KR20150003893U - An Automated System for Military Surveillance and Security utilizing RADAR and DRONE - Google Patents

Abstract

The present invention relates to a system that enables the boundary and operation of military and civilian water using a Doppler radar and a drone. Currently, the military and civilian facility boundary guard is installed in a closed circuit television (CCTV) RED CAMERA), so that it can not detect enemy infiltration due to its remarkable deterioration in fog and other bad weather conditions.

Description

[0001] The present invention relates to an automation system for a boundary and an expense using a radar and a drone,

The present invention relates to a system for automating and unmanning boundary guards for military use and civilian use, which is implemented using a radar and a drone. The system includes a device for detecting enemy infiltration using a Doppler radar, And to track the coordinates and transmit these coordinates to the drone to perform the operation using a technique to solve the problem that occurs when the drone is automatically moved to this coordinates and equipment attached to the drone And to solve the problems that arise when it occurs.

The radar technique used in this technique is a radar technique using a Doppler effect. This technology detects the enemy by using the Doppler effect that occurs in the phenomenon that the electromagnetic wave emitted from the radar and the reflected light return to the moving object. In addition, the drone device is capable of unmanned flight, and consists of the technique of moving the drone to the coordinates without collision with the landform by setting the coordinates of the enemy detected by manual or automatic adjustment to the target point. Equipment that can be attached to the drone during operations include mesh, explosives, laser pointing devices, and lighting devices

The inventive concept of the present invention is based on the technical limitations of the Doppler radar, namely, the problem of tracking an object that is not secured with a line-of-sight, an object that is moving or moving at a low speed We also solved the problem of tracking objects once they were detected, and solving the problem of moving the drone as a target.

Currently, the military boundary and guard system is mainly composed of CCTV and IR camera. However, the effective viewing distance of CCTV and IR camera is remarkably shortened in case of fog and other weather conditions. Therefore, if the enemy penetrates in the weather deterioration situation, the possibility of being discovered is lowered and the system is disabled. In order to compensate for this, there are tools such as using a laser to brighten it, but this also does not help much in the case of weather conditions such as fog. A radar using a Doppler effect can be used as a detection device that is not influenced by such a meteorological phenomenon. However, lasers are basically a system operated only when a line-of-sight distance is secured. If an enemy hides behind a rock or tree, it can not be detected by the current radar system. Also, it is impossible to detect a moving person or a vehicle using the Doppler effect. In addition, current boundary and guard systems do not have the ability to cope with risks in real time, so there is little effective way to approach intruders. As a method for solving such a problem, a drone which is remotely adjusted for confirmation or action is put into a corresponding position when an intruder's intrusion is detected by a radar or the like, and the necessary operation is performed to thereby rely on passive detection There is a need to create an automated border and guard system that can provide active troubleshooting in expense.

The drone may include a wind speed, a weather vane, an inertial sensor, a pressure temperature sensor, a video device, a sound device, an ultrasonic device, and an infrared ray imaging device to acquire additional information that the radar can not provide. The drone is equipped with such a sensor and various large application devices to detect the coordinates of the radar and to detect the coordinates of the radar.

Generally, the coordinate transmitted by the Doppler laser to the drone is calculated by the following algorithm.

The Doppler radar scans the reflected energy to calculate the distance to the moving object, generates the Doppler map based on the distance, and outputs the detected coordinate value when the energy reflection amount is larger than the designated amount. In order for object detection to be converted to distance and displayed on the map, the amount of energy reflection must exceed the specified amount of minimum unit.

The following parameters can be adjusted so that the user can conveniently use the target detection.

First, it is a parameter related to background noise and wind speed over a long time (maximum several minutes).

Secondly, it is detection sensitivity. Set from 1 to 10, with 10 being the most sensitive.

Third is the minimum movement speed. It can be set from 0.11m / s to 1.14m / s.

In Doppler map, the element that analyzes the algorithm related to the wind speed is set to a longer time. (Minutes instead of seconds)

It can be set in conjunction with information such as video, sound, and ultrasonic waves sent by a drone when setting parameters. Especially, various sensors such as wind speed and weather vane mounted on the drone can set the detection parameters of the radar using the information about the target, not the information of the base station operating the radar and the drone So that the accuracy can be increased.

For the tracking algorithm to work, the detection algorithm must exceed the minimum unit of detection for the above parameters. However, even if the minimum speed of the intruder is set to the lowest level, for example, if the intruder or the movement of the object is captured by the sensor of the drone, the target is kept as the detected target.

Once the target is detected, this value is passed to the tracking algorithm. The detection algorithm proceeds separately from the tracking algorithm. The Doppler radar internally runs the detection algorithm several times per second and outputs the above information every second.

On the other hand, there is an algorithm for tracking an object detected separately from the above detection algorithm. The role of this tracking algorithm is to initiate new traces or set criteria for existing traces. This tracking algorithm does not classify the type of target. That is, the target is not an animal, human, or vehicle.

The user can adjust the minimum detection distance. You can also adjust the number of goal tracking and the time that the tracking algorithm should be running.

The tracking algorithm tracks the detected target by applying a gate. Algorithms can be tracked while maintaining uniformity only within a range of distances, angles, and velocities. As you leave this gate, you may add or remove tracks from your target with a new target.

거리 게이트(Gate): +-10m

Distance Gate: + -10m

각도 게이트(Gate): +-10 degrees

Angle Gate (Gate): + -10 degrees

속도 게이트(Gate): +-1m/s

Speed gate (Gate): + -1m / s

The size of the gate as the default value can be changed in real time by the information sent from the drone. For example, for an intruder moving fast forward and backward, a range gate is enlarged and conversely, It is possible to construct a flexible system, such as increasing the angle gate for the intruder.

It is possible to increase classification accuracy of people and vehicles through object recognition algorithms and the like by image information sent by a drone

In determining the validity of the target, that is, whether to keep track, the information of the radar as well as the information of the drone can be determined by fusion.

The tracking algorithm estimates the position at which the target moves to the next position according to the speed of the target. To optimize this algorithm, the tracking stop time can be arbitrarily specified.

The tracking algorithm can also use an average of the coordinate values to minimize errors.

On the other hand, in the process of moving the drone to the set target, a problem of route setting occurs. Drone, however, does not necessarily have to fly at a straight line, and it may bypass obstacles or strategic routes. While the drone is flying to the target set to the coordinate value, the position of the drone itself can be grasped by the GPS or the inertial sensor in order to avoid collision with buildings or trees, The apparatus can detect the current position and speed of the drone by using a radar and transmit the data to the drone again so that the flight path can be interlocked in real time. Then, even if the GPS signals are disturbed, the drone can successfully fly to the target point. At this time, the flight path planning can be performed by a radar device or a drone's navigation device.

The drone also has an automatic return function. The Drone first interacts with the Doppler Radar in real time to calculate the minimum return battery capacity and automatically return to the designated location when it reaches it. The place of return may be the initial place of departure or the point newly established by the Radar system. If the radar signal is lost, you can use the GPS signal to return to the origin. If the disturbance is disturbed by the GPS signal, the camera traverses the trajectory using the image signal.

The present invention enables to detect enemies at close distance even in bad weather such as fog which is difficult to detect with the boundary guard system, and to attack when necessary, thereby enhancing the efficiency of boundary and capable of suppressing intruders.

FIG. 1 is a block diagram of a detection and boundary cost suppression system using a Doppler radar and a drone according to the present invention.
Figure 2 is a flow chart of an operating method of a system according to the present invention;
3 is a block diagram of a wireless communication exchange according to the present invention.

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

FIG. 1 is an overall system diagram of the present invention. When a Doppler radar 300 moves the movement of a target 400 at a distance of 0.11 meters per hour or more, the movement of the target 400 is detected and tracked using coordinates And transmits the coordinate value to the base station 200. The base station 200 transmits the coordinate values to the drone 100 through wireless communication such as WiFi, LTE, And the drone (100) receives this coordinate value and automatically moves to the target by the operator's instruction.

FIG. 2 is a flowchart illustrating an operation of the present invention. The Doppler radar detects a target through an algorithm (S100), generates coordinates and transmits the coordinates to a server (S200) Informs the operator of the detection, the operator can automatically or manually select the movement of the drone (S300) to the vicinity of the above coordinates. If the operator selects to move manually (S400), the drone is manually moved by the operator to the vicinity of the target. If the operator selects to move automatically (S500), the drone automatically moves to the vicinity of the target using the coordinate values provided by the GPS and the Doppler radar.

The drone 100 moving near the target is identified (S600) by using a camera, an Intra Red Camera, a laser scan or the like and confirms the target.

At this time, the operator can select the attack, attack the target (S800), and return to the designated position (S900). In order to take appropriate countermeasures against intruders, it is possible to equip them with netting, explosives, laser indicating devices, lighting devices and the like.

100: Drone
101: Propeller
102: Antenna
200: base station
201: PC with server function
202: Transmitter Transmitter
203: receiver in transceiver
300: Doppler radar
400: Target

Claims (3)

In boundary and cost automation systems using radar and drone,
It is necessary for the drone to acquire additional information that the radar does not provide and for this purpose it is necessary to provide the drone with the information such as wind speed, weather vane, inertial sensor, pressure temperature sensor, image device, sound device, Apparatus and the like and that the detection parameter of the radar can be varied by using the information of the drone.
At this time, the information can be used not only in the base station but also in the vicinity of the target.
The target detection criterion can also be changed according to the drone information. For example, if the movement of an intruder is captured by an image, an ultrasonic wave, or an infrared sensor held by a drone, the target remains as a detected target even if the radar target detection criterion is not satisfied. In the first aspect of the present invention, the tracking algorithm tracks a detected target by applying a gate. At this time, the size of the gate as a default can be varied in real time by information sent from a drone
It is possible to determine not only the information of the radar but also the information of the drone in the determination of the validity of the target such as tracking of the person and the vehicle through the image information and the object recognition algorithm sent by the drone, Can also be determined by fusion. In the above claim 1, the radar can track its own drone as an object. Using this information, it is possible to access the target and generate information and commands necessary for returning to the base station.

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