A two-stage method for trajectory optimization of mine sweeping

Abstract

The application discloses a two-stage mine barrier sweeping path optimization method, which comprises the following steps: entering a global blind sweeping stage, a mine sweeping fleet sweeps a pre-judged water area in a mine sweeping formation with a preset reference point deviation value and a preset overlap bandwidth, and a mine sweeping track realizes full coverage on the pre-judged water area; calculating a first mine sweeping time and a location, and expanding a potential mine barrier area from the first mine sweeping location in a preset mode; entering a local fine sweeping stage, the mine sweeping fleet sweeps the potential mine barrier area in a mine sweeping formation with a preset overlap bandwidth, a mine sweeping track realizes full coverage on the potential mine barrier area, a mine sweeping efficiency index optimization model is established, the mine sweeping efficiency index optimization model is solved, an optimal deviation value and an optimal overlap bandwidth are obtained, and the two-stage mine barrier sweeping is performed according to the optimal reference point deviation value and the optimal overlap bandwidth.

Description

Technical Field

[0001] This invention belongs to the field of intelligent planning technology, and in particular relates to a trajectory optimization method for two-stage mine clearance. Background Technology

[0002] Because naval mines are inexpensive to manufacture, powerful, easy to use, and difficult to sweep away, and pose a long-term threat to ports and waterways, mine countermeasures teams often have to expend considerable resources on challenging operations. Currently, many naval mines manufactured using advanced technologies have reached unprecedented levels in performance, destructive power, concealment, and ability to counter minesweeping operations. Therefore, the demands on mine countermeasures capabilities are increasing daily.

[0003] Whether from the perspective of national defense or the protection of people's lives and property, it is necessary to increase research on mine clearance strategies and corresponding intelligent planning methods to maximize the effectiveness of mine clearance. Therefore, an efficient and targeted method for minesweeping vessel trajectory planning is needed to enable minesweepers to exert greater mine clearance combat effectiveness. Summary of the Invention

[0004] In view of this, it is necessary to provide a two-stage mine clearance trajectory optimization method to address the aforementioned technical problems. This method divides mine clearance into two stages: a global blind sweep stage and a local fine sweep stage. The global blind sweep stage is used to conduct a large-scale blind sweep of a predetermined water area, while the local fine sweep stage occurs after the initial mine detonation during the global blind sweep, conducting a small-scale fine sweep of a specific sea area. Through the coordination of these two stages, potential mine-prone areas can be discovered earlier in large water areas (i.e., the initial detonation time is earliest), and fine sweeping can be performed on potential mine-prone areas, enabling more efficient removal of all mines, i.e., minimizing the mathematical expectation of the number of remaining mines after mine clearance.

[0005] This invention discloses a two-stage mine clearance trajectory optimization method, comprising the following steps:

[0006] Step 1: Enter the global blind sweep phase. The minesweeping fleet uses a minesweeping formation with a preset reference point deviation value and a preset overlap band width to perform blind sweeps on the predicted water area. The minesweeping trajectory achieves full coverage of the predicted water area.

[0007] Step 2: Calculate the time and location of the first mine clearance and detonation, and expand the potential minefield area according to the preset method based on the location of the first mine clearance and detonation;

[0008] Step 3: Enter the local fine sweeping stage. The minesweeping fleet uses a minesweeping formation with a preset overlap band width to perform fine sweeping of the potential minefield area, and the minesweeping trajectory achieves full coverage of the potential minefield area.

[0009] Specifically, the process of calculating the time of the first sweep includes the following steps:

[0010] Step 201: According to the minesweeping formation in Step 1, initialize the minesweeping trajectory of the minesweeping fleet and the detonation probability of all mines.

[0011] Step 202: Calculate the maximum number of rounds of global blind sweep based on the maximum working time of the minesweeping fleet, and set the number of iterations to 0;

[0012] Step 203: Calculate the distance from each mine to the trajectory of each minesweeper, and increment the iteration count by 1;

[0013] Step 204: Calculate the probability of each mine being detonated in this round of mine sweeping based on the distance, and sum it with the probability of detonation in the previous round;

[0014] Step 205: Determine whether the probability of bombing is greater than the preset bombing probability threshold after this round of mine clearing. If yes, proceed to step 206. If no, determine whether the number of iterations exceeds the maximum number of iterations. If yes, bomb clearing fails. If no, return to step 203.

[0015] Step 206: Obtain the track and x and y coordinates of the mine whose sweep probability is greater than the preset sweep probability threshold;

[0016] Step 207: Calculate the time when the minesweeper reaches the x-coordinate and y-coordinate of its track;

[0017] Step 208: Sort the detonation times to obtain the earliest detonation time of the mine, which is the first detonation time.

[0018] Preferably, an optimization model for mine clearance efficiency is established, with the objective function including minimizing the initial mine clearance time and minimizing the expected number of remaining mines. Minimizing the initial mine clearance time is expressed as min(t) sb Minimizing the expected value of the remaining mines is expressed as min(snum). s The constraints include that the working time of the minesweeping fleet is no greater than the maximum working time, and the mine detonation probability on the first sweep is greater than or equal to the preset detonation probability threshold. The optimization variables are the deviation between the starting point and the reference point of the minesweeper at the initial moment and the overlap band width, as shown below:

[0019]

[0020] T max T represents the working hours of the minesweeping fleet. max p represents the longest working time of the minesweeping fleet. b P' represents the probability of a mine being detonated on the first attempt, δ represents the preset detonation probability threshold, and d represents the reference point deviation value. p Indicates the overlap band width, δmin δ represents the lower bound of the reference point deviation value. max d represents the upper bound of the reference point deviation value. pmin d represents the lower bound of the overlap band width. pmax This indicates the upper bound of the overlap band width.

[0021] The optimization model for mine clearance efficiency index is solved to obtain the optimal deviation value and overlap band width. The two-stage mine clearance is then carried out according to the optimal reference point deviation value and overlap band width. Attached Figure Description

[0022] Figure 1 A flowchart illustrating the implementation method of the present invention is shown;

[0023] Figure 2 A schematic diagram of the table structure in this embodiment is shown;

[0024] Figure 3 The flowchart shows the calculation process for the first mine detonation.

[0025] Figure 4 The calculation process for the mathematical expectation of the remaining number of mines is shown. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] like Figure 1 As shown, this invention discloses a two-stage mine clearance trajectory optimization method, comprising the following steps:

[0028] Step 1: Enter the global blind sweep phase. The minesweeping fleet uses a minesweeping formation with a preset reference point deviation value and a preset overlap band width to perform blind sweeps on the predicted water area. The minesweeping trajectory achieves full coverage of the predicted water area.

[0029] Step 2: Calculate the time and location of the first mine clearance and detonation, and expand the potential minefield area according to the preset method based on the location of the first mine clearance and detonation;

[0030] Step 3: Enter the local fine sweeping stage. The minesweeping fleet uses a minesweeping formation with a preset overlap band width to perform fine sweeping of the potential minefield area, and the minesweeping trajectory achieves full coverage of the potential minefield area.

[0031] Specifically, the process of calculating the time of the first sweep includes the following steps:

[0032] Step 201: According to the minesweeping formation in Step 1, initialize the minesweeping trajectory of the minesweeping fleet and the detonation probability of all mines.

[0033] Step 202: Calculate the maximum number of rounds of global blind sweep based on the maximum working time of the minesweeping fleet, and set the number of iterations to 0;

[0034] Step 203: Calculate the distance from each mine to the trajectory of each minesweeper, and increment the iteration count by 1;

[0035] Step 204: Calculate the probability of each mine being detonated in this round of mine sweeping based on the distance, and sum it with the probability of detonation in the previous round;

[0036] Step 205: Determine whether the probability of bombing is greater than the preset bombing probability threshold after this round of mine clearing. If yes, proceed to step 206. If no, determine whether the number of iterations exceeds the maximum number of iterations. If yes, bomb clearing fails. If no, return to step 203.

[0037] Step 206: Obtain the track and x and y coordinates of the mine whose sweep probability is greater than the preset sweep probability threshold;

[0038] Step 207: Calculate the time when the minesweeper reaches the x-coordinate and y-coordinate of its track;

[0039] Step 208: Sort the detonation times to obtain the earliest detonation time of the mine, which is the first detonation time.

[0040] Preferably, an optimization model for mine clearance efficiency is established, with the objective function including minimizing the initial mine clearance time and minimizing the expected number of remaining mines. Minimizing the initial mine clearance time is expressed as min(t) sb Minimizing the expected value of the remaining mines is expressed as min(snum). s The constraints include that the working time of the minesweeping fleet is no greater than the maximum working time, and the mine detonation probability on the first sweep is greater than or equal to the preset detonation probability threshold. The optimization variables are the deviation between the starting point and the reference point of the minesweeper at the initial moment and the overlap band width, as shown below:

[0041]

[0042] T max T represents the working hours of the minesweeping fleet. max p represents the longest working time of the minesweeping fleet. b P' represents the probability of a mine being detonated on the first attempt, δ represents the preset detonation probability threshold, and d represents the reference point deviation value. p Indicates the overlap band width, δ minδ represents the lower bound of the reference point deviation value. max d represents the upper bound of the reference point deviation value. pmin d represents the lower bound of the overlap band width. pmax This indicates the upper bound of the overlap band width.

[0043] The optimization model for mine clearance efficiency index is solved to obtain the optimal deviation value and overlap band width. The two-stage mine clearance is then carried out according to the optimal deviation value and overlap band width.

[0044] In a specific embodiment, the relevant parameters were refined. Assume that a mine countermeasures operation is being conducted within a routine minesweeping area, aiming to clear a channel 10,000 meters long and 1,000 meters wide, symmetrical about the main channel, with an operation time of 3 days. After the Blue Force's minesweeper detonates a mine for the first time (determined by a detonation probability greater than 0.8), the minesweeping area is adjusted to a 4,000-meter-long area centered on the mine in the direction of the main channel. The minesweeping process mainly includes two phases. The first phase is a global blind sweep, which, within a specified time (3 days), uses limited resources (4 minesweepers) in a clear sweeping formation (2 minesweepers in a single line formation with an overlap of 4 meters) to conduct a large-scale blind sweep of a designated sea area (a rectangular sea area with ADEH as the vertices). The second phase is a local fine sweep, which occurs after the first mine is detonated during the blind sweep. Within a specified time, using the same resources and the same formation, a small-scale fine sweep is conducted on a specific sea area (an area along the main shipping lane centered on the mine, with a length shortened to 4000 meters). It is specifically noted that the reference point in this embodiment is point H, i.e., the point with coordinates (0, 0). Figure 2 As shown.

[0045] For the two phases of the activities mentioned above, two mine-clearing performance indicators need to be calculated: the time of the first mine detonation and the expected number of remaining mines in the minefield after mine clearance. However, in solving for these two performance indicators, it can be found that they are two mine-clearing efficiency indicators that can be optimized. The optimization variables include two aspects: first, the accurate position of the minesweeper on the AH line at the initial moment (since the x-coordinate of all points on the AH line is 0, the optimization variables are also the y-coordinate of the minesweeper at the initial moment); and second, the width of the overlap zone.

[0046] The calculation process for the first mine detonation is as follows: Figure 3 As shown. The calculation process for the mathematical expectation of the remaining number of mines is as follows. Figure 4 As shown.

[0047] Therefore, an optimization model for the following mine clearance efficiency indicators can be established.

[0048] There are two objective functions:

[0049] Minimize the first sweep time: min(t) sb Minimize the expected value of remaining mines: min(snum) s );

[0050] The constraints include:

[0051]

[0052] The optimization variables are: the deviation between the starting point and the origin of the minesweeper at the initial moment, and the width of the overlap band.

[0053] Constraint 1 is the operation time constraint, with a total operation time of 72 hours. Constraint 2 is the minesweeping probability constraint, where a minesweeping probability greater than 0.8 is considered as a minesweeping operation. Constraint 3 is the overlap zone width constraint; since the minesweeper's width is 40 meters, the overlap zone width is considered to be no more than half the width of the minesweeper. Constraint 4 is the deviation value between the minesweeping starting point and the origin; in this model, the trajectory is initialized by traversing upwards at 40-meter intervals, so the offset value is considered to be no more than half the offset value, otherwise it would be too close to the next trajectory line. Therefore, in the overlap zone width variable interval [0,20], six values ​​of 0, 4, 8, 12, 16, and 20 are taken with a step size of 4; in the offset value variable interval [0,20], five values ​​of 0, 4, 8, 12, and 16 are taken with a step size of 5. The initial minesweeping time and the expected index value of the remaining mines are calculated in the existing mine-laying schemes. The results are shown in the table.

[0054]

[0055] In the table above, each blank has two values: the time of the first sweep and the expected number of remaining mines. As can be seen from the table, when the overlap width is 4 meters, the time of the first sweep and the expected number of remaining mines is 22.01 hours and the expected number of remaining mines is 20. When the vertical axis is 4 meters, the time of the first sweep and the expected number of remaining mines is 23.29 hours and the expected number of remaining mines is 19.

[0056] It can be seen that both the deviation between the minesweeper's initial point and the origin, and the width of the overlap zone, affect the two key indicators: the initial detonation time and the expected value of remaining mines.

[0057] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0058] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0059] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A two-stage mine clearance trajectory optimization method, characterized in that, Includes the following steps: Step 1: Enter the global blind sweep phase. The minesweeping fleet uses a minesweeping formation with a preset reference point deviation value and a preset overlap band width to perform blind sweeps on the predicted water area. The minesweeping trajectory achieves full coverage of the predicted water area. Step 2: Calculate the time and location of the first mine clearance and detonation, and expand the potential minefield area according to the preset method based on the location of the first mine clearance and detonation; Step 3: Enter the local fine sweeping stage. The minesweeping fleet uses a minesweeping formation with a preset overlap band width to conduct fine sweeping of the potential minefield area. The minesweeping trajectory achieves full coverage of the potential minefield area. The process of calculating the time of the first sweep includes the following steps: Step 201: According to the minesweeping formation in Step 1, initialize the minesweeping trajectory of the minesweeping fleet and the detonation probability of all mines. Step 202: Calculate the maximum number of rounds of global blind sweep based on the maximum working time of the minesweeping fleet, and set the number of iterations to 0; Step 203: Calculate the distance from each mine to the trajectory of each minesweeper, and increment the iteration count by 1; Step 204: Calculate the probability of each mine being detonated in this round of mine sweeping based on the distance, and sum it with the probability of detonation in the previous round; Step 205: Determine whether the probability of bombing is greater than the preset bombing probability threshold after this round of mine clearing. If yes, proceed to step 206. If no, determine whether the number of iterations exceeds the maximum number of iterations. If yes, bomb clearing fails. If no, return to step 203. Step 206: Obtain the track and x and y coordinates of the mine whose sweep probability is greater than the preset sweep probability threshold; Step 207: Calculate the time when the minesweeper reaches the x-coordinate and y-coordinate of its track; Step 208: Sort the detonation times to obtain the earliest detonation time of the mine, which is the first detonation time. Establish a mine clearance efficiency index optimization model. The objective function includes minimizing the initial mine clearance time and minimizing the expected number of remaining mines. The minimum initial mine clearance time is expressed as: Minimize the expected value of the remaining mines as follows: The constraints include that the working time of the minesweeping fleet is no greater than the maximum working time, and the probability of the mine being detonated on the first attempt is greater than or equal to the preset detonation probability threshold. The optimization variables are the deviation between the starting point and the reference point of the minesweeper at the initial moment and the width of the overlap zone, as shown below: ； This indicates the working hours of the minesweeping fleet. This indicates the longest working time of the minesweeping fleet. This indicates the probability of a mine being detonated on the first attempt. This indicates the preset bomb sweep probability threshold. This represents the reference point deviation value. Indicates the width of the overlap band. This indicates the lower bound of the reference point deviation value. This indicates the upper bound of the reference point deviation value. This indicates the lower bound of the overlap band width. This indicates the upper bound of the overlap band width. The optimization model for mine clearance efficiency index is solved to obtain the optimal deviation value and overlap band width. The two-stage mine clearance is then carried out according to the optimal reference point deviation value and overlap band width.

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