Reconnaissance type unmanned aerial vehicle full-scene identification friend or foe automatic inquiry method

Abstract

The invention particularly relates to a full-scene identification friend or foe automatic inquiry method for a reconnaissance type unmanned aerial vehicle. The method comprises the following steps: judging whether a laser ranging value is valid or not in real time; under the condition that the laser ranging values are valid, whether a static target inquiry scene is entered or not is judged based on the laser ranging values in a plurality of continuous sampling periods; judging whether a moving target inquiry scene is entered or not based on the laser working state; based on the laser aiming azimuth angle rate or the laser aiming line pitch angle rate, judging whether to enter an inquiry scene during tracking target switching in the field of view or not; and calculating an identification matching probability of multiple inquiry results, and carrying out friend or foe identification based on the identification matching probability. The method can solve the defects that an existing unmanned aerial vehicle system has a plurality of targets needing to be inquired in some view fields, the terrain where the targets are located is complex, an operator needs to frequently and manually send inquiry instructions under the scenes where the moving targets need to be inquired, the inquiry instructions are not sent in time, and the error of the inquiry result of single inquiry is large.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle identification, and in particular to an automatic friend-or-foe identification query method for a reconnaissance unmanned aerial vehicle in all scenarios. Background Art

[0002] In the related technology, most of the current reconnaissance drones are equipped with IFF interrogator equipment to realize the function of identifying friend or foe attributes, but they all use the method of manually sending interrogation commands to identify the friend or foe attributes of the reconnaissance target. In some scenarios where there are multiple targets to be interrogated in the field of view, the terrain of the targets is complex, and moving targets need to be interrogated, not only does the operator need to frequently send interrogation commands manually to conduct interrogations, but some interrogation scenarios also require the operator to make accurate and real-time interrogation command sending responses. These requirements not only increase the operating burden of the drone operator, but also easily cause interrogation result errors due to untimely sending of commands, and there are certain defects.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0004] The present invention provides an automatic interrogation method for friend-or-foe identification in all scenarios of a reconnaissance drone, which is used to solve the problems of cumbersome operation, slow response speed and large error in the interrogation result caused by the untimely sending of interrogation commands when the operator manually sends interrogation commands to inquire about friend-or-foe attributes in certain interrogation scenarios.

[0005] Other features and advantages of the present invention will become apparent from the following detailed description, or may be learned in part by practice of the present invention.

[0006] According to a first aspect of the present invention, a full-scene friend-or-foe identification automatic query method for a reconnaissance drone is provided, the method comprising:

[0007] Real-time acquisition of the laser ranging value, laser working status, laser aiming azimuth rate, and laser aiming line pitch rate of the UAV’s airborne laser launching equipment;

[0008] Real-time judgment on whether the laser distance measurement value is valid;

[0009] When the laser ranging value is valid: determine whether to enter the static target interrogation scene based on the laser ranging value in multiple continuous sampling cycles; determine whether to enter the moving target interrogation scene based on the laser working state; determine whether to enter the interrogation scene when switching to the tracking target in the field of view based on the laser aiming azimuth rate or the laser aiming line pitch rate;

[0010] After the above judgment, when it is found that the drone enters an interrogation scenario of switching between static targets, moving targets or tracking targets in the field of view, an automatic interrogation command needs to be sent; the recognition matching probability of multiple interrogation results is calculated, and friend-or-foe identification is performed based on the recognition matching probability.

[0011] In some exemplary embodiments, the method for acquiring the laser aiming azimuth rate and the laser aiming line pitch rate includes:

[0012] Determine the laser aiming azimuth rate based on the difference between the azimuth of the laser aiming line currently sampled and the azimuth of the laser aiming line last sampled and the acquisition period;

[0013] The laser aiming pitch angle rate is determined based on the difference between the pitch angle of the laser aiming line currently sampled and the pitch angle of the laser aiming line last sampled and the acquisition period.

[0014] In some exemplary embodiments, the real-time determination of whether the laser ranging value is valid includes:

[0015] Determine whether the laser distance measurement value is between the minimum valid value and the maximum valid value. If it is between the two, it is valid.

[0016] In some exemplary embodiments, the step of querying whether to enter a static target scene based on laser ranging values ​​in a plurality of consecutive sampling periods includes:

[0017] When the laser ranging values ​​in multiple consecutive sampling cycles are all within the given range, the static target interrogation scene is entered; the minimum value of the given range is the difference between the laser ranging value of the last sample and the maximum value of the ranging value change in one sampling cycle; the maximum value of the given range is the sum of the laser ranging value of the last sample and the maximum value of the ranging value change in one sampling cycle.

[0018] In some exemplary embodiments, the method for determining the maximum value of the distance measurement value change within one sampling period is:

[0019] It is the sum of the product of the UAV ground speed value at the last sampling and the sampling period plus the fluctuation range of the laser ranging value.

[0020] In some exemplary embodiments, judging whether to enter a moving target interrogation scene based on the laser working state includes:

[0021] When it is detected that the laser working state changes from other states to the target tracking state, it indicates that the UAV system is tracking a moving target and entering the moving target interrogation scene.

[0022] In some exemplary embodiments, the query scenario for determining whether to switch to a tracking target within the field of view based on the laser aiming azimuth rate includes:

[0023] When the laser platform is in the target tracking state and meets the following conditions:

[0024]

[0025] in, is the change threshold of the azimuth rate of the laser aiming line, ω1 and ω1′ are the azimuth rates of the laser aiming line at the current and last sampling times, respectively, and continue to monitor the azimuth rates that meet the requirements in the subsequent seconds.

[0026] (Δω1′≤0)∧(Δω1=0)

[0027] Among them, Δω1=|ω1|-|ω1′|, Δω1′ is the Δω1 value calculated after the last sampling, and the inquiry scene when the target switches into the field of view is determined.

[0028] In some exemplary embodiments, the query scenario for determining whether to switch to a tracking target within the field of view based on the laser aiming pitch angle rate includes:

[0029] When the laser platform is in the target tracking state and meets the following conditions:

[0030]

[0031] in, is the change threshold of the laser sight line pitch angle rate, ω2 and ω2′ are the pitch angle rates of the laser sight line at the current and last sampling times, respectively, and continue to monitor the rate of change in the subsequent seconds.

[0032] (Δω2′≤0)∧(Δω2=0)

[0033] Among them, Δω2=|ω2|-|ω2′|, Δω2′ is the Δω2 value calculated after the last sampling, and the inquiry scene when the target switches into the field of view is determined.

[0034] According to a second aspect of the present invention, there is provided a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for automatic interrogation of friend-or-foe identification in all scenarios of a reconnaissance drone as described in the first aspect above is implemented.

[0035] According to a third aspect of the present invention, there is provided a computer program product having a computer program stored thereon, which, when executed by a processor, implements the full-scene friend-or-foe automatic interrogation method for reconnaissance drones as described in the first aspect.

[0036] The embodiment of the present invention provides a full-scene automatic interrogation method for friend-or-foe identification of reconnaissance drones. By automatically identifying and analyzing the time when friend-or-foe attribute inquiries are required, automatic interrogation can be achieved. This can solve the defects of existing drone systems in which operators need to frequently send manual interrogation commands, interrogation commands are not sent in a timely manner, and the results of a single interrogation have large errors in some scenarios where there are multiple targets to be interrogated in the field of view, the terrain of the targets is complex, and moving targets need to be interrogated.

[0037] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present invention, and together with the specification are used to explain the principles of the present invention. Obviously, the accompanying drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0039] Figure 1 A schematic diagram schematically illustrates the process of an automatic interrogation method for full-scene friend-or-foe identification of a reconnaissance drone according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0040] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0041] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0042] In view of the shortcomings and deficiencies of the prior art, this example implementation provides a full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones, which is used to achieve the following two purposes:

[0043] 1) Automatically identify the UAV inquiry scene. When the UAV enters the inquiry scene, it sends an automatic inquiry command to solve the problem of cumbersome manual instruction sending and slow instruction sending response speed in some inquiry scenes;

[0044] 2) Reduce the interrogation error caused by the failure to meet certain conditions such as the delay in the operation of the servo turntable mechanism in a single interrogation.

[0045] At present, the application scenarios that require inquiries from reconnaissance drones can be analyzed and abstracted into three typical inquiry scenarios that cover the entire scene, namely, inquiries to static targets, moving targets, and when switching between tracking targets in the field of view. At the same time, based on these three typical inquiry scenarios, automatic detection and inquiries can be performed.

[0046] refer to Figure 1 As shown, the specific method includes the following steps:

[0047] Step S1: Turn on the laser irradiation function of the UAV airborne laser emission equipment (provided by the optoelectronic reconnaissance payload and linked with the friend-or-foe identification interrogator equipment) to perform laser ranging;

[0048] Step S2: collect or calculate and record the range value L, laser aiming line azimuth rate ω1, laser aiming line pitch rate ω2, laser working state (target tracking state or other state) of the UAV airborne laser launching equipment in real time. ω1 and pitch rate ω2 can be calculated in real time according to the azimuth angle θ1 and pitch angle θ2 of the laser aiming line.

[0049] ω1=(θ1-θ1′) / T

[0050] ω2=(θ2-θ2′) / T

[0051] Where T is the time period for data collection, θ1′ and θ2′ are the azimuth and elevation angles of the laser aiming line sampled last time;

[0052] Step S3: Determine whether the UAV has entered the static target inquiry scene: perform real-time judgment on the laser ranging value. When the laser ranging value satisfies 300m≤L≤16000m, the ranging value is considered valid (300m and 16000m can be determined according to the specific UAV system usage scenario), and at the same time, the laser ranging value meets L′-ΔL≤L≤L′+ΔL for 5 or more consecutive sampling cycles, where L′ is the laser ranging value of the last sampling, ΔL is the maximum value of the ranging value change in one sampling cycle, and ΔL can be approximately calculated as ΔL=V′*T+ΔD, where V′ is the UAV ground speed value at the last sampling, and ΔD is the fluctuation range of the laser ranging value (which can be measured and determined according to the specific UAV system). Then, it can be determined that the laser ranging value has reached a stable state, indicating that the UAV system is measuring the distance to a static target at this time and entering the static target inquiry scene is a time to inquire about the enemy and friend attributes. At this time, an automatic inquiry instruction can be sent;

[0053] For example, to determine whether a drone has entered a static target interrogation scenario: Assume that a drone is flying at a constant speed of 60.3 m / s and is measuring the distance to a static target. The data sampling and calculation cycle is 20 ms, and the fluctuation range ΔD of the laser ranging is 10 m. The calculation to determine whether a drone has entered a static target interrogation scenario is shown in the following table:

[0054]

[0055] The calculation results in the above table show that there are five consecutive sampling cycles that meet the judgment condition of L′-ΔL≤L≤L′+ΔL, indicating that the UAV system is currently measuring the distance to a static target and has entered a static target interrogation scenario. This is a time to inquire about friend-or-foe attributes, and an automatic interrogation command can be sent at this time.

[0056] Step S4: Determine whether the UAV has entered the moving target inquiry scene: perform real-time judgment on the laser ranging value. When the laser ranging value satisfies 300m≤L≤16000m, the ranging value is considered valid (300m and 16000m can be determined according to the specific UAV system usage scenario), and when it is detected that the working state of the laser platform changes from other states to the target tracking state, it indicates that the UAV system is tracking a moving target at this time and has entered the moving target inquiry scene. It is a time to inquire about the enemy and friend attributes. At this time, the automatic inquiry command can be sent;

[0057] Exemplarily, judging whether the drone has entered a moving target interrogation scenario: The calculation for judging whether the drone has entered a stationary target interrogation scenario is shown in the following table:

[0058]

[0059]

[0060] In the above table, from the first to the second sampling, the laser ranging value is valid, and the working state of the laser platform changes from the search state to the target tracking state, indicating that the UAV system is tracking a moving target at this time and has entered the moving target interrogation scene. It is a time to inquire about the enemy attributes, and the automatic interrogation command can be sent at this time.

[0061] Step S5: Determine whether the UAV enters the field of view to track the target. Inquiry scenario when switching: Real-time judgment is made on the laser ranging value. When the laser ranging value satisfies 300m≤L≤16000m, the ranging value is considered valid (300m and 16000m can be determined according to the specific usage scenario of the UAV system). When the laser platform is in the target tracking state and satisfies:

[0062]

[0063] in, is the change threshold of the azimuth rate of the laser sight line (which can be determined by the specific UAV system measurement), ω1′ is the azimuth rate of the laser sight line at the last sampling, and continues to monitor within the next 3s.

[0064] (Δω1′≤0)∧(Δω1=0)

[0065] Among them, Δω1=ω1|-ω1′|, Δω1′ is the Δω1 value calculated after the last sampling, which indicates that the laser emission azimuth angle of the UAV system has a large change and tends to be stable; similarly, when the laser ranging value is valid, when the laser platform is in the target tracking state and satisfies

[0066]

[0067] in, is the change threshold of the pitch angle rate of the laser sight line (which can be determined by the specific UAV system measurement), ω2′ is the pitch angle rate of the laser sight line at the last sampling, and continues to monitor if it meets the following 3s.

[0068] (Δω2′≤0)∧(Δω2=0)

[0069] Among them, Δω2=ω2-ω2′|, Δω2′ is the Δω2 value calculated after the last sampling, which indicates that the laser emission pitch angle of the UAV system has a large change and tends to be stable. When one or both of the above two conditions are met, it means that the UAV system has switched the reconnaissance target during ranging and target tracking, and has entered the interrogation scene when switching targets in the field of view. It is a time to inquire about the enemy and friendly attributes, and the automatic interrogation command can be sent at this time;

[0070] Exemplary, the query scenario for judging whether the drone enters the field of view when switching targets: The calculation of the query scenario for judging whether the drone enters the field of view when switching targets is shown in the following table (only taking the change of azimuth rate as an example, during the calculation process, the laser ranging values ​​are valid and the working state of the laser platform is in the target tracking state, and the change threshold of the azimuth rate of the laser aiming line is taken is 0.2° / s, and the sampling period is 60ms):

[0071]

[0072]

[0073] The calculation in the above table shows that the judgment meets the requirement at the 9th collection / calculation. The condition is met again within 3S (Δω1′≤0)∧(Δω1=0), indicating that the laser emission azimuth angle of the UAV system has a large change and tends to be stable. That is, the UAV system switches the reconnaissance target during ranging and target tracking, and enters the interrogation scene when switching targets in the field of view. It is a time to inquire about the attributes of the enemy and the friend, and the automatic interrogation command can be sent at this time.

[0074] Step S6: After the above calculation and judgment, if the drone enters the interrogation scene of static target, moving target or tracking target switching in the field of view, it is necessary to send an automatic interrogation command; in other cases, it is not necessary to send an interrogation command. When the enemy interrogation machine receives the interrogation command, it can conduct 5 or more interrogations and collect the corresponding interrogation results, and calculate the recognition probability. When the recognition matching probability exceeds 30%, the target can be considered to be ours, and if it is less than 30%, the target is considered to be unrecognized. This method can reduce the enemy attribute recognition error caused by system delay or misrecognition.

[0075] Exemplarily, when it is determined that the drone enters any one or more of the above-mentioned inquiry scenarios, an automatic inquiry command is sent. Assuming that the interrogator has conducted 5 inquiries, one of which has an unknown result and four have friendly results, the probability of identifying it as a friendly party is 80%, which is greater than the friendly judgment standard of 30%, and the inquiry result is a friendly party.

[0076] The full-scenario friend-or-foe identification automatic interrogation method for reconnaissance drones provided by the present invention analyzes and abstracts the application scenarios that need to be interrogated by reconnaissance drones into three typical application scenarios that can cover the full interrogation scenarios, namely, interrogation of static targets, moving targets, and switching of targets in the field of view. The advantages are as follows:

[0077] 1) Realized the monitoring and automatic inquiry of drones entering static target inquiry scenes;

[0078] 2) Achieved monitoring and automatic querying of drones entering moving target query scenes;

[0079] 3) It realizes the monitoring and automatic inquiry of the inquiry scene when the UAV enters the field of view and switches to the tracking target;

[0080] 4) By counting the results of multiple inquiries, the error in the inquiry results caused by the failure to meet certain inquiry conditions during a single inquiry process can be reduced.

[0081] It should be noted that, as another aspect, the present application also provides a storage medium, which can be included in an electronic device; or it can exist independently without being installed in the electronic device. The above storage medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the following embodiments. For example, the electronic device can implement the following Figure 1 The individual steps of the method are shown.

[0082] In one embodiment, the present application provides a computer program product, including a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0083] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0084] Other embodiments of the invention will readily occur to those skilled in the art after considering the specification and practicing the invention herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0085] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones, characterized in that: The method comprises: Real-time acquisition of the laser ranging value, laser working status, laser aiming azimuth rate, and laser aiming line pitch rate of the UAV’s airborne laser launching equipment; Real-time judgment on whether the laser distance measurement value is valid; When the laser ranging value is valid: determine whether to enter the static target interrogation scene based on the laser ranging value in multiple continuous sampling cycles; determine whether to enter the moving target interrogation scene based on the laser working state; determine whether to enter the interrogation scene when switching to the tracking target in the field of view based on the laser aiming azimuth rate or the laser aiming line pitch rate; After the above judgment, when it is found that the drone enters an interrogation scenario of switching between static targets, moving targets or tracking targets in the field of view, an automatic interrogation command needs to be sent; the recognition matching probability of multiple interrogation results is calculated, and friend-or-foe identification is performed based on the recognition matching probability.

2. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The method for acquiring the laser aiming azimuth rate and the laser aiming line pitch rate comprises: Determine the laser aiming azimuth rate based on the difference between the azimuth of the laser aiming line currently sampled and the azimuth of the laser aiming line last sampled and the acquisition period; The laser aiming pitch angle rate is determined based on the difference between the pitch angle of the laser aiming line currently sampled and the pitch angle of the laser aiming line last sampled and the acquisition period.

3. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The real-time determination of whether the laser ranging value is valid includes: Determine whether the laser distance measurement value is between the minimum valid value and the maximum valid value. If it is between the two, it is valid.

4. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The step of querying whether to enter a static target scene based on laser ranging values ​​in a plurality of continuous sampling periods includes: When the laser ranging values ​​in multiple consecutive sampling cycles are all within the given range, the static target interrogation scene is entered; the minimum value of the given range is the difference between the laser ranging value of the last sample and the maximum value of the ranging value change in one sampling cycle; the maximum value of the given range is the sum of the laser ranging value of the last sample and the maximum value of the ranging value change in one sampling cycle.

5. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 4 is characterized in that: Method for determining the maximum value of the distance measurement value change within the sampling period: It is the sum of the product of the UAV ground speed value at the last sampling and the sampling period plus the fluctuation range of the laser ranging value.

6. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The step of judging whether to enter a moving target interrogation scene based on the laser working state includes: When it is detected that the laser working state changes from other states to the target tracking state, it indicates that the UAV system is tracking a moving target and entering the moving target interrogation scene.

7. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The inquiry scenario for judging whether to switch to a tracking target within the field of view based on the laser aiming azimuth rate includes: When the laser platform is in the target tracking state and meets the following conditions: in, is the change threshold of the azimuth rate of the laser aiming line, ω1 and ω1′ are the azimuth rates of the laser aiming line at the current and last sampling times, respectively, and continue to monitor the azimuth rates that meet the requirements in the subsequent seconds. (Δω1′≤0)∧(Δω1=0) Among them, Δω1=ω1-ω1′ | , Δω1′ is the Δω1 value calculated after the last sampling, and the inquiry scene when the target switches into the field of view is determined.

8. The full-scene friend-or-foe identification automatic inquiry method for reconnaissance drones according to claim 1 is characterized in that: The inquiry scenario for judging whether to switch to a tracking target within the field of view based on the laser aiming pitch angle rate includes: When the laser platform is in the target tracking state and meets the following conditions: in, is the change threshold of the laser sight line pitch angle rate, ω2 and ω2′ are the pitch angle rates of the laser sight line at the current and last sampling times, respectively, and continue to monitor the change threshold in the subsequent seconds. (Δω2′≤0)∧(Δω2=0) Among them, Δω2= | ω 2| - | ω2′ | , Δω2′ is the Δω2 value calculated after the last sampling, and the inquiry scene when the target switches into the field of view is determined.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the automatic query method for friend-or-foe identification of a reconnaissance drone in all scenarios is implemented as described in any one of claims 1 to 8.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the automatic query method for friend-or-foe identification of a reconnaissance drone in all scenarios according to any one of claims 1 to 8 is implemented.

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