Approaching flight method and system for unmanned aerial vehicle to collect single-target sensor data

Abstract

The invention discloses an approaching flight method and system for an unmanned aerial vehicle to collect single-target sensor data, and the method comprises the steps: obtaining the parameter information of the unmanned aerial vehicle if the unmanned aerial vehicle receives a command of flying to a certain sensor; when the unmanned aerial vehicle flies between the take-off point and the sensor, the total flight time t of the unmanned aerial vehicle from the take-off point to the sensor is discretely divided into a time interval of delta t, the acceleration of the unmanned aerial vehicle on the X axis, the Y axis and the Z axis is adjusted by calling the flight power of the unmanned aerial vehicle, and the speed and the position of the unmanned aerial vehicle are controlled; and calculating the data transmission rate of different flight stages, and constructing an optimization model by maximizing the data transmission rate to obtain the optimal flight time. A decision can be made for a way in which an unmanned aerial vehicle (UAV) arrives at a sensor, and a unique and efficient solution is provided.

Description

Technical Field

[0001] The invention belongs to the technical field of unmanned aerial vehicle flight control, and relates to a close-in flight method and system for unmanned aerial vehicle to collect single-target sensor data. Background Art

[0002] With the rapid development of science and technology, drone technology has been widely used in various fields, such as aerial photography, agricultural monitoring, environmental monitoring, military reconnaissance, etc. The end of drone flight control marks the completion of the drone mission and the entry into the safe landing and recovery stage. In the process of drones performing flight missions, the flight control system plays a vital role. It is responsible for key operations such as drone takeoff, hovering, route planning, obstacle avoidance and landing. Through advanced sensors and algorithms, the flight control system can perceive the state of the drone and environmental changes in real time to ensure that the drone can fly stably in various complex environments. When the drone completes the mission and is ready to end the flight, the flight control system will guide the drone to land safely according to the preset program or instructions. This stage also requires high-precision control and judgment to ensure that the drone can land smoothly and avoid accidents.

[0003] In scenarios such as smart cities, scattered sensors are responsible for collecting information about the surrounding environment, traffic, etc., and drones can fly close to the sensors by calling flight power to adjust their flight attitude, thereby obtaining sensor data. However, how to make decisions on the approach of drones to sensors is a key issue that needs to be addressed. The present invention focuses on the approach flight method of drones to solve the problem of sensor data transmission, and studies the flight method technology of drones (UAVs). Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for close-in flight of a UAV to collect single-target sensor data, which can make decisions on the way in which a UAV (UAV) approaches a sensor, providing a unique and efficient solution.

[0005] The technical solution to achieve the purpose of the present invention is:

[0006] A close-in flight method for collecting single-target sensor data by a drone comprises the following steps:

[0007] S01: If the drone receives a command to fly to a certain sensor, it obtains the drone parameter information;

[0008] S02: When the UAV is flying between the take-off point and the sensor, the total flight time t of the UAV from the take-off point to the sensor is discretely divided into time intervals of Δt, and the acceleration on the X-axis, Y-axis and Z-axis is adjusted by calling its own flight power to control the speed and position of the UAV;

[0009] S03: Calculate the data transmission rate at different flight stages, build an optimization model by maximizing the data transmission rate, and obtain the optimal flight time.

[0010] In the preferred technical solution, the parameters obtained in step S01 include the mass m of the drone, the gravity acceleration g of the current flight area, the location information of the drone and the target sensor, and the total flight power p. 总 , the coordinates of the drone take-off are set as the origin of the three-dimensional coordinate system (0,0,0), and the coordinates of the target sensor are (x E ,y E ,z E ).

[0011] In the preferred technical solution, in step S02, different flight modes are divided according to the time when the drone flies to the sensor, the acceleration and deceleration flight of the drone on the Z axis, and the acceleration, constant speed and deceleration flight in the horizontal direction.

[0012] In the preferred technical solution, the step S03 further includes:

[0013] After obtaining the optimal flight time, calculate the amount of data sent by the sensor to the drone;

[0014] The average data transmission rate is calculated, and the UAV selects the flight mode with the largest average data transmission rate in the set to fly close to the sensor.

[0015] The present invention also discloses a close-in flight system for a drone to collect single-target sensor data, comprising a processor, wherein the processor is built with the close-in flight method for a drone to collect single-target sensor data.

[0016] The present invention further discloses an unmanned aerial vehicle, comprising the close-in flight system for collecting single-target sensor data of the unmanned aerial vehicle.

[0017] The present invention further discloses a computer storage medium on which a computer program is stored. When the computer program is executed, the above-mentioned approach flight method of the unmanned aerial vehicle for collecting single-target sensor data is implemented.

[0018] Compared with the prior art, the present invention has the following significant advantages:

[0019] The approach flight method of the present invention is applied in scenarios such as smart cities. Scattered sensors are responsible for collecting information such as the surrounding environment and traffic. The UAV can fly close to the sensor by calling the flight power to adjust its flight attitude, thereby obtaining the sensor data. The key problem is solved by making decisions on the way the UAV approaches the sensor. The present invention conducts in-depth theoretical analysis and application exploration of the approach flight technology, aiming to provide a unique and efficient solution. The scenario physically conforms to real-life applications and can be effectively applied to engineering practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of the close-in flight method for collecting single-target sensor data by the UAV of this embodiment;

[0021] Figure 2 This is a flow chart of the close-in flight method for collecting single-target sensor data by the UAV of this embodiment. DETAILED DESCRIPTION

[0022] Embodiment 1:

[0023] like Figure 1 As shown, a close-in flight method for collecting single-target sensor data by a drone is characterized by comprising the following steps:

[0024] S01: If the drone receives a command to fly to a certain sensor, it obtains the drone parameter information;

[0025] S02: When the UAV is flying between the take-off point and the sensor, the total flight time t of the UAV from the take-off point to the sensor is discretely divided into time intervals of Δt, and the acceleration on the X-axis, Y-axis and Z-axis is adjusted by calling its own flight power to control the speed and position of the UAV;

[0026] S03: Calculate the data transmission rate at different flight stages, build an optimization model by maximizing the data transmission rate, and obtain the optimal flight time.

[0027] The specific implementation is as follows Figure 2 As shown, the following steps are included:

[0028] Step 1: If the drone receives a command to fly to a certain sensor, it needs to obtain the drone mass m, the gravity acceleration g of the current flight area, the location information of the drone and the target sensor, and the total flight power p. 总 The coordinates of the drone take-off are set to the origin O of the three-dimensional coordinate system (0,0,0), and the coordinates of the target sensor location E are (x E ,y E ,z E );

[0029] Step 2, if z E >0, go to step 3; otherwise, go to step 4;

[0030] Step 3, calculate OP1, OP2 and OP3 respectively. If there is a solution and Then calculate and UAV selects a set of average data transmission rates The largest flight mode is to fly close to the sensor;

[0031] Step 4, calculate OP4, OP5 and OP6 respectively. If there is a solution, and Then calculate and UAV selects a set of average data transmission rates The largest flight mode is to fly close to the sensor.

[0032] Specifically, according to the time when the UAV flies to the sensor, there are three different flight modes of the UAV, namely, accelerated and decelerated flight in the Z axis, and accelerated, constant speed and decelerated flight in the horizontal direction (X axis and Y axis).

[0033] When z E >0 and The acceleration motion phase of the UAV in the Z axis includes the acceleration motion, uniform motion, and partial deceleration motion of the UAV in the horizontal direction (X and Y axes), so that the UAV has four stages of flying toward the sensor.

[0034] In 1~N x,1 During the time interval, the UAV is accelerated in the X and Y axes, and in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the UAV moves at a constant speed in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0035] When z E >0 and The acceleration phase of the UAV in the Z axis includes the acceleration motion of the UAV in the horizontal direction (X axis and Y axis), part of the uniform motion, but does not include the deceleration motion, so that the UAV has four phases of flying toward the sensor.

[0036] In 1~N x,1During the time interval, the UAV is accelerated in the X and Y axes and accelerated in the Z axis; During the time interval, the UAV moves at a constant speed in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV moves at a constant speed in the X and Y axes and decelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0037] When z E >0 and At this time, the acceleration phase of the UAV in the Z axis includes the partial acceleration motion of the UAV in the horizontal direction (X axis and Y axis), excluding the uniform motion and deceleration motion, so that the UAV has four phases of flying toward the sensor.

[0038] exist During the time interval, the UAV is accelerated in the X and Y axes and accelerated in the Z axis; During the time interval, the UAV accelerates in the X and Y axes and decelerates in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the UAV moves at a constant speed in the X and Y axes and decelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0039] When z E <0 and The acceleration phase of the UAV in the Z axis includes the partial acceleration motion of the UAV in the horizontal direction (X and Y axis), but does not include the uniform motion and deceleration motion, so that the UAV has four phases of flying toward the sensor.

[0040] exist During the time interval, the UAV is accelerated in the X and Y axes and accelerated in the Z axis; During the time interval, the UAV accelerates in the X and Y axes and decelerates in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the UAV moves at a constant speed in the X and Y axes and decelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0041] When z E <0 and The acceleration phase of the UAV in the Z axis includes the acceleration motion of the UAV in the horizontal direction (X axis and Y axis), part of the uniform motion, but does not include the deceleration motion, so that the UAV has four phases of flying toward the sensor.

[0042] In 1~Nx,1 During the time interval, the UAV is accelerated in the X and Y axes and accelerated in the Z axis; During the time interval, the UAV moves at a constant speed in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV moves at a constant speed in the X and Y axes and decelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0043] When z E <0 and The acceleration motion phase of the UAV in the Z axis includes the acceleration motion, uniform motion, and partial deceleration motion of the UAV in the horizontal direction (X and Y axes), so that the UAV has four stages of flying toward the sensor.

[0044] In 1~N x,1 During the time interval, the UAV is accelerated in the X and Y axes, and in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the UAV moves at a constant speed in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the UAV decelerates in the X and Y axes and decelerates in the Z axis.

[0045] In step 3 or step 4, the UAV selects a set of average data transmission rates or The largest flight mode is to fly close to the sensor.

[0046] Combination Figure 1 As shown, the design scheme of the present invention is further specifically analyzed and described.

[0047] In the network described in the scheme of the present invention, the drone takes off from the control point to a sensor in the network that needs data transmission, and collects data during the flight to the sensor. Assume that the coordinates of the drone take off are set to the origin O (0,0,0) of the three-dimensional coordinate system, and the coordinates of the target sensor location E are (x E ,y E ,z E ). During the entire flight phase when the UAV is flying towards the sensor, the UAV can receive data from the target sensor, and the signal transmission power uploaded by the sensor to the UAV is constant at p0.

[0048] Since the UAV is flying in the air, the channel gain between the UAV and the sensor will change at different time periods. Assuming that the total flight time of the UAV from point O to point E is t, it can be discretely divided into time intervals of Δt. Since Δt is small enough, it can be assumed that the position of the UAV is unchanged in each time interval.

[0049] Since the UAV needs to adjust its acceleration on the X-axis, Y-axis and Z-axis by calling its own flight power when flying between the take-off point and the sensor point, so as to achieve precise control of the UAV's speed and position, the following will explain and analyze the UAV's motion state in the horizontal direction (X-axis and Y-axis) and vertical direction (Z-axis).

[0050] 1. The drone experiences acceleration, constant speed and deceleration in the horizontal direction

[0051] According to Newton's law of motion, the average flight power used by the UAV during the acceleration and deceleration phases in the horizontal direction (X-axis or Y-axis) is:

[0052]

[0053] Where m is the mass of the drone; s = |x E | or s = | y E |; t is the flight time of the UAV from point O to point E.

[0054] The time required for the acceleration and deceleration phases when the drone is accelerating, moving at a constant speed, and decelerating in the horizontal direction (X-axis or Y-axis) and needs to call the minimum flight power is:

[0055]

[0056] in, and They are the movement time of acceleration, uniform speed or deceleration phase in the horizontal direction (X-axis or Y-axis), respectively.

[0057] Since the UAV is flying in the air, the instantaneous power of the UAV will change at different speeds. Since Δt is small enough, it can be assumed that the instantaneous power of the UAV is constant in each time interval. The instantaneous flight power of the UAV in the nth time interval can be obtained by the classic kinematic power calculation formula P(n) = ma(v+anΔt), where a is the acceleration and v is the speed:

[0058] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0059]

[0060] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0061] P(n)=0,n∈{N x,1 +1,…,N x,1 +N x,2}

[0062] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0063]

[0064] n∈{N x,1 +N x,2 +1,…,N x,1 +N x,2 +N x,3}

[0065] Therefore, it can be seen that the maximum instantaneous power value of the UAV moving in the horizontal direction (X axis or Y axis) is

[0066]

[0067] The position information of the UAV in the X-axis direction can be given according to the acceleration, uniform speed and deceleration stages: 1) The speed information of the UAV in the X-axis direction during the nth time interval of the acceleration stage is expressed as:

[0068]

[0069] Among them, v x (0) = 0; The position information of the UAV in the nth time interval during the acceleration phase in the X-axis direction is expressed as:

[0070]

[0071] Among them, x(0)=0.

[0072] 2) The position information of the UAV in the nth time interval of the uniform speed stage in the X-axis direction is expressed as:

[0073]

[0074] in,

[0075] 3) The speed information of the nth time interval of the drone in the deceleration phase in the X-axis direction is expressed as:

[0076]

[0077] in, The position information of the nth time interval of the drone in the X-axis direction during the deceleration phase is expressed as:

[0078]

[0079] The position information of the UAV in the Y-axis direction can be given according to the acceleration, uniform speed and deceleration stages: 1) The speed information of the UAV in the Y-axis direction during the nth time interval of the acceleration stage is expressed as:

[0080]

[0081] Among them, v y (0) = 0; The position information of the UAV in the nth time interval during the acceleration phase in the Y-axis direction is expressed as:

[0082]

[0083] Among them, y(0)=0.

[0084] 2) The position information of the UAV in the nth time interval of the uniform speed stage in the Y-axis direction is expressed as:

[0085]

[0086] in,

[0087] 3) The speed information of the UAV in the nth time interval of the deceleration phase in the Y-axis direction is expressed as:

[0088]

[0089] in,

[0090] The position information of the nth time interval of the drone in the Y-axis direction during the deceleration phase is expressed as:

[0091]

[0092] 2. UAV movement in the vertical direction (Z axis)

[0093] Since the UAV has no speed on the Z axis when it receives the return command, if the UAV wants to reach the position of point E (x E ,y E ,z E ) needs to undergo acceleration and deceleration in the vertical direction.

[0094] 1) If z E >0, it means that point E is higher than the current position of point O. The UAV first accelerates upward and then decelerates through its own gravity acceleration g until the speed reaches 0.

[0095] According to Newton's laws of motion, when When , the average flight power called by the UAV in the vertical direction (along the Z axis) is:

[0096]

[0097] Where g is the acceleration due to gravity; t is the flight time of the UAV from point O to point E.

[0098] The time it takes for the drone to accelerate in the vertical direction (Z axis) and decelerate only due to its own gravity acceleration g is:

[0099]

[0100] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0101]

[0102] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0103] P(n)=0,n∈{N z,1 +1,…,N z,1 +N z,2}

[0104] Therefore, it can be seen that the maximum instantaneous power value of the UAV moving in the vertical direction (Z axis) is

[0105] (1) Therefore, the velocity information of the UAV in the nth time interval during the acceleration phase in the vertical direction is expressed as:

[0106]

[0107] Among them, v z (0) = 0;

[0108] The position information of the UAV at the nth time interval during the acceleration phase in the vertical direction is expressed as:

[0109]

[0110] Among them, z(0)=0.

[0111] (2) The velocity information of the nth time interval of the UAV in the vertical direction during the deceleration phase is expressed as:

[0112]

[0113] in,

[0114] The position information of the nth time interval of the UAV in the vertical direction during the deceleration phase is expressed as:

[0115]

[0116] 2) If z E <0, it means that point E is lower than the current position of point O. The UAV needs to accelerate by its own gravity acceleration g first, and then decelerate by calling the appropriate flight power until the speed reaches 0.

[0117] According to Newton's laws of motion, when When the UAV uses appropriate flight power in the vertical direction (along the Z axis) to decelerate until the speed reaches 0, the average flight power is:

[0118]

[0119] The time for the UAV to perform acceleration and deceleration in the vertical direction (Z axis) is:

[0120]

[0121] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0122] P(n)=0,n∈{1,…,N z,1}

[0123] UAVs Total in time time interval, and the instantaneous power of the UAV is:

[0124] Therefore, it can be seen that the maximum instantaneous power value of the UAV moving in the vertical direction (Z axis) is

[0125] (1) Therefore, the velocity information of the UAV in the nth time interval during the acceleration phase in the vertical direction is expressed as:

[0126]

[0127] Among them, v z (0) = 0;

[0128] The position information of the UAV at the nth time interval during the acceleration phase in the vertical direction is expressed as:

[0129]

[0130] Among them, z(0)=0.

[0131] (2) The velocity information of the nth time interval of the UAV in the vertical direction during the deceleration phase is expressed as:

[0132]

[0133] in,

[0134] The position information of the nth time interval of the UAV in the vertical direction during the deceleration phase is expressed as:

[0135]

[0136] 1) When z E >0, there is

[0137] When The acceleration time of UAV on the Z axis is That is, the acceleration motion stage of the UAV in the Z axis includes the acceleration motion, uniform motion and partial deceleration motion of the UAV in the horizontal direction (X axis and Y axis).

[0138] a) The drone is at the nth position, The position information of the time interval is expressed as

[0139]

[0140]

[0141] In the nth time interval, the channel gain between the UAV and the sensor can be expressed as

[0142]

[0143] Here, let τ0 represent the channel gain at a distance of 1 meter.

[0144] The drone is on the nth, The data transmission rate for a time interval is:

[0145]

[0146] in, B is the signal bandwidth; σ 2 is the receiver noise;

[0147] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0148]

[0149] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0150]

[0151] in,

[0152] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0153]

[0154]

[0155] Therefore, the UAV is in the nth The data transmission rate of the time interval

[0156] The rate is:

[0157]

[0158] in, and

[0159] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0160]

[0161] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0162]

[0163] in, and

[0164] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0165] OP1:

[0166] st

[0167]

[0168] Among them, p 总 is the maximum instantaneous flight power available to the UAV (known).

[0169] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0170] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0171] When The acceleration time of UAV on the Z axis is That is, the acceleration motion phase of the UAV in the Z axis includes the acceleration motion of the UAV in the horizontal direction (X axis and Y axis), part of the uniform motion, but does not include the deceleration motion.

[0172] a) The drone is at the nth position, The position information of a time interval is expressed as:

[0173]

[0174] The drone is on the nth, The data transmission rate for a time interval is:

[0175]

[0176] in, B is the signal bandwidth; σ 2 is the receiver noise;

[0177] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0178]

[0179] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0180]

[0181] in,

[0182] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0183]

[0184] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0185]

[0186] in, and

[0187] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0188]

[0189] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0190]

[0191] in, and

[0192] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0193] OP2:

[0194]

[0195] st

[0196]

[0197] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0198] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0199] When The acceleration time of UAV on the Z axis is That is, the acceleration motion phase of the UAV in the Z axis includes the partial acceleration motion of the UAV in the horizontal direction (X axis and Y axis), but does not include uniform motion and deceleration motion.

[0200] a) The drone is at the nth position, The position information of a time interval is expressed as:

[0201]

[0202] The drone is on the nth, The data transmission rate for a time interval is:

[0203]

[0204] in, B is the signal bandwidth; σ 2 is the receiver noise;

[0205] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0206]

[0207] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0208]

[0209] in,

[0210]

[0211] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0212]

[0213] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0214]

[0215] in, and

[0216] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0217]

[0218] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0219]

[0220] in, and

[0221] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0222] OP3:

[0223]

[0224] st

[0225]

[0226] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0227] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0228] 2) When z E <0, there is

[0229] When The acceleration time of UAV on the Z axis is That is, the acceleration motion phase of the UAV in the Z axis includes the partial acceleration motion of the UAV in the horizontal direction (X axis and Y axis), but does not include uniform motion and deceleration motion.

[0230] a) The drone is at the nth position, The position information of a time interval is expressed as:

[0231]

[0232] In the nth time interval, the channel gain between the UAV and the sensor can be expressed as:

[0233]

[0234] Here, let τ0 represent the channel gain at a distance of 1 meter.

[0235] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0236]

[0237] in,

[0238] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0239]

[0240] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0241]

[0242] in, and

[0243] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0244]

[0245] Therefore, the UAV is in the nth The data transmission rate of the time interval

[0246] The rate is:

[0247]

[0248] in, and

[0249] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0250]

[0251] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0252]

[0253] in, and

[0254]

[0255] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0256] OP4:

[0257]

[0258] st

[0259]

[0260] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0261] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0262]

[0263] When The acceleration time of UAV on the Z axis is That is, the acceleration motion phase of the UAV in the Z axis includes the acceleration motion of the UAV in the horizontal direction (X axis and Y axis), part of the uniform motion, but does not include the deceleration motion.

[0264] a) The drone is at the nth position, The position information of a time interval is expressed as:

[0265]

[0266] In the nth time interval, the channel gain between the UAV and the sensor can be expressed as:

[0267]

[0268] Here, let τ0 represent the channel gain at a distance of 1 meter.

[0269] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0270]

[0271] in,

[0272] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0273]

[0274] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0275]

[0276] in, and

[0277] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0278]

[0279] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0280]

[0281] in, and

[0282] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0283]

[0284] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0285]

[0286] in, and

[0287] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0288] OP5:

[0289]

[0290] st

[0291]

[0292] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0293] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0294] When The acceleration time of UAV on the Z axis is That is, the acceleration motion stage of the UAV in the Z axis includes the acceleration motion, uniform motion and partial deceleration motion of the UAV in the horizontal direction (X axis and Y axis).

[0295] a) The drone is at the nth position, The position information of a time interval is expressed as:

[0296]

[0297] The drone is on the nth, The data transmission rate for a time interval is:

[0298]

[0299] in, B is the signal bandwidth; σ 2 is the receiver noise;

[0300] b) The drone is at the nth position, The position information of a time interval is expressed as:

[0301]

[0302]

[0303] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0304]

[0305] in,

[0306] c) The drone is at the nth position, The position information of a time interval is expressed as:

[0307]

[0308] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0309]

[0310] in, and

[0311] d) The drone is in the nth position, The position information of a time interval is expressed as:

[0312]

[0313]

[0314] Therefore, the UAV is in the nth The data transmission rate for a time interval is:

[0315]

[0316] in, and

[0317] When the UAV is approaching the sensor, the UAV hopes to obtain the highest data transmission rate, so the model is as follows:

[0318] OP6:

[0319]

[0320] st

[0321]

[0322] The above problem is a convex optimization problem, and the optimal flight time can be obtained by the Lagrange multiplier method.

[0323] Furthermore, as the UAV flies toward the sensor, the amount of data sent by the sensor to the UAV is:

[0324]

[0325] When z E >0, calculate OP1, OP2 and OP3 respectively. If there is a solution, and Then calculate and UAV selects a set of average data transmission rates The largest flight mode is to fly close to the sensor.

[0326] Similarly, when z E <0, calculate OP4, OP5 and OP6 respectively. If there is a solution, and Then calculate and UAV selects a set of average data transmission rates The largest flight mode is to fly close to the sensor.

[0327] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principles of the present invention shall be equivalent replacement modes and shall be included in the protection scope of the present invention.

Claims

1. A close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle, characterized in that: The following steps are involved: S01: If the drone receives a command to fly to a certain sensor, it obtains the drone parameter information; S02: When the UAV is flying between the take-off point and the sensor, the total flight time t of the UAV from the take-off point to the sensor is discretely divided into time intervals of Δt, and the acceleration on the X-axis, Y-axis and Z-axis is adjusted by calling its own flight power to control the speed and position of the UAV; S03: Calculate the data transmission rate at different flight stages, build an optimization model by maximizing the data transmission rate, and obtain the optimal flight time.

2. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 1, characterized in that: The parameters obtained in step S01 include the mass of the drone m, the gravity acceleration g of the current flight area, the location information of the drone and the target sensor, and the total flight power p. 总 , the coordinates of the drone take-off are set as the origin of the three-dimensional coordinate system (0,0,0), and the coordinates of the target sensor are (x E ,y E ,z E ).

3. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 2, characterized in that: In step S02, different flight modes are divided according to the different flight times of the drone towards the sensor, the acceleration and deceleration flight of the drone on the Z axis, and the acceleration, constant speed and deceleration flight in the horizontal direction: When z E >0 and The acceleration phase of the drone in the Z axis includes the acceleration, uniform motion and deceleration motion of the drone in the horizontal direction, so that the drone flies towards the sensor in four stages: In 1~N x,1 During the time interval, the drone accelerates in the X and Y axes and decelerates in the Z axis; In N x,1 +1~N x,1 +N x,2 During the time interval, the drone moves at a constant speed on the X and Y axes and accelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone decelerates in the X and Y axes and in the Z axis; N x,1 is the number of time intervals during which the UAV accelerates in the horizontal direction, N x,2 is the time interval of the UAV accelerating in the horizontal direction, is the time interval of the UAV moving at a constant speed in the horizontal direction; When z E >0 and The acceleration phase of the drone in the Z axis includes the drone's acceleration in the horizontal direction and part of the uniform motion, but does not include the deceleration motion, so that the drone's flight toward the sensor has four stages: In 1~N x,1 During the time interval, the drone accelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone moves at a constant speed on the X and Y axes and accelerates on the Z axis; During the time interval, the drone moves at a constant speed on the X and Y axes and decelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and slows down in the Z axis; When z E >0 and At this time, the acceleration phase of the drone in the Z axis includes the partial acceleration of the drone in the horizontal direction, excluding the uniform speed and deceleration, so that the drone flies towards the sensor in four stages: exist During the time interval, the drone accelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone accelerates in the X and Y axes and decelerates in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the drone moves at a constant speed on the X and Y axes and decelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and slows down in the Z axis; When z E <0 and The acceleration phase of the drone in the Z axis includes the partial acceleration of the drone in the horizontal direction, but does not include the uniform motion and deceleration motion, so that the drone's flight toward the sensor has four phases: exist During the time interval, the drone accelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone accelerates in the X and Y axes and decelerates in the Z axis; x,1 +1~N x,1 +N x,2 During the time interval, the drone moves at a constant speed on the X and Y axes and decelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and slows down in the Z axis; When z E <0 and The acceleration phase of the drone in the Z axis includes the drone's acceleration in the horizontal direction and part of the uniform motion, but does not include the deceleration motion, so that the drone's flight toward the sensor has four stages: In 1~N x,1 During the time interval, the drone accelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone moves at a constant speed on the X and Y axes and accelerates on the Z axis; During the time interval, the drone moves at a constant speed on the X and Y axes and decelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and slows down in the Z axis; When z E <0 and The acceleration phase of the drone in the Z axis includes the drone's acceleration, uniform motion, and partial deceleration in the horizontal direction, so that the drone's flight toward the sensor has four phases: In 1~N x,1 During the time interval, the drone accelerates in the X and Y axes and decelerates in the Z axis; In N x,1 +1~N x,1 +N x,2 During the time interval, the drone moves at a constant speed on the X and Y axes and accelerates on the Z axis; During the time interval, the drone decelerates in the X and Y axes and accelerates in the Z axis; During the time interval, the drone decelerates in the X and Y axes and slows down in the Z axis.

4. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 3 is characterized in that: The position and speed of the drone on the X, Y, and Z axes include: The position information of the drone in the X-axis direction is given according to the acceleration, uniform speed and deceleration stages: 1) The velocity information v of the nth time interval that undergoes the acceleration phase in the X-axis direction x (n) is expressed as: Among them, v x (0) = 0; The position information x(n) of the UAV in the nth time interval of the acceleration phase in the X-axis direction is expressed as: Where x(0)=0; 2) The position information of the UAV in the nth time interval of the uniform speed stage in the X-axis direction is expressed as: in, 3) The speed information of the nth time interval of the drone in the deceleration phase in the X-axis direction is expressed as: in, The position information x(n) of the UAV in the nth time interval of the deceleration phase in the X-axis direction is expressed as: The position information of the drone in the Y-axis direction is given according to the acceleration, uniform speed and deceleration stages: 1) The velocity information v of the UAV during the nth time interval of the acceleration phase in the Y-axis direction y (n) is expressed as: Among them, v y (0) = 0; The position information of the UAV in the nth time interval during the acceleration phase in the Y-axis direction is expressed as: Where y(0)=0; 2) The position information of the UAV in the nth time interval of the uniform speed stage in the Y-axis direction is expressed as: in, 3) The speed information of the UAV in the nth time interval of the deceleration phase in the Y-axis direction is expressed as: in, The position information of the nth time interval of the drone in the Y-axis direction during the deceleration phase is expressed as: If E >0, the drone first accelerates upward, and then decelerates due to its own gravity acceleration g until the speed reaches 0; The speed information of the UAV in the nth time interval of the acceleration phase in the Z-axis direction is expressed as: Among them, v z (0) = 0; The position information of the UAV in the nth time interval during the acceleration phase in the Z-axis direction is expressed as: Where z(0)=0; The speed information of the nth time interval of the drone in the Z-axis direction during the deceleration phase is expressed as: in, The position information of the nth time interval of the drone in the Z-axis direction during the deceleration phase is expressed as: If E <0, the drone first accelerates by its own gravity acceleration g, and then decelerates by calling the appropriate flight power until the speed reaches 0; The speed information of the UAV in the nth time interval of the acceleration phase in the Z-axis direction is expressed as: Among them, v z (0) = 0; The position information of the UAV in the nth time interval during the acceleration phase in the Z-axis direction is expressed as: Where z(0)=0; (2) The speed information of the nth time interval of the drone in the Z-axis direction during the deceleration phase is expressed as: in, The position information of the nth time interval of the drone in the Z-axis direction during the deceleration phase is expressed as:

5. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 4, characterized in that: In step S02, the average flight power used by the drone in the horizontal acceleration and deceleration movement phase is: Where m is the mass of the drone; s = |x E | or s = | y E |; Drones in Total in time time interval, and the instantaneous power of the UAV is: Drones in Total in time time interval, and the instantaneous power of the UAV is: P(n)=0,n∈{N x,1 +1,…,N x,1 +N x,2 } Drones in Total in time time interval, and the instantaneous power of the UAV is: The vertical motion of the drone, if z E >0, when When , the average flight power called by the UAV in the vertical direction is: The time it takes for the drone to accelerate in the vertical direction and decelerate only due to its own gravity acceleration g is: Drones in Total in time time interval, and the instantaneous power of the UAV is: Drones in Total in time time interval, and the instantaneous power of the UAV is: P(n)=0,n∈{N z,1 +1,…,N z,1 +N z,2 } If E <0, when When the UAV uses appropriate flight power in the vertical direction to decelerate until the speed reaches 0, the average flight power is: And the time for the UAV to accelerate and decelerate in the vertical direction is: Drones in Total in time time interval, and the instantaneous power of the UAV is: P(n)=0,n∈{1,…,N z,1 } Drones in Total in time time interval, and the instantaneous power of the UAV is:

6. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 5, characterized in that: The step S03 of constructing the optimization model includes: When z E >0, When , the modeling is as follows: OP1: The above problem is a convex optimization problem. The optimal flight time is obtained by the Lagrange multiplier method. when When , the modeling is as follows: OP2: The above problem is a convex optimization problem. The optimal flight time is obtained by the Lagrange multiplier method. When z E >0, When , the modeling is as follows: OP3: The above problem is a convex optimization problem. The optimal flight time is obtained by the Lagrange multiplier method. When z E <0, When , the modeling is as follows: OP4: The above problem is a convex optimization problem, and the optimal flight time is obtained by the Lagrange multiplier method. when When , the modeling is as follows: OP5: The above problem is a convex optimization problem. The optimal flight time is obtained by the Lagrange multiplier method. When z E <0, When , the modeling is as follows: OP6: The above problem is a convex optimization problem, and the optimal flight time is obtained by the Lagrange multiplier method.

7. The close-in flight method for collecting single-target sensor data by an unmanned aerial vehicle according to claim 1, characterized in that: The step S03 further includes: After obtaining the optimal flight time, calculate the amount of data sent by the sensor to the drone; The average data transmission rate is calculated, and the UAV selects the flight mode with the largest average data transmission rate in the set to fly close to the sensor.

8. A close-in flight system for collecting single-target sensor data by an unmanned aerial vehicle, characterized in that: The invention comprises a processor, wherein the processor is equipped with the close-in flight method for collecting single-target sensor data by a drone as described in any one of claims 1 to 7.

9. A drone, characterized in that: A close-in flight system for collecting single-target sensor data using an unmanned aerial vehicle as described in claim 8.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the close-in flight method for collecting single-target sensor data by a drone as described in any one of claims 1 to 7 is implemented.

Images