Multi-unmanned aerial vehicle elasticity measurement method for formation topology reconstruction

Abstract

The invention provides an elasticity measurement method for a formation topology reconstruction process of multiple unmanned aerial vehicles. The method comprises the following steps: 1, calculating a reconstruction availability factor; 2, calculating a reconstruction accuracy factor: 2.1, selecting a reference center unmanned aerial vehicle, constructing a formation relative coordinate system, and determining an expected coordinate of each unmanned aerial vehicle relative to the reference center unmanned aerial vehicle; 2.2, calculating the value of a reconstruction accuracy factor according to the actual topology reconstruction condition of the formation; 3, calculating a reconstruction time factor; and 4, calculating an elasticity measurement value.

Description

(I) Technical field

[0001] The invention belongs to the technical field of reliability, and in particular relates to a multi-UAV elasticity measurement method for formation topology reconstruction. (II) Background technology

[0002] With the continuous development of modern warfare technology, the battlefield environment is becoming increasingly complex. A large number of uncertain factors such as saturation fire strikes, multi-source enemy intrusions, and system failures make drone clusters extremely vulnerable to interference and destruction. In order to ensure the survivability and sustained combat capability of drone clusters in complex battlefield environments, the clusters are usually required to have a certain degree of resilience, that is, the ability to resist damage and recover from it. Therefore, how to correctly measure the resilience of multiple drones has become a key issue in the design of resisting damage and recovering self-healing capabilities.

[0003] At present, the measurement of multi-UAV resilience is still an open problem and lacks a unified definition. Domestic and foreign scholars have proposed a variety of measurement methods, most of which are designed for specific tasks such as reconnaissance and surveillance. The research on the universal resilience measurement method of multi-UAV is still blank. There is a lack of a resilience measurement scheme independent of the task, which has brought obstacles to the evaluation of the resilience of multi-UAV under a unified standard.

[0004] Topological reconstruction is an important way for a multi-UAV formation to recover performance after encountering external damage. When a formation loses some aircraft due to weather, failure or enemy attack, it usually performs topological reconstruction with the predetermined formation as the goal, in order to restore mission performance as soon as possible. Correspondingly, factors such as the speed and effect of topological reconstruction will greatly affect the survival probability and combat capability of the formation on the battlefield. Therefore, measuring the resilience of multi-UAVs in the process of formation topological reconstruction is a measurement method that can reflect the essence of resilience and is reasonable and universal.

[0005] Based on this, the present invention proposes a multi-UAV resilience measurement method for the formation topology reconstruction process. The method has certain versatility and can provide support for the design of UAV cluster's ability to resist destruction and recover. (III) Summary of the invention

[0006] This paper analyzes the main factors affecting the formation topology reconstruction performance of multiple UAVs, proposes three mathematical factors that quantitatively describe the reconstruction performance, integrates them based on the elasticity index framework, and proposes a multi-UAV elasticity measurement method for formation topology reconstruction. This method can solve the defects of the current multi-UAV elasticity measurement method that is bound to task types and has poor versatility, and provides a new solution for multi-UAV elasticity measurement.

[0007] The specific steps are as follows:

[0008] Step 1: Calculate the reconstruction availability factor;

[0009] Step 2: Calculate the reconstruction accuracy factor, including:

[0010] Step 2.1 Select the reference center drone, build the formation relative coordinate system, and determine the expected coordinates of each drone relative to the reference center drone;

[0011] Step 2.2: Calculate the reconstruction accuracy factor value based on the actual reconstruction of the formation;

[0012] Step 3: Calculate the reconstruction time factor;

[0013] Step 4: Calculate the elasticity measure. (IV) Description of the drawings

[0014] Figure 1 This is a schematic flow chart of a multi-UAV resilience measurement method based on formation topology reconstruction proposed in the present invention. (V) Specific implementation methods

[0015] The following detailed description of the exemplary implementation of the present invention is provided in conjunction with the accompanying drawings. The following description includes specific details to assist understanding, but these specific details should be shown as exemplary only. Therefore, it will be appreciated by those skilled in the art that various changes and modifications may be made to the various examples described herein without departing from the scope and spirit of the present disclosure. In addition, for the sake of clarity and simplicity, descriptions of well-known functions and structures are omitted.

[0016] The terms and words used in the following description and claims are not limited to their literal meanings, but are only used by the inventor to implement a clear and consistent understanding of the present invention. Therefore, it should be clear to those skilled in the art that the following description of various example implementations of the present invention is provided only for illustrative purposes and is not intended to limit the present invention defined by the attached claims and their equivalents.

[0017] Step 1: Calculate the reconstruction availability factor:

[0018] Availability refers to the upper limit of the remaining performance of the formation in the topology reconstruction of the UAV formation. When only the reconstruction effect is considered and the time cost is not considered, the upper limit of the remaining performance of the formation is mainly determined by the number of remaining UAVs after the destruction occurs. Therefore, it is quantified by the ratio of the number of remaining UAVs to the number of original UAVs. Assume that the number of UAVs is N0, and the number of UAVs remaining after external destruction is N m , calculate its availability factor according to the following formula:

[0019]

[0020] Example 1: Take a multi-UAV formation performing a reconnaissance mission as an example. According to step 1, the initial size of the formation is 20. After being damaged externally, the number of remaining UAVs is 16. According to the formula, its availability factor can be calculated as 16 / 20=0.8.

[0021] Step 2: Calculate the reconstruction accuracy factor, including:

[0022] Step 2.1: Select the reference center drone, build the formation relative coordinate system, and determine the expected coordinates of each drone relative to the reference center drone: In order to facilitate the measurement of the relative positions between drone formation individuals, select the formation head drone as the coordinate origin and the reference center drone to build the formation relative coordinate system. After determining the coordinate system, calculate the expected relative coordinates of each drone in the ideal reconstructed formation relative to the reference center drone. m is the drone number selected as the reference center, then x i,m is the expected coordinate of the i-th UAV after ideal reconstruction in the relative coordinate system.

[0023] Step 2.2: Calculate the reconstruction accuracy factor based on the actual topology reconstruction of the formation: When reconstructing the topology of multiple drones, it is impossible to guarantee that each drone can accurately reach the specified location. At this time, the error between the formation after reconstruction and the target configuration is an important factor in measuring the performance of the reconstruction process. Therefore, the reconstruction accuracy factor is used to measure the similarity between the reconstructed formation and the target configuration. The calculation formula is as follows:

[0024]

[0025] Where E is the reference error value, which represents the acceptable reconstruction error threshold of the formation and is set according to the specific situation. p is the number of spatial coordinate dimensions of the UAV considered, which is generally 3. is the j-th dimension coordinate value of the i-th UAV after reconstruction.

[0026] Example 2, continued from Example 1.

[0027] Take a multi-UAV formation performing a reconnaissance mission as an example. The reference error value E is set to 100, the number of spatial dimensions p is set to 3, and the UAV numbered 4 is selected as the reference center, m = 4. First, the position of UAV No. 4 is used as the coordinate origin to construct a relative coordinate system. The ideal coordinates x of the remaining 16 UAVs in the relative coordinate system are calculated based on the expected reconstructed formation. i,4 , i = 1, 2, 3..., 16. Then the real coordinates x of each drone after reconstruction are i ,i=1,2,3...,16Substitute into the formula and calculate the reconstruction accuracy factor σ r =0.9.

[0028] Step 3: Calculate the reconstruction time factor:

[0029] The time from the start of reconstruction to the final completion of reconstruction is called reconstruction time, which is an important factor affecting the performance of formation topology reconstruction. It is measured by the reconstruction time factor, and the calculation formula is as follows:

[0030]

[0031] Where T is the actual reconstruction time, T m This is the maximum allowed reconstruction time and needs to be set in advance.

[0032] Example 3, continued from Example 2.

[0033] Take a multi-UAV formation performing a reconnaissance mission as an example. The maximum allowable reconstruction time T m Set to 50 seconds, the actual reconstruction time is 40 seconds, and the reconstruction time factor can be calculated as e -40 / 50 =0.45.

[0034] Step 4: Calculate the elasticity metric value: The three mathematical factors are combined to calculate the elasticity metric value of the topological reconstruction of the multi-UAV formation. The calculation formula is:

[0035] R=δ r σ r ρ r

[0036] Example 4, continued from Example 3.

[0037] Take a multi-UAV formation performing a reconnaissance mission as an example. In steps 1, 2, and 3, the reconstruction availability factor δ is calculated respectively. r =0.8, reconstruction accuracy factor σ r =0.9, reconstruction time factor ρ r =0.45, based on which the topological reconstruction elasticity metric value of the multi-UAV formation can be summarized as R=0.8×0.9×0.45=0.324.

[0038] It can be seen that the flexible measurement of multiple drones can be achieved according to the steps described in the present invention.

[0039] This paper analyzes the main factors affecting the formation topology reconstruction performance of multiple UAVs, proposes three mathematical factors that quantitatively describe the reconstruction performance, integrates them based on the elasticity index framework, and proposes a multi-UAV elasticity measurement method for formation topology reconstruction. This method can solve the defects of the current multi-UAV elasticity measurement method that is bound to task types and has poor versatility.

[0040] The examples described above have provided detailed explanations of the implementation methods of various parts of the present invention. The specific implementation forms of the present invention are not limited thereto. For those skilled in the art, various obvious changes to the method of the present invention without departing from the spirit of the method of the present invention and the scope of the claims are within the protection scope of the present invention.

Claims

1. A multi-UAV elasticity measurement method for formation topology reconstruction, characterized in that: The following steps are involved: Step 1: Calculate the reconstruction availability factor. Specifically, let the number of drones be N0, and the number of remaining working drones after the damage be N m , and its topology reconstruction process availability factor is Step 2: Calculate the reconstruction accuracy factor. Specifically, select the formation head aircraft as the coordinate origin and the reference center UAV to construct the formation relative coordinate system. After determining the coordinate system, calculate the expected relative coordinates of each UAV in the ideal reconstructed formation relative to the reference center UAV. m is the number of the UAV selected as the reference center, then x i,m is the expected coordinate of the i-th UAV after ideal reconstruction in the relative coordinate system; the topological reconstruction accuracy factor is calculated based on the ideal formation and the actual reconstruction of the formation, x i is the coordinate value of the i-th UAV after actual reconstruction, and x i,m and x i Substitute into the formula The topology reconstruction accuracy factor can be obtained from Step 3: Calculate the reconstruction time factor, specifically: record the time from the start of reconstruction to the completion of reconstruction, recorded as T, and pre-set the maximum allowable reconstruction time T m , substitute into the formula Calculate the topology reconstruction time factor; Step 4: Calculate the elasticity metric, specifically: the reconstruction availability factor δ obtained in step 1 r , the reconstruction accuracy factor σ obtained in step 2 r , and the reconstruction time factor ρ obtained in step 3 r , substitute into the formula R = δ r σ r ρ r Calculate the elasticity measure.

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