Method and device for providing engagement information based on occurrence of non-linear maneuver of aircraft, and storage medium storing instructions to perform method for providing engagement information

Patent metadata

Field	Value
Publication number	US-12560416-B2
Application number	US-202418781312-A
Country	US
Kind code	B2
Filing date	Jul 23, 2024
Priority date	Mar 4, 2024
Publication date	Feb 24, 2026
Grant date	Feb 24, 2026

Abstract

Proposed is a method for providing engagement information. The method may include obtaining detection information related to an aircraft detected by radar, and obtaining preliminary information including information on enemy units, friendly units, and friendly facilities. The method may also include determining whether the aircraft is performing non-linear maneuver including pull up maneuver from the detection information and the preliminary information using a pre-trained neural network, and predicting an impact point of the aircraft based on whether the non-linear maneuver of the aircraft are performed. The method may further include generating an engagement strategy for the aircraft to display an intercept point based on the impact point. The determining whether the aircraft is performing the non-linear maneuver may include predicting a timing of the non-linear maneuver based on location information of a target aimed at by the aircraft.

First claim

What is claimed is:

1 . A method for providing engagement information performed by an engagement information providing apparatus including an input/output interface and a communication interface, the method comprising:
obtaining detection information related to an aircraft detected by radar via the communication interface; obtaining preliminary information including information on enemy units, friendly units, and friendly facilities via the communication interface; determining whether the aircraft is performing non-linear maneuver including pull up maneuver from the detection information and the preliminary information using a pre-trained neural network; predicting an impact point of the aircraft based on whether the non-linear maneuver of the aircraft are performed; and generating an engagement strategy for the aircraft to display an intercept point based on the impact point, wherein the engagement strategy includes at least one of an altitude of the aircraft, a range of an interception system, or an availability of the interception system, wherein the determining comprises, in response to the aircraft performing non-linear maneuver, predicting a timing of the non-linear maneuver based on location information of a target aimed at by the aircraft, wherein the location information of the target is obtained via the communication interface, and wherein the generating comprises: predicting the intercept point in a glide section of the aircraft based on the predicted timing of the non-linear maneuver, wherein the intercept point varies depending on the predicted timing of the non-linear maneuver; and displaying the predicted intercept point in the glide section of the aircraft via the input/output interface.

2 . The method of claim 1 , wherein the predicting comprises determining a timing when the aircraft approaches a preset distance from the location information of the target as the timing of the non-linear maneuver.

3 . The method of claim 2 , wherein the target is set based on priority of information on the friendly units and friendly facilities.

4 . The method of claim 3 , wherein the predicting comprises predicting the timing of the non-linear maneuver of the aircraft based on the location information of the target with a highest priority using the priority of information on the friendly units and friendly facilities.

5 . The method of claim 1 , wherein the generating comprises:
predicting an auxiliary intercept point in a horizontal glide flight section after the non-linear maneuver of the aircraft based on the predicted timing of the non-linear maneuver; and displaying the predicted auxiliary intercept point in the horizontal glide flight section via the input/output interface.

6 . The method of claim 1 , wherein obtaining the detection information comprises extracting dynamic characteristic information of the aircraft detected by the radar by replaying a video including the detected aircraft, and
wherein the video is generated by post-processing radar signal data to visualize a movement of the aircraft.

7 . The method of claim 6 , wherein the dynamic characteristic information comprises at least one of a launch point of the aircraft, movement locations of the aircraft, a movement trajectory of the aircraft, a speed of the aircraft, an acceleration of the aircraft, or a radar cross section (RCS) of the aircraft.

8 . The method of claim 1 , wherein the neural network is trained by discriminating whether the aircraft is performing the non-linear maneuver corresponding to the detection information and the preliminary information, and
wherein the neural network comprises:
an input layer for inputting-a training detection information and training preliminary information;
an output layer for setting training label information specifying whether the aircraft is performing the non-linear maneuver; and
a model parameter for a correlation between the training detection information and the training preliminary information with respect to an occurrence of the non-linear maneuver of the training label information using a supervised learning algorithm.

9 . The method of claim 8 , wherein obtaining the detection information comprises extracting dynamic characteristic information of the aircraft detected by the radar by replaying a video including the detected aircraft,
wherein the training detection information comprises the extracted dynamic characteristic information, and wherein the video is generated by post-processing radar signal data to visualize a movement of the aircraft.

10 . A device for providing engagement information, the device comprising:
a communication interface configured to obtain detection information related to an aircraft detected by radar, and preliminary information including information on enemy units, friendly units, and friendly facilities; an input/output interface; a memory configured to store one or more instructions; and one or more processors configured to execute the one or more instructions to:
determine whether the aircraft is performing non-linear maneuver including pull up maneuver from the detection information and the preliminary information using a pre-trained neural network;
predict an impact point of the aircraft based on whether the non-linear maneuver of the aircraft are performed;
generate an engagement strategy for the aircraft to display an intercept point based on the impact point, wherein the engagement strategy includes at least one of an altitude of the aircraft, a range of an interception system, or an availability of the interception system; and
in response to the aircraft performing non-linear maneuver, predict a timing of the non-linear maneuver based on location information of a target aimed at by the aircraft, wherein the location information of the target is configured to be obtained via the communication interface,
wherein at least one of the one or more processors is configured to:
predict the intercept point in a glide section of the aircraft based on the predicted timing of the non-linear maneuver, wherein the intercept point varies depending on the predicted timing of the non-linear maneuver, and
display the predicted intercept point in the glide section of the aircraft via the input/output interface.

11 . The device of claim 10 , wherein at least one of the one or more processors is configured to determine a timing when the aircraft approaches a preset distance from the location information of the target as the timing of the non-linear maneuver.

12 . The device of claim 11 , wherein the target is configured to be set based on priority of information on the friendly units and friendly facilities.

13 . The device of claim 12 , wherein at least one of the one or more processors is configured to predict the timing of the non-linear maneuver of the aircraft based on the location information of the target with a highest priority using the priority of information on the friendly units and friendly facilities.

14 . The device of claim 10 , wherein at least one of the one or more processors is configured to predict an auxiliary intercept point in a horizontal glide flight section after the non-linear maneuver of the aircraft based on the predicted timing of the non-linear maneuver, and display the predicted auxiliary intercept point in the horizontal glide flight section.

15 . The device of claim 10 , wherein the neural network is configured to be trained by discriminating whether the aircraft is performing the non-linear maneuver corresponding to the detection information and the preliminary information, and

Assignees

• Agency Defense Dev

Inventors

• Jeon Hocheol
• Choi Hyoek Jin
• Choi Jae Kak
• Kim Young Min

Classifications

• F41G7/002

  target simulators · CPC title

• G08G5/21

  located onboard the aircraft · CPC title

• F41G7/224

  Deceiving or protecting means (jamming or anti-jamming of radio-wave systems in general G01S7/36, G01S7/38; defense installations in general F41H11/02; chaff dispensers F42B12/70) · CPC title

• G01S13/723

  by using numerical data · CPC title

• F41G7/007

  Preparatory measures taken before the launching of the guided missiles · CPC title