A thunder and lightning combined unmanned aerial vehicle flight attitude automatic decision method

Abstract

The application provides a lightning and unmanned aerial vehicle flight attitude automatic decision method, and aims at an unmanned aerial vehicle detection and countermeasure system comprising a radar with an automatic starting function and an infrared photoelectric device with an automatic zooming function; after the countermeasure device executes a deception or interference countermeasure on the unmanned aerial vehicle, the radar target track and the optical image are used to process and extract features of information obtained by each sensor, so that feature parameters required for unmanned aerial vehicle flight attitude decision are obtained, and the flight attitude of the unmanned aerial vehicle after the countermeasure is further judged, thereby providing a reference for next countermeasure decision. The method effectively solves the problem of unmanned aerial vehicle flight attitude judgment after the unmanned aerial vehicle detection and countermeasure system takes countermeasures, and lays a foundation for automatic evaluation and automatic judgment of the anti-unmanned aerial vehicle system.

Description

Technical Field

[0001] This invention is applicable to the field of drone countermeasures, and in particular relates to a method for evaluating the effectiveness of drone countermeasures. Background Technology

[0002] Unmanned aerial vehicle (UAV) detection and countermeasure systems are used to detect and counter UAVs. For systems incorporating jamming and suppression countermeasures, radar, photoelectric, and electronic reconnaissance sensors are used to detect UAVs. These systems guide the jamming and countermeasures equipment to select appropriate countermeasures based on different scenarios, such as communication link jamming, navigation suppression jamming, pinpoint trapping, directional expulsion, and no-fly zones. The effectiveness of different countermeasures varies, and different UAVs react differently to jamming and deception. Possible reactions include UAVs crashing, landing, returning to base, hovering, and continuing forward. The system needs to determine the UAV's flight attitude after being countermeasured, assess the effectiveness of the countermeasures, and decide on the next course of action. This requires judging the UAV's flight attitude.

[0003] "A Countermeasure Method and System for Unmanned Aerial Vehicles" proposes a countermeasure method that uses a countermeasure drone carrying near-explosive charges to directly attack unauthorized drones. "An Evaluation Method for a Civil Unmanned Aerial Vehicle Countermeasure System" provides evaluation indicators and methods for the countermeasure system, but does not provide a method for judging the flight attitude of the drone, which is not conducive to quickly judging the flight attitude of the drone and taking the next step. Summary of the Invention

[0004] To address the problem of automatically determining the flight attitude of drones after the execution of drone detection and countermeasure systems, this invention proposes a method for automatically determining the flight attitude of drones using a combination of lightning and optical methods.

[0005] To achieve the above objectives, this invention utilizes radar-detected flight paths and image information acquired by optoelectronic devices in a UAV countermeasure system to analyze and extract feature parameters, and determines the UAV's flight attitude based on these feature parameters. The technical solution includes:

[0006] The first step is to analyze the data from three moments, T0, T1 = T0 + T, and T2 = T0 + 2T, 5 seconds after the countermeasure is activated, for the drone flying in the initial direction of the countermeasure and the image data generated by the radar detection and the photoelectric / infrared sensing.

[0007] The second step is to take three radar track data points from the two consecutive cycles: Track0, Track1, and Track2. These three track data points correspond to T0, T1 = T0 + T, and T2 = T0 + 2T, respectively, for analysis.

[0008] Extract the heading information from the track, denoted as H0, H1, and H2, and calculate using the following formula:

[0009] △H1=H1-H0

[0010] △H2=H2-H0

[0011] In the formula: △H1 and △H2 represent the degree of heading change at times T1 and T2, respectively.

[0012] The third step involves taking the target image acquired by the infrared / optoelectronic equipment. Under stable target tracking conditions, the lens azimuth points to θ1 and θ2, the elevation angle points to β1 and β2, and the lens focal lengths are f1 and f2, respectively, with the target to be driven away at θ0 and the target elevation angle to be driven away at β0. The following parameters are calculated:

[0013] △θ1=|θ1-θ0|, △θ2=|θ2-θ0|, △β1=|β1-β0|, △β2=|β2-β0|

[0014] △f=f2-f1, △β=β2-β1

[0015] In the formula: △θ represents the azimuth deviation between the lens pointing and the driving direction, △β represents the elevation angle deviation between the lens pointing and the driving direction, and △f represents the degree of change in the lens focal length.

[0016] Fourth step: Make a comprehensive judgment based on the above parameters:

[0017] The flight path information is stable, the image is stable and clear, and △H1-△H2<-ε H , △f<-ε f Assessment: The drone is in normal condition and will continue flying towards the station.

[0018] Target information is lost, but the image is stable and clear; |△θ2-△θ1|<ε θ And |△β2-△β1|<ε β And |△f|<ε f Judgment: The drone is hovering.

[0019] Target track lost, image stable and clear, |△f|<ε f If △β < 0, it indicates that the drone has landed.

[0020] The flight path information is stable, the image is stable and clear, and ΔH2 - ΔH1 > ε. H , △f>ε f The drone returned to base.

[0021] The flight path information is stable, the image is stable and clear, and △θ2-△θ1<-ε θ , △β2-△β1<-εβ The drone flies in the direction of the drive-away. Preferably, the radar period T ≥ 2s;

[0022] Preferably, the ε θ =0.05°;

[0023] Preferably, the ε β =0.05°;

[0024] Preferably, the ε f =0.1mm;

[0025] Preferably, the ε H =0.01°.

[0026] This invention targets a UAV detection and countermeasure system composed of detection sensors including radar and optical sensors. After countermeasures are implemented, the system acquires target trajectory and image information through radar and optical sensors. By analyzing the information, it extracts the trajectory change rate, the degree of focal length change corresponding to the photoelectric image, and the degree of lens pointing change, constructs a decision model, and obtains the current flight attitude of the UAV. This provides a reference for taking the next countermeasure measures and has significant engineering application value. Attached Figure Description

[0027] Appendix Figure 1 Flowchart for automatic flight attitude determination of drones using a combination of radar and optical sensors. Detailed Implementation

[0028] The invention will be further explained below with reference to the accompanying drawings.

[0029] This invention proposes a radar-optical combined method for automatically determining the flight attitude of unmanned aerial vehicles (UAVs) in a UAV detection and countermeasure system that incorporates radar with automatic start-up functionality and infrared optoelectronic devices with automatic zoom. After the countermeasure device performs deception or jamming against the UAV, the method utilizes radar target tracks and optical images to process and extract features from the information acquired by each sensor. Based on the feature parameters, it determines whether the UAV's flight attitude after being countermeasured is to crash, land, return to base, hover, or continue normally, serving as the basis for further countermeasure decisions. This method effectively solves the problem of evaluating the UAV's reaction after countermeasures are taken in multi-method UAV detection and countermeasure systems, providing strong support for the engineering application and promotion of anti-UAV systems.

[0030] The present invention proposes a method for automatic flight attitude determination of unmanned aerial vehicles (UAVs) combining lightning and light, and the flowchart of a preferred embodiment is attached. Figure 1 As shown, the specific description is as follows:

[0031] Suppose there is a drone flying towards a drone countermeasure system. After the drone countermeasure system detects it and takes countermeasures, the drone's flight attitude changes after being countered. At this time, the radar track and the electro-optical image are stable.

[0032] For the flight tracks generated by radar detection and the image data generated by photoelectric / infrared sensing, data from both sources at the same time are analyzed.

[0033] Take data from two consecutive radar cycles (T≥2s) (T0, T1=T0+T, T2=T0+2T, Track0, Track1, and Track2 correspond to times T0, T1, and T2, respectively).

[0034] Extract the heading information from the track, denoted as H0, H1, and H2, and calculate using the following formula:

[0035] △H1=H1-H0

[0036] △H2=H2-H0

[0037] In the formula: △H1 and △H2 represent the degree of heading change at time 1 and time 2, respectively.

[0038] For target images acquired by infrared / optoelectronic devices, under stable target tracking conditions, images from two consecutive cycles are extracted. Lens pointing directions θ1 and θ2, lens focal lengths f1 and f2, and the direction of target departure θ0 are extracted. The following parameters are calculated:

[0039] △θ1=|θ1-θ0|, △θ2=|θ2-θ0|, △β1=|β1-β0|, △β2=|β2-β0|

[0040] △f=f2-f1, △β=β2-β1

[0041] In the formula: △θ represents the azimuth deviation between the lens pointing and the driving direction, △β represents the elevation angle deviation between the lens pointing and the driving direction, and △f represents the degree of change in the lens focal length.

[0042] At this point, if △H2—△H1>0.01° and △f>0.1mm, it can be determined that the UAV is moving away from the detection equipment and is in a return-to-home state.

Claims

1. A method for automatically determining the flight attitude of a UAV using a combination of lightning and optical signals, characterized in that: Step 1: For a drone flying in the initial flight direction toward the countermeasure device, after the countermeasure is activated for 5 seconds, analyze the data from the flight path generated by the radar detection and the image data generated by the photoelectric / infrared sensing, taking the data from three moments in two consecutive radar cycles T: T0, T1 = T0 + T, and T2 = T0 + 2T. Step 2: Take three radar track data points from the two consecutive cycles, Track0, Track1, and Track2. The three track data points Track0, Track1, and Track2 correspond to T0, T1 = T0 + T, and T2 = T0 + 2T respectively for analysis. Extract the heading information from the track, denoted as H0, H1, and H2, and calculate using the following formula: △H1=H1-H0 △H2=H2-H0 In the formula: △H1 and △H2 are the degrees of change in heading at times T1 and T2, respectively; Step 3: For the target image acquired by the infrared / optoelectronic equipment, under the condition of stable target tracking, take the lens azimuth pointing to θ1, θ2 and the elevation angle pointing to β1, β2 at two consecutive time points T1 and T2, the lens focal length f1, f2, the azimuth of the target to be driven away as θ0, and the elevation angle of the target to be driven away as β0, and calculate the following parameters: △θ1=|θ1-θ0|, △θ2=|θ2-θ0|, △β1=|β1-β0|, △β2=|β2-β0| △f=f2-f1, △β=β2-β1 In the formula: △θ represents the azimuth deviation between the lens pointing and the driving direction, △β represents the elevation deviation between the lens pointing and the driving direction, and △f represents the degree of change in the lens focal length; Step 4: Make a comprehensive judgment based on the above parameters: The flight path information is stable, the image is stable and clear, and △H1-△H2<-ε H And Δf < -ε f Assessment: The drone is in normal condition and will continue flying towards the station. Target information is lost, but the image is stable and clear; |△θ2-△θ1|<ε θ And |△β2-△β1|<ε β And |△f|<ε f Judgment: The drone is hovering. The target track is lost, the image is stable and clear, |△f|<ε f If △β < 0, then the drone has landed. The flight path information is stable, the image is stable and clear, and ΔH2 - ΔH1 > ε. H And △f>ε f Judgment: The drone returned to base. The flight path information is stable, the image is stable and clear, and △θ2-△θ1<-ε θ Judgment: The drone flew in the direction of the expulsion.

2. The automatic flight attitude determination method for UAVs combining lightning and light as described in claim 1, characterized in that: The radar period T ≥ 2s.

3. The automatic flight attitude determination method for UAVs combining lightning and optical signals according to claim 1, characterized in that: The ε θ =0.05°.

4. The automatic flight attitude determination method for UAVs combining lightning and optical signals according to claim 1, characterized in that: The ε β =0.05°.

5. The automatic flight attitude determination method for UAVs combining lightning and light as described in claim 1, characterized in that: The ε f =0.1mm.

6. The automatic flight attitude determination method for UAVs combining lightning and light as described in claim 1, characterized in that: The ε H =0.01°.

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