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A security level prediction method and system for UAV clusters

A security level, unmanned aerial vehicle technology, applied in control/regulation systems, complex mathematical operations, instruments, etc., can solve problems such as unsuitable drone clusters

Active Publication Date: 2021-02-05
NAT INNOVATION INST OF DEFENSE TECH PLA ACAD OF MILITARY SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, similar approaches rely on monitoring centers and are not suitable for autonomous drone swarms

Method used

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  • A security level prediction method and system for UAV clusters
  • A security level prediction method and system for UAV clusters
  • A security level prediction method and system for UAV clusters

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Embodiment 1: as figure 1 As shown, the present invention provides a method for predicting and evaluating the safety level of unmanned aerial vehicle clusters, including:

[0052] S1 Based on the set UAV cluster failure type, each individual UAV in the UAV cluster calculates its own performance degradation trajectory based on its own flight status data;

[0053] S2 Each individual UAV obtains the cumulative failure probability prediction value based on its own performance decline track;

[0054] S3 Determine the safety level of the UAV cluster based on the cumulative failure probability prediction value combined with a preset evaluation index.

[0055] pass figure 2 right figure 1 Provided technical solutions for specific analysis, including: failure type analysis of UAV swarms, data collection of UAV flight status, feature extraction of UAV performance degradation, cumulative failure probability of UAV swarms and analysis of UAV Cluster security level evaluation. ...

Embodiment 2

[0126] Embodiment 2: In this embodiment, a cluster composed of six quadrotor UAVs is used for case analysis, and the specific implementation steps are as follows:

[0127] (1) Adapt the output interface of the individual UAV flight controller in the cluster to collect the output data of the airborne sensors.

[0128] The airborne sensor output data types used include: GPS latitude (unit: degree), GPS longitude (unit: degree), heading angle (unit: degree), pitch angle (unit: degree), roll angle (unit: degree) , horizontal flight speed (unit: mm / s), vertical flight speed (unit: mm / s), altitude measured by the barometer (unit: m), body temperature (unit: degree), vibration acceleration in the three-axis direction (Unit: m / s 2 ), the voltage value of the flight controller (unit: V), and the magnetic heading angle (unit: degree).

[0129] (2) Analyze the failure types of UAV clusters, and select the rough features of the failure of the whole machine. The coarse features selected...

Embodiment 3

[0157] Embodiment 3: Based on the same inventive concept, the present invention also provides a safety level prediction system for drone clusters, including:

[0158] The first calculation module is used to calculate the performance decline track of each individual drone in the drone cluster based on its own flight state data based on the set failure type of the drone cluster;

[0159] The second calculation module is used for each individual UAV to obtain a cumulative failure probability prediction value based on its own performance decline track;

[0160] A determining module, configured to determine the safety level of the unmanned aerial vehicle cluster based on the cumulative failure probability prediction value combined with a preset evaluation index.

[0161] In an embodiment, the first calculation module includes:

[0162] The analysis unit is used to analyze the airborne sensor data from the output interfaces of the controllers of all the drones in the cluster based ...

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Abstract

The invention discloses a security level prediction method and system for an unmanned aerial vehicle cluster. The method comprises the steps: calculating the performance degradation orbit of each individual unmanned aerial vehicle in an unmanned aerial vehicle cluster based on the flight state data of the individual unmanned aerial vehicle based on a set unmanned aerial vehicle cluster failure type; each individual unmanned aerial vehicle obtains a cumulative failure probability prediction value based on the performance degradation orbit of the individual unmanned aerial vehicle; subscribing the cumulative failure probability prediction values broadcasted by all the individual unmanned aerial vehicles by the piloting aircraft, and calculating the danger failure probability of the unmannedaerial vehicle cluster; and the piloting aircraft determines the safety level of the unmanned aerial vehicle cluster based on the danger failure probability of the unmanned aerial vehicle cluster. According to the technical scheme, the cognitive ability of the unmanned aerial vehicle cluster to the safety and risk of the unmanned aerial vehicle cluster can be improved, and the destroy-resistant ofthe unmanned aerial vehicle cluster is indirectly improved.

Description

technical field [0001] The invention relates to the field of safety and risk assessment of unmanned aerial vehicle clusters, in particular to a safety level prediction method and system for unmanned aerial vehicle clusters. Background technique [0002] In a dynamic environment, it is a very challenging technical problem for UAV swarms to perform complex cooperation and formation transformation. However, the premise of performing these actions is that UAV swarms must be able to recognize their own security status. For UAVs with autonomous flight capabilities, since humans withdraw from direct control, higher requirements are placed on the safety and risk status of UAVs. As long as drones are used, there are risks. The risk of drone clusters is much higher than that of a single drone. The introduction of artificial intelligence has exacerbated the possibility of drones being subject to moral ambiguity or even malicious use of technology. Hackers can infiltrate systems to pro...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/10G06F17/16G06F17/18
CPCG05D1/104G06F17/16G06F17/18
Inventor 赵林任小广王彦臻
Owner NAT INNOVATION INST OF DEFENSE TECH PLA ACAD OF MILITARY SCI
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