Matrix method synthesis of transmitting antenna for wireless power transmission

The synthesis of the radiating structure of wireless power transmission (WPT) systems has some unique aspects. An important attribute is the efficiency of coupling the radiated energy into the receiving aperture. There are possibilities of improving the WPT by variations of the wave field distribution on the aperture and its configuration too. The matrix method of synthesis of the aforesaid structure is examined.     

Intelligent sequential multi-impulse collision avoidance method for non-cooperative spacecraft based on an improved search tree algorithm

The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years. Non-cooperative targets exhibit uncertain states and unpredictable behaviors, making collision avoidance significantly more challenging than that for space debris. Much existing research focuses on the continuous thrust model, whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally, it is important to minimize the impact on the original mission while avoiding noncooperative targets. On the other hand, the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer, posing challenges for practical engineering applications. To conquer these difficulties, this paper makes the following key contributions:(A) a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B) a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST) algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS). Numerical simulations confirm the effectiveness and efficiency of the proposed method.     

An optimized GPS carrier phase ambiguity search method focusing onspeed and reliability

An optimized ambiguity search method is described in this paper focusing on speed and reliability. The method has incorporated several existing fast ambiguity search concepts and the ambiguity search speed can be further improved. In addition to the improvement of the ambiguity search speed, special attention has been paid to the improvement of the reliability of the ambiguity search process. Several theoretical and practical aspects involved in an ambiguity search algorithm are also addressed which have not been explored in previous literatures     

Fast wideband search for spurious responses

A technique for quickly searching frequencies in a signal path to find and measure low-level spurs is described. It couples a wideband tuned receiver with a tuned digital, parallel filter bank analyzer to greatly reduce spur testing times. The receiver is step-tuned across the region of frequencies to be searched, and at each step the filter bank is step-tuned across the IF output. An example system is described, and search time and sensitivity are discussed     

Efficient exhaustive search for optimal-peak-sidelobe binary codes

The work presented here describes an exhaustive search for minimum peak sidelobe level (PSL) binary codes, combining several devices for efficiency. These include combinatoric tree search techniques, the use of PSL-preserving symmetries to reduce search space, data representations and operations for fast sidelobe computation, and a partitioning scheme for parallelism. All balanced 64-bit minimum PSL codes are presented, and the upper limit on known consecutive lengths to have PSL = 4 codes is extended to 70. In addition, a technique for determining balance properties of a code for given PSL-preserving transformations is developed.     

Evaluation of the state and development of aerial targets for testing contemporary and promising arms systems

The results of evaluating the state and development of aerial targets designed for testing aircraft weapon, systems of air defense and combat crew training are presented. The basic types of aerial targets are examined using as an example existing ones and problems are posed to consider the necessity of creating new types of aerial targets for extending a range of FV types being simulated. The basic characteristics of aerial targets are separated and their classification is proposed.     

Demonstration-enhanced policy search for space multi-arm robot collaborative skill learning

The increasing complexity of on-orbit tasks imposes great demands on the flexible operation of space robotic arms, prompting the development of space robots from single-arm manipulation to multi-arm collaboration. In this paper, a combined approach of Learning from Demonstration(LfD) and Reinforcement Learning(RL) is proposed for space multi-arm collaborative skill learning. The combination effectively resolves the trade-off between learning efficiency and feasible solution in LfD, as well as the time-consuming pursuit of the optimal solution in RL. With the prior knowledge of LfD, space robotic arms can achieve efficient guided learning in high-dimensional state-action space. Specifically, an LfD approach with Probabilistic Movement Primitives(ProMP) is firstly utilized to encode and reproduce the demonstration actions, generating a distribution as the initialization of policy. Then in the RL stage, a Relative Entropy Policy Search(REPS) algorithm modified in continuous state-action space is employed for further policy improvement. More importantly, the learned behaviors can maintain and reflect the characteristics of demonstrations. In addition, a series of supplementary policy search mechanisms are designed to accelerate the exploration process. The effectiveness of the proposed method has been verified both theoretically and experimentally. Moreover, comparisons with state-of-the-art methods have confirmed the outperformance of the approach.     

Graph-based multi-agent reinforcement learning for collaborative search and tracking of multiple UAVs

This paper investigates the challenges associated with Unmanned Aerial Vehicle(UAV)collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning(MARL) method based on Graph Neural Network(GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network(GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments.Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.     

Reduction rules-based search algorithm for opportunistic replacement strategy of multiple life-limited parts

The opportunistic replacement of multiple Life-Limited Parts(LLPs) is a problem widely existing in industry.The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment.This article focuses on finding a quick and effective algorithm for this problem.To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality.Based on these six reduction rules, a search algorithm is proposed.This search algorithm can identify one or several optimal solutions.A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than11.A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining tobe-replaced LLPs when determining the maintenance workscope of an aircraft engine.Therefore,the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines.     

A search of short-period coronal waves

In 1973, during the total solar eclipse, we flew an experiment aboard the Concorde supersonic airliner in order to investigate the possible presence of white-light coronal waves. Our experiment failed to detect any significant effects, so it became clear that such waves should be searched for by use of finer, i.e., spectroscopic methods.Proceedings of the Conference Solar Physics from Space, held at the Swiss Federal Institute of Technology Zurich (ETHZ), 11–14 November 1980.     

Investigation of promising ceramic materials in discharge chambers of stationary plasma thrusters

The characteristics of the insulator wear process in the discharge chamber of a stationary plasma thruster (SPT) are analyzed. The results of studying the erosion resistance to ionic spraying of different ceramic compositions are presented. It is shown experimentally that the integral characteristics (the value of thrust and thrust efficiency) as well as the SPT lifetime can be improved in changing from the conventional hot-pressed boron silicate (BN + SiO₂) ceramics to the BN + Si₃N₄ ceramic compositions.     

飞机蒙皮裂纹的数学形态学识别方法

提出了一种基于数学形态学的飞机蒙皮裂纹磁光图像检测方法。首先应用内距均值法确定磁光图像中类圆形铆钉区域的圆形参数,然后利用自适应线性星形形态学腐蚀算子分割裂纹缺陷。其中,以四点方向快速定位法确定腐蚀算子的方向,并用中心对称法处理裂纹缺陷区域粘连的情况,最后,根据备选区域相关特征进行分类,判别缺陷存在及其特征参数。实验结果表明：算法在检测裂纹的多种特征方面具有优越性。     

级数展开法在捷变频雷达综合测试仪误差估计中的应用

针对捷变频雷达综合测试仪测频算法进行了误差分析,用级数展开法推导了计数式瞬时测频中测频误差与观测时间、基准时钟频率及被测信号频率之间的关系,给出了测频精度与雷达脉宽、载频之间的关系式.     

A LODBO algorithm for multi-UAV search and rescue path planning in disaster areas

In disaster relief operations, multiple UAVs can be used to search for trapped people. In recent years, many researchers have proposed machine le arning-based algorithms, sampling-based algorithms, and heuristic algorithms to solve the problem of multi-UAV path planning. The Dung Beetle Optimization(DBO) algorithm has been widely applied due to its diverse search patterns in the above algorithms. However, the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic, potentially leading to an inability to fully explore the search space and a tendency to converge to local optima, thereby not guaranteeing the discovery of the optimal path. To address these issues, we propose an improved DBO algorithm guided by the Landmark Operator(LODBO). Specifically, we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space. Second, we expand the search range of the rolling ball dung beetle by using the landmark factor. Finally, by using the adaptive factor that changes with the number of iterations., we improve the global search ability of the stealing dung beetle, making it more likely to escape from local optima. To verify the effectiveness of the proposed method, extensive simulation experiments are conducted, and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA), the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA) and the original DBO algorithm in the disaster search and rescue task set.     

The AM CVn systems: A bibliographic search for clues to their cataclysmic nature

The nature of AM CVn, GP Com, CR Boo, and V803 Cen is investigated in detail on the basis of a comprehensive review of all that to-date is known about these systems. They are classified as cataclysmic variables, within these forming the subclass of AM CVn systems; their distinguishing characteristic is an extreme H-deficiency. Besides, they are very blue and display periodicities on the order of minutes. Although in several aspects they behave like cataclysmics, in others they differ from them. The most widely accepted interpretation for their nature involves two interacting He white dwarfs in a very close orbit. The validity of such a model is evaluated in the present work.This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France.     

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm's ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory's flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system(FMS). The global optimal solution was validated against an exhaustive search algorithm(ESA), other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.     

Optimization method for sensor planning

This article looks at the development of algorithm-based tools with a view to meeting future operational needs for intelligence. More precisely, it concerns the management of sensors and proposes a new heuristic capable of optimizing (globally speaking and subject to constraints) the planning of sensors to meet the intelligence needs expressed by the High Command.     

Generalized approach for μ synthesis of robust switchingregulators

A general method using μ synthesis to design controllers applicable to pulsewidth modulated (PWM) converters is described. System uncertainties from component tolerances are included in the synthesis procedure, adding a quantifiable measure of robustness. Furthermore, these uncertainties have been implemented in a structured format which maximizes available system performance. A boost converter example is presented demonstrating the controller synthesis procedure and advantages of this method