875 results about "Flight time" patented technology

The invention relates to a low-altitude logistics unmanned aerial vehicle path planning method, which comprises the following steps of 1, discretizing an urban low-altitude region into computable grid units, a dynamic-static obstacle classification modeling technology is combined to endow a static obstacle with a basic risk degree, a height attenuation factor is introduced to quantify the influence of a high-altitude obstacle on a low-altitude path, and a collision risk of a dynamic obstacle is dynamically evaluated through a time dimension risk degree prediction model; 2, based on an improved genetic algorithm, comprehensively considering flight time, height change, risk degree and dynamic risk cost through a multi-objective optimization objective function, and generating a globally optimal task allocation scheme; 3, generating a local optimal three-dimensional path considering meteorological conditions and dynamic obstacle influence by adopting an improved particle swarm algorithm; and 4, performing path planning to feed back actual flight time and energy consumption to task allocation for optimization.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a gas-electric hybrid composite wing unmanned aerial vehicle system, which comprises an intelligent energy management module, a gas-electric hybrid composite wing unmanned aerial vehicle control module and a gas-electric hybrid composite wing unmanned aerial vehicle control module, the self-adaptive flight control module is used for optimizing the flight attitude, dynamically adjusting the flight route and improving the flight safety; the task adaptive scheduling module is used for adaptively adjusting a task execution strategy according to the task category, the load condition and the environmental parameters; the data monitoring and remote control module is used for collecting the operation state of the unmanned aerial vehicle in real time and storing and analyzing flight data; the intelligent safety management module is used for improving the autonomous safety of the unmanned aerial vehicle; and the environment perception optimization module is used for perceiving external environment factors in real time. According to the invention, the intelligent energy management module realizes intelligent scheduling of fuel and electricity power, and dynamically optimizes the power distribution of the battery and fuel oil, so that the flight time of the unmanned aerial vehicle is greatly prolonged.

A distance measuring device includes: a pixel array unit that performs a light receiving operation for time-of-flight distance measurement using a modulation frequency; a distance measurement processing unit that performs dual mode distance measurement that causes the pixel array unit to alternately perform a light receiving operation using a first frequency as the modulation frequency and a row receiving operation using a second frequency having a higher frequency than the first frequency as the modulation frequency, and single mode distance measurement that causes the pixel array unit to perform only a light receiving operation using a predetermined frequency as the modulation frequency; and a switching processing unit that switches the distance measurement in the dual mode and the distance measurement in the single mode according to a predetermined condition.

The invention discloses a civil aircraft PHM modeling method based on cross-modal coupling, a medium and equipment, and belongs to the technical field of aircrafts. The method comprises the steps of S1, multi-modal data preprocessing: performing feature extraction and time-space / event alignment for three modalities of flight time sequence data, text data and image data, and laying a foundation for subsequent fusion modeling; s2, cross-modal feature fusion and holographic data sample construction: constructing a holographic data sample library covering the whole life cycle through cross-domain fusion and dynamic optimization; and S3, PHM physical-knowledge fusion comprehensive modeling: constructing a double-layer collaborative framework combining physical simulation and knowledge reasoning, and realizing controllable fusion of physical simulation and multi-modal knowledge. The problems that in the prior art, multi-source heterogeneous data alignment is difficult, physical mechanism and data driving fusion is insufficient, and model interpretability is poor can be solved.

The invention discloses an unmanned aerial vehicle real-time vegetation classification system and method based on a lightweight AI model, and belongs to the technical field of vegetation monitoring and analysis. On the basis of an existing processor of the unmanned aerial vehicle, vegetation real-time classification is achieved by optimizing the deep learning model, and the flight path is dynamically adjusted according to the classification result. The method comprises the steps of system configuration and initialization, lightweight AI model development and optimization, real-time data acquisition and processing, adaptive flight path adjustment and feedback optimization. The method has the following advantages: (1) real-time classification of vegetation and adaptive flight path adjustment are realized, and the acquisition efficiency is optimized; (2) the sampling density is adaptively adjusted for different value regions, and the precision and coverage efficiency of vegetation classification are improved; (3) the acquisition strategy is optimized in real time in combination with the battery state, and unnecessary flight time and energy consumption are reduced; and (4) the method is suitable for application fields such as agricultural monitoring, forestry management and ecological protection.

The invention discloses a method and a system for processing route planning data for electric power line inspection. The method comprises the following steps: acquiring line distribution and topographic feature data; gridding the power network region, determining the patrol priority, and generating a region priority sequence; the overall patrol task is decomposed, a plurality of task subsets are generated, one task is allocated to each unmanned aerial vehicle, and each task subset comprises an initial position and a target line section; generating an initial route path based on the topographic features; comprehensively analyzing all initial paths, identifying potential airspace intersections and performing conflict prediction, and generating a conflict-free route path set by performing height hierarchical adjustment on related paths; and calculating predicted flight time and energy consumption of each unmanned aerial vehicle, redistributing boundary tasks according to a load balancing principle, and finally generating a balanced multi-unmanned aerial vehicle cooperative route scheme. According to the method, the safe and efficient multi-machine collaborative inspection route can be automatically generated through systematic task decomposition, conflict prediction and load balancing optimization.

An autonomous flying device achieving a large payload and a long continuous flight time and also accurately adjust position and orientation while flying. The device includes: a main rotor and the like that provide main thrust; a sub rotor and the like that controls the orientation; an engine that generates energy for rotating the main rotor and the like and the sub rotor and the like; and an arithmetic control device that controls rotation of the sub rotor and the like. Also, the main rotor and the like are rotated by being drivingly connected to the engine, whereas the sub rotor and the like are rotated by motors driven by electric power generated from generator and the like operated by the engine. Further, when orientation control to tilt the fuselage is performed, the arithmetic control device increases the output distribution ratio of the sub rotor to above the output distribution ratio of the sub rotor when hovering is performed.

The invention belongs to the technical field of satellite positioning, and discloses an unmanned aerial vehicle positioning cruise method and system based on satellite-based enhancement, and the method comprises the steps: setting an unmanned aerial vehicle cruise region range, a high-coverage cruise route and flight time; and checking software and hardware equipment of the unmanned aerial vehicle, taking off from a safe area, and starting automatic cruise. Observation data, broadcast ephemeris and Beidou B2b and Galileo HAS products are obtained through an unmanned aerial vehicle receiver. Carrying out decoding and correction number matching on the B2b and the HAS messages; correcting the satellite orbit, the clock error and the code and phase deviation according to the correction number provided by the B2b and the HAS; performing gross error elimination, clock jump repair and cycle slip detection on the data; and performing parameter estimation by using Kalman filtering to obtain high-precision position coordinates. If an emergency occurs, an operator can send a return instruction to the unmanned aerial vehicle through a Beidou short message. And after the cruise task is finished or a return instruction is received, the unmanned aerial vehicle completes safe landing at the planned return point.

The invention belongs to the technical field of air traffic management, and relates to a flight time adjustment management method and system in a special scene. According to the method, the flight release priority sequence is constructed, the airport taxiway network topology and the dynamic limitation information are combined, the taxiing path is planned, the space-time conflict is detected, and the dynamic adjustment of flight ground operation and the coordination verification of the runway access time window are realized. The problems of frequent flight ground taxiing path conflicts, low scheduling efficiency and difficulty in accurate take-off time control in special scenes are solved, the safety and efficiency of airport ground operation are effectively improved, the flight taxiing time and the runway waiting time are reduced, the flight release sorting and the runway use plan are optimized, and the flight taxiing efficiency is improved. The flight scheduling cooperation capability in a complex operation environment is enhanced, and the orderliness and stability of flight operation are guaranteed.

The invention relates to the technical field of unmanned aerial vehicle cluster control, in particular to an unmanned aerial vehicle cluster control method and system, and the method comprises the steps: predicting the remaining flight time of an unmanned aerial vehicle cluster for safely arriving at a destination in a current carrying state; calculating a cluster energy consumption deviation degree according to the current energy consumption parameter, predicting the remaining endurance time of each unmanned aerial vehicle, and determining the minimum predicted endurance time; dynamically generating a safe flight time threshold according to the minimum predicted endurance time and a preset safety margin; if the remaining flight time is smaller than the safe flight time threshold value, a cooperative control instruction is generated according to the offset, the offset speed and the cluster energy consumption deviation degree; and distributing the cooperative control instruction to the corresponding unmanned aerial vehicle in the unmanned aerial vehicle cluster. And the flight endurance crisis caused by non-uniform energy consumption in the irregular article carrying process is effectively solved.

The invention provides an anomaly detection method of an ultrasonic gas meter and the ultrasonic gas meter, and relates to the technical field of flow monitoring. The invention provides a more accurate and timely anomaly detection method aiming at the problem that an existing detection method for judging whether an instrument is abnormal or not only by judging flight time of an ultrasonic gas meter is not timely and accurate enough in anomaly response. The method comprises the following steps: exciting a first transducer according to a preset frequency to enable the first transducer to emit an ultrasonic signal; the second transducer receives the ultrasonic signal transmitted by the first transducer and generates an echo signal waveform; and waveform features are extracted from the echo signal waveforms, and if the waveform features do not conform to a preset rule, it is judged that detection of the ultrasonic gas meter is abnormal. In addition, according to different identification results, different processing modes are adopted, the anti-interference capability of the instrument is improved, and the abnormal detection of the instrument is more accurate.

The invention provides an airspace gridding method based on flight time, electronic equipment and a storage medium, and relates to the technical field of airspace gridding, and the method comprises the steps: obtaining a flight path RE of a target unmanned plane; determining the level L of the airspace grid corresponding to the RE; obtaining each L-level target airspace grid corresponding to the RE to obtain an airspace grid list A; determining an L-level code of each target airspace grid to obtain a target airspace grid code list GL; according to the waypoint information corresponding to the RE, determining the time when the target unmanned aerial vehicle flies to each target airspace grid so as to obtain a to-be-coded time list t; encoding each time to be encoded in the t to obtain an L-level time encoding list TL; adding the TLi into the GLi to obtain a target airspace grid code containing the flight time; according to the invention, whether the airspace grid is occupied or not can be determined according to the corresponding time coding information, so that collision is avoided.

The invention discloses a 110KV power transmission line unmanned aerial vehicle cluster inspection control method and system, and relates to the technical field of power systems and automatic control, and the method comprises the steps: generating an inspection region three-dimensional map through first data, and carrying out the distributed task distribution through a first algorithm; performing path search based on three-dimensional expansion of a second algorithm; and a third control algorithm is adopted to realize unmanned aerial vehicle cluster coordinated flight, and a dynamic window method is combined to realize real-time obstacle avoidance. According to the method, the flight path of the unmanned aerial vehicle can be more accurately planned through three-dimensional expansion of an existing path planning algorithm in combination with topographic data, and unnecessary flight time and energy consumption are reduced; through cluster collaborative operation, multiple sections of power transmission lines can be inspected at the same time, the inspection time is greatly shortened, the operation efficiency is improved, all corners of the data lines are fully covered, and the blind area or missing detection problem is avoided.

The embodiment of the invention discloses a terminal airspace flight scheduling decision-making method and system based on mixed linear integer programming, and the method comprises the steps: obtaining the information of flights participating in scheduling in a time window from a flight information base, and obtaining the environment information from an operation environment information base; constructing a flight scheduling set; defining decision variables according to business requirements, and constructing a target function of a terminal airspace single-path flight ordering scheduling model; constructing a constraint condition library of the scheduling model; selecting a model according to business requirements; solving and calculating; and outputting decision information of the flight needing to be scheduled. According to the method, complex operation logic and control operation rules between flight pairs operated in a terminal airspace are accurately and abstractly modeled into mathematical linear constraint expression, and an objective function is constructed by minimizing the air waiting time of an incoming flight and minimizing the scheduling time deviation of the incoming and leaving flights; compared with a traditional first-arrival first-service algorithm, a flight sequence with higher efficiency can be obtained, and serious flight time slot waste cannot be generated.

The invention provides an unmanned aerial vehicle flight path dynamic planning method and system, and relates to the technical field of flight path planning, and the method comprises the steps: obtaining the starting and ending points of the flight of an unmanned aerial vehicle, and planning an initial unmanned aerial vehicle flight path based on the starting and ending points of the flight of the unmanned aerial vehicle and a preset constraint; constructing an unmanned aerial vehicle flight environment model based on a preset flight area map, the elevation information and the obstacle information; route optimization is carried out based on the initial unmanned aerial vehicle flight route and a flight environment model, and an unmanned aerial vehicle initial obstacle avoidance route is generated; the unmanned aerial vehicle initial obstacle avoidance route is optimized based on a preset iterative optimization model, and an optimized unmanned aerial vehicle obstacle avoidance route is obtained; and updating the optimized unmanned aerial vehicle obstacle avoidance route to the initial unmanned aerial vehicle flight route to generate a final unmanned aerial vehicle flight route. According to the invention, the flight time and cost are saved, the adaptability to the environment, especially the urban complex environment, is enhanced, and the safety is guaranteed.

The invention provides a high-speed aircraft time cooperative guidance method and system based on sliding mode control, and belongs to the field of aircraft guidance and control. The problems that an existing guidance method is large in calculation amount, insufficient in real-time performance and poor in cooperation precision are solved. According to the method, the residual flight time of multiple aircrafts is quickly predicted through a centralized collaborative strategy, and the time deviation of the aircrafts is adjusted according to the principle that who follows the aircrafts slowly; designing a bottom layer time controllable guide law based on sliding mode control, and introducing a saturation function to improve a buffeting phenomenon and solve a singular point problem; realizing transverse trajectory bending of the aircraft through a three-dimensional offset proportional guidance law so as to adjust the flight time; the precision and efficiency of residual flight time calculation are improved by using a variable step size numerical integration method; and completing formation transformation of multiple aircrafts at the tail end of the gliding section to support a terminal guidance task. According to the method, the calculation complexity is reduced, meanwhile, the precision and robustness of time cooperation are remarkably improved, and reliable technical support is provided for a multi-aircraft cooperative guidance task.

The invention discloses an unmanned aerial vehicle automatic homeward voyage method based on a global topological map and a graph search algorithm, which comprises a global passable area topological connected graph module, a homeward voyage path search module, a homeward voyage path optimization module and a homeward voyage path error processing module. According to the method, global path searching is carried out in combination with a Dijkstra algorithm, path smoothness, flight time and obstacle avoidance are optimized by using a B spline curve, the precision and speed of path planning are effectively improved, and meanwhile, the system can cope with changes in the environment by updating a topological connected graph and optimizing the path in real time, so that the path planning efficiency is improved. And secondly, the path safety and the flight stability are both considered, and an obstacle distance penalty term is introduced, so that the flight path can avoid the obstacle, and the collision risk is reduced.

The invention belongs to the field of aircraft control, and discloses a composite guidance aircraft guidance control method and system considering flight time falling angle constraint, and the method comprises the steps: inputting target values of flight time and a terminal falling angle according to a specific task requirement; pre-planning a flight path; in the flight process, estimating the current remaining flight time of reaching the target in real time, and performing feedback adjustment on the flight time error; in a flight approaching target stage, calculating a falling angle error in real time according to the attitude and speed of the aircraft, and correcting the flight attitude; through a nonlinear optimal control algorithm, two constraints of flight time and a falling angle are comprehensively balanced; executing mechanisms such as engine thrust, control surface angle and attitude control spray pipes of the aircraft are adjusted in real time according to a composite guidance algorithm instruction; and when the aircraft is about to arrive at the target, final falling angle correction is performed to ensure that the aircraft hits the target at an accurate angle. According to the method, the balance problem between the flight time constraint and the falling angle constraint is effectively solved, and the guidance precision and the task success rate of the aircraft are remarkably improved.

The invention relates to a multi-unmanned aerial vehicle maritime cooperative reconnaissance method based on an Archimedes algorithm and hierarchical scheduling, and the method comprises the steps: defining a patrol task region and task targets, and constructing a topological model of an unmanned aerial vehicle cluster for each task target; according to the cooperation characteristic of the unmanned aerial vehicle cluster, Archimedes patrol path planning is carried out on various unmanned aerial vehicles; based on the performance of the unmanned aerial vehicle, factors such as path length, flight time, unmanned aerial vehicle scanning range and search efficiency are comprehensively considered, and the path of the unmanned aerial vehicle is optimized, so that the unmanned aerial vehicle has relatively high execution efficiency and stability; when the leader unmanned aerial vehicle finds a target during patrol, the cluster dispatches the investigation unmanned aerial vehicle to perform a tracking task; and the investigation data is returned to the command center, and next task planning is carried out. The cooperative reconnaissance capability of the unmanned aerial vehicle cluster in complex tasks can be effectively improved.

The invention discloses an unmanned aerial vehicle power supply management system, belongs to the technical field of unmanned aerial vehicle power supply management, and solves the problem that no power supply management for cooperation of a whole unmanned aerial vehicle cluster is provided to improve power supply utilization. Comprising a flight monitoring module, an endurance monitoring module, a track comparison module and a flight control module, the flight monitoring module, the endurance monitoring module and the track comparison module are all in communication connection with the flight control module, and the flight monitoring module and the endurance monitoring module are also in communication connection with the track comparison module. The flight monitoring module is used for collecting flight parameters of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and flight formation of the unmanned aerial vehicle cluster and feeding back to the flight control module, and the endurance monitoring module is used for collecting endurance information of each unmanned aerial vehicle in the unmanned aerial vehicle cluster and feeding back to the flight control module. The leader unmanned aerial vehicle and the communication unmanned aerial vehicle are replaced regularly, so that all the unmanned aerial vehicles share energy consumption, cluster influence caused by insufficient electric energy of a single unmanned aerial vehicle is avoided, power management is optimized, and cluster flight time of the unmanned aerial vehicles is prolonged.

A modular unmanned aerial vehicle (UAV) system comprises a body module, a rotor module, and a wing module. The body module includes a flight controller and a power distribution device. The body module is releasably attachable to the rotor module or the wing module, and the body module is releasably attachable to the rotor module. The rotor module includes one or more motors and electronic speed controllers (ESCs), while the wing module includes a wing having a flap, elevator, aileron, or rudder. Various UAV configurations can be formed from the body module, the rotor module, and the wing module. Each configuration includes different advantages for flight time, distance, battery life, and payload capacity. A UAV can be configured to a particular configuration to optimize parcel delivery.

The invention relates to the technical field of non-controlled airspace intelligent operation management, in particular to an urban-level low-altitude airspace intelligent operation supervision method and system, and the method comprises the following steps: receiving task data indicating a flight plan of an aircraft, the flight plan comprising planned flight time and a planned route; whether the airspace capacity corresponding to the planned flight time can meet the flight requirement of an operator or not is determined, if not, first information indicating re-planning of a flight plan is generated and fed back to the operator, and the first information comprises recommended flight time and a recommended route; receiving dynamic data indicative of a flight course of the aircraft within the airspace; and determining whether the aircraft deviates from the planned route based on the flight route, and if yes, generating second information indicating to return to the route and feeding back the second information to the aircraft. According to the invention, through perception and acquisition of aircraft basic data, aircraft flight dynamic data and aircraft state data, digital services of airspace and flight are provided, and unified supervision of aircrafts can be realized.

The invention discloses a power line anomaly detection method and system based on an unmanned aerial vehicle. The method comprises the steps that a server analyzes a power line detection request to obtain a detection area and a detection time period; planning an initial detection track, generating a power line detection instruction based on the initial detection track, the detection area and the detection time period, and issuing the instruction to the unmanned aerial vehicle; the unmanned aerial vehicle executes an inspection task in the electronic fence, the initial detection track is dynamically corrected in the inspection process, and a flight time sequence image is collected; analyzing the flight time sequence image through a line anomaly detection model, and outputting a line anomaly detection result; an actual detection track is recorded, and abnormity marking is carried out on the actual detection track; and recording, encrypting and uploading an inspection log to the server. The method has the advantages that the detection efficiency, the intelligent level and the safety management capability of power line anomaly detection are greatly improved.

The embodiment of the invention provides a transducer echo line sequence test method and a transducer echo line sequence test device, and the method comprises the steps: enabling a detection surface and a horizontal plane to form a first angle in an echo detection state, comparing waveform data of feedback signals obtained by reflecting the ultrasonic signals emitted by the plurality of test array elements through the detection surface with preset qualified data to determine a performance result of the transducer; in the line sequence detection state, a second angle is formed between the detection surface and the horizontal plane, and the actual flight time difference value of each adjacent test array element in the plurality of test array elements is determined according to waveform data of feedback signals obtained by reflecting ultrasonic signals emitted by the plurality of test array elements through the detection surface, and according to a comparison relation between a difference value between the actual flight time difference value and the theoretical flight time difference value and a preset threshold value, whether welding of each test array element is correct or not is determined. Therefore, an echo performance detection function and a multi-array element line sequence detection function can be integrated.

The invention relates to a motion control method and device, a robot and a storage medium, and the method comprises the steps: carrying out the tracking of a state variable error and a control input error in the remaining flight time under a constraint condition under the condition that the robot is in a flight state, and obtaining a state variable optimization result and a control input optimization result, the residual flight time comprises the time from the current moment to the completion of the current action, the state variable error comprises an error between a state variable in a preset reference trajectory and a state variable optimization result, and the control input error comprises an error between control input in the reference trajectory and a control input optimization result; the constraint condition comprises at least one of centroid dynamics constraint, full kinematics constraint and collision dynamics constraint; and controlling the robot to move according to the state variable optimization result and the input optimization result.

The invention belongs to the technical field of radar detection, and discloses a bird positioning method of a quantum radar bird detection system, which is characterized in that quantum characteristics such as polarization state and phase of echo photons are accurately analyzed by means of a quantum state demodulation technology, and high-precision measurement of the flight time of the photons is combined, so that the resolution limitation of the traditional radar is broken through from the quantum level; the technical combination not only can capture fine actions such as wing flapping frequency and steering angle of birds, but also can exert remarkable advantages in a dense bird flock scene: by utilizing quantum state differences of echo photons of different birds, overlapping signals are decomposed into independent individual signals through a quantum state separation algorithm; the individual distinguishing problem caused by traditional radar signal aliasing is solved; in high-precision demand scenes such as airports and the like, small bird targets can be accurately locked, flight potential safety hazards caused by misjudgment are greatly reduced, and the system can physically resist copying and deception interference of the outside to quantum signals based on the quantum unclonable principle.

The invention discloses a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning method. The method comprises the following steps: constructing an unmanned aerial vehicle motion model; constructing a collaborative detection distribution income measurement index, an estimated detection time difference measurement index and an energy consumption measurement index which take unmanned aerial vehicle task node selection parameters as optimization variables, and taking the weighted sum of the three indexes as a measurement index of collaborative detection task efficiency; establishing a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning model by taking given unmanned aerial vehicle voyage, endurance, effective communication distance and inter-vehicle anti-collision distance limitation as constraint conditions and taking minimization of a heterogeneous unmanned aerial vehicle cluster cooperative detection task efficiency cost function as an optimization target; and solving the optimization model by combining an interior point and an improved Hungary algorithm. According to the method, optimal distribution of the heterogeneous unmanned aerial vehicle cluster task area, the base takeoff point and the area boundary entry point is realized, and the heterogeneous unmanned aerial vehicle cluster cooperative detection performance is effectively improved.

To appropriately set an area where a flight device can fly.SOLUTION: An information processing device 1 sets a flight route of a flight device. The information processing device includes: a registration section 131 for registering performance or a purpose of usage of the flight device; a schedule acquisition section 132 for acquiring flight schedule data indicating a scheduled route for the flight of the flight device; a setting section 134 for setting an upper limit range of a flight possible area of the flight device based on the performance or the purpose of usage registered in the registration section 131; and an area determination section 135 for determining the flight possible area of the flight device based on the flight schedule data and the upper limit range.SELECTED DRAWING: Figure 4

The invention relates to the technical field of ultrasonic flow measurement, and discloses a relative flight time estimation method based on an ultrasonic flowmeter, and the method comprises the steps: carrying out the time domain alignment of uplink and downlink echo signals through prior absolute flight time, and preventing phase cycle skipping; carrying out FFT (Fast Fourier Transform) and frequency domain conjugate multiplication on the signal, and extracting amplitude and phase information; and a cost function is constructed by using frequency spectrum amplitude weighting, residual delay is estimated through least square fitting, and finally high-precision relative flight time is obtained. According to the method, correlation operation is realized in the frequency domain, the calculation complexity is remarkably reduced, the estimation precision and the anti-noise capability are improved, and the method is suitable for an embedded low-power-consumption system.

Techniques related to measuring a time-of-flight (ToF), comprising switching a first measuring station to a main operating mode, transmitting, by the first measuring station, a first ToF packet to a remote device, switching the first measuring station to a receive mode to receive a first ToF response packet from the remote device, receiving, by the first measuring station, the first ToF response packet, determining, a time interval between transmitting of the first ToF packet and receiving the first ToF response packet, receiving a plurality of time intervals from one or more other measuring stations, determining a ToF measurement based on the first time interval and the plurality of time intervals, switching the first measuring station to a secondary operating mode, and transmitting to a second measuring station, an indication to switch to the main operating mode.