CN115292857B - Sound network layout method for unmanned aerial vehicle detection - Google Patents
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Abstract
The application discloses a sound net layout method for unmanned aerial vehicle detection, which comprises the following steps: s1, establishing an environment model of an area to be detected, and acquiring barrier information and area information in the area to be detected based on the environment model; s2, deploying a plurality of sensors based on the environment model, and calculating the resultant force of virtual force borne by each sensor and the position of the sensor in the next step; and S3, judging whether sampling nodes in the detection system meet the reliability requirement, if so, outputting a sensor layout structure, and if not, increasing the number of sensors and returning to S2. The layout method provided by the application fully considers the complex environment factors, enhances the detection target area and avoids detecting the obstacle area, and improves the environmental adaptability of the sensor detection system.
Description
Technical Field
The application belongs to the technical field of wireless sensor network coverage control, and particularly relates to a sound network layout method for unmanned aerial vehicle detection.
Background
The unmanned aerial vehicle detection technology is an important research subject in the field of sensor detection at present. The micro unmanned aerial vehicle has small volume, light weight and good concealment, can play all roles in a detection task or a search task with high risk, and can be widely applied to tactical detection, distance detection, destruction of enemy missiles and the like in future war. By establishing the sound network layout method for unmanned aerial vehicle detection, the unmanned aerial vehicle can be judged and identified quickly and accurately.
However, most of the current research focuses on coverage optimization of a single type of sensor in a simple environment, and does not deeply explore the problems related to fusion detection of multiple sensors in a sensor system under complex and variable situations. To sum up, the problem that exists in present sensor layout technical field is: 1) The sensor network has poor robustness and slow convergence; 2) Local oscillation can occur in the layout; 3) The simple sensor network layout of the sensor detection system environment usually only considers the layout of a single type of sensor and can not integrate multiple types of sensors, thereby generating more reasonable layout.
In summary, the difficulties in solving the above problems are: the optimal arrangement point is found for the sound sensor by combining different types of sensors, so that the detection reliability of the sensor system is ensured, and the coverage rate of the sensor network is considered; after the environment changes, the sensor network can be adjusted in a self-adaptive mode, and the reliability of the overall detection is guaranteed.
Content of application
The application provides a sound net layout method for unmanned aerial vehicle detection, combines temperature, humidity and optical sensor detection results, and adjusts a sound sensor network to improve the reliability and robustness of the whole detection system.
In order to achieve the above purpose, the present application provides the following solutions:
a sound net layout method for unmanned aerial vehicle detection comprises the following steps:
s1, establishing an environment model of a region to be detected, and acquiring barrier information and region information in the region to be detected based on the environment model;
s2, deploying a plurality of sensors based on the environment model, and calculating the resultant force of virtual force borne by each sensor and the position of the next sensor;
and S3, judging whether sampling nodes in the detection system meet the reliability requirement, if so, outputting a sensor layout structure, otherwise, increasing the number of sensors, and returning to the S2.
Optionally, the S1 includes:
performing mathematical modeling on the area to be detected, establishing the environment model, and initializing environment information, wherein the environment information is an environment influence source of the sensor;
and monitoring the environmental information, and adjusting the position of the sensor when the environmental parameter of the environmental information is lower than an environmental threshold value. Optionally, the environmental information includes noise, illuminance, relative humidity, and occlusion.
Optionally, the S2 includes:
s21, initializing the number and the positions of the sensors;
s22, calculating the resultant force of the virtual force applied to each sensor,
s23, calculating the next step position of the sensor according to the resultant force of the virtual forces received by the sensor;
and S24, assuming to update the position of the sensor, calculating the coverage area of the detection system at the moment, updating the position of the sensor if the coverage area is increased, returning to S22, and otherwise, keeping the position of the sensor unchanged and entering S3.
Optionally, the virtual resultant force sources to which the sensors are subjected include mutual force between the sensors, attraction force of the target area and repulsion force of the obstacle.
Optionally, the virtual resultant force
Expressed as:
the attractive force of the target area is expressed as:
wherein, w A As a parameter of the magnitude of the attraction, d iA Is the Euclidean distance, alpha, of the sensor from the target area iA Is the direction included angle between the sensor and the target area;
the repulsive force of the obstacle is expressed as:
wherein, w R As a parameter of the magnitude of the repulsive force, d iR Is a sensor S i Euclidean distance from obstacle, α iR Is a sensor S i The direction included angle with the barrier area;
the mutual force between the sensors is expressed as:
wherein w A As a parameter of the magnitude of the attractive force, w R Parameter of magnitude of repulsive force, d ij Is the Euclidean distance between the sensors, d th Is a distance threshold between sensors, alpha ij Is a sensor S i And a sensor S j Is included in the direction of (a).
Optionally, the formula for calculating the next position of the sensor is as follows:
wherein,
predicting the displacement for the sensor, d 0 In order to set the step size of the movement,
is the resultant of the virtual forces experienced by the sensor,
is the magnitude of the resultant of the virtual forces, F th To set the threshold, λ is the ratio of the virtual force magnitude to the threshold.
Optionally, the relationship between the reliability of the sensors and the distance between the sensors is as follows:
wherein d is the distance between the sensor and the preset point, α and β are parameters describing the variation of the sensor reliability with the distance, δ is a reliability parameter, r 1 、r 2 Detecting a range parameter for the sensor is related to a sensor characteristic.
Optionally, the formula of the reliability is:
wherein γ = γ n γ l γ w γ b Representing environmental influencing factors.
Compared with the prior art, the beneficial effects of this application are as follows:
1) The layout method provided by the application fully considers complex environmental factors, enhances the detection target area, avoids detecting the obstacle area, and also considers the influence of environmental factors such as shielding degree and noise interference on the detection reliability, thereby greatly improving the environmental adaptability of the sensor detection system;
2) The layout method provided by the application can meet the detection requirements of different conditions by adjusting parameters, so that the maximum system function can be exerted while the minimum resources are used;
3) The layout method provided by the application integrates various sensors, and the influence of environmental factors on the sensors is comprehensively considered, so that the sensor system can better adapt to the influence of complex conditions on the reliability of the sensor system, which is very key for constructing a novel unmanned aerial vehicle detection system;
4) The layout method has high universality, can be applied to the layout of various sensors, and has obvious application value and prospect.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings required to be used in the embodiments are briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
Fig. 1 is a schematic flow chart of a sound network layout method for unmanned aerial vehicle detection according to an embodiment of the present application;
FIG. 2 is a schematic diagram of modeling of different blocking conditions of an obstacle in a detection range of a sensor in the embodiment of the application;
fig. 3 is a schematic diagram of a virtual force applied to a sensor in a virtual force strategy according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
Example one
As shown in fig. 1, which is a schematic flow chart of a sound network layout method for unmanned aerial vehicle detection according to an embodiment of the present application, the present embodiment integrates multiple detection means and is based on a virtual force strategy with respect to the layout of sound sensors, and mainly includes the following steps,
the first step is as follows: the method comprises the steps of carrying out mathematical modeling on a region to be detected, establishing an environment model of the region to be detected, determining barrier information and region information in the region to be detected based on the environment model, and periodically monitoring environmental changes. The obstacle information and the area information need to be determined according to specific situations, for example, in a security task of a major activity, a detection system needs to protect an activity meeting place, so that a field area is modeled as a target area to be detected, and areas which do not need to be detected, such as buildings around the meeting place, are modeled as obstacles.
According to the preliminary detection result, environment information is initialized, and the introduced parameter gamma represents the influence of the environment on the performance of the sensor network, wherein the gamma n Representing the effect of noise on the sensor; gamma ray l Representing the effect of light intensity on the sensor; gamma ray w Represents the effect of air humidity on the sensor; gamma ray b As shown in fig. 2, the influence of an obstruction such as a building on the sensor can be roughly classified into mild, moderate, and severe cases of obstruction of different degrees in the present embodiment.
And periodically checking parameters of noise, illuminance and environment relative humidity, and adjusting the sensor system if the monitored environment parameters are lower than a threshold value. For example, when the system enters the night, the distance parameter of the sound sensor system is reduced, the optimization reliability of the overlapping area between the sound sensors is increased, otherwise, the distance parameter of the sound sensor is increased, and the overlapping area between the sound sensors is reduced, so that the coverage rate of the system is optimized.
S13, periodically checking the communication of the sensors, and if the sensors fail or cannot work, excluding the sensors from the system and then entering the step S2.
The second step is that: based on an environment model, sensors are initially deployed, a certain number of sensors are randomly distributed in an area, and the sensors are numbered S 1 、S 2 、...、S i .. Suppose a sensor S i Is placed at point (x) i ,y i ) To (3). For any point P (x, y), the distance from the sensor to the point P can be obtained according to a distance formula
In this embodiment, the relationship between the sensor reliability and the distance is modeled as follows:
wherein e is a natural constant, d is a sensor S i The distance from point P, alpha and beta are parameters describing the variation of sensor reliability with distance, and delta isThe reliability parameter, r 1 、r 2 Detecting a range parameter for the sensor is related to a sensor characteristic.
The third step: the resultant virtual force on each sensor is calculated, as shown in FIG. 3, and the sensor S i Receiving three virtual forces, namely the attraction force of the target area
Repulsive force of obstacle
The resultant force of the mutual force between the sensor and other sensors and the virtual force applied to the sensor
Can be expressed as:
wherein, the attractive force formula of the target area is,
w A as a parameter of the magnitude of the attraction, d iA Is a sensor S i Euclidean distance, α, from the target region iA Is a sensor S i At an angle to the direction of the target area.
The repulsive force of the obstacle is formulated as,
w R as a parameter of the magnitude of the repulsive force, d iR Is a sensor S i Euclidean distance from obstacle, α iR Is a sensor S i Angled with respect to the direction of the barrier area.
The mutual stress formula among the sensors is as follows:
w A as a parameter of the magnitude of the attractive force, w R As a parameter of the magnitude of the repulsive force, d ij Is a sensor S i And a sensor S j Euclidean distance between, d th Is a sensor S i And a sensor S j A distance threshold value between, alpha ij Is a sensor S i And a sensor S j Is included in the direction of (a).
As shown in FIG. 3, with S 1 Sensor is an example, S 2 Too close to receive S 2 Repulsive force of
Off-sensor S 3 Too far away to receive S 3 Attractive force of
Is attracted by the target area
Repulsive force due to obstacle
So that the resultant force can be calculated.
The fourth step: obtaining the next displacement according to the resultant force, thereby calculating the next position of the sensor and using the sensor S i The next step of the displacement calculation for the example is as follows,
wherein,
prediction of displacement for the sensor, d 0 In order to set the step size of the movement,
is a sensor S i The resultant of the virtual forces experienced by the device,
is the magnitude of the resultant force of the virtual forces, F th For the set threshold, lambda is the ratio of the virtual force magnitude to the threshold, so that the sensor displacement is more flexible and the local vibration is reduced.
The fifth step: and according to the fourth step, calculating new positions of all the sensors and then judging whether the coverage area of the system is increased. If the coverage area is increased, the position of the sensor is updated, and the step III is returned, otherwise, the step VI is carried out to calculate the node reliability.
And a sixth step: a certain number of sampling nodes are taken for a sensor detection system, and the purpose is to monitor the coverage condition and the reliability of the detection system. Consider a point (x, y) in the detection range at which the system detects an object with a reliability c x,y (S all ) Then:
wherein c is x,y (S i ) Indicating that the sensor is at this point S i The reliability of the detected target can be calculated according to a probability formula, and the reliability of the detected target in the whole system can be calculated at the point (x, y).
After the influence of the introduced regional environment on the reliability is introduced, the node detection reliability formula is changed into:
wherein γ = γ n γ l γ w γ b Representing environmental influences.
The seventh step: and judging whether the nodes in the system meet the reliability according to the calculation result of the sixth step, namely:
c x,y (S all )≥c th
wherein c is x,y (S all ) As node reliability, c th To set a reliability threshold.
If the conditions are met, outputting a layout result, otherwise, increasing the number of the sensors, and returning to the second step.
The above-described embodiments are merely illustrative of the preferred embodiments of the present application, and do not limit the scope of the present application, and various modifications and improvements made to the technical solutions of the present application by those skilled in the art without departing from the design spirit of the present application should fall within the protection scope defined by the claims of the present application.
Claims (3)
1. A sound net layout method for unmanned aerial vehicle detection is characterized by comprising the following steps:
s1, establishing an environment model of an area to be detected, and acquiring obstacle information and area information in the area to be detected based on the environment model;
s2, deploying a plurality of sensors based on the environment model, and calculating the resultant force of virtual force borne by each sensor and the position of the next sensor;
s3, judging whether sampling nodes in the detection system meet the reliability requirement or not, if so, outputting a sensor layout structure, and if not, increasing the number of sensors and returning to S2;
the S2 comprises the following steps:
s21, initializing the number and the positions of the sensors;
s22, calculating the resultant virtual force received by each sensor,
s23, calculating the next step position of the sensor according to the resultant force of the virtual forces received by the sensor;
s24, assuming to update the position of the sensor, calculating the coverage area of the detection system at the moment, if the coverage area is increased, updating the position of the sensor and returning to S22, otherwise, keeping the position of the sensor unchanged and entering S3;
the virtual force resultant force source borne by the sensors comprises mutual force among the sensors, attractive force of a target area and repulsive force of an obstacle;
resultant force of the virtual forces
Expressed as:
the attractive force of the target area is expressed as:
wherein, w A As a parameter of the magnitude of the attraction, d iA Is the Euclidean distance, alpha, of the sensor from the target area iA Is the direction included angle between the sensor and the target area;
the repulsive force of the obstacle is expressed as:
wherein, w R As a parameter of the magnitude of the repulsive force, d iR Is a sensor S i Euclidean distance from obstacle, α iR Is a sensor S i The direction included angle with the obstacle area;
the mutual force between the sensors is expressed as:
wherein, w A As a parameter of the magnitude of the attractive force, w R Parameter of magnitude of repulsive force, d ij Is the Euclidean distance between the sensors, d th Is a distance threshold between sensors, alpha ij Is a sensor S i And a sensor S j The included angle of the directions of (1);
the formula for calculating the next position of the sensor is as follows:
wherein,
predicting the displacement for the sensor, d 0 In order to set the step size of the movement,
is the resultant of the virtual forces experienced by the sensor,
is the magnitude of the resultant of the virtual forces, F th For a set threshold, λ is the ratio of the virtual force magnitude to the threshold;
the reliability of the sensors and the distance between the sensors are related as follows:
wherein d is the distance between the sensor and the preset point, α and β are parameters describing the variation of the sensor reliability with the distance, δ is a reliability parameter, r 1 、r 2 Detecting for the sensor a distance parameter related to a sensor characteristic;
the formula for the reliability is:
wherein γ = γ n γ l γ w γ b Representing environmental impact factors; c. C x，y (S i ) Indicates that the sensor is at S i The reliability of the object is detected.
2. The sound net layout method for unmanned aerial vehicle detection according to claim 1,
the S1 comprises:
performing mathematical modeling on the area to be detected, establishing the environment model, and initializing environment information, wherein the environment information is an environment influence source of the sensor;
and monitoring the environmental information, and adjusting the position of the sensor when the environmental parameter of the environmental information is lower than an environmental threshold value.
3. The drone detection-oriented sound net layout method of claim 2, wherein the environmental information includes noise, illuminance, relative humidity, and occlusion.
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| CN101051973A (en) * | 2007-05-17 | 2007-10-10 | 浙江大学 | Method and device for layout mobile radio sensor network node based on virtual force |
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| CN107295541A (en) * | 2016-03-31 | 2017-10-24 | 扬州大学 | A kind of radio sensing network coverage optimization method based on fictitious force and glowworm swarm algorithm |
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