reference point (value) in the distributed MIMO radar system, A new reference point that can minimize the approximation error is updated and updated, and an operation of deriving the estimation result of the target position using the Taylor linear approximation estimation technique at the updated new reference point (value) is repeated by a predetermined number (P) .

Accordingly, the present invention easily tracks the nonlinearity problem of the TDoA information equation which has not been overcome by existing technologies by tracking the Taylor approximation equation close to the position of the target through repetitive computation by updating the reference point and providing the position of the precise target through the Taylor approximation equation There is an effect that can be.

The present invention described above can be embodied as computer-readable codes on a medium on which a program is recorded. The computer readable medium includes all kinds of recording devices in which data that can be read by a computer system is stored. In addition, the computer may include a control unit. Accordingly, the above description should not be construed in a limiting sense in all respects and should be considered illustrative. The scope of the present invention should be determined by rational interpretation of the appended claims, and all changes within the scope of equivalents of the present invention are included in the scope of the present invention.

Claims (8)

A distributed MIMO radar system in which a plurality of transmitters, a target, and a plurality of receivers are distributed on a two-dimensional plane,
A plurality of transmitters for transmitting a transmission signal orthogonal to the target; And
A plurality of receivers for receiving a signal transmitted from the plurality of transmitters and passing through a target and estimating a target position using Taylor linear approximation at an initial reference point of the target,
Each receiver
And a new target reference point that minimizes the absolute value of the equation based on the linear approximate error equation of the estimated target position is updated so that the target position estimation by the Taylor linear approximation estimation technique is repeatedly performed. Radar system. The receiver of claim 1, wherein each receiver
Wherein a new target reference point for deriving the one-way function to zero is calculated by calculating a one-way function for a target reference point in an equation obtained by squaring the defined linear approximation error equation. 2. The method of claim 1,
And the MIMO radar system is repeatedly performed a predetermined number of times. 2. The method of claim 1, wherein the estimated target position is
And as the number of repetitions increases, it becomes closer to an actual target. A method for estimating a target position in a distributed MIMO radar system in which a plurality of transmitters, a target, and a plurality of receivers are distributed on a two-dimensional plane,
Receiving signals transmitted from a plurality of transmitters via a target;
Estimating a target position by applying Taylor linear approximation to the received signal at an initial reference point of the target;
Defining a linear approximation error equation of the estimated target position;
Deriving and updating a new target reference point that minimizes the absolute value of the linear approximation error equation defined above; And
And repeatedly performing a target position estimation using the Taylor linear approximation estimation method at the updated new target reference point. 6. The method of claim 5, wherein deriving the new target reference point
Calculating a partial derivative of the linear approximation error equation with respect to a target reference point in an equation obtained by squaring the linear approximation error equation; And
And deriving a new target reference point that makes the calculated one way function zero. ≪ Desc / Clms Page number 19 > 6. The method of claim 5,
Is repeatedly performed a predetermined number of times,
Wherein the estimated target location is closer to an actual target as the number of iterations increases. ≪ Desc / Clms Page number 19 > 6. The method of claim 5, wherein estimating the target position comprises:
Estimating a propagation delay time of a received signal using a maximum likelihood estimation technique;
Deriving a linear approximation equation for the estimated propagation delay time using Taylor linear approximation at an initial reference point;
Deriving a linear approximation equation of the derived propagation delay time as a determinant for all transmitters and receivers; And
Estimating a target position by applying a least squares estimation technique to the determinant of the derived linear approximation equation; and estimating a target position by applying a least square estimation technique to the determinant of the derived linear approximation equation.

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