KR101567769B1 - Method for reducing acquisition time for searching a moving target through multi node cooperation based on network - Google Patents

Abstract

More particularly, the present invention relates to a technology for detecting a moving target, and more particularly, it predicts the traveling direction of a moving target in a plurality of ground unmanned vehicle operating environments and then propagates the moving target to a near unmanned vehicle in real time to shorten the target detection acquisition time, This is a method of shortening the detection acquisition time so as to prevent the situation of the detection acquisition.

Description

[0001] The present invention relates to a method for reducing acquisition time of a moving target by using a network-based multi-

More particularly, the present invention relates to a technology for detecting a moving target, and more particularly, it predicts the traveling direction of a moving target in a plurality of ground unmanned vehicle operating environments and then propagates the moving target to a near unmanned vehicle in real time to shorten the target detection acquisition time, This is a method of shortening the detection acquisition time so as to prevent the situation of the detection acquisition.

There are many threats in the battlefield environment, and the higher the level of threat, the more difficult it is to deal with them on a single platform. The concept of Cooperative Engagement is aimed at increasing the ability to defend and respond to all platforms in the area, as well as within themselves, by closely cooperating and cooperating forces within the operational zone.

Especially, in order to maximize the ability to perform mission in the center of the ground network, it is necessary to apply the concept of cooperative engagement operation among a large number of unmanned vehicles scheduled to operate in the future battlefield. In the terrestrial environment, if the unmanned vehicle is moving due to problems such as topographical features or obstacles, it often happens that the target is missed, which may cause difficulties in maintaining the mission.

In a typical platform-based battlefield environment, a single weapon system or surveillance equipment is responsible for the surveillance and reconnaissance service of the target. Therefore, when the mobile target deviates from the surveillance area of the corresponding equipment, there is a difficulty in quickly grasping the position of the target.

However, in the future battlefield environment where all the unmanned systems are network-based, it is necessary to predict the moving direction of the target through convergence processing using the information acquired from each unmanned vehicle and to transfer the monitoring task of the important target to the adjacent unmanned vehicle .

Also, when performing surveillance missions on a stand-alone basis, it is necessary to overcome situations where targets are often missed.

1. Korean Registered Patent No. 10-1200747

1. Song, Jae-Bok et al., "Estimation of Outdoor Position of Mobile Robot by Matching GPS Information and Lane Information" Control ㅇ Robot ㅇ Systems Journal Vol. 18, No. 6 (June 2012) pp.594-600 1976-4529 KCI

The present invention has been proposed in order to solve the problem according to the above background art. The present invention predicts the traveling direction of a moving target in a plurality of ground unmanned vehicle operating environments, shortens the target detection acquisition time by real- The present invention provides a method for shortening the detection time of a moving target by network-based multi-node cooperation.

In addition, the present invention provides a method for detecting a moving target by network-based multi-node cooperation that shortens target acquisition time of an adjacent unmanned vehicle by preliminarily determining if the unmanned vehicle is obstructed by an obstacle in detecting a moving target, There are other purposes to provide a method of shortening the acquisition time.

In addition, the present invention provides a method for detecting a moving target by a network-based multi-node cooperative operation in which a predicted trajectory of a moving target is predicted and a position value and a directional angle value corresponding to the trajectory value are transmitted to a non- There is another purpose in providing a time reduction method.

In order to achieve the above-mentioned object, in order to achieve the above-mentioned object, it is desirable to predict the traveling direction of a moving target in a plurality of ground unmanned vehicle operating environments and to shorten the target detection acquisition time The present invention provides a method for shortening the detection time of the moving target by network-based multi-node cooperation.

The method for shortening the detection acquisition time of the moving target includes:

Generating a plurality of unmanned vehicles with target location information for a particular target;

Analyzing the tracking and monitoring continuity of the specific target by receiving target position information on which the unmanned vehicle control device is generated;

If the unmanned vehicle control apparatus can not track and monitor the specific target, the unmanned vehicle control apparatus may generate a target anticipated path by predicting the movement path of the specific target.

The unmanned vehicle control apparatus searching for an unmanned vehicle around a target expected path generated among a plurality of unmanned vehicles; And

And transmitting the monitoring orientation angle information to the unmanned vehicle detected by the unmanned vehicle control apparatus.

In this case, the target expected path may be calculated using a least square method.

In addition, the target expected path may be a predicted path for each specific target based on the velocity calculated using the least squares method and the coordinates of the specific target.

Also, the search for the unmanned vehicle around the generated target anticipated path may be performed by calculating a contact point at which an extension line of the anticipated traveling direction of the target intersects with an extension line of the mission equipment angle of a plurality of unmanned vehicles adjacent to the anticipated traveling direction, And selecting the unmanned vehicle in the distance.

In addition, the search for the unmanned vehicle around the generated target expected path may be performed using the three-dimensional map information.

(여기서, X,

는 추정과정을 통해 얻어진 표적의 위치이고,

는 일차방정식을 구성하는 계수이다.)에 의해 산출되는 것을 특징으로 할 수 있다.Further, an extension line of the predicted traveling direction of the target is expressed by the following equation

(Wherein X,

Is the position of the target obtained through the estimation process,

Is a coefficient constituting a linear equation).

In addition, the generated target anticipated route may be displayed on a digital map screen.

According to the present invention, it is possible to determine the necessity of takeover of a target through path estimation of a moving target, and it is possible to shorten the detection acquisition time of the target by analyzing the appearance point of the target, and smooth continuous monitoring of the important target becomes possible .

In addition, as another effect of the present invention, it is possible to improve information accuracy and / or availability and the like in a single unmanned vehicle operation by fusing digital tactical information obtained from a plurality of unmanned vehicles, .

1 is a configuration diagram of a detection target acquisition time reduction system 100 according to an embodiment of the present invention.
FIG. 2 is an example of a GUI (Graphic User Interface) screen for performing a target detection acquisition time reduction function according to an embodiment of the present invention.
FIG. 3 is a conceptual diagram for deriving a linear equation using the target position value 310 by applying the least squares method according to an embodiment of the present invention.
4 is an example of a function for predicting a path of a moving target according to an embodiment of the present invention.
5 is a conceptual diagram for exploring a target detectable unmanned vehicle according to an embodiment of the present invention.
FIG. 6 is an example showing a detection sustainability confirmation based on a target predicted path display on a digital map screen according to an embodiment of the present invention.
FIG. 7 is a flowchart of convergence processing related to the target detection acquisition time reduction according to an embodiment of the present invention.
FIG. 8 is a configuration diagram of a test equipment for verification of convergence processing related to shortening of target detection acquisition time according to an embodiment of the present invention.
9 is a graph of a result approximate expression according to another embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method for shortening a detection time of a moving target by network-based multi-node cooperation according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a configuration diagram of a detection target acquisition time reduction system 100 according to an embodiment of the present invention. Referring to FIG. 1, the detection acquisition time reduction system 100 includes a ground unmanned vehicle control device 110, first to third unmanned vehicles 121-a to 121-c, A surveillance surveillance network 120, and a communication network 130 for connecting them.

The ground unmanned vehicle control device 110 includes a mission integration device 111 and a mission control device 112. Accordingly, the mission control device 112 assigns surveillance and reconnaissance missions to the first to third unmanned vehicles 121-a to 121-c so that each unattended vehicle 121-a to 121-c performs the mission . In addition, the mission control device 112 outputs the video display screen 115 to the display. Of course, the mission control devices 112 may be composed of one or more, and may be connected to each other to exchange data and / or control signals.

The task integration device 111 performs functions of providing information to the operator 119 or providing an instruction of the operator 119 to the mission control device 112. [ In addition, the mission control device 112 is integratedly controlled, the moving direction of the target is estimated from the received target position information, and the target is continuously monitored until several seconds afterwards.

The communication network 130 may be a public switched telephone network (PSTN), a public switched data network (PSDN), an Integrated Services Digital Network (ISDN), a Broadband Integrated Services Digital Network (BISDN), a Local Area Network However, the present invention is not limited to this, and may be applied to a wireless communication system such as a CDMA (Code Division Multiple Access) system, a wireless communication system, (WCDMA), Wireless Broadband (Wibro), Wireless Fidelity (WiFi), and High Speed Downlink Packet Access (HSDPA) networks.

In addition to these commercial networks, there is a dedicated unmanned network for controlling unmanned vehicles. The unmanned system dedicated communication network consists of multi-hop OFDMA (Orthogonal Frequency Division Multiple Access) communication method, 4x4 multi-input / output (MIMO) signal processing technology for spectral transmission efficiency and communication distance compared to existing communication method, To-vehicle network configuration and an adaptive network technology capable of ad-hoc relaying are possible.

The first to third unmanned vehicles 121-a to 121-c are robots selected as targets capable of detecting a target. The first to third unmanned vehicles 121-a to 121-c may perform a mission (for example, detection of the target 122, etc.) due to the obstacle and / If not, analyzes the associated prediction information and transmits the analysis information to the unmanned vehicle control device 110 before entering the obstacle and / or feature area. Accordingly, the unmanned vehicle control apparatus 110 sends a warning alarm to the operator 119.

In this case, the unmanned vehicle control apparatus 110 analyzes the optimum monitoring clock range for the other unmanned vehicles 121-a to 121-c capable of detecting the target 122 hidden by the obstacle, And transmits the monitoring-oriented angle information.

The unmanned vehicles 121-a to 121-c change the field of view (FOV) of the unmanned vehicle at this time and display the anticipated target route after entering the obstacle zone of the target 122, -a through < RTI ID = 0.0 > 121-c). < / RTI >

Although targets can not be monitored due to obstacles and / or features, it is possible to monitor the route of the target by displaying the route of the target to the operator. A diagram showing this is shown in Fig. FIG. 2 is an example of a GUI (Graphic User Interface) screen for performing a target detection acquisition time reduction function according to an embodiment of the present invention. Referring to Fig. 2, target information fusion information and the like by the unmanned vehicles 121-a to 121-c are displayed. Such information includes azimuth angle, distance, moving direction, and position correction.

When the target (122 in FIG. 1) exits the obstacle zone, the unmanned vehicle selected as the unmanned vehicle capable of detecting the target detects the target, and then the target 122 is continuously tracked.

Here, the predicted target path is predicted through the least square method. In addition, the velocity is calculated using the coordinates of the target, and the predicted target anticipated path of the target is predicted using the target predicted path and velocity of the target 122.

That is, if the position value of the target 122 is continuously estimated with time, the optimal linear equation is calculated by using this value. The optimal linear equation is as follows.

는 추정과정을 통해 얻어진 표적의 위치이고,

는 일차방정식을 구성하는 계수이다.Here, X,

Is the position of the target obtained through the estimation process,

Is a coefficient constituting a linear equation.

Describing this optimal linear equation in another way, If the position value of the target is constantly estimated over time, this value is used to calculate the optimal linear equation.

Here, the position value was calculated as the coordinate value on the map. Let f (x) = ax + b be the approximate expression for the estimated position value. The sum of squares of the errors can be expressed as:

Here, finding f that minimizes E is least squares. The following is an example of the least squares method using four observed ( n = 4 ) target values. Here, numerical values are simplified for convenience of calculation and confirmation of results. Each coordinate value is as follows.

property first second third fourth Sum x 2 3 5 6 16 y 3 5 6 8 22 x ² 4 9 25 36 74 xy 6 15 30 48 99

The following two formulas can be obtained from the above coordinate values and calculated values.

From the above two formulas, a can be obtained as 1.1 and b as 1.1. Therefore, the following approximate expression can be obtained and the graph is shown in FIG.

In addition, the search for the target detectable unmanned vehicle can be performed by detecting the presence of other unattended vehicles (121-a to 121-c of FIG. 1) adjacent to the extension of the expected direction of travel of the target (122 in FIG. 1) After calculating the contact point with the possible extension line, it selects the contactless unmanned vehicle which can detect the target among the contacts as soon as possible. Fig. 3 is a diagrammatic representation for easy understanding. That is, FIG. 3 is a conceptual diagram for deriving a linear equation using a target position value by applying a least squares method according to an embodiment of the present invention. A straight line 320 is generated at a distance from the target position value 310.

4 is an example of a function for predicting a path of a moving target according to an embodiment of the present invention. Of course, this is for the sake of example and it is also possible to create functions using other programming.

5 is a conceptual diagram for exploring a target detectable unmanned vehicle according to an embodiment of the present invention. 5, a field of view (FOV) 500 that can be detected by the first unmanned vehicle 121-a includes a detectable range 540, an obstacle 560, and / And an undetectable range (550) in which landfall detection is impossible due to the terrain (570).

In this case, in the detectable range 540, the first unmanned vehicle 121-a is used to detect the target 122. [ In the undetectable range 550, detection is performed using the second and third unmanned vehicles 121-b and 121-c.

The obstacle 560 and / or the obstacle 560 can be detected using the contacts 510 and 530 where the mission equipment angles of the second and third unmanned vehicles 121-b and 121-c meet the target predicted path 530 of the target 122, Or terrain 570, as shown in FIG.

FIG. 6 is an example showing a detection sustainability confirmation based on a target predicted path display on a digital map screen according to an embodiment of the present invention. Referring to FIG. 6, the detection areas 610, 620, 630 and the obstacle area 640 are displayed on the digital map screen.

FIG. 7 is a flowchart of convergence processing related to the target detection acquisition time reduction according to an embodiment of the present invention. Referring to FIG. 7, the mission integrating apparatus 111 for integrally controlling the mission control apparatus (112 in FIG. 1) estimates the direction of movement of the target 122 from the target positions 710 and 720 to be received, Analyze whether the target can be continuously monitored (730). Analysis information includes estimation time from initial detection, azimuth and elevation angle for initial detection.

If continuous detection of the target is impossible, the mission integrating unit 111 predicts the movement route of the target 122 and keeps track of a specific target, and analyzes whether the target unmanned vehicles can detect the target. The mission integrating device 111 searches for an unmanned vehicle (121-a to 121-c in FIG. 1) capable of detecting the target the earliest by using the travel route predictive value of the target and the three- And requests maintenance to the mission control device 1112 (740).

The mission control device 112 transfers the monitoring orientation information to the detected unmanned vehicle (121-a to 121-c in FIG. 1) to take over the mission (750). This makes it possible to accomplish the mission of the unmanned vehicle without interrupting the mission (760,770). The convergence processing result for shortening the target detection acquisition time can be confirmed through the mission status screen on which the 3D digital map is displayed.

FIG. 8 is a configuration diagram of a test equipment for verification of convergence processing related to shortening of target detection acquisition time according to an embodiment of the present invention. 8, the electric field simulator 810 generates target position information for the virtual target 801 of the virtual unmanned vehicles 821-a to 821-n through the target position information error generator 811, To the vehicle control device 110. The control device analyzes the target movement route estimation and detection continuity and analyzes the area where the virtual unmanned vehicle can be scouted so that the adjacent unmanned vehicle can continue its mission.

100: Detection acquisition time reduction system
110: Unmanned vehicle control device
111: Mission Integration Device 112: Mission Control Device
120: Reconnaissance Surveillance Network
121-a to 121-c: unmanned vehicles
122: Target
130: communication network

Claims (7)

Generating a plurality of unmanned vehicles with target location information for a particular target;
Analyzing the tracking and monitoring continuity of the specific target by receiving target position information on which the unmanned vehicle control device is generated;
If the unmanned vehicle control apparatus can not track and monitor the specific target, the unmanned vehicle control apparatus may generate a target anticipated path by predicting the movement path of the specific target.
The unmanned vehicle control apparatus searching for an unmanned vehicle around a target expected path generated among a plurality of unmanned vehicles; And
Transmitting the position value of the target expected path and the monitoring orientation angle information to the unmanned vehicle in which the unmanned vehicle control apparatus searches;
, ≪ / RTI &
The search for the unmanned vehicle around the generated target anticipated path is performed by calculating a contact point at which an extension line of the mission equipment angle of the plurality of unmanned vehicles adjacent to the extension line of the anticipated traveling direction of the target crosses, And selecting an unmanned vehicle that is located at a distance closer to the target that can not be searched but is capable of target searching after a predetermined time elapses. The method according to claim 1,
Wherein the target expected path is calculated using a least square method. The method of claim 1, wherein the target expected path is calculated using a least square method. 3. The method of claim 2,
Wherein the target expected path is a path predicted by time of the specific target based on the speed calculated using the least squares method and the coordinates of the specific target. Shortening method.
delete The method according to claim 1,
Wherein the searching of the unmanned vehicle around the generated target expected path is performed using the three-dimensional map information.
The method according to claim 1,
The extension line of the anticipated traveling direction of the target is calculated by the following equation

(Wherein X,

Is the position of the target obtained through the estimation process,

Is a coefficient constituting a linear equation). ≪ RTI ID = 0.0 > 1, < / RTI >
The method according to claim 1,
Wherein the generated target anticipated path is displayed on a digital map screen.

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