Joint mission and route planning of unmanned air vehicles via a learning-based heuristic

Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.

Weapon configuration, allocation and route planning with time windows for multiple unmanned combat air vehicles

Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.

3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote sensing.Considering the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data.Using professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is evaluated.Based on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water body.The results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.

Design and Wind Tunnel Study of a Top-mounted Diverterless Inlet

Combined with a UAV of the shape like Global Hawk, a new inlet is advanced to obtain high performance in both Radar Cross Section(RCS) and aerodynamic drag. Efforts are made to achieve this goal such as adopting a top-mounted inlet configuration, utilizing the diverterless technique and putting forward a new shape of entrance. A design method is brought forward and verified by wind tunnel tests. Results indicate: (1) Despite the negative effect of the front fuselage and the absence of the conventional boundary diverter, the performance of the top-mounted diverterless inlet advanced here(Ma:0.50-0.70, α:-4°-6°,σ>0.975) is equivalent to that of conventional S shaped inlet with diverter; (2) The integration of the inlet with the fuselage is realized by the utilization of a special inlet section and the diverterless technique, which disposes the whole inlet in the shield of the head of UAV, improving the drag characteristics and the stealthy performance of the aircraft; (3) The bump which is equal to the local boundary layer thickness in height can divert the boundary layer effectively. As a result, no obvious low total pressure zone is found at the outlet of the inlet; (4) According to the experimental results, negative angle of attack is favorable to the total pressure recovery and positive angle of attack is favorable to the total pressure distortion, while yaw brings bad effects on both; (5) The design of cowl lip is of great importance to the inlet performance at yaw, therefore, further improvement of the inlet performance will rely on the lip shapes of the cowl chosen.

Optimal search for moving targets with sensing capabilities using multiple UAVs

This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.

LQR Controller with Kalman Estimator Applied to UAV Longitudinal Dynamics

The aim of this study is designing an optimal controller with linear quadratic regulator (LQR) method for a small unmanned air vehicle (UAV). To better evaluate the effect of disturbances on the obtained measurements a Kalman filter is also used in the system. For this purpose a small UAV that is normally used as a radio controlled plane is chosen. The linearized equations for a wings level flight condition and the state space matrices are obtained. An optimal controller using LQR method to control the altitude level is then designed. The effect of the disturbances on the measurements are taken into account and the effectiveness of the Kalman filter in obtaining the correct measurements and achieving the desired control level are shown using the controller designed for the system. The small UAV is commanded to the desired altitude using the LQR controller through the control inputs elevator deflection and thrust rate. The LQR effectiveness matrices are chosen to find the gains necessary to build an effective altitude controller. Firstly the controller is tested under the situation where disturbances are absent. Then a Kalman filter is designed and the system under disturbances is tested with the designed controller and the filter. The results reveal the effectiveness of the Kalman filter and the LQR controller.

Threat sequencing of multiple UCAVs with incomplete information based on game theory

The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dynamics of the air combat environment, the weight coefficients of the threat indicators are usually time-varying. Moreover, the air combat data is difficult to be obtained accurately. In this study, a threat sequencing method of multiple UCAVs is proposed based on game theory by considering the incomplete information. Firstly, a zero-sum game model of decision maker( D) and nature(N)with fuzzy payoffs is established to obtain the uncertain parameters which are the weight coefficient parameters of the threat indicators and the interval parameters of the threat matrix. Then,the established zero-sum game with fuzzy payoffs is transformed into a zero-sum game with crisp payoffs(matrix game) to solve. Moreover, a decision rule is addressed for the threat sequencing problem of multiple UCAVs based on the obtained uncertain parameters. Finally, numerical simulation results are presented to show the effectiveness of the proposed approach.

Cooperative Path Dynamic Planning Model of UCAV Team Based on Global Optimization Method

Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.

MEMS-Based Low-Cost Flight Control System for Small UAVs

Small unmanned air vehicles （UAVs） can be used for various kinds of surveillance and data collection missions. The UAV flight control system is the key to a successful mission. This paper describes a low-cost micro-electro mechanical system-based flight control system for small UAVs. The integrated hardware flight control system weighs only 24 g. The system includes a highly-integrated wireless transmission link, which is lighter than traditional links. The flight control provides altitude hold control and global positioning system navigation based on gain scheduling proportional-integral-derivative control. Flight tests to survey the grass quality of a large lawn show that the small UAV can fly autonomously according to a series of pre-arranged waypoints with a controlled altitude while the wireless video system transmits images of the surveillance target to a ground control station.

Distortion minimization for multimedia transmission in NOMA HAP-UAV integrated aerial access networks

Aerial access networks have been envisioned as a promising 6G solution to enhance the ground communication systems in both coverage and capacity. To better utilize the spectrum and fully explore different channel characteristics, this paper constructs an integrated network comprising the High Altitude Platform(HAP) and Unmanned Air Vehicles(UAVs) with the NonOrthogonal Multiple Access(NOMA) technology. In order to improve the transmission quality of images and videos, a power management scheme is proposed to minimize the distortion of the transmissions from the HAP and UAVs to the terminals. The power control is formulated as a non-convex problem constrained by the maximal transmit power and the minimal terminal rate requirements. The variable substitution and the first-order Tailor’s expansion is used to transform it into a sequence of convex problems, which are subsequently solved through the gradient projection method. Simulation demonstrates the signal distortion and error rate improvement achieved by the proposed algorithm.

A modeling and simulation framework for UAVs utilizing 4G-LTE cellular networks

Only a small amount of work has been published on the topic of exploiting existing Long-Term Evolution-Advanced(LTE)cellular communication network infrastructure for Unmanned Aerial Vehicles(UAV)data links.This paper documents a modeling and simulation(m&s)framework that has been developed utilizing the powerful OMNeT++simulation tool for assessing the feasibility and effectiveness of this prospect in various UAV scenarios.Using multiple scenarios,we have studied the data rate requirements for communications between small and medium-sized UAVs and base stations.Using this framework,we have shown that the data rate requirements for the links are within the data throughput achieved by LTE networks.The developed framework implements a propagation model endorsed by the 3GPP LTE project team and also accurately models the high mobility of UAVs.The framework is highly configurable and extensible and boasts of automatic aggregation of results and chart plotting.The outcomes of this research may be utilized by industry for rapidly deploying highly mobile,low-cost UAVs in a wide range of applications and scenarios.