CN112269395B - Fixed-wing unmanned aerial vehicle formation reconstruction method based on scanning method - Google Patents

Abstract

The invention relates to a fixed wing unmanned aerial vehicle formation reconstruction method based on a scanning method, which mainly adopts computational geometry as a main calculation method and realizes formation recombination of a fixed wing unmanned aerial vehicle considering inter-aircraft collision. The method specifically comprises the following steps: 1. establishing a mathematical model of the fixed-wing unmanned aerial vehicle; 2. obtaining the position information of the unmanned aerial vehicle and the relative position information of the new team shape; 3. and solving the matching relation between the unmanned aerial vehicle and the new team shape by a scanning method of calculating geometry. The formation recombination algorithm is designed on the basis of formation of the fixed-wing unmanned aerial vehicles, and compared with most of the existing formation recombination algorithms, the resolving time is shorter; meanwhile, the problem of inter-machine collision in the formation reconstruction process is considered, so that the formation reconstruction problem in engineering practice is effectively solved.

Description

A Formation Reconstruction Method for Fixed-wing UAV Based on Scanning Method

technical field

The invention relates to a formation reconfiguration method of a fixed-wing unmanned aerial vehicle, which belongs to the field of formation reconfiguration of unmanned aerial vehicles.

Background technique

Since the 1990s, the United States has achieved remarkable results in various wars through the skillful use of drones. Since then, various countries have started a research boom on UAVs. After decades of research, development and application, the technology and experience of using UAVs have been relatively mature, and they have played an important role in civilian use. Its unique and irreplaceable role. But even today, when the use of drones is becoming more and more mature, some restrictions are inevitable in the process of performing tasks for a single drone. For example, when a single aircraft is performing a combat strike mission, if it is destroyed or interfered with, the entire mission will fail and cannot be remedied, but UAV formation operations can make up for this deficiency. When some UAVs in the formation are disturbed or destroyed, a series of task allocation algorithms can be used, and the remaining UAVs can still complete the mission or complete the main task; for example, in the process of environmental exploration, a single UAV Due to the limitations of position, speed, and sensors, man-machines cannot conduct comprehensive and accurate detection of the environment within the required time range, but the UAV formation can make up for this deficiency. Through reasonable deployment, the environment can be detected in a short period of time. Carry out full-coverage detection; for example, in the process of short-distance formation long-range cruising, by configuring a reasonable formation cruising formation, the flight resistance of the UAV can be reduced through the phenomenon of aerodynamic coupling, thereby reducing the energy consumption of the UAV, and increasing the power consumption of the UAV. Flight of man-machine, etc.

However, due to the uncertainty of the environment and the influence of various unknown factors in formation flight, a fixed formation cannot meet the increasingly complex mission requirements. Therefore, formation change and formation reorganization during missions are a better choice to increase the formation capability of UAVs. The reliability and rationality of the formation reconstruction algorithm are particularly important. Existing reconstruction algorithms have problems such as not considering the collision problem, or the algorithm is too complex, and the solution time is too long.

Contents of the invention

technical problem to be solved

In order to avoid the deficiencies of the prior art, the present invention proposes a scanning method-based formation reconstruction method for fixed-wing UAVs.

Technical solutions

A method for reconfiguring the fixed-wing unmanned aerial vehicle formation based on the scanning method is characterized in that the steps are as follows:

Step 1: Obtain the three-dimensional position information of each drone;

Step 2: Design the formation formation, and obtain the relative position information of each position in the formation relative to the virtual leader or formation center;

Step 3: Based on computational geometry, match the position of the UAV and the formation through the scanning algorithm:

Step 3-1: Use the center point of the UAV group position as the coordinate origin to establish a ground coordinate system, assuming that the new formation is on the upper half plane of the ground coordinates and is at a certain distance from the current position of the group;

Step 3-2: First, according to the abscissa, number the fleet and the new formation positions respectively from small to large. If the abscissas are equal, the sizes can be arranged arbitrarily;

Step 3-3: Select the aircraft with the smallest number in the fleet to scan clockwise starting from the negative half-axis of the abscissa and take the center of the drone as a fixed point, and match the first formation position scanned to obtain A directed matching line from the aircraft position to the formation position;

Step 3-4: Determine whether the straight line passes through other aircraft or formation positions except the aircraft and formation positions mentioned in step 3-3; if there are other aircraft or formation positions collinear with the matching straight line, then give Add a small amount of ε to the coordinates, and repeat step 3-3; if there is no collinear phenomenon, proceed to step 3-5;

Step 3-5: Determine whether there is an aircraft falling on the left side of the matching line at this time: if it exists, select the position of the aircraft falling on the left side of the line as the reference point, and repeat the operation of step 3-3; if it does not exist, set Aircraft and formation positions that match straight lines pass through are removed from the fleet and formation points;

Step 3-6: Determine whether there are unmatched aircraft and formation positions: if yes, return to step 3-3, if not, end.

The technical solution of the present invention further states: in step 1, the three-dimensional position information is acquired through GPS or other means.

The technical solution of the present invention further says: in the step 2, design formation formation is rhombus.

The technical solution of the present invention further states: in step 3, ε=[3,0] ^T .

Beneficial effect

A fixed-wing unmanned aerial vehicle formation reconstruction method based on the scanning method proposed by the present invention has a shorter solution time than most existing formation reorganization algorithms; at the same time, the collision problem between aircrafts in the formation reconstruction process is considered , thus effectively solving the formation reconstruction problem in engineering practice and enhancing the formation capability of UAVs.

Description of drawings

Figure 1 is a schematic diagram of the aircraft algorithm on the left;

Figure 2 is a schematic diagram of the normal process algorithm;

Fig. 3 is a schematic diagram of collinear algorithm;

Figure 4 is a schematic diagram of trajectory intersecting and non-intersecting;

Fig. 5 is the final matching result figure;

Figure 6 is a flowchart of the algorithm.

Detailed ways

Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

In this example, eight fixed-wing UAVs are used for formation reconstruction. The specific implementation steps of a fixed-wing unmanned aerial vehicle formation reconstruction method based on the scanning method are as follows:

Step 1: Obtain the three-dimensional position information of each drone through GPS or other means;

The initial position of each UAV in this example is set as:

Table 1. The initial position of each UAV in the ground coordinate system

Step 2: Design the formation formation, and obtain the relative position information of each position in the formation relative to the virtual navigator or formation center;

The formation formation in this example is a rhombus, and the expected distance of each UAV relative to the formation center is designed as:

Table 2. The relative position of each point in the formation and the center

Step 3: Based on computational geometry, match the position of the UAV and the formation through the scanning algorithm. The process is as follows:

Step 1) Use the center point of the UAV group position as the coordinate origin to establish a ground coordinate system. Without loss of generality, we assume that the new formation is in the upper half plane of the ground coordinates and is at a certain distance from the current position of the group.

Step 2) Firstly, according to the abscissa coordinates, number the cluster and the new formation positions respectively from small to large, and if the abscissa coordinates are equal, the sizes can be arranged arbitrarily.

The above table has completed step 1) and step 2). Then the UAV1 matching process that works in step 5) is explained below:

UAV1 starts to perform the scanning algorithm, that is, step 3), and it is obtained that UAV1 matches the position p1. Verify that there is no collinear problem mentioned in step 4), go to step 5), verify that there is an aircraft on the left, so trigger the re-selection of the reference point mechanism, select UAV2 as the matching aircraft, and perform the operation in step 3) again, finally Get the match between UAV2 and p1, and remove UAV2 and p1 points from the aircraft and position points to be selected. As shown in Figure 1.

At this time, UAV1 becomes the aircraft with the smallest abscissa among the remaining aircraft, so it is matched. This time the matching process is a regular one:

UAV1 starts to perform the scanning algorithm, that is, step 3), and it is obtained that UAV1 matches the position p2. Verify that there is no collinear problem mentioned in step 4), go to step 5), find that there is no collinear problem, and remove UAV1 and p2 points from the aircraft and position points to be selected. as shown in picture 2.

The UAV4 matching process that works in step 4) is explained below.

UAV4 starts to perform the scanning algorithm, ie step 3), and it is obtained that UAV4 matches positions p4 and p5. Verify that there is a collinear problem mentioned in step 4), then add a small amount ε=[3,0] ^T to the coordinates of UAV4, at this time the coordinates of UAV4 become UAV4'=[3,0] ^T , and then turn Going to step 3), step 4), it is found that there is no collinear problem, and finally UAV4 and p4 are matched, and UAV4 and p4 are eliminated from the aircraft and position points to be selected. As shown in Figure 3.

The formation reorganization algorithm that the present invention proposes can prevent the description of the inter-machine collision problem:

The formation change of the fixed-wing UAV is generally carried out when the formation is flying in a straight line, and the position where the formation is expected to form should be at a certain distance from the current fleet. In this hypothetical background, the formation reconstruction algorithm proposed by the present invention considers the track of the UAV as a line segment, so that the two line segments do not intersect to avoid the problem of collision between aircrafts. Then, a necessary condition for judging the intersection of two line segments is that the two ends of a line segment must be located at the left and right ends of the line where the other line segment is located. However, the algorithm designed by the present invention ensures that each trajectory line segment cannot cross another trajectory line segment. As shown in Fig. 4 and Fig. 5, therefore, the formation reconfiguration strategy designed by the present invention can avoid the collision problem between aircrafts.

Finally, the description of the above examples is the preferred implementation of the present invention. Although the present invention has been described in detail through the above preferred examples, those skilled in the art should understand that the present invention has been made differently in terms of form and details. All such insubstantial changes are within the scope of protection required by the claims of the present invention.

Claims (4)

1. a kind of fixed-wing unmanned aerial vehicle formation reconstruction method based on scanning method, it is characterized in that the steps are as follows: Step 1: Obtain the three-dimensional position information of each drone; Step 2: Design the formation formation, and obtain the relative position information of each position in the formation relative to the virtual leader or formation center; Step 3: Based on computational geometry, match the position of the UAV and the formation through the scanning algorithm: Step 3-1: Use the center point of the UAV group position as the coordinate origin to establish a ground coordinate system, assuming that the new formation is on the upper half plane of the ground coordinates and is at a certain distance from the current position of the group; Step 3-2: First, according to the abscissa, number the fleet and the new formation positions respectively from small to large. If the abscissas are equal, the sizes can be arranged arbitrarily; Step 3-3: Select the aircraft with the smallest number in the fleet to scan clockwise starting from the negative half-axis of the abscissa and take the center of the drone as a fixed point, and match the first formation position scanned to obtain A directed matching line from the aircraft position to the formation position; Step 3-4: Determine whether the straight line passes through other aircraft or formation positions except the aircraft and formation positions mentioned in step 3-3; if there are other aircraft or formation positions collinear with the matching straight line, then give Add a small amount of ε to the coordinates, and repeat step 3-3; if there is no collinear phenomenon, proceed to step 3-5; Step 3-5: Determine whether there is an aircraft falling on the left side of the matching line at this time: if it exists, select the position of the aircraft falling on the left side of the line as the reference point, and repeat the operation of step 3-3; if it does not exist, set Aircraft and formation positions that match straight lines pass through are removed from the fleet and formation points; Step 3-6: Determine whether there are unmatched aircraft and formation positions: if yes, return to step 3-3, if not, end. 2. a kind of fixed-wing unmanned aerial vehicle formation reconstruction method based on scanning method according to claim 1 is characterized in that in step 1, obtains three-dimensional position information by GPS. 3. a kind of fixed-wing unmanned aerial vehicle formation reconstruction method based on scanning method according to claim 1, it is characterized in that in step 2, design formation formation is rhombus. 4. A method for reconfiguring the formation of fixed-wing unmanned aerial vehicle based on scanning method according to claim 1, characterized in that ε=[3,0] ^T in step 3.

Images