Flight Test Results Research Articles

Формирование и отображение видеоинформации в бортовых мультиспектральных системах улучшенного видения

The article considers the results of long-term research and real flight tests for developing a multichannel system for enhanced vision in difficult for aircraft crew visibility conditions. The multicomponent nature of the aggregate video signal generated by a multispectral video system is shown, justifying its representation in color and the need to develop a color indicator of the aircraft windshield to obtain a better quality of situational awareness for pilot compared to the capabilities of traditionally used monochrome indicators. A method for integrating monochrome images of multichannel enhanced vision system spectral channels into a color multicomponent image is proposed. For more natural perception of the resulting color images by the human eye, the spectrum of the spectral characteristics of the video channels is rearranged in the direction of decreasing wavelength. For the most common RGB color image format, the red component R of the display system records the image of the long-wave thermal range, the green component G records the image of the mid-wave infrared range, the blue component B records the image of the short-wave visible television range. The resulting pseudo-color image allows unambiguous restoring the original images. This proves the absence of information loss during image integration. Since there are no colored windscreen displays yet, a method for reproducing a pseudo-color image on a mono-chrome display is proposed. To convert a pseudo-color image to monochrome one, methods are used in which color contrasts are preserved in the form of tonal contrasts. The advantages of the proposed technology are demonstrated on real examples

Functional Intelligence-Based Scene Recognition Scheme for MAV Environment-Adaptive Navigation

Adaptive navigation is the core of micro aerial vehicles (MAVs) conducting autonomous flights in diverse environments. Different navigation techniques are adopted according to the availability of navigation signals in the environment. MAVs must navigate using scene recognition technology to ensure the continuity and reliability of the flight. Therefore, our work investigated the scene recognition method for MAV environment-adaptive navigation. First, we exploited the functional intelligence-adaptive navigation (FIAN) scheme by imitating the physiological decision-making process. Then, based on sufficient environment-sensitive measurements from the environment perception subsystem in FIAN, the two-level scene recognition method (TSRM) in the decision-making subsystem consisting of two deep learning frameworks, SceneNet and Mobile Net-V2 was proposed to extract scene features for accurate diverse scenes recognition. Furthermore, the four-rotor MAV-Smartphone combined (MSC) platform simulating the owl’s omni-directional head-turning behavior was built. The proposed TSRM was evaluated for accuracy, delay, and robustness compared with PSO-SVM and GIST-SVM. The results of practical flight tests through MSC platform show that TSRM has higher classification accuracy than PSO-SVM and GIST-SVM, and performs smoothly with self-regulatory adaptations under diverse environments.

Cooperative Navigation for Low-Cost UAV Swarm Based on Sigma Point Belief Propagation

As navigation is a key to task execution of micro unmanned aerial vehicle (UAV) swarm, the cooperative navigation (CN) method that integrates relative measurements between UAVs has attracted widespread attention due to its performance advantages. In view of the precision and efficiency of cooperative navigation for low-cost micro UAV swarm, this paper proposes a sigma point belief propagation-based (SPBP) CN method that can integrate self-measurement data and inter-UAV ranging in a distributed manner so as to improve the absolute positioning performance of UAV swarm. The method divides the sigma point filter into two steps: the first is to integrate local measurement data; the second is to approximate the belief of position based on the mean and covariance of the state, and pass message by augmentation, resampling and cooperative measurement update of the state to realize a low-complexity approximation to traditional message passing method. The simulation results and outdoor flight test results show that with similar performance, the proposed CN method has a calculation load more than 20 times less than traditional BP algorithms.

Ground and flight tests of AlSat-1B butane propulsion system

On September 26, 2016 Algerian Space Agency launched AlSat-1B, the second in a series of medium resolution earth observation satellites mission. AlSat-1B electro-thermal propulsion system follows the classic design principle that has been used on previous SSTL-100 missions. With a total dry weight of 5.17 kg, the system is filled with 2.35 L self-pressurized butane. The thruster assembly is designed to use 15 W (at 28 V) redundant heater elements, it is designed to have an average mission thrust of 50 mN. With a warm up time of 10 min, the temperature of the butane will be increased by over 250 °C. This is the equivalent of about 35% gain in specific impulse over ambient temperature butane. The spacecraft dry weigh at launch site was 107 kg, the propulsion system is designed to provide at least 19 m/s Delta-v to meet the spacecraft's mission requirement. To investigate the system readiness for flight, a series of performance tests have been completed at the Surrey Satellite Technology Ltd laboratories (United Kingdom), Satellite Development Centre (Algeria) and Satish Dhawan Space Centre rocket launch site (India), the results of these tests as well as initial flight test results are presented in this paper.

Robust variational Bayesian method-based SINS/GPS integrated system

SINS/GPS integrated systems are influenced by non-Gaussian noise and unknown measurement noise due to exogenous disturbances and inaccurate noise statistics. To overcome this problem, a robust variational Bayesian method-based SINS/GPS integrated system is designed. First, the variational Bayesian-based Kalman filter is selected to estimate unknown measurement noise covariance. Second, the maximum correntropy criterion is introduced to the nonlinear robust filter to handle interference from non-Gaussian noise. Finally, the robust variational Bayesian method is designed based on the interacting multiple model, which not only fuses the variational Bayesian-based Kalman filter and the robust filter but also avoids non-Gaussian noise interference to the estimation result of measurement noise covariance. The robustness and adaptivity of the robust variational Bayesian method are verified by numerical simulation. Furthermore, the flight test results show improved performance of the SINS/GPS integrated system using the proposed method.

КОНСТРУКЦІЯ РОТОРА ТА ЛІТАЛЬНИХ БПЛА ДЛЯ ПОЛІТУ ПО ЗАДАНІЙ ТРЕКОРІЇ З ВИКОРИСТАННЯМ ТЕЛЕМЕТРІЇ. ПОРІВНЯННЯ ТЕХНОЛОГІЙ, ПЕРЕВАГИ ТА ПЕРСПЕКТИВИ ВИКОРИСТАННЯ

In this research, the budgetary (no more than $ 120) UAVs of aircraft and rotary types have been designed, that are able to maintain altitude and position, automatically return to the takeoff point on command from the control panel or in case of loss of communication with it, perform automatic flight along a given trajectory and fly with taking into account telemetry data. It has been shown experimentally, that for flight on the mission on airplane to ensure a straight-line flight, it’s advisable to use only a GPS receiver for navigation. The compass setting distorts the plane's straight flight. It was found that in navigation mode, the UAV flight along waypoints, the INAV firmware works more correctly, when the compass is installed in the direction corresponding to the direction of the gyroscopic sensor of the flight controller. Based on the results of flight tests, it was found, that a quadcopter flies waypoints much more accurately, than aircraft. It’s shown, that it’s possible, using the Blackbox INAV 2.5.0 toolkit and the Google Earth Pro service, to form a real flight path of the aircraft and quadrocopter, to determine the speed parameters, and the flight altitude according to the readings of the GPS receiver. The possibility of using 3DR modules for telemetry flight has been established. It’s noted in the work, that for ground stations implemented by INAV Configurator ver.2.5, the Mission Planner for INAV (Android) only MSP protocol works. No automatic switching to LTM protocol detected, that limits telemetry range compared to Ardupilot firmware. The constructed aircraft and quadrocopter can be used to perform photo and video surveys of the terrain in automatic mode with a route length of 6-8 km, using a lithium polymer battery with a capacity of 1500-2200 mAh.

Algorithm for Determining the Aerodynamic Performance by the Flight Test Results

Algorithm for Determining the Aerodynamic Performance by the Flight Test Results

First Flight-Testing of LoRa Modulation in Satellite Radio Communications in Low-Earth Orbit

At present, the use of LoRa modulation in satellite radio communications and the construction of a CubeSat constellation for the satellite Internet of Things based on LoRa technology has already begun. However, the limits of applicability of LoRa modulation in low-Earth orbits have not yet been established. This paper presents the results of the first flight tests of LoRa modulation for robustness against the Doppler effect in the satellite-to-Earth radio channel, carried out using a NORBY CubeSat operating at 560 km. Flight tests confirmed the very high immunity of LoRa modulation to the Doppler effect for modes with spreading factor <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SF</i> ≤ 11 and spread spectrum modulation bandwidth <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">BW</i> >31.25 kHz. LoRa modulation in these modes can be used in satellite communication without any limitations caused by the Doppler effect. For <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">BW</i> = 31.25 kHz, the LoRa radio channel is affected by the static Doppler effect. Communication with the satellite is possible in this case only at high elevation angles. For <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SF</i> = 12, the dynamic Doppler effect becomes significant, and communication is possible only at low satellite elevation angles, which leads to the formation of a “hole” in the center of the coverage area directly below the satellite. In both cases, the duration of the communication session is significantly reduced because of the Doppler effect. In the case of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SF</i> = 11 and 12 at <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">BW</i> = 31.25 kHz, both static and dynamic Doppler effect catastrophically affect the LoRa radio channel, so that communication with the satellite becomes impossible.

A Novel Movable UWB Localization System Using UAVs

Recently, interest in ultrawideband (UWB)-based localization systems has increased in various application fields. However, since UWB anchors are usually fixed, they work only within the limited range that UWB measurement signals can reach. To address this issue, a swarm flight system with movable UWB anchors is developed. One ground station controls multiple unmanned aerial vehicles (UAVs), each of which is equipped with a UWB anchor and real-time kinematic global positioning system (RTK-GPS) capabilities, and collects the precise (centimeter-level) positions of the UWB anchor UAVs through RTK-GPS. In this way, the constraints of existing UWB systems can be alleviated by changing the UWB anchor positions in real time as desired by the user. In addition, this paper proposes a novel localization algorithm using only time-of-flight (TOF) measurements from UWB signals, heading information from an attitude and heading reference system (AHRS), and altitude information from a barometer. The results of UAV flight tests show that the proposed algorithm provides better localization performance than existing algorithms.

Enhanced Disturbance Suppression Method Based on NonlinearH∞Filtering for Distributed POS in Aerial Earth Observation Imaging Application

Multinode remote sensing imaging loads have long been a fascinating focus of aerial earth observation applications, where the load denotes the device or equipment located on the aircraft for a specific task, such as aerial camera, scanning laser, and synthetic aperture radar. In order to guarantee high-quality imaging, distributed position and orientation system (POS) serves as high accuracy spatio-temporal reference information for remote sensing loads to realize motion compensation. As a result of the working environment, the flexible structure of the wing will suffer the external disturbance, then for distributed POS, the lever arm between the master system below the abdomen and slave system under the wing is time-varying, also the noise disturbance influences markedly on the motion parameters measurement accuracy. Then aiming at the transfer alignment accuracy improvement of distributed POS, a central difference <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> filtering algorithm is proposed, which adopts the central difference Kalman filtering to realize nonlinear state estimation and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> filtering to suppress the disturbance influence on estimation, then the high accuracy motion parameters can be obtained. The flight test results show that the developed algorithm can effectively deal with the disturbance influence on transfer alignment estimation and enhance the parameter estimation accuracy, which can be used in aerial earth observation imaging.

Refining the aerodynamic moment of the missile based on flight test results

This research paper is intended to refine the aerodynamic moment of the missile based on an analysis of flight tests and results of gas dynamics software computations. The paper compares mathematical simulation results with flight test data in order to demonstrate an improved convergence due to the proposed refinement.

Experimental comparison of the effect of the number of redundant rotors on the fault tolerance performance for the proposed multilayer UAV

In this paper, experimental investigation of the flight performance of the proposed universal Unmanned Aerial Vehicle (UAV) in case of rotor failures is presented. In the experimental flight tests, proposed universal UAV that can be converted to many different configurations due to its non-standard multi-layer structure was used in two different configurations as a standard octorotor and a multi-layer dodecarotor. Multiple outdoor experiments are conducted to show flight safety and reliability of the proposed UAV in terms of rotor failure tolerance. In order to evaluate flight safety and reliability of the proposed UAV, take-off, hovering and landing flight performance analyzes were performed in cases where one or two motors/propellers were completely lost. As performance criteria, errors in the UAV’s roll, pitch and yaw angles, altitude error and vibration in three axes were determined. The flight test results are presented both numerically and graphically. According to the results, multi-layer dodecarotor type has shown a more stable flight performance in terms of angular position errors. In addition, in both types of UAVs, in the case of failure of two rotors rotating in the opposite direction, it has been observed that the error in yaw angle is less than a rotor failure, as expected. Likewise, in the case of failure of two rotors rotating in the same direction, performance loss was observed in the control of yaw angle.

Improved Immune Genetic Algorithm to Optimize the Design of Wing Structure of Competition Aircraft

An improved immune genetic algorithm is used to design and optimize the wing structure parameters of a competition aircraft. According to the requirements of aircraft design, multi-objective optimization index is established. On this basis, the basic steps of using immune algorithm to optimize the main design parameters of aircraft wing structure are proposed, and the optimization of the wing parameters of a competition aircraft is used as an example for simulation calculation. The design variables in the optimization are the size of the wing components, and the optimization goal is to minimize the weight of the wing and the maximum deformation of the wing structure. Research shows that compared with traditional optimization methods; the improved immune genetic algorithm is a very effective optimization method. At the same time, a prototype is made to check the validity and feasibility of the design. Flight test results show that the optimization method is very effective. Although the method is proposed for competition aircraft, it is also applicable to other types of aircraft.

Energy-optimal trajectory planning for solar-powered aircraft using soft actor-critic

High-Altitude Long-Endurance (HALE) solar-powered Unmanned Aircraft Vehicles (UAVs) can utilize solar energy as power source and maintain extremely long cruise endurance, which has attracted extensive attentions from researchers. Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day. In this work, a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning (RL) framework is introduced. According to flight and environment information, a neural network controller outputs commands of thrust, attack angle, and bank angle to realize an autonomous flight based on energy maximization. The validity of the proposed method was evaluated in a 5-km radius area in simulation, and results have shown that after one day-night cycle, the battery energy of the RL-controller was improved by 31% and 17% compared with those of a Steady-State (SS) strategy with a constant speed and a constant altitude and a kind of state-machine strategy, respectively. In addition, results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.

A survey on modelling, control and challenges of stratospheric airships

The stratospheric airship, which is a new concept of autonomous atmospheric flight platforms, can operate over a period of time at very high altitudes to accomplish various military or commercial missions, such as monitoring, surveillance, and scientific exploration. The worldwide interest in stratospheric airships is still growing. However, modelling and control techniques for airships have fallen far behind those for fixed-wing aircraft. To show recent advances in modelling and control for stratospheric airships, this paper provides an insightful description of the related problems and a list of references for researchers and engineers focusing on this area. The literature is categorized according to major topics in this area: dynamic modelling, control design, and ascent/descent flight control. Moreover, an application of the path-following control with real-time flight test results is presented for an autonomous prototype airship. Finally, some challenging issues are addressed for future research.

Optimizing Urban LiDAR Flight Path Planning Using a Genetic Algorithm and a Dual Parallel Computing Framework

This paper introduces a genetic algorithm (GA) and a beam tracing algorithm incorporated within a dual parallel computing framework to optimize urban aerial laser scanning (ALS) missions to maximize vertical façade data capture, as needed for many three-dimensional reconstruction and modeling workflows. The optimization employs a low-density point cloud from the site of interest as a spatial representation of the urban scene. The GA is suitable for LiDAR flight path optimization due to its capability of handling open-ended problems that have many solutions. However, GAs require evaluating a very large number of candidates. The use of an initial point cloud allows realistic modeling of the urban environment in the optimization at the cost of high data input volumes. To cope with the computational and data demands, a dual parallel computing framework was devised. The parallel computing framework consists of two layers of parallelization. In the upper layer, multiple evaluators work in parallel and in conjunction with a main multi-threading GA optimizer to perform GA operations and evaluate the flight paths. In the lower layer, to evaluate assigned flight paths, each evaluator distributes its data and computation to multiple executors, which can reside on multiple physical nodes of a distributed-memory computing cluster. In addition to parallelism, the data partitioning on the lower layer allows out-of-core computation. Namely, data partitions are efficiently transferred between disks and memory so that only relevant subsets of data are kept in the main memory. The objective of the proposed method is threefold: (1) search for flight paths that yield the highest numbers of vertical points, (2) create a means to explicitly consider the detailed spatial configuration of urban environments, and (3) assure that the proposed optimization strategy is fast and can scale to large problem sizes. Multiple experiments were conducted and demonstrated the success of the proposed method. Converged results were achieved after dozens of generations within two hours. Two flight paths identified by the GA as the most and the least optimal candidates were deployed in real flight missions. The optimal flight path captured 16% more vertical points than the least optimal one, slightly higher than the 13% predicted. Both layers of parallelization were efficient: 13.1/16 for the lower layer and 3.2/4 for the upper layer. The two complementary layers of parallelization allowed flexible and efficient use of distributed computing resources to reduce the runtime. The scalability of the proposed approach was successfully demonstrated up to a data size of 460 million points. The optimization results were realistic and aligned well with the test flight results.

Novel Deep-Learning-Aided Multimodal Target Tracking

Existing interacting multiple models (IMMs) are limited by the time delay in responding to system model jumps due to the nature of the soft hand-off algorithm that interacts among subfilters. To address this issue, a novel method for deep-learning-aided localization of a multimodel system is proposed in this paper. The main contribution of the proposed algorithm is that a mode estimation network based on a bidirectional long short-term memory network (BiLSTM) is newly proposed to quickly and accurately estimate the multimodal system mode, which minimizes the delay. In addition, a federated Kalman filter with a selective reinitialization algorithm from the proposed BiLSTM is proposed for better estimation of multimodal systems. Simulation and flight test results of a UAV demonstrate that the proposed algorithm yields better localization performance than the conventional IMM algorithm because the proposed mode estimation network has fast and accurate mode detection.

Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuvers and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were used in the analysis, with aerodynamic moment dependencies modeled by linear expansions in the aircraft states and controls. Aerodynamic parameters were estimated simultaneously with inertia parameters using equation-error modeling applied to flight test data from maneuvers designed specifically for this problem. The approach was demonstrated using a nonlinear F-16 simulation, then applied to a remotely piloted subscale aircraft flight test. Errors in the aircraft moment of inertia parameters determined from simulated F-16 flight test data were less than 6% compared to the true values in the simulation. Flight test results for the subscale aircraft were within 6% of ground-test values obtained using the same aircraft.

Development of Large Capacity FM Telemetry System for Long March 5 Launch Vehicle

The telemetry system is responsible for obtaining the telemetry data of the whole rocket flight, which is the key to evaluate the comprehensive performance of the rocket afterwards. This paper introduces the overall scheme and composition of a new generation of large capacity FM telemetry system applied to Long March 5 carrier rocket. Focusing on the problems faced by the application of the key technology of 10 Mbps high bit rate FM telemetry, the technical breakthrough and flight test result are given from the aspects of the application of FM telemetry enhancement technology, the synthesis and transmission of hierarchical baseband data and the high gain antenna feed. Combined with the development process, the development experience and application of a new generation of large capacity FM telemetry system for rockets are summarized.

Обґрунтування моделі турбулентної в’язкості для дослідження характеристик співвісного гвинтовентилятора і вхідного пристрою ГТД

The issues of substantiation of the most rational, based on adequacy, model of turbulent viscosity for mathematical modeling of the flow near the propfan and in the inlet of the turbine-propeller engine are considered. It was found that at present there is no universal turbulence model for determining the parameters of the boundary layer, energy loss in the flow, and laminar-turbulent transition. Analysis of the results of previous studies showed that there is a need to select and justify a turbulent viscosity model for each type of research object. The task of modeling the flow near the propfan and in the inlet device of the power plant was performed using the ANSYS CFX software product, which allows using various standard mathematical models and tools for modeling turbulent flow. The object of research is an annular axial inlet device, in front of which there is a coaxial propfan with two rows of propellers: the first row has eight blades, the second - six. 7 types of models of turbulent viscosity, which most fully describe the phenomena in the flow around the propfan and the inlet device, have been investigated: k-ωmodel; SSТ (shear stress transport) SST Transitional №1 Fully turbulence; SST Transitional №2 Specified Intermittency; SST Transitional №3 Gamma model; SST Transitional №4 Gamma theta model; SST Transitional №5 Intermittency. The results of mathematical modeling of the flow near the propfan and in the inlet device at the corresponding operating mode of the turbopropfan engine using the selected models of turbulent viscosity, the total pressure value in front of and behind the inlet device was obtained to determine the total pressure recovery coefficient in it and the value of the propfan thrust. The value of the recovery factor of the total pressure in the inlet device and the propfan thrust are compared with the flight test data of the prototype. An analysis of the comparison of the values of the total pressure recovery factor in the inlet device and the propfan thrust showed that the use of the SST Transitional №4 Gamma theta model allows obtaining the value of the total pressure recovery factor in the inlet device and the propfan thrust that is closest to the flight test results.