Waveform design is one of the key technologies in radar signal processing for the netted collocated Multiple Input Multiple Output(MIMO)radar system.To improve the target detection capability of the system under clutter interference while taking into account hardware compatibility,good ambiguity and pulse compression properties of the designed waveform,the paper considers constructing a model for the radar output Signal to Clutter and Noise Ratio(SCNR)under constant modulus constraints and waveform similarity metrics;then by equivalent transformation of the original non-convex problem,a polynomial-time iterative algorithm based on successive convex approximation is proposed and analyzed for convergence.To further reduce the computational complexity,the paper also proposes an algorithm based on Gradient Projection(GP).Finally,the proposed method is simulated and verified,and the results show that the method can provide a new feasible method for the waveform design of each transmitting site under the netted radar system.
Path planning is one of the key technologies for UAVs to accomplish operation missions in complex battlefield environments.In this paper,we propose a UAV path planning method based on PER-D3QN,which realizes the path planning for UAVs in the battlefield environment through network model design,state space design,action space design and reward function design.The PER-D3QN algorithm combines the target network,dueling network and prioritized experience replay,which effectively solves the overfitting problem and unstable problem in deep reinforcement learning.In the end,it is verified through simulation experiments that the proposed method achieved better convergence,stability and applicability compared with double DQN and DQN algorithms,and better real-time performance compared with A* algorithm,which can efficiently realize the path planning of UAVs in the complex battlefield environment,and effectively help the UAVs to attempt the operational mission.
In order to meet the requirement of rapid prediction of fluid-structure interaction system in aircraft design,a data-driven unsteady flow field modeling strategy was explored to shorten the time spent on flow field evolution solution and accelerate the simulation speed of fluid-structure interaction system.The solution of flow field evolution in fluid-structure interaction system is partially equivalent to the evolution of unsteady flow field with moving boundary.This paper proposes a flow field prediction model based on neural networks to learn and predict the evolution of unsteady flow fields with moving boundaries.This neural network can predict the flow field at next timestep based on the current flow field and boundary motion information.The prediction accuracy and generalization ability of the proposed neural network model were tested by the flow around a moving cylinder under different vibration frequencies and amplitudes.The predicted flow fields of the neural network are in accordance with the computational fluid dynamics simulation results.The aerodynamic force obtained by integrating the pressure on the boundary of the predicted flow field data also has a high accuracy.The test results demonstrate that the good predictive performance of the neural network model,so this method can be used to quickly and accurately obtain the unsteady flow field state around the moving boundary.
The poor wear resistance of titanium alloys severely limits their application in the aerospace field.In order to study the mechanism of improving wear resistance of Ti-6Al-4V(TC4)titanium alloy after ultrasonic impact strengthening,ultrasonic impact strengthening test of Ti-6Al-4V(TC4)titanium alloy was conducted.The influence rule and sensitivity of ultrasonic impact treatment process parameters(tool diameter,air float table pressure,impact pass,tool head shape,feed step)on the surface quality and performance of titanium alloy were investigated.It was found that when the ball head tool was used,the pressure of air float table was 0.45MPa,and the feed step was 0.3mm,the ultrasonic impact strengthening had the most obvious improvement on the wear resistance of titanium alloy.Through the study and analysis of the tribological test results such as friction coefficient,ball grinding spot diameter,disk wear rate and surface topography,it is found that the wear resistance of titanium alloy after ultrasonic impact strengthening treatment is improved by the joint action of compressive stress suppression crack mechanism,surface hardening strengthening mechanism and gully oil storage mechanism.The actual enhancement effect of ultrasonic impact treatment on the wear resistance of titanium alloy was verified.
Flap-slat electromechanical actuator is a key motion part in the aircraft high lift system,and its speed control is very important for the opening and closing precision of the flap-slat.However,the speed control loop of electromechanical actuator is prone to periodic or aperiodic interference of external aerodynamic load and the traditional proportional integral speed controller cannot guarantee satisfactory control performance.Therefore,a speed controller based on a proportional resonance Active Disturbance Rejection Control(ADRC)is proposed.It can not only suppress aperiodic interference but also suppress specific periodic interference.The periodic interference is estimated by an extended state observer using a proportional resonance term.By comparing the control performance of proportional integral controller,traditional linear ADRC controller and proportional resonant controller,it is proved that the proposed method can significantly suppress the interference,improve the control performance of flap-slat electromechanical actuator,and enhance the smoothness of aircraft take-off and landing.
