Police service multi-unmanned aerial vehicle target searching method based on normal distribution probability graph

Abstract

The invention discloses a police service multi-unmanned aerial vehicle target searching method based on a normal distribution probability graph, multiple unmanned aerial vehicles comprise a master unmanned aerial vehicle and a plurality of slave unmanned aerial vehicles. The method comprises the following steps: gridding a specified region, and distributing probability for each grid according to prior information including pre-defined key searching positions to obtain an initial probability graph; the main unmanned aerial vehicle receives information when each slave unmanned aerial vehicle arrives at the current position; updating the initial probability graph based on the information to obtain a probability graph; controlling each slave unmanned aerial vehicle to perform target search based on a probability graph and a particle swarm algorithm; when a target suspicious position is received, assigning a value to the probability graph according to normal probability distribution, and setting a grid where the target suspicious position is located as a normal distribution center to obtain a normal distribution probability graph; and on the basis of the normal distribution probability graph, controlling each slave unmanned aerial vehicle to perform target search according to a particle swarm algorithm. According to the method provided by the invention, the search efficiency is improved, and the target suspect can be effectively searched.

Description

technical field

[0001] The invention relates to the technical field of target search, in particular to a police multi-UAV target search method based on a normal distribution probability map. Background technique

[0002] With the rapid development of science and technology, many technological products have appeared, such as drones, which can not only be used in rescue and shooting, but also in police security, because police security drones are equipped with cameras , and then police officers can use the camera to carry out police prevention and target search and tracking, which is convenient for monitoring suspicious personnel and arresting criminal suspects.

[0003] At present, when multi-UAVs perform target search, the probability map based on the random distribution of target existence probability values. However, this search method has randomness and blindness, especially in the case of determining the suspicious position of the target. If the target search is still c...

Examples

Embodiment approach

[0087] The first way:

[0088] Calculate the probability values ​​of each grid in turn according to the joint probability density formula of normal distribution; among them, the joint probability density formula of normal distribution is as follows:

[0089] Among them, x and y are the abscissa and ordinate of the grid respectively, μ x and μ y is the grid coordinate (x, y) of the suspicious position of the target, σ x and σ y take 2;

[0090] For example, when a suspected target suspect is found in the grid (5, 5), the center position of the normal distribution is selected as (5, 5), μ x and μ y The value is 5,

[0091] P * (1,1)=1 / 8π*exp{-1 / 2(4+4)}=0.0007;

[0092] P * (1,2) = 0.0017;

[0093] P * (5,5)=1 / 8π=0.0398;

[0094] The probability values ​​of each grid are calculated in turn, and the obtained normal distribution probability map is as follows: Figure 5 shown;

[0095] Then calculate the sum of all grid probabilities P t ; via P k (i,j)=P * k (i,...

technical field

[0001] The invention relates to the technical field of target search, in particular to a police multi-UAV target search method based on a normal distribution probability map. Background technique

[0002] With the rapid development of science and technology, many technological products have appeared, such as drones, which can not only be used in rescue and shooting, but also in police security, because police security drones are equipped with cameras , and then police officers can use the camera to carry out police prevention and target search and tracking, which is convenient for monitoring suspicious personnel and arresting criminal suspects.

[0003] At present, when multi-UAVs perform target search, the probability map based on the random distribution of target existence probability values. However, this search method has randomness and blindness, especially in the case of determining the suspicious position of the target. If the target search is still c...

Examples

Embodiment approach

[0087] The first way:

[0088] Calculate the probability values ​​of each grid in turn according to the joint probability density formula of normal distribution; among them, the joint probability density formula of normal distribution is as follows:

[0089] Among them, x and y are the abscissa and ordinate of the grid respectively, μ x and μ y is the grid coordinate (x, y) of the suspicious position of the target, σ x and σ y take 2;

[0090] For example, when a suspected target suspect is found in the grid (5, 5), the center position of the normal distribution is selected as (5, 5), μ x and μ y The value is 5,

[0091] P * (1,1)=1 / 8π*exp{-1 / 2(4+4)}=0.0007;

[0092] P * (1,2) = 0.0017;

[0093] P * (5,5)=1 / 8π=0.0398;

[0094] The probability values ​​of each grid are calculated in turn, and the obtained normal distribution probability map is as follows: Figure 5 shown;

[0095] Then calculate the sum of all grid probabilities P t ; via P k (i,j)=P * k (i,...

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