Current Issue : July-September Volume : 2023 Issue Number : 3 Articles : 5 Articles
The superior performance of factor graphs compared to Kalman filtering in various fields and the use of factor graph algorithms instead of Kalman filtering algorithms in moving target localization tasks can reduce target localization error by more than 50%. However, the global factor graph algorithm may cause computational delays due to excessive computational effort. A moving target localization algorithm based on a combination of global and incremental optimization with improved factor graphs is proposed to improve localization accuracy and ensure that the computation time can be adapted to the requirements of online location. A reference point is introduced into the incremental calculation process, and it is first determined whether global or incremental calculation is used for this calculation by comparing the distance between the incremental localization results of the calculated reference point. The position of the UAV itself is then corrected by determining the position of the reference point, and this is used to finally locate the target. Simulation results show that the algorithm has good real-time performance compared to the time-consuming global algorithm. The online localization error of moving targets can be reduced by 17% compared to the incremental calculation results of the classical factor graph algorithm....
The firing accuracy of the projectile has a positive relation with aerodynamic parameters. Due to the complex dynamic characteristics of projectiles, there is an overfitting risk when a single extreme learning machine (ELM) is used to identify the aerodynamic parameters of the projectile, and the identification results oscillate transonic region. To obtain the aerodynamic parameters of the projectile accurately, an aerodynamic parameter identification model based on ensemble learning theory and ELM optimized by improved particle swarm optimization is proposed. The improved particle swarm optimization algorithm (IPSO) with an adaptive update strategy is used to optimize the weight and threshold of ELM. Combined with the ensemble learning theory, the improved ELM neural network is regarded as a weak learner to generate a strong learner. The structural parameters of the strong learner were continuously optimized through training, and an aerodynamic parameter identification model of projectile based on ensemble learning theory is obtained. The simulation results show that the introduction of the IPSO and ensemble learning theory enables the model to exhibit excellent generalization ability. The proposed identification model can accurately describe the variation of aerodynamic parameters with the Mach number....
An on-board autonomous task planning system is designed and implemented in this article, aiming at the problem that the current remote sensing satellite needs complex instruction support to perform tasks and depends on the ground system too much. The complex earth observation task description and injection decomposition modules are designed in the system. No more than 128 ordered points describe the curve area task or irregular polygon area task, and the complex task is decomposed into several strips according to the satellite imaging width. Then, the task’s orbit, attitude, mobility, energy, and time constraints are calculated through the modules of on-board orbit prediction, agile attitude calculation, track planning, energy prediction, and visible arc calculation. Finally, the on-board autonomous task planning and execution are completed through task solution space search and metatask command generation modules. The on-orbit flight verification is carried out on the high-resolution multimode (GFDM) satellite. The results show that this paper’s on-board autonomous task planning system can complete complex task injection and autonomous planning and finally execute....
There is a strong aerodynamic interference when launching the missile in the embedded mode. During the separation process, the carrier aircraft safety may be threatened due to large slenderness ratio, low structural stiffness, and aeroelasticity effects of the missile. The present study simulates missile separation in the presence of the aeroelasticity effects based on the computational fluid dynamics (CFD), rigid body dynamics (RBD), and computational structure dynamics (CSD) coupling method. A hybrid dynamic grid method consisting of the mixed overset unstructured grid and deformation grid is utilized. In order to verify the accuracy of the coupled numerical method, store separation from a wing and AGARD 445.6 wing flutter are first simulated as two standard test cases. The verification results imply that the present coupled numerical method is reliable and capable in simulation of the aeroelastic effect in missile separation. The influence of aeroelasticity on the separation trajectory of a missile from the internal bay is systematically studied at different states. Numerical results show that aeroelasticity substantially affects the missile angular displacement, while it has a slight impact on the linear displacement of the center of mass. Mach number and flight altitude are two important flight parameters that characterize the aeroelasticity effect on missile separation from the internal bay....
Probabilistic failure risk analysis of aeroengine life-limited parts is of great significance for flight safety. Current probabilistic failure risk analysis uses equal amplitude load calculations for conservative estimation, avoiding inclusion of the interference effect analyzing random loads due to its massive computational complexity and leading to reduced analysis accuracy. Here, an efficient algorithm is established to solve this computational problem, and an analytical framework is established to consider the interference effect of variable amplitude load. The corresponding probabilistic failure risk analysis is performed for the centrifugal compressor disk. The results show that considering the interference effect of random variable amplitude loads causes a significant decrease in the risk of failure, and the efficient algorithm has advantages over the Monte Carlo sampling method in accuracy and efficiency when considering load interference. This work provides a reference for exploring the probabilistic damage tolerance method under complex loads and supports the optimal design of life-limited parts....
Loading....