UAV Operations Research Articles

A Review on UAV-Based Remote Sensing Technologies for Construction and Civil Applications

UAV-based technologies are evolving and improving at a rapid pace. The abundance of solutions and systems available today can make it difficult to identify the best option for construction and civil projects. The purpose of this literature review is to examine the benefits and limitations of UAV-based sensing systems in the context of construction management and civil engineering, with a focus on camera-based and laser-based systems. The risk factors associated with UAV operations at construction sites are also considered.

The Method for Distribution of Aircrafts of Joint Aviation Groups Depending on Importance of Targets and Probability of their Defeat

This study considers the approach for the distribution of a limited number of combat means - unmanned aerial vehicles during preparation for their application at objects (targets) of impact, taking into account the importance of targets and the state of their protection (probability of defeat). The approach is based on one of the non-linear programming methods, but is reduced to an algorithm available for practical use among practitioners who prepare data for decision making in headquarters, control points, support services. It is noted that such an approach can be useful in case of limited quantity of combat means, when there is a need to direct them primarily to priority targets for implementing a general ultimate task set by the highest authority. It is shown that the proposed approach can be extended to the distribution of any material and technical resources, with importance of the limited amount of resource, the priority of resource distribution objects and the resource provision level of these objects at the time of decision on distribution. Technically, unmanned aerial vehicles control, distribution of unmanned aerial vehicles to objects (targets) is carried out by UAV operators. Keywords— Maximal element method, objects of impact, objective function, distribution algorithm, optimization process.

A Reasonable Alternative System for Searching UAVs in the Local Area.

UAVs, used for professional purposes, often intervene in unfamiliar terrain and challenging conditions. Unlike recreational UAVs, such professional and specialised UAVs are very expensive to develop and operate, and their value is not negligible. Due to the nature of operations in an unknown or dangerous environment, there are also situations with forced interruption and termination of the flight mission or a collision with the environment. Locating a lost vehicle presents a new challenge for UAV operators. The possibilities of today’s localised commercial aircraft in distress (COSPASS/SARSAT systems) are undesirable for selective special-purpose drones. The optimisation of the location in the event of an emergency or catastrophic landing may be justified by a social or other condition, where the user wants to search for the device by a system other than the one experienced for rescuing people, ideally on their reserved frequencies. The article proposes a new approach to solving the problem based on the design of a terrestrial localisation system based on the methods of processing and correlation of the obtained data by the physical principle of the Doppler effect and its own system adaptation. This creates an innovative concept of a targeting system based on the broadcasting of distress (VHF) signal by crashed UAV. This signal is captured and evaluated by the IDVOR system, making it possible to determine the direction in which the searched UAV is placed. In order to determine the difference between standard targeting systems of the UAV, which use information about position (exact coordinates (x,y,z)), the IDVOR system is able to determine direction, independent of other systems in every “enemy” or “inhospitable” territory.

Geometric calibration of a hyperspectral frame camera with simultaneous determination of sensors misalignment

The recent development of lightweight and relatively low-cost hyperspectral sensors has created new perspectives for remote sensing applications. This study aimed to investigate the geometric calibration of a hyperspectral frame camera based on a tuneable Fabry–Pérot interferometer (FPI) and two sensors. The radiation passes through the optics and then through the FPI, where it is redirected to two sensors using a beam-splitting prism. Previous studies have shown significant variations between the interior orientation parameters for the different bands, both between bands of the same sensor and between different sensors, and that these variations are due to the principle of image acquisition. Discrepancies of tens of pixels were obtained by comparing image coordinates measured in different bands. In this research, it was proposed to calibrate this camera in a static mode with changes in the mathematical calibration model. The restriction of obtaining only one set of exterior orientation parameters by hypercube was applied, adding parameters related to the misalignment between the sensors and parameters of a linear function relating the camera principal distance to the wavelength values. The application of the parameters estimated with this approach reduced the discrepancies between image coordinates measured in different bands to values smaller than one pixel. Using the sensor calibration parameters in the mobile UAV operation in an aerial bundle adjustment reduced the root mean square error (RMSE) on checkpoints by approximately 20% compared to the traditional model in which the interior orientation parameters and lens distortions were calibrated for each band separately. Thus, it was possible to obtain accurate results that make the use of this camera more practical since only one set of calibration parameters for all bands is needed.

UAV Noise Emission—A Combined Experimental and Numerical Assessment

Noise emission will be a significant obstacle to the widespread uptake of unmanned aerial vehicles or UAVs. The assessment and mitigation of UAV noise will require validated modelling approaches. The European Union has recently mandated an UAV sound power measurement procedure based on a procedure for measuring machinery or equipment. It is not clear if this legally mandated noise assessment will provide useful data for environmental noise modelling of UAVs. This research aimed to determine the sound power level of a UAV according to the legally mandated ISO 3744 and to investigate the suitability of commercial implementations of ISO 9613 for modelling noise emission from UAVs. A class C1 UAV was used for the investigation which also included controlled flyover tests. Several different operating conditions were measured and modelled and the results compared. The small scale UAV used had a sound power of 86.8 dB (A) and modelled flyover tests agreed with experimental values within ±2.1 decibels at distances up to 30 m and within angles of 45–90° of the receiver. The validated model was then used for a case study of UAV noise emission in an urban setting. The model demonstrated the potential for UAV noise emission to significantly exceed urban background noise levels by up to 10 dB. It was found that flight altitude relative to building height had a significant impact on the number of allowable UAV operations within WHO LDEN guidelines.

Swarm Unmanned Aerial Vehicles (SUAVs): A Comprehensive Analysis of Localization, Recent Aspects, and Future Trends

Within the last decade, Swarm Unmanned Aerial Vehicles (SUAVs) are booming and growing at a surprisingly rapid pace. From military combat, environmental surveillance, and air transport to the blossoming public entertainment sector, there is a wide range of UAV applications. For these above use cases, the accurate location of the target of interest can be requested/queried, which is very important for their mission accomplishment. In the case of GPS-armed SUAVs, this is an easy task. However, the GPS signal can be obscured, affected by environmental conditions, or suppressive jamming. Therefore, location information needs to be improved/assisted by some other localization techniques, which constitutes the main scope of this article. Besides, with the advancements in localization, guidance, and communication technologies; future SUAVs will be operating autonomously by distributing tasks and coordinating the operation of many UAVs. Thus, UAV to UAV communication is presented as it constitutes the SUAV’s autonomous coordination ability. In addition, future research directions and open challenges that need to be addressed, including autonomous SUAVs, are also discussed.

Modified Tentacle Algorithm for Collision Avoidance for UAV

A collision avoidance methodology in UAV Operation using the modified tentacles algorithm is proposed in this work. Tremendous and remarkable achievements have been recorded in the area of collision avoidance in UAV operations. Applying the modified tentacles algorithm, this research used two point research objectives the principal aim was to maintain accurate collision avoidance. With a reliable simulation result, an algorithm based on the modified tentacles technique was proposed. This was also modeled. In executing the proposed algorithm, a 3D environmental data and information were converted to 2D information for ease of mathematical computation. Appropriate occupancy grid maps were generated to show a practical result of the 3D conversion to 2D. Thus, instead of dealing with an x, y, z or three dimensional environments, an x, y or two dimensional environment results and mathematical differentiation was applied. A development of an integrated model comprising of the conventional, Modified Tentacles Algorithm. This all inclusive integrated model was simulated in order to validate and justify the work. It is a justification and validation of this research on the use of Modified Tentacles Algorithm in achieving energy efficiency in UAV operations. It has been established that energy consumption in UAV operations is influenced by its mode of operation at a given time.

There Has Never Been “Old” Wars, or, Drone Ethics

The article challenges traditional notions of war and war ethics from the standpoints of a terrorist attack victim and of a drone strike victim, of the decentralized opposition of “old” and “new” wars, “major” wars and “small” ones, combatants vs. non-combatants, soldiers vs guerilla fighters, friends vs enemies, victors vs defeated. Accordingly, the authors consider the political status and social role of ethnographic, anthropological and ethical research within the context of “new wars,” which include guerilla warfare and resort to terrorist tactics. Building on current research in sociology, anthropology, ethics and political studies (Hugh Gusterson, Mary Kaldor, Jeff McMahan, Lucy Sachman, Emran Feroz, Grégoire Chamayou, Kirill Martynov, Victor Vakhshtayn et al.), the authors regard whether drone technologies and other automated weapons conform to the Russia’s military ethics. They also speculate upon prospects of some technologies being socially adapted in different world cultures. The article brings up to date critique of violence by Walter Benjamin and problematizes the concept of the political by Carl Schmitt through the lens of the present-day military ethnography (see Nikolai Ssorin-Chaikov’s Hybrid Peace: Ethnographies of War in this issue of Logos). Analyzing historical transformations and inversions of guerillas, suicide pilots, UAV operators and suicide bombers deconstructs the notion of “hybrid war” as well as “hybrid peace.” Finally, the authors introduce a project of a less rigoristic and not purely prohibitive ethical program (“drone ethics”) which might serve as a basis for automated systems’ algorithms to make decisions during military crises and states of emergency. The article continues to address the range of problems brought up in the Logos issue on war (Vol. 29 #3 2019).

Task Offloading and Trajectory Scheduling for UAV-Enabled MEC Networks: An Optimal Transport Theory Perspective

In this letter, we propose a task offloading framework for UAV-enabled MEC networks, where all smart mobile devices are scattered randomly following an arbitrary distribution. By exploiting the hovering and mobilizing capability of a UAV, task offloading service can be provided to the devices in all sub-areas of the network. To extend UAV operating time and associated network lifetime, we formulate an optimization problem to minimize the total energy consumption of the UAV through joint region partitioning and UAV trajectory scheduling. To solve it, we decompose it into two independent sub-problems, i.e., region partitioning and UAV trajectory optimization. For the first sub-problem, we model it as a semi-discrete optimal transport problem by considering the traffic balance among different sub-areas and propose an iterative algorithm to achieve the optimal solution. Then, the UAV trajectory optimization sub-problem is modeled as a traveling salesman problem to determine the shortest route. Simulation results show that the proposed scheme can significantly reduce the energy consumption of the UAV while achieving proper load balance.

Possible Utilization of Low Frequency Magnetic Fields in Short Range Multirotor UAV Detection System

The multirotor UAVs or so called n-copters have become very popular in the last decade and they have been utilized in many services. However, with the broaden options of buying multirotors, there is higher risk to the safety and security not only of the airports, but also of the urbanized areas. There are many UAV detection systems that have been developed in the world, the most sophisticated of them utilize multisensoric approach to fulfill the detection task. The paper presents chosen experimental results of the magnetic field measurements around a small quadcopter UAV that can serve as a proof of concept for possible utilization of low frequency magnetic fields in a short range multirotor UAV detection system. Although the fields created by the UAVs are small, they are clearly detectable by a simple coil sensor and in addition, they can be correlated with audio band signals to improve detection capabilities. The presented approach confirms the main advantage of the magnetic fields measurement - the possibility to detect a multirotor UAV operating in a completely autonomous mode without RF communication in urbanized areas where radars could not be used.

New Complex Military and Civil UAV/RPA Classification System for Registration, Administrative Purposes, and Special Operation Preparation

In addition to the existing different UAV classification terms (e.g. NATO JAPCC, UVSI, US ARMY, EASA, CAA, etc.), the article deals with the necessity and possibilities of creating a new, more sophisticated and unified classification system, combined with a high security labelling system that provides a more professional registry of UAVs (both civilian and military). Based on the new unique code system, it is possible to clearly identify the most essential properties and specification data (e.g. payload, armaments, hanging points, sensors, range, endurance, speed and altitude ranges, weather minimums, etc.), nature of use (e.g. military recon/assault, SAR, agriculture, law enforcement, recreation, hobby, commercial, etc.), type of flight modes, risk level (combined with accident statistics), cost of the unit, VIN, etc. It also helps the efficient work of law enforcement agencies/authorities to check the lawfulness of UAV operation onsite (database contains photos, insurance status and other detailed information), avoiding corrupt identification of the unit.

ABOUT THE STRATEGY OF IMPRESSING ENEMY UAVS

The article emphasizes that Ukraine is currently faced with an acute problem of protecting its state system, in connection with which the Armed Forces of Ukraine have to repel attacks, in particular, by enemy aircraft, an essential part of which is the use of unmanned aerial vehicles. The necessity of training qualified UAV operators, which, together with their acquisition of skills in practical control of the device, should include the tasks of theoretical substantiation of the strategy and tactics of UAV use is indicated. This means that the future operator of drones must be able to formalize the practical task set before him, know rational algorithms for its solution, acquire the skills of quick and optimal solution. A statistical analysis of the types and purpose of enemy drones shot down recently by the Armed Forces of Ukraine was carried out. The specified types of combat operations, as elements of the strategy of impressing or damaging enemy UAVs. Namely, we are considering combat operations aimed at impressing enemy UAVs primarily with our UAVs directly or in combination with the described means of destroying drones. It is noted that in combat conditions there are often tasks of destroying the enemy, in which the effectiveness of the combat operation is determined not by one, but by several indicators at once, some of which should be made larger, others smaller. For example, it is necessary to plan a combat operation in such a way that as a result, a maximum of enemy drones are destroyed with the greatest possible damage to them, and at the same time, so that a minimum of our objects are hit with the least losses. Tasks in which several goals must be achieved at the same time are called multi-objective or multi-criteria tasks. In such problems, the goals are usually incompatible – a decision that maximizes one indicator usually does not minimize the other. The concept of a multi-objective problem is considered and the algorithm of one of the methods of its solution is formulated – the method of successive concessions in combination with the method of expert evaluations. At the same time, each of the methods can be considered as a separate way of solving certain strategic problems. An example of the application of these methods in planning the strategy of impressing enemy UAVs is presented and solved. Since the statistics of military operations are currently being accumulated, it is emphasized that the statistical material should be regularly analyzed in order to train highly qualified UAV operators. The prospect of further research in this direction is a similar analysis that will allow us to determine the dynamics and patterns of changes in military operations, and, ultimately, will allow us to increase the effectiveness of the use of UAVs by our military in combat operations.

Designing a Reliable UAV Architecture Operating in a Real Environment

The article presents a method of designing a selected unmanned aerial platform flight scenario based on the principles of designing a reliable (Unmanned Aerial Vehicle) UAV architecture operating in an environment in which other platforms operate. The models and results presented relate to the medium-range aerial platform, subject to certification under the principles set out in aviation regulations. These platforms are subject to the certification process requirements, but their restrictions are not as restrictive as in the case of manned platforms. Issues related to modeling scenarios implemented by the platform in flight are discussed. The article describes the importance of Functional Hazard Analysis (FHA) and Fault Trees Analysis (FTA) of elements included in the hardware and software architecture of the system. The models in Unified Modeling Language (UML) used by the authors in the project are described, supporting the design of a reliable architecture of flying platforms. Examples of the transformations from user requirements modeled in the form of Use Cases to platform operation models based on State Machines and then to the final UAV operation algorithms are shown. Principles of designing system test plans and designing individual test cases to verify the system’s operation in emergencies in flight are discussed. Methods of integrating flight simulators with elements of the air platform in the form of Software-in-the-Loop (SIL) models based on selected algorithms for avoiding dangerous situations have been described. The presented results are based on a practical example of an algorithm for detecting an air collision situation of two platforms.

НАВЧАЛЬНО-ТРЕНУВАЛЬНА СИСТЕМА ДЛЯ ПІДГОТОВКИ ОПЕРАТОРІВ БЕЗПІЛОТНИХ АВІАЦІЙНИХ КОМПЛЕКСІВ

In order to meet the needs of the Armed Forces of Ukraine (AFU) for specialists in the operation of unmanned aerial systems, the Zhitomir Military Institute named by S. P. Korolev deployed training for operators - military pilots. While creating the material and technical base, the issue of developing and introducing into the training process of simulators that would meet the requirements of higher military education training. Development of the scientific training system was carried out on the basis of the list of basic training issues, profound mastery of which is mandatory for the UAV operator’s. The training system was developed, manufactured and implemented in the training process, which is built as a schematic-abstracted one to ensure the conditions of effective learning material assimilation. The content basis of the scientific training system is a flat schematic outline of the aircraft, which contains typical onboard equipment of unmanned aerial vehicles and a reconstructed connection scheme of the elements. The power of the onboard equipment is provided from the classroom power supply via a stabilized power supply unit. Operation of the onboard equipment can be controlled from the manual control panel and from the ground control station via the Mission Planner program. The Mission Planner can also be controlled from the X - Plane flight simulator. In flight simulation mode, the Mission Planner screen displays a map of the flight route, the X-Plane screen displays the view and spatial orientation as well as the corresponding servo drives of the aircraft's steering surfaces and the main engine operation modes. The software of the scientific training system allows planning and adjusting the route and flight program, practicing UAV piloting skills in the flight simulator mode, simulating flight in different weather conditions. The scientific training system includes a two-channel hardware-software oscilloscope which allows to research electric processes in different electric lines of airborne equipment of the aircraft and pair interconnections between them. Functional properties of scientific training system allow to study theoretically and practice practically a wide range of training issues required in training of UAV operators. Up to this circle includes both the issues necessary for mastering drone piloting and the issues necessary for mastering the maintenance and repairs of UAV.

Construction and Research of Safety Management System for Machine Patrol Operation

Aiming at the flight safety problems existing in UAV power patrol inspection, this study proposes a UAV patrol inspection safety management system (SMS) scheme, which takes the safety target level specified in soar as the target management, based on safety management, modern control theory, risk management, and UAV operation regulations, combined with the actual needs of machine patrol inspection of China Southern Power Grid and the requirements of local government. The UAV SMS scheme is developed from four parts: safety policy, risk management, safety guarantee, and safety promotion, and the application analysis is carried out in combination with the Kobe accident case in 2020. The experimental results demonstrate that the implementation of SMS scheme can effectively reduce the accident risk level during UAV power patrol inspection.

A Cost-Sensitive Diagnosis Method Based on the Operation and Maintenance Data of UAV

In the fault diagnosis of UAVs, extremely imbalanced data distribution and vast differences in effects of fault modes can drastically affect the application effect of a data-driven fault diagnosis model under the limitation of computing resources. At present, there is still no credible approach to determine the cost of the misdiagnosis of different fault modes that accounts for the interference of data distribution. The performance of the original cost-insensitive flight data-driven fault diagnosis models also needs to be improved. In response to this requirement, this paper proposes a two-step ensemble cost-sensitive diagnosis method based on the operation and maintenance data of UAV. According to the fault criticality from FMECA information, we defined a misdiagnosis hazard value and calculated the misdiagnosis cost. By using the misdiagnosis cost, a static cost matrix could be set to modify the diagnosis model and to evaluate the performance of the diagnosis results. A two-step ensemble cost-sensitive method based on the MetaCost framework was proposed using stratified bootstrapping, choosing LightGBM as meta-classifiers, and adjusting the ensemble form to enhance the overall performance of the diagnosis model and reduce the occupation of the computing resources while optimizing the total misdiagnosis cost. The experimental results based on the KPG component data of a large fixed-wing UAV show that the proposed cost-sensitive model can effectively reduce the total cost incurred by misdiagnosis, without putting forward excessive requirements on the computing equipment under the condition of ensuring a certain overall level of diagnosis performance.

Numerical verification on influence of multi-feature parameters to the downwash airflow field and operation effect of a six-rotor agricultural UAV in flight

The airflow field produced by UAV is an important factor to determine the movement of spray droplets, which can enhance deposition and reduce drift. Therefore, in this study, the downwash airflow field of the six-rotor plant protection UAV in the flight state was simulated based on the Lattice Boltzmann method (LBM), and the distribution characteristics at multi-feature parameters including different flight speed, flight height, crosswind speed and work load were studied. In addition, take the coverage area and the penetrable area as evaluating index, the influence of multi-feature parameters and prediction model to the operation effect were investigated. The results showed that, with the increase of flight speed and height, the angle of backward tilt of the downwash airflow field gradually increased, and the length and width of longitudinal and horizontal spread on the ground decreased. The optimal flight speed and height for UAV operations respectively were 2 m or 2.5 m, and 4 m/s based on the evaluating index. As the flight height increased from 2 m to 3 m, the eddies became larger, and they would entrain and affect the spatial movement and distribution of droplets. Furthermore, the distribution of the airflow structure was obviously changed with the increase of crosswind speed, and the coverage area and the penetrable area had a huge decline when the crosswind speed was greater than 3 m/s, which was not fit for operations. By the designed orthogonal test, the prediction models of the coverage area and the penetrable area were established, the R square was 0.952 and 0.759, respectively; the influence of multi-parameters to the operation effect was analyzed, and the prediction of the models for the dependent variables were relatively accurate. The results of the study could provide reference for exploring the downwash airflow field and droplet deposition pattern in the complex airflow field when UAV sprayings.

Based on minimum fuel consumption mode integrated optimal control of fixed-wing UAV flight propulsion system

Purpose In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption. Design/methodology/approach In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller. Findings The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time. Practical implications The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV. Originality/value Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

TODA Passive location for UAV based on chicken swarm algorithm

Accurate positioning of drones is one of the key technologies for drone management and security. Aiming at the characteristics of the active emission of electronic radiation signals during the operation of UAVs, the passive positioning method based on multi-station time difference of arrival (TDOA) is studied, and the problem of solving the nonlinear equation of time difference of arrival passive location is transformed into an optimization problem of seeking the extreme value of the time difference likelihood function. The chicken swarm algorithm is used to search for the best positioning coordinates. The simulation results show that the chicken swarm algorithm can quickly and stably converge to the target position in time difference of arrival passive location system.

CRITERIA FOR ESTIMATING THE SENSORIMOTOR REACTION TIME BY THE SMALL UAV OPERATOR

Context. The rapid development of science and technology predetermines a significant expansion of the fields of application of UAVs different purposes. The key to the effective use UAVs is high-quality training of operators, an important element of which is the PPS of candidates, in particular, the assessment of their sensorimotor reactions. This can be achieved by selecting and justifying appropriate criteria. Objective. The goal of the work is the justification criteria for estimating the time sensorimotor reactions of a small UAV operator by analyzing the density distribution of statistical data. Method. A method has been developed to determine criteria for evaluating the time of sensorimotor reactions a small UAV operator based on the accumulation statistical material and its mathematical processing based on the results of a field experiment. The method allows to estimate numerical characteristics the distribution of the average reaction time in three modes: training production, in the conditions overload, in the conditions of overtraining and to obtain a generalized estimation. It was possible, by analyzing the occasional noninterruptible values, which take values within a certain range of values, to establish standards against which the obtained values the sensorimotor reaction time of the small UAV operator are compared and a decision is made on their suitability for training. Results. We obtained statistical series for the modes of assessment: skill development, under obstacle conditions, under conditions skill restructuring. For a visual representation of the series the corresponding histograms the distribution of the average reaction time duration were constructed. In order to eliminate the representativeness error, statistical series alignment was carried out by selecting a theoretical distribution curve for each series, which displays only essential features of the statistical material. For this purpose, we approximated the histogram of distribution by the polynomialf fourth degree. The interval theoretical density of distribution, in which the time sensomotor reaction of an arbitrary person is considered normal, with a given probability reliability such event – 0.95 has been established. To verify the effectiveness of the proposed method, algorithms for estimating the sensorimotor reaction time of a small UAV operator in three modes have been synthesized and the corresponding software that implements the proposed algorithms has been developed. Conclusions. The criteria for evaluating the sensorimotor reaction time for UAV operator to a visual stimulus using specialized software were substantiated. This allowed the previous PPS training candidates to take into account the requirements to the motor skills of the small UAV operator and the specificity his movements. The conducted experiments confirmed the validity of decisions made. Prospects for further research may include expansion of testing modes with justification for appropriate evaluation criteria.