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

Distributed mimo radar system and method of target position estimation thereof Download PDF

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KR101760392B1
KR101760392B1 KR1020160051777A KR20160051777A KR101760392B1 KR 101760392 B1 KR101760392 B1 KR 101760392B1 KR 1020160051777 A KR1020160051777 A KR 1020160051777A KR 20160051777 A KR20160051777 A KR 20160051777A KR 101760392 B1 KR101760392 B1 KR 101760392B1
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target
linear approximation
equation
target position
reference point
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신혁수
김종만
정원주
여광구
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국방과학연구소
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/006Theoretical aspects
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06Systems determining position data of a target
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28Details of pulse systems
    • G01S7/285Receivers
    • G01S7/295Means for transforming co-ordinates or for evaluating data, e.g. using computers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/42Diversity systems specially adapted for radar
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S2013/0236Special technical features

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.

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

Figure 112016040723210-pat00001
And the N receivers are located at
Figure 112016040723210-pat00002
, And the target
Figure 112016040723210-pat00003
Respectively. Regardless of the order in which they appear, k refers to the index of the transmitter,
Figure 112016040723210-pat00004
Quot; refers to the index of the receiver.

As shown in FIG. 2 in the above-described distributed configuration, when a plurality of transmitters are orthogonal to each other,

Figure 112016040723210-pat00005
To the target, the corresponding signal reaches the receiver via the target (S10). At this time
Figure 112016040723210-pat00006
Th receiver can be expressed by Equation (1). &Quot; (1) "

[Equation 1]

Figure 112016040723210-pat00007

here

Figure 112016040723210-pat00008
Lt; RTI ID = 0.0 >
Figure 112016040723210-pat00009
Means the complex amplitude proportional to the RCS (Radar Cross Section) of the target,
Figure 112016040723210-pat00010
The
Figure 112016040723210-pat00011
(Zero Mean White Gaussian) noise generated in the first receiver. In Equation (1)
Figure 112016040723210-pat00012
Lt; RTI ID = 0.0 > k < / RTI >
Figure 112016040723210-pat00013
Th receiver, and can be expressed by Equation (2) below.

&Quot; (2) "

Figure 112016040723210-pat00014

Where c is the speed of light.

From Equation (1), the maximum likelihood estimation (MLE)

Figure 112016040723210-pat00015
) Is a well-known basic technique. Therefore, in the present invention,
Figure 112016040723210-pat00016
And the white Gaussian noise (1), which can be seen in Equation (1)
Figure 112016040723210-pat00017
)
Figure 112016040723210-pat00018
(S11). Therefore, the estimated propagation delay time is
Figure 112016040723210-pat00019
Can be expressed as Equation (3). &Quot; (3) "

&Quot; (3) "

Figure 112016040723210-pat00020

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,

Figure 112016040723210-pat00021
The estimated propagation delay time (t) is calculated using the Taylor linear approximation in Equation (4)
Figure 112016040723210-pat00022
) Is obtained from the linear approximation equation.

&Quot; (4) "

Figure 112016040723210-pat00023

In the linear approximate equation of the equation (4)

Figure 112016040723210-pat00024
,
Figure 112016040723210-pat00025
And
Figure 112016040723210-pat00026
Can be calculated as the Taylor linear approximation result of Equation (3), and are expressed by Equation (5), respectively.

&Quot; (5) "

Figure 112016040723210-pat00027

Since Equation (4) is a linear equation, it is possible to perform target estimation using the existing estimation technique,

Figure 112016040723210-pat00028
Is different from the position of the target, precise estimation is impossible due to the linear approximation error.

Therefore, the present invention can be applied to the propagation delay time

Figure 112016040723210-pat00029
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.

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)

Figure 112016040723210-pat00030
Lt; / RTI > The reference point in the i-th operation
Figure 112016040723210-pat00031
, To obtain the i-th target position estimation result, the propagation delay time (
Figure 112016040723210-pat00032
) Is expressed by a matrix formula for all transmitters and receivers as shown in Equation (6). &Quot; (6) "

&Quot; (6) "

Figure 112016040723210-pat00033
Figure 112016040723210-pat00034

In Equation (6)

Figure 112016040723210-pat00035
When
Figure 112016040723210-pat00036
ego,
Figure 112016040723210-pat00037
Figure 112016040723210-pat00038
to be. Also,
Figure 112016040723210-pat00039
Is defined as Equation (7) (S13).

&Quot; (7) "

Figure 112016040723210-pat00040

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) "

Figure 112016040723210-pat00041

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) "

Figure 112016040723210-pat00042

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

Figure 112016040723210-pat00043
The following equation (10) is used to find the equation
Figure 112016040723210-pat00044
To calculate the one-way function for < RTI ID = 0.0 >
Figure 112016040723210-pat00045
.

&Quot; (10) "

Figure 112016040723210-pat00046

That is, a new (i + 1) th reference point (

Figure 112016040723210-pat00047
Is calculated as shown in the following Equation 11, and the corresponding reference point is updated for the next operation (S16).

&Quot; (11) "

Figure 112016040723210-pat00048

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)

Figure 112016040723210-pat00049
(S17).

&Quot; (12) "

Figure 112016040723210-pat00050

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)

  1. 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.
  2. 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.
  3. 2. The method of claim 1,
    And the MIMO radar system is repeatedly performed a predetermined number of times.
  4. 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.
  5. 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. 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 >
  7. 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 >
  8. 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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Cited By (1)

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Publication number Priority date Publication date Assignee Title
KR20190019755A (en) * 2017-08-18 2019-02-27 국방과학연구소 Method, apparatus and system for target object localization using a distributed Multiple Input Multiple Output radar system

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JP4644197B2 (en) * 2003-08-14 2011-03-02 センシス コーポレーションSensis Corporation Target location method and apparatus using TDOA distributed antenna
KR101615151B1 (en) * 2015-03-04 2016-04-25 국방과학연구소 Method of 3-D MIMO InISAR Imaging for a Stealth Target

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JP2009186456A (en) * 2008-02-06 2009-08-20 Mitsubishi Electric Research Laboratories Inc Method for estimating delay in toa (time of arrival) of transmit signal
KR101615151B1 (en) * 2015-03-04 2016-04-25 국방과학연구소 Method of 3-D MIMO InISAR Imaging for a Stealth Target

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