CN110286699B - Unmanned aerial vehicle optimal speed scheduling method based on actual model in wireless sensor network data acquisition - Google Patents

Unmanned aerial vehicle optimal speed scheduling method based on actual model in wireless sensor network data acquisition Download PDF

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CN110286699B
CN110286699B CN201910451515.6A CN201910451515A CN110286699B CN 110286699 B CN110286699 B CN 110286699B CN 201910451515 A CN201910451515 A CN 201910451515A CN 110286699 B CN110286699 B CN 110286699B
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熊润群
李修阳
单冯
罗军舟
东方
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Southeast University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
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    • G05D13/00—Control of linear speed; Control of angular speed; Control of acceleration or deceleration, e.g. of a prime mover
    • G05D13/62—Control of linear speed; Control of angular speed; Control of acceleration or deceleration, e.g. of a prime mover characterised by the use of electric means, e.g. use of a tachometric dynamo, use of a transducer converting an electric value into a displacement
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Abstract

The invention discloses an unmanned aerial vehicle optimal speed scheduling method based on an actual model in wireless sensor network data acquisition. The method comprises three parts, namely scene information preprocessing, effective speed calculation of 'segments' and unmanned aerial vehicle flight speed setting. Firstly, processing sensor information and initializing segment information; then calculating the effective speed of each segment according to the parameters of the effective distance, the effective time and the like; and finally, screening the obtained effective speed to finally obtain the optimal speed plan of the unmanned aerial vehicle.

Description

Unmanned aerial vehicle optimal speed scheduling method based on actual model in wireless sensor network data acquisition
Technical Field
The invention belongs to the field of wireless sensor network data acquisition research, and particularly relates to an unmanned aerial vehicle optimal speed scheduling method based on an actual model in wireless sensor network data acquisition.
Background
Recently, wireless communication technology based on unmanned aerial vehicles has attracted great attention. The main advantage of this emerging technology is that drones can take advantage of their high mobility to establish a visual communication link with the ground, thereby mitigating signal blocking. One of the key applications is the collection of massive amounts of data in wireless sensor networks. In conventional wireless sensor network data collection, especially in remote, rugged terrain environments, static sensors must perform multi-hop transmissions due to limited communication range. This means that some sensors need to transmit their own data as well as other sensors, which results in the sensors quickly draining their own power and increasing the packet loss rate. To address the problem of fast sensor battery power consumption in the traditional mode, many applications use mobile vehicles to collect data in wireless sensor networks. It is clear that the data collection model based on moving vehicles reduces the number of data transfers and improves the network lifetime, but the cost of vehicle collection and the limitation of terrain are still significant disadvantages. In order to solve the above-mentioned shortcoming in traditional data acquisition mode, a data collection mode based on unmanned aerial vehicle has been developed in recent years.
Obviously, the number of times is forwarded to information has been reduced to data acquisition mode based on unmanned aerial vehicle to have advantages such as not being restricted by topography, cost low cost, extension wireless sensor network life-span, but also have not negligible simultaneously not enoughly: unmanned aerial vehicle battery energy is limited. Therefore, how to ensure that the unmanned aerial vehicle performs information collection with low energy consumption is crucial, which means that precise modeling of the energy consumption of the unmanned aerial vehicle is necessary. At present, in the existing mode, the flying energy consumption of the unmanned aerial vehicle is generally considered to be only related to the length of a driving distance, because the energy consumption model of the unmanned aerial vehicle in the existing mode generally adopts a theoretical energy consumption model in which the power of the unmanned aerial vehicle linearly increases along with the increase of the speed. Obviously, the unmanned aerial vehicle energy consumption model ignores the influence of speed and time on energy consumption.
In fact, through a test flight test in a real environment, the relationship between the actually measured unmanned aerial vehicle power and different speeds is found, as shown in fig. 2, the unmanned aerial vehicle power firstly drops and then rises along with the increase of the speed, and a convex function relationship is presented, and the difference between the unmanned aerial vehicle power and the theoretical model is large. Obviously, the application developed based on the theoretical model has great risk due to the fact that the residual capacity of the unmanned aerial vehicle cannot be accurately measured in the specific implementation process. And the energy consumption model of the unmanned aerial vehicle in the actual environment obtained from the experiment is as shown in fig. 2, and the flight energy consumption of the unmanned aerial vehicle is not only related to the flight distance, but also closely related to the flight speed. Therefore, how to design the flight control strategy of the unmanned aerial vehicle based on the actual energy consumption model enables the unmanned aerial vehicle to collect all sensor information and enables the energy consumption of the unmanned aerial vehicle to be the lowest, and the method is a key challenging problem.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems, the invention provides an optimal speed scheduling method of the unmanned aerial vehicle based on an actual model in data acquisition of a wireless sensor network, and aims to solve the problem of energy consumption optimization of the unmanned aerial vehicle in the data collection process. According to the method, aiming at a scene that the sensors are linearly distributed, the speed of the unmanned aerial vehicle at any position is calculated according to the transmission time of the global sensor and the required transmission range, so that the unmanned aerial vehicle can acquire all equipment information and the energy consumption is the lowest. Because the corner energy consumption of the unmanned aerial vehicle is very little, after the driving route is determined, the unmanned aerial vehicle can be equivalently converted into a straight line model. Therefore, the method has universality.
The technical scheme is as follows: in order to realize the purpose of the invention, the technical scheme adopted by the invention is as follows: an optimal speed scheduling method for an unmanned aerial vehicle based on an actual model in data acquisition of a wireless sensor network is shown in fig. 1 and comprises the following steps:
step 1, initializing scene information according to relevant parameters of sensors in the environment and calculating the maximum energy-saving speed of the unmanned aerial vehicle in the flight unit distance according to a known energy consumption model aiming at a scene that the sensors are linearly distributed and the unmanned aerial vehicle with a known power and flight speed functional relationship.
Without loss of generality, as shown in fig. 3, suppose that n sensors are distributed on a straight line, this patent adopts the number axis to represent unmanned aerial vehicle flight track, and the point on all tracks all represents the distance from the origin, remembers unmanned aerial vehicle departure position as origin P0End point is Pf. The transmission range of the sensor is limited due to the small transmission power of the sensor. For sensor k, two points where the farthest transmission range of sensor k intersects with the flight trajectory of unmanned aerial vehicle are recorded as lk，rk. Therein, call lkIs the left transmission boundary point of sensor k, rkIs the right transmission boundary point of sensor k, then the interval (l)k，rk) That means that unmanned aerial vehicle flies in this interval and can gather the information of sensor k promptly, and k is more than or equal to 1 and is less than or equal to n.
Due to the n sensors in the scene, there will be a total of 2n transmission boundary points. However, since the left transmission boundary point of a certain sensor may be the right transmission boundary point of other sensors, as shown in FIG. 3, r1Is both the right transmission boundary point of sensor 1 and the left transmission boundary point of sensor 3, so the number m of transmission boundary points may be less than 2n, m ≦ 2 n. Sequencing the m transmission boundary points according to the distance from the origin, and sequentially marking as b1，…，bm. Use of this patentξ (-) function to map the left transmission boundary point l of the sensorkOr right transmission boundary point rkAt b1，…，bmSequence number in (1), as shown in FIG. 3, transmission boundary point l1At b1，…，bmMiddle rank second, therefore ξ (l)1)＝2。
This patent will transmit the boundary point bkAnd bk+1The interval between is defined as a unit interval, k is more than or equal to 1 and less than m, and C is used in the patentkDenotes the kth unit interval, i.e. Ck＝(bk,bk+1). Any sensor i sets a flag bit O according to the requirement of the methodiAny unit interval CkSetting a flag bit AkMarker bit Oi、AkBut only 0 or 1, i is more than or equal to 1 and less than or equal to n.
The functional relations between the power and the flying speed of different unmanned aerial vehicles are different, but all accord with the trend shown in fig. 2, and the power and the flying speed functional relation of the unmanned aerial vehicle in the patent is represented by using p (p) (v). In addition, a fixed speed is inevitably existed when the functional relation is specifically determined, so that the energy consumption of the unmanned aerial vehicle per unit distance is the lowest, and the speed is called as the most energy-saving speed in the patent. The method specifically comprises the following steps:
step 101, all unit intervals CkIs marked with akInitializing to 0, wherein k is more than or equal to 1 and less than m;
102, marking the flag bits O of all the sensorsiInitializing to 0, wherein i is more than or equal to 1 and less than or equal to n;
step 103, transmitting the left transmission boundary points l of all the sensors1，…，lnOrdered according to distance from origin
Figure BDA0002075294790000031
Wherein, a1,a2,..,anIs the corresponding sensor number, as shown in FIG. 3, a1＝2，a2＝1，a3＝3。
104, transmitting the right transmission boundary points r of all the sensors1,…,rnOrdered according to distance from origin
Figure BDA0002075294790000032
Wherein d is1,d2,..,dnIs the corresponding sensor number, as shown in FIG. 3, d1＝1,d2＝2,d4＝4。
And 105, calculating the most energy-saving speed V according to the relation p ═ p (V) between the power of the unmanned aerial vehicle and the speed*. Wherein v ismaxRepresenting the maximum speed at which the drone can travel. V*The calculation is as follows: if equation (1) exists, the understanding is denoted as v1Then V is*＝min(v1,vmax) Else, V*＝vmax。
Figure BDA0002075294790000033
And 2, acquiring the left boundary and the right boundary of the transmission range of all the sensors according to the initialization information acquired in the step 1, and calculating the effective speed of all 'sections' in the scene. Without loss of generality, according to the ordered sequence of steps 103 and 104
Figure BDA0002075294790000034
This patent defines "segment" S (i, j) as the left transmission boundary of the sensor
Figure BDA0002075294790000035
And right transmission boundary
Figure BDA0002075294790000036
In the interval between, i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n. As shown in figure 3 of the drawings,
Figure BDA0002075294790000037
since each sensor has different data volume and different transmission rate, the patent uses tkRepresents the minimum time required for the sensor k to transmit the data of the sensor k to the unmanned aerial vehicle, wherein k is more than or equal to 1 and less than or equal to n, tkReferred to as the sensor k transit time. This patent defines the effective distance of the "segment" S (i, j)D (i, j) is the flag bit A in the segmentkThe length of the unit interval being 0, and the effective time T (i, j) of a "segment" S (i, j) being defined by the patent as the flag bit O located within the "segmentiThe transmission time of the sensor is 0 and the effective velocity V (i, j) of the "segment" S (i, j) is the ratio of the effective distance to the effective time in the "segment".
The step 2 specifically comprises the following steps:
step 201, counting the distribution information of all the segments S (i, j) according to the scene information initialized in step 1, and initializing the effective distances D (i, j), the effective time T (i, j) and the effective speeds V (i, j) of all the segments to 0, wherein i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n.
And 202, calculating the effective distance and the effective time of all the segments S (i, j).
Step 2021, calculating the effective distance D (i, j) of the segment S (i, j) according to the S (i, j) distribution obtained in step 201. The specific calculation process is shown in formula 2.
Figure BDA0002075294790000041
And step 2022, calculating the effective time T (i, j) of the segment S (i, j) according to the S (i, j) distribution obtained in the step 201. The specific calculation process is shown in formula 3. Wherein, tkRepresents the transit time of sensor k:
Figure BDA0002075294790000042
step 203, for any "segment" S (i, j), combining the effective distance D (i, j) obtained in step 2021 and the effective time T (i, j) obtained in step 2022, if T (i, j) ≠ 0, then the effective speed of the "segment" is determined
Figure BDA0002075294790000043
If T (i, j) is equal to 0, the effective speed V (i, j) of the "segment" is set to positive infinity.
Step 3, aiming at the effective speed V (i, j) obtained in the step 203, wherein i is more than or equal to 1 and less than or equal to in,1 is more than or equal to j and less than or equal to n, searching the section S (i, j) with the minimum effective speed, determining the flying speed of the unmanned aerial vehicle on the section when acquiring the sensor information, and changing the flag bit Ak、OiAnd (5) repeating the steps 201, 202 and 203 until the iteration is finished.
The method comprises the following specific steps:
step 301, combining the effective speeds V (i, j) of all the segments obtained in step 203, wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, searching the minimum effective speed V (p, q) which is not 0 and the corresponding segment S (p, q), and if V (p, q) < V*Step 302 is entered, otherwise step 306 is entered;
step 302, regarding the section S (p, q) obtained in the step 301, all the flag bits A of the unmanned aerial vehicle in the section S (p, q)kThe flying speed in the unit interval of 0 is set to V (p, q);
step 303. flag bits A of all unit intervals in the "section" S (p, q) of step 301kSetting as 1;
step 304. flag bit O of the sensor included in the "segment" S (p, q) of step 301iSetting as 1;
step 305, checking whether a flag bit O exists in the sceneiIf the sensor is 0, the step 201 is entered, otherwise, the step 306 is entered;
step 306, if the scene still has the flag bit AkIn the unit interval of 0, the unmanned aerial vehicle is positioned at all the flag bits AkThe flying speed in the unit interval of 0 is defined as V*If so, ending the process of the method; if not, the method flow ends. And determining the flight speed of the unmanned aerial vehicle in each unit interval, and finishing the speed planning of the unmanned aerial vehicle.
Has the advantages that: compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
(1) the method is simple and effective in algorithm, clear in logic, low in complexity, optimal in an off-line state and high in efficiency in an on-line state, and therefore the method can be applied to large-scale wireless sensor network data acquisition in an actual environment.
(2) The key performance indexes of the wireless sensor network are wide coverage, low cost and low power consumption. The default unmanned aerial vehicle power increases linearly along with speed increase under the current collection mode, and is great with unmanned aerial vehicle energy consumption model difference under the actual conditions to the risk of occurence of failure has been increased. The invention starts from an actual energy consumption model, aims at reducing energy consumption, reasonably controls the flight speed of the unmanned aerial vehicle, and accords with the large trend of green energy-saving network acquisition in the industry.
Drawings
FIG. 1 is a flow chart of an optimal speed scheduling method of an unmanned aerial vehicle based on an actual model in wireless sensor network data acquisition, which is implemented by the invention;
FIG. 2 is a diagram showing the relationship between the power and the flying speed of the unmanned aerial vehicle in a real environment;
fig. 3 is a scene diagram of information of four sensors collected based on an unmanned aerial vehicle in a wireless sensor network.
Detailed Description
The present invention is further illustrated by the following description in conjunction with the accompanying drawings and the specific embodiments, it is to be understood that these examples are given solely for the purpose of illustration and are not intended as a definition of the limits of the invention, since various equivalent modifications will occur to those skilled in the art upon reading the present invention and fall within the limits of the appended claims.
The invention provides an unmanned aerial vehicle optimal speed scheduling method based on an actual model in data acquisition of a wireless sensor network, which comprises the following steps as shown in figure 1:
step 1, initializing scene information according to relevant parameters of sensors in the environment and calculating the maximum energy-saving speed of the unmanned aerial vehicle in the flight unit distance according to a known energy consumption model aiming at a scene that the sensors are linearly distributed and the unmanned aerial vehicle with a known power and flight speed functional relationship.
Without loss of generality, as shown in fig. 3, assuming that n sensors are distributed on a straight line, the flight trajectory of the unmanned aerial vehicle is represented by a numerical axis, points on all trajectories represent distances from an origin, and the unmanned aerial vehicle is recordedThe starting position of the machine is the origin P0End point is Pf. The transmission range of the sensor is limited due to the small transmission power of the sensor. For sensor k, two points where the farthest transmission range of sensor k intersects with the flight trajectory of unmanned aerial vehicle are recorded as lk，rk. Therein, call lkIs the left transmission boundary point of sensor k, rkIs the right transmission boundary point of sensor k, then the interval (l)k,rk) That means that unmanned aerial vehicle flies in this interval and can gather the information of sensor k promptly, and k is more than or equal to 1 and is less than or equal to n.
Due to the n sensors in the scene, there will be a total of 2n transmission boundary points. However, since the left transmission boundary point of a certain sensor may be the right transmission boundary point of other sensors, as shown in FIG. 3, r1Is both the right transmission boundary point of sensor 1 and the left transmission boundary point of sensor 3, so the number m of transmission boundary points may be less than 2n, m ≦ 2 n. Sequencing the m transmission boundary points according to the distance from the origin, and sequentially marking as b1，…，bm. This patent uses the ξ (-) function to map the sensor's left transmission boundary point lkOr right transmission boundary point rkAt b1，…，bmSequence number in (1), as shown in FIG. 3, transmission boundary point l1At b1，…，bmMiddle rank second, therefore ξ (l)1)＝2。
This patent will transmit the boundary point bkAnd bk+1The interval between is defined as a unit interval, k is more than or equal to 1 and less than m, and C is used in the patentkDenotes the kth unit interval, i.e. Ck＝(bk,bk+1). Any sensor i sets a flag bit O according to the requirement of the methodiAny unit interval CkSetting a flag bit AkMarker bit Oi、AkBut only 0 or 1, i is more than or equal to 1 and less than or equal to n.
The functional relations between the power and the flying speed of different unmanned aerial vehicles are different, but all accord with the trend shown in fig. 2, and the power and the flying speed functional relation of the unmanned aerial vehicle in the patent is represented by using p (p) (v). In addition, a fixed speed is inevitably existed when the functional relation is specifically determined, so that the energy consumption of the unmanned aerial vehicle per unit distance is the lowest, and the speed is called as the most energy-saving speed in the patent. The method specifically comprises the following steps:
step 101, all unit intervals CkIs marked with akInitializing to 0, wherein k is more than or equal to 1 and less than m;
102, marking the flag bits O of all the sensorsiInitializing to 0, wherein i is more than or equal to 1 and less than or equal to n;
step 103, transmitting the left transmission boundary points l of all the sensors1,…,lnOrdered according to distance from origin
Figure BDA0002075294790000061
Wherein, a1,a2,..,anIs the corresponding sensor number, as shown in FIG. 3, a1＝2,a2＝1,a3＝3。
104, transmitting the right transmission boundary points r of all the sensors1,…,rnOrdered according to distance from origin
Figure BDA0002075294790000062
Wherein d is1,d2,..,dnIs the corresponding sensor number, as shown in FIG. 3, d1＝1,d2＝2,d4＝4。
And 105, calculating the most energy-saving speed V according to the relation p ═ p (V) between the power of the unmanned aerial vehicle and the speed*. Wherein v ismaxRepresenting the maximum speed at which the drone can travel. V*The calculation is as follows: if equation (1) exists, the understanding is denoted as v1Then V is*＝min(v1,vmax) Else, V*＝vmax。
Figure BDA0002075294790000071
And 2, acquiring the left boundary and the right boundary of the transmission range of all the sensors according to the initialization information acquired in the step 1, and calculating the effective speed of all 'sections' in the scene. Without loss of generalityAccording to the ordered sequence of step 103 and step 104
Figure BDA0002075294790000072
This patent defines "segment" S (i, j) as the left transmission boundary of the sensor
Figure BDA0002075294790000073
And right transmission boundary
Figure BDA0002075294790000074
In the interval between, i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n. As shown in figure 3 of the drawings,
Figure BDA0002075294790000075
since each sensor has different data volume and different transmission rate, the patent uses tkRepresents the minimum time required for the sensor k to transmit the data of the sensor k to the unmanned aerial vehicle, wherein k is more than or equal to 1 and less than or equal to n, tkReferred to as the sensor k transit time. This patent defines the effective distance D (i, j) of the "segment" S (i, j) as the marker bit A in the "segmentkThe length of the unit interval being 0, and the effective time T (i, j) of a "segment" S (i, j) being defined by the patent as the flag bit O located within the "segmentiThe transmission time of the sensor is 0 and the effective velocity V (i, j) of the "segment" S (i, j) is the ratio of the effective distance to the effective time in the "segment".
The step 2 specifically comprises the following steps:
step 201, counting the distribution information of all the segments S (i, j) according to the scene information initialized in step 1, and initializing the effective distances D (i, j), the effective time T (i, j) and the effective speeds V (i, j) of all the segments to 0, wherein i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n.
And 202, calculating the effective distance and the effective time of all the segments S (i, j).
Step 2021, calculating the effective distance D (i, j) of the segment S (i, j) according to the S (i, j) distribution obtained in step 201. The specific calculation process is shown in formula 2.
Figure BDA0002075294790000076
And step 2022, calculating the effective time T (i, j) of the segment S (i, j) according to the S (i, j) distribution obtained in the step 201. The specific calculation process is shown in formula 3. Wherein, tkRepresents the transit time of sensor k:
Figure BDA0002075294790000077
step 203, for any "segment" S (i, j), combining the effective distance D (i, j) obtained in step 2021 and the effective time T (i, j) obtained in step 2022, if T (i, j) ≠ 0, then the effective speed of the "segment" is determined
Figure BDA0002075294790000081
If T (i, j) is equal to 0, the effective speed V (i, j) of the "segment" is set to positive infinity.
Step 3, aiming at the effective speed V (i, j) obtained in the step 203, wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, searching the section S (i, j) with the minimum effective speed, determining the flying speed of the unmanned aerial vehicle on the section when the unmanned aerial vehicle collects the sensor information, and changing the flag bit Ak、OiAnd (5) repeating the steps 201, 202 and 203 until the iteration is finished.
The method comprises the following specific steps:
step 301, combining the effective speeds V (i, j) of all the segments obtained in step 203, wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, searching the minimum effective speed V (p, q) which is not 0 and the corresponding segment S (p, q), and if V (p, q) < V*Step 302 is entered, otherwise step 306 is entered;
step 302, regarding the section S (p, q) obtained in the step 301, all the flag bits A of the unmanned aerial vehicle in the section S (p, q)kThe flying speed in the unit interval of 0 is set to V (p, q);
step 303. flag bits A of all unit intervals in the "section" S (p, q) of step 301kSetting as 1;
step 304. flag bit O of the sensor included in the "segment" S (p, q) of step 301iSetting as 1;
step 305, checking whether a flag bit O exists in the sceneiIf the sensor is 0, the step 201 is entered, otherwise, the step 306 is entered;
step 306, if the scene still has the flag bit AkIn the unit interval of 0, the unmanned aerial vehicle is positioned at all the flag bits AkThe flying speed in the unit interval of 0 is defined as V*If so, ending the process of the method; if not, the method flow ends. And determining the flight speed of the unmanned aerial vehicle in each unit interval, and finishing the speed planning of the unmanned aerial vehicle.
The invention mainly solves the problem of reducing the flight energy consumption of the unmanned aerial vehicle in the data acquisition of the wireless sensor network based on the unmanned aerial vehicle. The method mainly comprises three parts logically, namely scene information preprocessing, effective speed calculation of 'segments' and unmanned aerial vehicle flight speed setting. Firstly, processing sensor information and initializing segment information; then calculating the effective speed of each segment according to the parameters of the effective distance, the effective time and the like; and finally, screening the obtained effective speed to finally obtain the optimal speed plan of the unmanned aerial vehicle.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (1)

1. An unmanned aerial vehicle optimal speed scheduling method based on an actual model in wireless sensor network data acquisition is characterized by comprising the following steps:
the method comprises the following steps that (1) scene information is initialized according to relevant parameters of sensors in the environment aiming at scenes that the sensors are linearly distributed and unmanned aerial vehicles with known power and flight speed functional relations, and the maximum energy-saving speed of the unmanned aerial vehicles in unit flight distance is calculated according to a known energy consumption model;
step (2) of acquiring the left sides of the transmission ranges of all the sensors according to the initialization information acquired in the step (1)Calculating the effective velocity V (i, j) of all 'sections' in the scene, wherein the 'sections' S (i, j) are the left transmission boundaries of the sensor
Figure FDA0002742313830000011
And right transmission boundary
Figure FDA0002742313830000012
In the interval between the two sensors, i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, and n is the number of the sensors;
step (3), aiming at the obtained effective speed V (i, j), searching a section S (i, j) with the minimum effective speed, determining the flying speed of the unmanned aerial vehicle on the section when the unmanned aerial vehicle collects the sensor information, and changing a zone bit Ak、OiAnd (3) repeating the step (2) until the optimal scheduling speed of the unmanned aerial vehicle on all sections is determined;
the specific method for initializing the scene information in the step (1) is as follows:
(1.1) assuming that n sensors are distributed on a straight line, adopting a numerical axis to represent the flight track of the unmanned aerial vehicle, points on all tracks represent the distance from the original point, and recording the starting position of the unmanned aerial vehicle as the original point P0End point is PfFor sensor k, the two points where the farthest transmission range of sensor k intersects with the flight trajectory of unmanned aerial vehicle are recorded as lk，rkTherein, call lkIs the left transmission boundary point of sensor k, rkIs the right transmission boundary point of sensor k, then the interval (l)k，rk) Namely, the unmanned aerial vehicle flies in the interval to acquire the information of the sensor k, wherein k is more than or equal to 1 and less than or equal to n;
(1.2) because n sensors in the scene have 2n transmission boundary points in total, but because the left transmission boundary point of a certain sensor may be the right transmission boundary point of other sensors, the number m of the transmission boundary points may be less than 2n, that is, m is less than or equal to 2 n; sequencing the m transmission boundary points according to the distance from the origin, and sequentially marking as b1，…，bmMapping the left transmission boundary point l of the sensor using the ξ (-) functionkOr right transmission boundary point rkAt b1，…，bmThe serial number in (1);
(1.3) will transmit the boundary point bkAnd bk+1The interval between is defined as a unit interval, k is more than or equal to 1 and less than m, C is usedkDenotes the kth unit interval, i.e. Ck＝(bk，bk+1) Any sensor i is set with a flag bit OiAny unit interval CkSetting a flag bit AkMarker bit Oi、AkOnly 0 or 1, i is more than or equal to 1 and less than or equal to n;
in the step (1), the maximum energy-saving speed of the unmanned aerial vehicle in unit distance of flight is calculated according to a known energy consumption model, and the method comprises the following steps:
step 101, all unit intervals CkIs marked with akInitializing to 0, wherein k is more than or equal to 1 and less than m;
102, marking the flag bits O of all the sensorsiInitializing to 0, wherein i is more than or equal to 1 and less than or equal to n;
step 103, transmitting the left transmission boundary points l of all the sensors1，...，lnOrdered according to distance from origin
Figure FDA0002742313830000021
Wherein, a1，a2，..，anIs the corresponding sensor number;
104, transmitting the right transmission boundary points r of all the sensors1，...，rnOrdered according to distance from origin
Figure FDA0002742313830000022
Wherein d is1，d2，..，dnIs the corresponding sensor number;
and 105, calculating the most energy-saving speed V according to the relation p ═ p (V) between the power of the unmanned aerial vehicle and the speed*Wherein v ismaxRepresents the maximum speed, V, at which the unmanned aerial vehicle can travel*The calculation is as follows: if equation (1) exists, the understanding is denoted as v1Then V is*＝min(v1，vmax) Else, V*＝vmax；
Figure FDA0002742313830000023
The specific method of the step (2) is as follows:
(2.1) defining "segment" S (i, j) as the left transmission boundary of the sensor
Figure FDA0002742313830000025
And right transmission boundary
Figure FDA0002742313830000026
In the interval between, i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, tkThe transmission time of the sensor k is the minimum time required by the sensor k to transmit the self data to the unmanned aerial vehicle, the time is only related to the data transmission amount and the transmission rate, wherein k is more than or equal to 1 and less than or equal to n, and the effective distance D (i, j) of the segment S (i, j) is defined as a mark bit A in the segmentkThe sum of the lengths of the unit intervals of 0, the effective time T (i, j) defining a "segment" S (i, j) being the flag bit O located within this "segmentiThe sum of the transmission times of all sensors is 0, and the effective speed V (i, j) of the section S (i, j) is the ratio of the effective distance to the effective time in the section;
(2.2) counting the distribution information of all the sections S (i, j) according to the scene information initialized in the step (1), and initializing the effective distances D (i, j), the effective time T (i, j) and the effective speeds V (i, j) of all the sections to be 0, wherein i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n;
(2.3) calculating the effective distance and the effective time of all the 'sections' S (i, j);
step 2031, calculating the effective distance D (i, j) of the "segment" S (i, j) according to the distribution of S (i, j) obtained in step (2.2), the specific calculation process is shown in formula 2:
Figure FDA0002742313830000024
step 2032, calculating the effective time T (i, j) of the "segment" S (i, j) according to the S (i, j) distribution obtained in step (2.2), wherein the specific calculation process is shown in formula 3, wherein T iskRepresents the transit time of sensor k:
Figure FDA0002742313830000031
(2.4) for any "segment" S (i, j), combining the valid distance D (i, j) obtained in step 2031 and the valid time T (i, j) obtained in step 2032, if T (i, j) ≠ 0, then the valid speed of the "segment" is
Figure FDA0002742313830000032
If T (i, j) is 0, the effective speed V (i, j) of the "segment" is set to positive infinity;
the specific method of the step (3) is as follows:
step 301, combining the effective speeds V (i, j) of all the segments obtained in the step (2.4), wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, searching the minimum effective speed V (p, q) which is not 0 and the corresponding segment S (p, q), and if V (p, q) < V*Step 302 is entered, otherwise step 306 is entered;
step 302, for the "section" S (p, q) obtained in step 301, setting the flight speed of the unmanned aerial vehicle on the unit section where all the flag bits Ak are 0 in the "section" S (p, q) to V (p, q);
step 303. flag bits A of all unit intervals in the "section" S (p, q) of step 301kSetting as 1;
step 304. flag bit O of the sensor included in the "segment" S (p, q) of step 301iSetting as 1;
step 305, checking whether a flag bit O exists in the sceneiIf the sensor is 0, then go to step (2.1), otherwise go to step 306;
step 306, if the scene still has the flag bit AkIn the unit interval of 0, the unmanned aerial vehicle is positioned at all the flag bits AkThe flying speed in the unit interval of 0 is defined as V*If so, ending the process of the method; if not, the flow of the method is ended until the flight speed of the unmanned aerial vehicle in each unit interval is determined, and the speed planning of the unmanned aerial vehicle is completed.
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