CN119012136B - Method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wake-up - Google Patents
Method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wake-up Download PDFInfo
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Abstract
本发明属于无人机管控技术领域。提供了利用气压唤醒监测无人机定位的方法，包括：将监测器安装在无人机上，监测器包括处理器、电子气压计、有源射频标签、定位设备，电子气压计连续检测所处区域内的若干组气压信息；处理器根据各组所述气压信息计算得出气压波动数据，并根据气压波动数据判断无人机是否切换至飞行状态；若是，则激活有源射频标签和定位设备，有源射频标签将无人机ID和定位设备检测得到的定位信息发送给无人机管理平台；无人机管理平台根据无人机ID、定位信息及内部存储的飞行备案信息进行比对，对该无人机是否属于黑飞做出判断。本发明的方案既实现了对无人机黑飞的监测管控，还有效降低了监测过程中的电能消耗问题。
The present invention belongs to the technical field of drone control. A method for monitoring the positioning of a drone using air pressure wake-up is provided, comprising: installing a monitor on a drone, the monitor comprising a processor, an electronic barometer, an active radio frequency tag, and a positioning device, the electronic barometer continuously detecting several groups of air pressure information in the area in which it is located; the processor calculates air pressure fluctuation data based on each group of air pressure information, and determines whether the drone is switched to a flight state based on the air pressure fluctuation data; if so, the active radio frequency tag and the positioning device are activated, and the active radio frequency tag sends the drone ID and the positioning information detected by the positioning device to a drone management platform; the drone management platform compares the drone ID, positioning information, and internally stored flight filing information to determine whether the drone is an illegal flight. The solution of the present invention not only realizes the monitoring and control of illegal drone flights, but also effectively reduces the problem of power consumption during the monitoring process.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle control, in particular to a method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wake-up.
Background
The standard management of the flight activities of unmanned aerial vehicles is important content for promoting the healthy development of unmanned aerial vehicle industry. In the prior art, in order to prevent unmanned aerial vehicle from flying in black, positioning equipment and communication equipment can be configured on the unmanned aerial vehicle, positioning information of the unmanned aerial vehicle is fed back to an unmanned aerial vehicle management and control platform in real time by the communication equipment, the flight state of the unmanned aerial vehicle can be judged according to the positioning information, and judgment can be made on whether the unmanned aerial vehicle belongs to flying in black or not by comparing the unmanned aerial vehicle with the recorded flight time.
However, the existing mode needs the positioning device and the communication device to be in a real-time communication state, which can consume a large amount of electric energy of the unmanned aerial vehicle, and is unfavorable for carrying out long-time black flight control monitoring on the unmanned aerial vehicle. The present invention aims to improve this technical problem.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method, a system, electronic equipment, a computer storage medium and a computer program product for monitoring the positioning of an unmanned aerial vehicle by utilizing air pressure wake-up, so as to realize the purpose of effectively reducing the monitoring power consumption while completing the black flight monitoring of the unmanned aerial vehicle.
The invention discloses a method for monitoring unmanned aerial vehicle positioning by means of air pressure awakening, which comprises the following steps of installing a monitor on an unmanned aerial vehicle, wherein the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, the active radio frequency tag and the positioning equipment are in a low-power-consumption dormant state in general, the electronic barometer continuously detects a plurality of groups of air pressure information in a region and transmits the air pressure information to the processor, the processor calculates air pressure fluctuation data according to the air pressure information, judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, activates the active radio frequency tag and the positioning equipment, the active radio frequency tag sends the positioning information detected by the unmanned aerial vehicle ID and the positioning equipment to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle management platform compares the unmanned aerial vehicle ID, the positioning information and internally stored standby flight plan information corresponding to the unmanned aerial vehicle ID, and judges whether the unmanned aerial vehicle belongs to a black flight state.
Optionally, the processor is further configured to communicate with a flight recording device of the unmanned aerial vehicle to obtain a latest set of flight recording data, extract a flight duration and a flight speed from the flight recording data, predict a heat value to be emitted according to the flight duration and the flight speed, compare the heat value to be emitted with a preset comparison table, and obtain a silence duration, wherein the silence duration in the preset comparison table and the heat value to be emitted show a positive correlation, and receive each set of air pressure information sent by the electronic barometer when the silence duration is reached.
Optionally, the predicting the heat value to be dissipated according to the flight duration and the flight speed comprises inputting the flight duration, the flight speed, basic parameters of the unmanned aerial vehicle and the ambient temperature into a heat accumulation prediction model based on a large model, wherein the basic parameters comprise motor parameters, electric adjustment parameters, battery parameters and propeller parameters, and generating the heat value to be dissipated based on a prediction result of the heat accumulation prediction model.
The method comprises the steps of generating a heat quantity value to be dissipated based on a prediction result of a heat accumulation prediction model, wherein the heat accumulation prediction model outputs a predicted preliminary heat quantity value to be dissipated, the unmanned aerial vehicle management platform sends other unmanned aerial vehicle information in a parking area of the unmanned aerial vehicle to the processor, the other unmanned aerial vehicle information comprises the number of unmanned aerial vehicles with parking time duration being lower than a preset time duration, the processor converts the number of unmanned aerial vehicles to obtain an optimization coefficient, and the preliminary heat quantity value to be dissipated is adjusted by using the optimization coefficient to obtain the heat quantity value to be dissipated.
Optionally, the parking area is a circular area based on the position of the unmanned aerial vehicle, and the radius of the circular area is determined according to the preliminary heat value to be emitted, specifically, the radius is inversely related to the preliminary heat value to be emitted.
The method comprises the steps of calculating air pressure fluctuation data according to each set of air pressure information, judging whether an unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, wherein the air pressure fluctuation data comprise a plurality of air pressure fluctuation amplitudes which are sequenced in time sequence according to each set of air pressure information, each air pressure fluctuation amplitude is provided with a sign, the positive sign represents that the air pressure behind is larger than the air pressure adjacent to the air pressure in front, the negative sign represents that the air pressure behind is smaller than the air pressure adjacent to the air pressure in front, extracting air pressure fluctuation characteristics from the air pressure fluctuation data by using a convolution network, inputting the air pressure fluctuation characteristics into a classifier, and outputting the probability of switching the unmanned aerial vehicle to the flight state by the classifier, if the probability is higher than a threshold value, judging that the unmanned aerial vehicle is switched to the flight state, otherwise, judging that the unmanned aerial vehicle is not switched to the flight state.
The invention further provides a system for monitoring unmanned aerial vehicle positioning by means of air pressure awakening, the system comprises a processing module and a storage module, a computer program is stored in the storage module, the processing module calls the computer program in the storage module to achieve the following method steps of installing a monitor on an unmanned aerial vehicle, the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, the active radio frequency tag and the positioning equipment are in a low-power sleep state normally, the electronic barometer continuously detects a plurality of sets of air pressure information in an area where the active radio frequency tag and the positioning equipment are located and transmits the air pressure information of each set to the processor, the processor calculates air pressure fluctuation data according to the air pressure information of each set and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the active radio frequency tag sends the positioning information obtained by the unmanned aerial vehicle ID and the positioning equipment to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle management platform correspondingly judges whether the unmanned aerial vehicle ID and the positioning information stored in the unmanned aerial vehicle belong to the flight state or not.
The invention also discloses an electronic device comprising at least one processor, a memory and a computer program stored in the memory and executable on the at least one processor, the processor executing the computer program to implement the method as described above.
The invention also discloses a computer storage medium storing a computer program to be executed by a processor to implement the method as described above.
The invention also discloses a computer program product which when being called and executed by a processor of an electronic device, performs the method as described above.
According to the scheme, the black flight monitoring control of the unmanned aerial vehicle is realized, and the electric energy consumption problem in the monitoring process is effectively reduced.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for monitoring unmanned aerial vehicle positioning by using air pressure wake-up according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a system for monitoring unmanned aerial vehicle positioning by using air pressure wake-up according to an embodiment of the present invention.
Detailed Description
Other advantages and advantages of the present application will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the technical features of the different embodiments of the present application described below may be combined with each other as long as they do not collide with each other.
The embodiment of the invention discloses a method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wakeup, which comprises the following steps of installing a monitor on an unmanned aerial vehicle, wherein the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, the active radio frequency tag and the positioning equipment are in a low-power dormant state in general, the electronic barometer continuously detects a plurality of groups of air pressure information in an area where the active radio frequency tag and the positioning equipment are located and transmits the air pressure information to the processor, the processor calculates air pressure fluctuation data according to the air pressure information of each group and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the active radio frequency tag sends the positioning information obtained by detection of the unmanned aerial vehicle ID and the positioning equipment to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle management platform compares the unmanned aerial vehicle ID, the positioning information with internally stored flight record information corresponding to the unmanned aerial vehicle ID, and judges whether the unmanned aerial vehicle belongs to the unmanned aerial vehicle.
Compared with the prior art, the active radio frequency tag and the positioning equipment in the monitor are in a low-power-consumption dormant state in normal, and only the electronic barometer and the processor are in a normally open state, so that the power consumption of the monitor is reduced, and the black flight monitoring duration of the unmanned aerial vehicle is prolonged.
Specifically, the electronic barometer detects the air pressure of the area where the unmanned aerial vehicle is located to obtain a plurality of groups of air pressure information, the processor calculates air pressure fluctuation data according to each group of air pressure information, and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the positioning equipment detects the positioning information of the unmanned aerial vehicle in real time, the active radio frequency tag sends the unmanned aerial vehicle ID and the positioning information to the unmanned aerial vehicle management platform, the unmanned aerial vehicle management platform compares the positioning information of the unmanned aerial vehicle with flight record information (flight request of specific time) of the unmanned aerial vehicle stored in the unmanned aerial vehicle according to the positioning information of the unmanned aerial vehicle, if not matched, for example, the recorded flight time is not the current time, the unmanned aerial vehicle is judged to be in a black flight, and otherwise, the unmanned aerial vehicle is judged to be in a normal flight.
According to the method, whether the unmanned aerial vehicle is in a flight state is judged by detecting the air pressure information of the area where the unmanned aerial vehicle is located, and the active radio frequency tag and the positioning equipment in the low-power-consumption sleep state are triggered to be switched to the enabling state, so that the ID and the positioning information of the unmanned aerial vehicle are sent to the unmanned aerial vehicle management platform in real time, and accordingly whether the unmanned aerial vehicle has black flight is judged by the unmanned aerial vehicle management platform. Therefore, the scheme of the invention not only realizes the monitoring and controlling of the black flight of the unmanned aerial vehicle, but also effectively reduces the problem of electric energy consumption in the monitoring process.
It should be noted that the unmanned aerial vehicle management platform may be a local platform, for example, the distance between the layout position of the unmanned aerial vehicle management platform and the storage position of each unmanned aerial vehicle is within 100 meters, so that the unmanned aerial vehicle management platform can receive the unmanned aerial vehicle ID and the positioning information sent by each unmanned aerial vehicle through the radio frequency communication technology.
Optionally, the processor is further configured to communicate with a flight recording device of the unmanned aerial vehicle to obtain a latest set of flight recording data, extract a flight duration and a flight speed from the flight recording data, predict a heat value to be emitted according to the flight duration and the flight speed, compare the heat value to be emitted with a preset comparison table, and obtain a silence duration, wherein the silence duration in the preset comparison table and the heat value to be emitted show a positive correlation, and receive each set of air pressure information sent by the electronic barometer when the silence duration is reached.
In the embodiment of the invention, a motor, an electronic speed regulator, a power battery, a propeller and the like of the unmanned aerial vehicle can generate certain heat in the flying process, and more heat can be generated after the unmanned aerial vehicle body rubs with air, and the heat can be gradually emitted to surrounding areas within a period of time after the unmanned aerial vehicle lands, so that the temperature of the air in the area is increased. The air temperature changes to cause air pressure changes, and the electronic barometer may detect a set of air pressure information with overlarge fluctuation amplitude, so that the processor is easy to misjudge that the unmanned aerial vehicle enters a flight state, namely, flies in black.
According to the technical problem, the method is arranged after the monitor is installed on the unmanned aerial vehicle or the unmanned aerial vehicle is stopped in a landing mode (at the moment, the monitor is fixedly installed on the unmanned aerial vehicle), and the processor of the monitor timely communicates with the flight recording device of the unmanned aerial vehicle to obtain the latest set of flight recording data of the unmanned aerial vehicle, wherein the latest set of flight recording data comprises the flight duration and the flight speed. The processor can predict the heat generated by the last flight according to the flight time and the flight speed, namely, the heat value to be dissipated at the moment is predicted, and the heat value to be dissipated is compared with a preset comparison table for analysis, so that the silence time is obtained. Finally, the control processor receives multiple groups of air pressure information detected by the electronic barometer after the silence duration, and because heat accumulated in the flight process of the unmanned aerial vehicle is dissipated, the air temperature of the located area is recovered to be normal, and at the moment, whether the unmanned aerial vehicle is switched to a flight state or not is judged based on the air pressure information of the located area, so that the situation of misjudgment of black flight caused by the factor is basically avoided.
A comparison table is preset, wherein the comparison table comprises a plurality of groups of silence duration and heat value to be emitted, and the corresponding silence duration can be determined through table lookup.
Optionally, the predicting the heat value to be dissipated according to the flight duration and the flight speed comprises inputting the flight duration, the flight speed, basic parameters of the unmanned aerial vehicle and the ambient temperature into a heat accumulation prediction model based on a large model, wherein the basic parameters comprise motor parameters, electric adjustment parameters, battery parameters and propeller parameters, and generating the heat value to be dissipated based on a prediction result of the heat accumulation prediction model.
In the embodiment of the invention, the heat generated by the unmanned aerial vehicle in the flight process is derived from two aspects, namely 1) the heat generated by self equipment such as a motor, an electronic speed regulator, a power battery, a propeller and the like in the operation process, and 2) the heat generated by friction between the unmanned aerial vehicle and the air in the flight process. Meanwhile, the heat generation amount is positively correlated with the flight time length and the flight speed, namely, the longer the flight time length is, the faster the flight speed is, the more heat is generated, and the faster the flight speed is, the lower the environment temperature is, the faster the heat dissipation speed is, and correspondingly, the heat value to be dissipated is negatively correlated with the flight speed and positively correlated with the environment temperature. It can be seen that the relationship between the heat value to be dissipated and the flight time, the flight speed, the basic parameters of the unmanned aerial vehicle and the ambient temperature is very complex, and it is difficult to construct a corresponding conversion function for the heat value.
Aiming at the technical problems, the invention constructs the heat accumulation prediction model based on a large model, wherein the large model refers to a machine learning model with large-scale parameters and a complex calculation structure, and is usually constructed by a deep neural network and has billions or even billions of parameters. In the training and optimizing process, the models utilize large-scale data to carry out self-adjustment and optimization, and intelligent data analysis and processing are realized. The present invention preferably uses the latest existing large models, such as Qwen2.5-Math-72B, llama3.1-405B, GPT-4o mini, gemma2-9B, etc., which are not particularly limited in this regard. Meanwhile, records of various types (corresponding to different basic parameters) of unmanned aerial vehicles flying for various durations according to different flying speeds in various temperature environments are collected, the temperature emission amount of the unmanned aerial vehicles after landing is detected, a small sample fine adjustment data set is formed by the data, fine adjustment training is carried out on any one of the existing large models by using the small sample fine adjustment data set, and then the heat accumulation prediction model suitable for the prediction task of the heat value to be emitted is obtained.
The method comprises the steps of generating a heat quantity value to be dissipated based on a prediction result of a heat accumulation prediction model, wherein the heat accumulation prediction model outputs a predicted preliminary heat quantity value to be dissipated, the unmanned aerial vehicle management platform sends other unmanned aerial vehicle information in a parking area of the unmanned aerial vehicle to the processor, the other unmanned aerial vehicle information comprises the number of unmanned aerial vehicles with parking time duration being lower than a preset time duration, the processor converts the number of unmanned aerial vehicles to obtain an optimization coefficient, and the preliminary heat quantity value to be dissipated is adjusted by using the optimization coefficient to obtain the heat quantity value to be dissipated.
In the embodiment of the invention, the heat accumulation prediction model after fine adjustment training can preliminarily predict the heat value to be emitted of the unmanned aerial vehicle based on the flight time, the flight speed, the basic parameters of the unmanned aerial vehicle and the environmental temperature, and the preliminary heat value to be emitted does not consider the environment in the parking area of the unmanned aerial vehicle. A plurality of unmanned aerial vehicles can be placed in a parking area corresponding to the unmanned aerial vehicle management platform, part of unmanned aerial vehicles can just fly, heat is not completely emitted, and the heat emitted by the unmanned aerial vehicles can also cause the change of the air pressure of the area where the unmanned aerial vehicle is located.
According to the technical problems, after the unmanned aerial vehicle is landed and stopped, the unmanned aerial vehicle management platform sends the number of unmanned aerial vehicles with the parking time length lower than the preset time length in the unmanned aerial vehicle parking area to the processor of the monitor, the processor converts the number of the unmanned aerial vehicles to obtain the corresponding optimization coefficient, and then the optimization coefficient is used for adjusting the preliminary heat value to be dissipated, which is predicted by the heat accumulation prediction model, so that the final heat value to be dissipated is obtained.
Wherein the predetermined time period is an empirical value representing that the standing drone has completed the dissipation of the accumulated heat after the predetermined time period. The invention is not particularly limited to a conversion formula between the optimization coefficient and the number of unmanned aerial vehicles, but it is obvious that a conversion formula having a positive correlation relationship should be adapted therebetween, for example, the optimization coefficient=the reference optimization coefficient+f (number of unmanned aerial vehicles). Wherein the optimization factor should be a value greater than 1.
Optionally, the parking area is a circular area based on the position of the unmanned aerial vehicle, and the radius of the circular area is determined according to the preliminary heat value to be emitted, specifically, the radius is inversely related to the preliminary heat value to be emitted.
In the embodiment of the invention, after the unmanned aerial vehicle lands and stops, a circular area is drawn by taking the position of the unmanned aerial vehicle as a reference, and the radius of the circular area is inversely related to the preliminary heat value to be emitted predicted by the heat accumulation prediction model. The reason for this arrangement is that when the preliminary heat to be dissipated predicted by the heat accumulation prediction model is larger, the heat generated by the unmanned aerial vehicle is higher, at this time, the air temperature change in the area is less influenced by the heat dissipated by other unmanned aerial vehicles in the periphery, so that the circular area is reduced to properly reduce the number of unmanned aerial vehicles with the parking time period lower than the preset time period, and conversely, when the preliminary heat to be dissipated predicted by the heat accumulation prediction model is smaller, the heat generated by the unmanned aerial vehicle is lower, at this time, the air temperature change in the area is relatively more influenced by the heat dissipated by other unmanned aerial vehicles in the periphery, so that the circular area is enlarged to properly increase the number of unmanned aerial vehicles with the parking time period lower than the preset time period.
By adjusting the size of the circular area, excessive consideration of heat dissipation of other surrounding unmanned aerial vehicles can be reduced.
The method comprises the steps of calculating air pressure fluctuation data according to each set of air pressure information, judging whether an unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, wherein the air pressure fluctuation data comprise a plurality of air pressure fluctuation amplitudes which are sequenced in time sequence according to each set of air pressure information, each air pressure fluctuation amplitude is provided with a sign, the positive sign represents that the air pressure behind is larger than the air pressure adjacent to the air pressure in front, the negative sign represents that the air pressure behind is smaller than the air pressure adjacent to the air pressure in front, extracting air pressure fluctuation characteristics from the air pressure fluctuation data by using a convolution network, inputting the air pressure fluctuation characteristics into a classifier, and outputting the probability of switching the unmanned aerial vehicle to the flight state by the classifier, if the probability is higher than a threshold value, judging that the unmanned aerial vehicle is switched to the flight state, otherwise, judging that the unmanned aerial vehicle is not switched to the flight state.
In the embodiment of the invention, after the processor receives each group of air pressure information detected by the electronic barometer, the air pressure information can be sequenced according to the acquisition sequence, the difference value between the adjacent air pressure information, namely the air pressure fluctuation amplitude, is calculated, the air pressure fluctuation amplitude has positive fluctuation and negative fluctuation, the air pressure fluctuation amplitude is distinguished by signs, and the air pressure fluctuation data is formed by the air pressure fluctuation amplitudes which are sequenced correspondingly. And then, carrying out characteristic extraction of air pressure fluctuation amplitude on the air pressure fluctuation data by using a convolution network, wherein the extracted air pressure fluctuation characteristic represents the air pressure fluctuation characteristic of the stage.
When the change of the upper and lower height appears in unmanned aerial vehicle, the fluctuation of atmospheric pressure can be detected to electronic barometer, but unmanned aerial vehicle's high change both probably is that unmanned aerial vehicle switches to the state of flight and leads to, also probably is that relevant personnel unmanned aerial vehicle leads to, need distinguish this. In this regard, the invention constructs a classifier, the classifier classifies the air pressure fluctuation feature extracted from the convolution network, and outputs the probability of the unmanned aerial vehicle switching to the flight state correspondingly, when the probability is lower than the threshold value, the classifier considers that the air pressure fluctuation feature corresponds to the air pressure fluctuation feature caused when the related personnel manually take the unmanned aerial vehicle, and when the probability is higher than the threshold value, the classifier considers that the air pressure fluctuation feature corresponds to the air pressure fluctuation feature caused when the unmanned aerial vehicle switching to the flight state.
When the unmanned aerial vehicle is manually taken and put by a relevant person, the height of the unmanned aerial vehicle changes, and at the moment, the electronic barometer can detect the change of the air pressure, but the change of the air pressure is greatly different from the air pressure fluctuation characteristics (fluctuation amplitude, fluctuation frequency and the like) corresponding to the condition that the unmanned aerial vehicle is switched to the flying state. Because unmanned aerial vehicle is when switching to the flight state, except the change of height, the air current that the rotor caused also can directly lead to the atmospheric pressure that the electronic barometer detected to appear by a wide margin undulant, and the atmospheric pressure undulant characteristic and the manual condition of taking and putting at this moment are different completely, and the classifier can comparatively light distinguish.
In addition, the classifier may adopt any one of SVM, decision tree, naive bayes, etc., which is not limited in the present invention.
The embodiment of the invention also discloses a system for monitoring the positioning of the unmanned aerial vehicle by utilizing the air pressure awakening, which comprises a processing module and a storage module, wherein a computer program is stored in the storage module, the processing module calls the computer program in the storage module to realize the following method steps of installing a monitor on the unmanned aerial vehicle, the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, the active radio frequency tag and the positioning equipment are in a low-power dormant state normally, the electronic barometer continuously detects a plurality of groups of air pressure information in an area where the electronic barometer is located and transmits the air pressure information to the processor, the processor calculates air pressure fluctuation data according to the air pressure information in each group and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the positioning information obtained by the detection of the unmanned aerial vehicle ID and the positioning equipment is sent to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle is compared with the unmanned aerial vehicle platform according to the information stored in the unmanned aerial vehicle.
The embodiment of the invention also discloses an electronic device, which comprises at least one processor, a memory and a computer program stored in the memory and capable of running on the at least one processor, wherein the processor executes the computer program to realize the method according to the previous embodiment.
The embodiment of the invention also discloses a computer storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method according to the previous embodiment.
The embodiment of the invention also discloses a computer program product which is used for realizing the method according to the previous embodiment when being called and executed by a processor of an electronic device.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention.
Claims (9)
1. A method for monitoring unmanned aerial vehicle positioning by utilizing air pressure awakening is characterized by comprising the following steps of installing a monitor on an unmanned aerial vehicle, wherein the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, the active radio frequency tag and the positioning equipment are in a low-power dormant state in general, the electronic barometer continuously detects a plurality of sets of air pressure information in a region and transmits the air pressure information to the processor, the processor calculates air pressure fluctuation data according to the air pressure information of the sets and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the active radio frequency tag sends the positioning information detected by the unmanned aerial vehicle ID and the positioning equipment to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle management platform compares the unmanned aerial vehicle ID, the positioning information and internally stored standby flight plan information corresponding to the unmanned aerial vehicle ID according to the unmanned aerial vehicle ID;
The processor is also used for communicating with a flight recording device of the unmanned aerial vehicle to obtain the latest flight recording data, extracting the flight duration and the flight speed from the flight recording data, predicting the heat value to be emitted according to the flight duration and the flight speed, comparing and analyzing the heat value to be emitted with a preset comparison table to obtain the silence duration, wherein the silence duration and the heat value to be emitted in the preset comparison table show a positive correlation, and receiving each group of air pressure information sent by the electronic barometer when the silence duration is reached.
2. The method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wake-up according to claim 1, wherein the method for predicting the heat value to be dissipated according to the flight duration and the flight speed is characterized by comprising the steps of inputting basic parameters of the flight duration, the flight speed and the unmanned aerial vehicle and ambient temperature into a heat accumulation prediction model based on a large model, wherein the basic parameters comprise motor parameters, electric adjustment parameters, battery parameters and propeller parameters, and generating the heat value to be dissipated based on a prediction result of the heat accumulation prediction model.
3. The method for monitoring unmanned aerial vehicle positioning by utilizing air pressure wake-up is characterized in that the heat quantity value to be dissipated is generated based on a prediction result of the heat quantity accumulation prediction model, the method comprises the steps that the heat quantity accumulation prediction model outputs a preliminary heat quantity value to be dissipated, the unmanned aerial vehicle management platform sends other unmanned aerial vehicle information in a parking area of the unmanned aerial vehicle to the processor, the other unmanned aerial vehicle information comprises the number of unmanned aerial vehicles with parking time duration being lower than a preset time duration, the processor converts the number of unmanned aerial vehicles to obtain an optimization coefficient, and the preliminary heat quantity value to be dissipated is adjusted by using the optimization coefficient to obtain the heat quantity value to be dissipated.
4. A method for monitoring the positioning of a drone by means of air pressure wake-up according to claim 3, wherein the parking area is a circular area based on the location of the drone, and the radius of the circular area is determined according to the preliminary heat value to be emitted, in particular, the radius is inversely related to the preliminary heat value to be emitted.
5. The method for monitoring unmanned aerial vehicle positioning by utilizing air pressure awakening according to claim 4, wherein the processor calculates air pressure fluctuation data according to each set of air pressure information and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, the air pressure fluctuation data comprise a plurality of air pressure fluctuation amplitudes which are sequenced in time sequence according to each set of air pressure information, each air pressure fluctuation amplitude is provided with a sign, the positive sign represents that the air pressure after the unmanned aerial vehicle is larger than the air pressure before the unmanned aerial vehicle is adjacent, the negative sign represents that the air pressure after the unmanned aerial vehicle is smaller than the air pressure before the unmanned aerial vehicle is adjacent, the air pressure fluctuation characteristics are extracted from the air pressure fluctuation data by using a convolution network, the air pressure fluctuation characteristics are input into a classifier, the classifier outputs the probability that the unmanned aerial vehicle is switched to the flight state, if the probability is higher than a threshold value, and otherwise, the unmanned aerial vehicle is not switched to the flight state is judged.
6. A system for monitoring unmanned aerial vehicle positioning by utilizing air pressure awakening, which is used for realizing the method according to any one of claims 1-5, and comprises a processing module and a storage module, wherein a computer program is stored in the storage module, and is characterized in that the processing module calls the computer program in the storage module to realize the following method steps of installing a monitor on the unmanned aerial vehicle, wherein the monitor comprises a processor, an electronic barometer, an active radio frequency tag and positioning equipment, and the active radio frequency tag and the positioning equipment are in a low-power-consumption sleep state normally; the electronic barometer continuously detects a plurality of groups of air pressure information in an area where the electronic barometer is located and transmits the air pressure information to the processor, the processor calculates air pressure fluctuation data according to the air pressure information of each group and judges whether the unmanned aerial vehicle is switched to a flight state according to the air pressure fluctuation data, if so, the active radio frequency tag and the positioning equipment are activated, the active radio frequency tag sends positioning information detected by the unmanned aerial vehicle ID and the positioning equipment to an unmanned aerial vehicle management platform, and the unmanned aerial vehicle management platform compares the unmanned aerial vehicle ID, the positioning information and internally stored flight record information corresponding to the unmanned aerial vehicle ID to judge whether the unmanned aerial vehicle belongs to black flight.
7. An electronic device comprising at least one processor, a memory and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method of any one of claims 1-5.
8. A computer storage medium storing a computer program, wherein the computer program is executed by a processor to implement the method of any one of claims 1-5.
9. A computer program product, which when being invoked and executed by a processor of an electronic device, is characterized in that it is executed to implement the method according to any one of the claims 1-5.
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