KR101882483B1 - Apparatus and method for detecting obstacle by unmanned surface vessel - Google Patents

Abstract

The present invention relates to an apparatus and a method for detecting an obstacle of an unmanned surface vessel. More specifically, the present invention provides an apparatus and a method for detecting an obstacle of an unmanned surface vessel which can detect an obstacle by mutually supplementing a short range detection limit of a radar sensor detecting an obstacle in an unmanned surface vessel, and computation amount and data processing time limits of a lidar sensor.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an apparatus and method for detecting an obstacle,

More particularly, the present invention relates to an apparatus and method for detecting an obstacle in an unmanned aerial vehicle, and more particularly, to an apparatus and method for detecting obstacles in an unmanned aerial vehicle including an obstacle detection limit of a radar sensor, And more particularly, to an apparatus and method for detecting an unmanned waterborne obstacle.

Recently, marine robots have been used in various forms according to their purpose in order to carry out marine exploration and specific missions according to the research. Among marine robots, unmanned surface vehicle (USV) has been studied and developed for various purposes such as military, environmental protection,

In order to carry out the mission according to each purpose, common factors such as self-location, path planning, path follow-up, and obstacle avoidance are required for autonomous navigation.

Of these, obstacle detection is an important part for safe autonomous navigation. Various researches have been conducted from simple algorithms to recognize obstacles to avoid obstacles with very sophisticated algorithms.

Korean Registered Patent No. 10-1514407 (registered)

The object of the present invention is to compensate for the proximity detection limit of a radar sensor for detecting obstacles in the unmanned water condition, the computation amount of the rider sensor and the data processing time limit, and integrate the object information obtained from the radar sensor and the rider sensor, And an object of the present invention is to provide an apparatus and method for detecting an obstacle in an important area by predicting an object movement trajectory through fusion of a radar sensor and a rider sensor.

According to another aspect of the present invention, there is provided a method of detecting radar data, comprising the steps of: obtaining radar data for an object using a radar sensor with respect to an area around an unmanned aerial image; Generating a predicted locus by predicting the trajectory of the object based on the already acquired radar data; acquiring the ladder data for the object in the region including the limit radius range through the Lidar sensor; Setting the Lidar data in the predicted trajectory as valid data, and tracking an obstacle based on an analysis of the valid data.

Preferably, before obtaining the radar data for the object, the limit radius range reflecting the detection limit distance of the radar sensor from the unmanned water estimation is set in accordance with the detection limit distance for the short range of the radar sensor .

Preferably, the step of generating the predicted locus of the object predicts a point at which the next radar data will be successively detected based on the already extracted radar data as the object enters the limit radius range, And generates the predicted locus based on the points.

Preferably, the step of generating the predicted trajectory of the object includes applying a Kalman filter to generate the predicted trajectory, and using the velocity and the heading angle of the object, And calculates the probability that radar data will be detected.

Preferably, after obtaining the radar data for the object, it is determined whether or not the object is an obstacle to the unattended water pres- sure according to the bow angle and the relative velocity of the object for the unattended water pres- sure, and Determining whether the object enters the limit radius range based on the assumption of the unmanned water when the object is determined to be an obstacle.

Preferably, the step of determining whether the object is an obstacle to the unattended water presupposition may include determining whether or not the bow angle of the object corresponds to a predetermined direction range toward the unattended water presupposition, The obstacle is determined as an obstacle to the unmanned water presupposition.

According to another aspect of the present invention, there is provided a radar sensor system including a radar sensor unit for collecting radar data for an object in an area around an unmanned aerial image, a lidar sensor unit for collecting radar data for the object in the area around the unmanned aerial image definition, When entering the limit radius range based on the assumption of unattended water, generating a predicted trajectory by predicting the trajectory of the object based on the already obtained radar data, analyzing the LIDAR data in the predicted trajectory, And a signal processing unit for detecting an obstacle.

Preferably, the signal processing unit includes: a data collecting unit for collecting the radar data and the ladder data; and a control unit for, when the object enters the limit radial range, A predicted locus generator for predicting a point to be continuously detected and generating a predicted locus based on the points; a valid data setting unit for setting the LIDAR data in the predicted locus as effective data; And an obstacle detection unit for tracking the obstacle based on the analysis.

Preferably, the signal processing unit sets the limit radius range reflecting the detection limit distance of the radar sensor from the unattended water detection according to a detection limit distance for a short distance of the radar sensor.

Preferably, the predicted locus generation unit predicts a point at which the next radar data will be successively detected based on the already extracted radar data as the object enters the limit radius range, and based on the points, And generates a predicted locus.

Preferably, the predicted locus generator applies a Unscented Kalman filter to generate the predicted locus, and uses a heading angel of the object to generate the predicted locus, And calculates the probability.

Preferably, the signal processing unit determines whether or not the object is an obstacle to the unmanned water reception according to the bow angle and the relative speed of the object with respect to the unattended water injection, and when the object is determined to be an obstacle, It is determined whether or not the object enters the limit radius range based on the unattended water estimation.

Preferably, the signal processing unit is configured to set the object so that when the bow angle of the object corresponds to a predetermined direction range toward the unattended water correction, and the relative speed of the object with respect to the unattended water correction exceeds a threshold value, It is judged that it is an obstacle to the unmanned water.

According to another aspect of the present invention, there is provided a computer-readable recording medium on which a computer-readable recording medium is recorded.

According to the apparatus and method for detecting an unmanned waterborne obstacle according to the embodiment of the present invention, while compensating for the proximity detection limit of the radar sensor for detecting an obstacle in the unmanned water determination, the computation amount of the rider sensor and the data processing time limit, And the object information obtained from the rider sensor are integrated to enable more accurate dynamic object estimation.

Also, according to the apparatus and method for detecting an unmanned aerial vehicle according to an embodiment of the present invention, an obstacle can be detected in an important area by predicting an object movement trajectory through fusion of a radar sensor and a rider sensor.

1 is a block diagram showing a schematic configuration of an apparatus for detecting an unmanned waterborne obstacle according to an embodiment of the present invention.
FIG. 2 shows a radar sensor and a Lada sensor-specific detection area for the unmanned water around the assumed water level set according to the embodiment of the present invention.
FIG. 3 is an exemplary diagram for determining whether or not an object to be predicted locus generation is conditioned according to an embodiment of the present invention.
4 is an exemplary diagram showing an example in which an identification number is assigned to an object to be predicted locus generation according to an embodiment of the present invention.
5 is a diagram for explaining a method of detecting an obstacle by the apparatus for detecting unmanned water based obstacle according to an embodiment of the present invention.
6 is a flowchart illustrating a method for detecting an unmanned aerial vehicle according to an embodiment of the present invention.
FIG. 7 shows an example of an execution screen for tracking an object through the unmanned aberration-based obstacle detection program according to the embodiment of the present invention.

The present invention will be described in detail with reference to the accompanying drawings.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings and accompanying drawings, but the present invention is not limited to or limited by the embodiments.

The term used in the specification of the present invention selects the general term that is widely used in the present invention while considering the function of the present invention, but it may be changed depending on the intention or custom of the technician engaged in the field or appearance of new technology . Also, in certain cases, there may be a term chosen arbitrarily by the applicant, in which case the meaning thereof will be described in the description of the corresponding invention. Therefore, it is intended that the terminology used herein should be interpreted based on the meaning of the term rather than on the name of the term, and on the entire contents of the specification. For example, certain features, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the invention in connection with an embodiment.

Further, although the reference numerals and the like of the drawings are denoted by the same reference numerals and signs as possible, even if they are shown in different drawings, the same reference numerals and signs are used. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is to be limited only by the appended claims, along with the full scope of equivalents to which such claims are entitled, if properly explained. In the drawings, like reference numerals refer to the same or similar functions throughout the several views.

Hereinafter, an apparatus and method for detecting an unmanned aerial vehicle according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. Like numbers refer to like elements throughout the drawings.

1 is a block diagram showing a schematic configuration of an apparatus for detecting an unmanned waterborne obstacle according to an embodiment of the present invention. Referring to FIG. 1, an apparatus 100 for detecting an unmanned aerial vehicle according to an embodiment of the present invention includes a radar sensor unit 110, a lidar sensor unit 120, and a signal processing unit 130. The signal processing unit 130 includes a data collecting unit 132, a predicted locus generating unit 134, a valid data setting unit 136, and an obstacle detecting unit 138.

The radar sensor unit 110 collects the radar for the object 20 in the peripheral region of the unmanned water reception system 10 and transmits it to the data collection unit 132.

The rider sensor unit 120 acquires the Raid data for the object 20 in the peripheral region of the unmanned water reception system 10 and transmits it to the data collection unit 132. The rider sensor unit 120 is operated by the signal processing unit 130 to acquire the Raid data for the object 20 when the object 20 is close to the detection limit distance of the radar sensor unit 110. [ A detailed description thereof will be given later.

Since the radar sensor unit 110 is a remote device originally detecting about 15 km, it is difficult to accurately detect an object as the object being detected is closer to the near side. In other words, since the detection limit distance to the object of the radar sensor unit 110 is within 50 m, it is considered that accurate detection is difficult for the object 20 approaching within 50 m from the unmanned water reception system 10.

The signal processing unit 130 sets a limit radius range that reflects the detection limit distance of the radar sensor unit 110 from the unmanned water reception system 10 in accordance with the detection limit distance for the short distance of the radar sensor unit 110. [

The range of the limit radius may be set within a range of 50 m to 80 m from the unmanned water reception system 10. It is to be understood that the scope of the present invention may be changed depending on the respective functions and states of the radar sensor unit 110 and the lidar sensor unit 110 And can be changed within a range that does not deviate.

The signal processing unit 130 first acquires radar data from the radar sensor unit 110 through the data collecting unit 132.

The signal processing unit 130 emits an electromagnetic wave from the radar sensor unit 110 and calculates a distance according to the amount of reflected electric power. Here, the distance between the radar transceiver and the object 20 can be calculated through the measured transmission power.

The signal processing unit 130 calculates the locus along the time from the distance calculated from the radar transmitter to the object 20 as described above and calculates the relative speed and azimuth angle between the dynamic object 20 and the unmanned water reception system 10 do. Since these techniques are already known, detailed description will be omitted.

FIG. 2 shows a radar sensor and a Lada sensor-specific detection area for the unmanned water around the assumed water level set according to the embodiment of the present invention. Referring to FIG. 2, since the detection limit distance of the radar sensor unit 110 is 50 to 80 meters from the unmanned water intake 10, it is considered that accurate detection is difficult for the object 20 approaching the detection limit range.

Accordingly, the present invention is limited to the object 20 whose bow angle is directed toward the unmanned water receiving surface 10 within the range of 50 m to 1 km from the waterless water receiving surface 10 and whose relative speed to the unmanned water receiving surface 10 is equal to or higher than the threshold, Which is a trajectory predicted with respect to the object 20, is generated. The basic condition to be selected by the object 20 to be the target of the predicted locus generation will be described with reference to FIG.

3 is a reference diagram for explaining a method for calculating the coordinate system between the unmanned water estimation 10 and the object 20 in the peripheral region. 3, the signal processing unit 130 determines whether or not the bow angle of the object 20 is heading to the predetermined position before determining whether the object 20 in the surrounding environment of the water-free water table 10 is an obstacle And it is analyzed whether or not the relative speed V _r > 0.

That is, the signal processing unit 130 determines whether or not the angle of the bow of the object 20 corresponds to a predetermined directional range toward the unmanned water table 10 and the relative velocity of the object 20 to the unmanned water table 10 is the threshold , It is determined that the object 20 is an obstacle to the unmanned water reception system 10 and a predicted locus of the object 20 is generated.

Here, the bow angle with respect to the object 20 is defined as θ _usv with respect to the true north direction as the direction angle of the unmanned water _{receiving system} 10, and the bow angle θ _r with respect to the object 20 is the radar sensor unit 110 Can be calculated by using an angle between the distance d to the object 20 acquired by using the angle? Thus, the heading calculated through the movement trajectory of x (t), y (t) over time can be transformed on the basis of the true north direction, and the object 20 can be transformed by comparing θ _usv and θ _r , It is possible to judge whether or not the bow angle of the player is heading toward the unmanned water receiving side 10.

As shown in FIG. 4, the signal processing unit 130 assigns a unique identification number to an object satisfying the condition of an object to be predicted locus generation, and then obtains a movement locus for an object to which an identification number is assigned And traces the object by associating the movement trajectory with the Lada data for the object.

As shown in Fig. 5, the predicted locus generator 134 predicts the point at which the next radar data is successively detected based on the already obtained radar data as the object 20 enters the limit radius range , And generates the predicted locus based on the points.

At this time, a Kalman filter (Unscented Kalman filter) is applied to generate consecutive predicted trajectories based on pointers on which the next radar data will be continuously detected, and then the velocity and the heading angle of the object 20 Predicts a point at which radar data will be successively detected, and calculates a probability for the point.

The signal processing unit 130 may detect the distance from the radar sensor unit 110 to the object 20 within a range of the limit radius of the radar sensor unit 110, Even when the radar data can not be acquired normally, the lidar sensor unit 120 is driven to acquire the ladder data for the object 20 existing between 50 and 80 m.

The signal processing unit 130 detects the position of the object 20 based on the already acquired radar data from the time when the radar sensor unit 110 can not normally acquire the radar data for the object 20 within a certain range from the detection limit distance, Lt; / RTI >

In addition, since the radar sensor unit 110 is connected to the unmanned water tank 10 via a fixed shaft without stabilizer, it is vulnerable to rolling and pitch of the unmanned water tank 10, The signal processing unit 130 may generate a predicted locus for the object 20 and may drive the RI sensor unit 120 at this time as well.

The following equation is used for the Kalman filter and the algorithm that uses the bow angle for the continuous trajectory extraction expected for the radar data that disappears as the object 20 enters the limit radius range.

[Equation 1]

를 통해서, 추정값

를 계산할 수 있으며, 수학식 1에는

: 칼만필터 이득값을 통해서 추정값을 계산한다. From the above equation (1), the measurement value

, The estimated value

, And Equation (1)

: Calculate the estimate through the Kalman filter gain value.

&Quot; (2) "

:

번째의 오차공분산이 된다. 이를 통해서 칼만필터 이득값을 계산하는 수학식 3이 적용 가능해진다.The error covariance calculation is performed through Equation (2)

:

Th error covariance. The equation (3) for calculating the Kalman filter gain value becomes applicable.

&Quot; (3) "

&Quot; (4) "

는 레이더 탐색 물체의 위치와 선수각이 포함되어 있으며, 수학식 1에는

; 물체의 상대속도를 포함하여 예측정보로 갱신하게 된다.The predicted value < RTI ID = 0.0 >

Includes the position and the bow angle of the radar search object, and Equation 1

; And updates the prediction information including the relative velocity of the object.

Since the data processing time and the computation amount of the LIDAR sensor are large in order to detect obstacles in the unmanned water under only the rider sensor, in the present invention, the LIDAR sensor is selectively used according to the state of the data signal detected from the radar sensor, Advantages are utilized, defects are compensated, and obstacles can be detected quickly and accurately.

The valid data setting unit 136 sets the LADID data in the predicted locus as valid data. Referring to FIG. 5, it can be seen that the point of the Lada data comes into contact with the predicted locus of the object 20 generated through the radar data. At this time, the points of the LR data corresponding to the predicted locus may be at least one or more, and the points of the LR data are set as the valid data.

The obstacle detection unit 138 judges the object 20 as an obstacle based on the analysis of the valid data and continuously tracks the movement of the obstacle.

That is, the lidar point data generated in the contact area of the predicted locus and the lidar data and the predicted locus are set as the interest group, and based on the analysis of the set lidar point data, Movements to obstacles can be detected and tracked.

On the other hand, the signal processing unit 130 receives the radar data acquired from the radar sensor unit 110, the rider data acquired from the lid sensor unit 120, the object data to which the identification number is assigned, the object 20 ), And the Lattice data in contact with the predicted locus can be expressed as an image on the display.

FIG. 7 shows an example of an execution screen for tracking an object through the unmanned aberration-based obstacle detection program according to the embodiment of the present invention. The execution screen can display the moving direction of the object to be tracked with an arrow. When the bow angle of the object is directed toward the unmanned water elevation, the object is highlighted, and as the object enters the limit radius range, Based on the data, the prediction point to which the next data is successively detected can also be displayed so that the user can intuitively recognize the prediction point.

As described above, the present invention improves the efficiency of obstacle detection in the vicinity of the unmanned aerial vehicle by acquiring valid data by fusing the characteristics of a three-dimensional ray sensor and a radar sensor with respect to an object which is difficult to detect at a close range by a radar sensor alone.

Since the data processing time and the computation amount of the LIDAR sensor are large in order to detect the obstacle around the unmanned water only by the rider sensor, in the present invention, the LIDAR sensor is selectively used according to the state of the data signal detected from the radar sensor, By utilizing the merits of the two sensors and compensating for their disadvantages, it is possible to increase the accuracy of dynamic obstacle estimation and to detect obstacles quickly and accurately.

6 is a flowchart illustrating a method for detecting an unmanned aerial vehicle according to an exemplary embodiment of the present invention.

Referring to FIG. 6, in the method for detecting an unmanned aerial image according to an exemplary embodiment of the present invention, radar data for an object is acquired using a radar sensor for an area around the unmanned aerial image (S110). Here, before the step of acquiring radar data for the object, the step of setting the limit radius range reflecting the detection limit distance of the radar sensor from the unmanned water estimation in accordance with the detection limit distance for the short range of the radar sensor .

Determining whether the object is an obstacle to the unmanned water reception in accordance with the bow angle and relative velocity of the object with respect to the unattended water presumption after obtaining the radar data for the object; Determining whether the object enters the limit radius range based on the assumption of the unmanned water when it is determined that the object is an obstacle. Specifically, when the bow angle of the object corresponds to a predetermined direction range toward the unmanned water intake, and the relative velocity of the object with respect to the unmanned water intake exceeds the threshold value, the object is determined as an obstacle to the unmanned water intake. An object identification number is assigned to an object judged to be an obstacle.

This is to detect not only all objects in the vicinity of the unmanned water, but also the moving trajectory by selecting only the obstacles to the unmanned water.

Next, it is determined whether the object enters the limit radius range based on the unmanned water estimation (S120). If it is determined that the object enters the limit radius range, the trajectory of the object is predicted based on the radar data, (S130). To this end, as the object enters the limit radius range, the next radar data is continuously predicted based on the already extracted radar data, and the predicted locus is generated based on the points.

At this time, a Kalman filter is used to generate the predicted locus, and the probability that the radar data is detected within the limit radius range is calculated using the velocity and the heading angle of the object, It is used to generate.

Next, the LIDAR data for the object is obtained in the region including the limit radius range through the LIDAR sensor (S140).

Next, the Lattice data in the predicted locus is set as valid data (S150).

Generally, the radar data that can be acquired through the radar sensor is represented by a rectangular coordinate system, and the radar data that can be acquired through the radar sensor can be displayed in a polar coordinate system. Accordingly, in order to acquire valid data by fusing a radar sensor and a radar sensor, the radar data acquired through the radar sensor is converted into a rectangular coordinate system such as Lada data and displayed.

Next, the obstacle is detected based on the analysis of the valid data (S160). That is, the lidar point data generated in the contact area of the predicted locus and the lidar data and the predicted locus can be set as the interest group, and the near obstacle can be detected and tracked based on the analysis of the set lidar point data.

According to the apparatus for detecting an unmanned waterborne obstacle according to the embodiment of the present invention, while the limit of the near detection limit of the radar sensor for detecting an obstacle in the unmanned water reception, the calculation amount of the rider sensor and the data processing time are complemented, And the object information obtained from the rider sensor are integrated to enable more accurate dynamic object estimation.

Also, according to the apparatus and method for detecting an unmanned aerial vehicle according to an embodiment of the present invention, an obstacle can be detected in an important area by predicting an object movement trajectory through fusion of a radar sensor and a rider sensor.

It is to be understood that the present invention is not limited to these embodiments, and all elements constituting the embodiment of the present invention described above are described as being combined or operated in one operation. That is, within the scope of the present invention, all of the components may be selectively coupled to one or more of them. In addition, although all of the components may be implemented as one independent hardware, some or all of the components may be selectively combined to perform a part or all of the functions in one or a plurality of hardware. As shown in FIG. In addition, such a computer program may be stored in a computer readable medium such as a USB memory, a CD disk, a flash memory, etc., and read and executed by a computer to implement an embodiment of the present invention. As the recording medium of the computer program, a magnetic recording medium, an optical recording medium, or the like can be included.

Furthermore, all terms 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, unless otherwise defined in the Detailed Description. Commonly used terms, such as predefined terms, should be interpreted to be consistent with the contextual meanings of the related art, and are not to be construed as ideal or overly formal, unless expressly defined to the contrary.

It will be apparent to those skilled in the art that various modifications, substitutions and substitutions are possible, without departing from the scope and spirit of the invention as disclosed in the accompanying claims. will be. Therefore, the embodiments disclosed in the present invention and the accompanying drawings are intended to illustrate and not to limit the technical spirit of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments and the accompanying drawings . The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of equivalents should be construed as falling within the scope of the present invention.

Claims (14)

Acquiring radar data for an object using a radar sensor for an area around the unmanned aerial image;
Generating a predicted trajectory by predicting the trajectory of the object based on the already obtained radar data when the object enters the limit radius range based on the unattended water presumption;
Obtaining lidar data for the object in the region including the limit radius range through the lidar sensor;
Setting the Lattice data in the predicted trajectory as valid data; And
And tracking an obstacle based on an analysis of the valid data,
After acquiring radar data for the object,
Determining whether the object is an obstacle to the unmanned water reception according to the bow angle and the relative speed of the object with respect to the unattended water reception; And
Further comprising the step of determining whether the object enters the limit radius range based on the assumption of the unmanned water when the object is determined to be an obstacle. The method according to claim 1,
Prior to acquiring radar data for the object,
Further comprising the step of setting the limit radius range reflecting the detection limit distance of the radar sensor from the unattended water presumption according to a detection limit distance for a short distance of the radar sensor. 3. The method of claim 2,
Wherein the step of generating the predicted locus of the object comprises:
Predicts a point at which the next radar data will be successively detected based on the already extracted radar data as the object enters the limit radius range and generates the predicted locus based on the points. How to Track a Defined Obstacle. The method of claim 3,
Wherein the step of generating the predicted locus of the object comprises:
Wherein a probability of detecting radar data within the limit radius range is calculated by applying a Kalman filter to generate the predicted trajectory and using a heading angel of the object and a velocity of the object. How to Track a Defined Obstacle. delete The method according to claim 1,
Wherein the step of determining whether the object is an obstacle to the unattended water presumption comprises:
When the bow angle of the object corresponds to a predetermined direction range toward the unattended water presupposition and the relative speed of the object with respect to the unattended water presupposition exceeds the threshold value, the object is determined to be an obstacle to the unattended water presupposition Wherein the method further comprises the steps of: A computer-readable storage medium on which a computer-readable program for performing the method of claim 1, 2, 3, 4, 5, 6, A radar sensor unit for collecting radar data for an object in an area around the unmanned aerial image;
A lidar sensor unit for collecting lidar data for the object in the area around the unmanned aerial image; And
When the object enters the limit radius range based on the unattended water estimation, generates a predicted trajectory by predicting the trajectory of the object based on the already obtained radar data, and analyzes the LR data in the predicted trajectory And a signal processing unit for tracking an obstacle,
Wherein the signal processing unit determines whether the object is an obstacle to the unmanned water reception according to the bow angle and the relative speed of the object with respect to the unattended water reception,
Wherein if the object is determined to be an obstacle, it is determined whether the object enters the limit radius range based on the assumption of the unmanned water. 9. The method of claim 8,
The signal processing unit,
A data collecting unit collecting the radar data and the ladder data;
A predicted locus generator for predicting a point at which the radar data is continuously detected within the limit radius range when the object enters the limit radius range and generating a predicted locus based on the points;
A valid data setting unit for setting the Lattice data in the predicted locus as effective data; And
And an obstacle detection unit for tracking an obstacle based on the analysis of the valid data. 9. The method of claim 8,
The signal processing unit,
Wherein the limit radius range reflecting the detection limit distance of the radar sensor is set based on the detection limit distance for the short range of the radar sensor. 10. The method of claim 9,
Wherein the predicted locus generator comprises:
Predicts a point at which the next radar data will be successively detected based on the already extracted radar data as the object enters the limit radius range and generates the predicted locus based on the points. An augmented obstacle tracking device. 12. The method of claim 11,
Wherein the predicted locus generator comprises:
Applying a Kalman filter to generate the predicted trajectory and calculating a probability for the points within the limit radius range using a velocity and a heading angle of the object. An augmented obstacle tracking device. delete 9. The method of claim 8,
The signal processing unit,
When the bow angle of the object corresponds to a predetermined direction range toward the unattended water presupposition and the relative speed of the object with respect to the unattended water assumption exceeds a threshold value, the object is determined to be an obstacle to the unattended water guidance Wherein the obstacle tracking device is an unmanned aerial vehicle.

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