Uneven temperature distribution of an aero-engine during hot restart can lead to initial thermal deformation of its rotors, which causes excessive engine vibration, or even a start-up failure. In view of the problem, this paper takes a typical rotor in aero-engines as an object, establishes its dynamic equation based on the effects of thermal deformation on vibration, and analyzes the effects of thermal deformation on vibration response of rotor system through modal coordinate transformation. The results show that thermal deformation is equivalent to additional excitations acting on the rotor, that is, initial shaft bow excitation, additional unbalance excitation and additional gyroscopic moment excitation, all of which are synchronous with the rotating speed. Moreover, the amplitude of unbalance and gyroscopic moment excitation is related to the rotating speed, therefore influencing rotor vibration response at different critical speeds to an equivalent extent, while that of initial shaft bow excitation is not related to the rotating speed and the response of low-order critical rotating speeds is more affected.

Aimed at measurement delay in the narrow field of view (NFOV) star sensor used for attitude estimation, a robust extended Kalman filter (REKF) algorithm is proposed to solve the measurement delay. According to the minimum mean square error criterion, the minimum upper bound of the variance is solved and the filter gain is determined by the minimum upper bound. The designed REKF algorithm can effectively solve the problem of measurement delay and improve the accuracy of attitude estimation. Finally, the simulation results show that the algorithm is superior to the conventional additive robust extended Kalman filter (AEKF), robust finite-horizon filter (RFHF) and robust Kalman filter (RKF) algorithm, which can better solve the problem of measurement delay in nonlinear systems, and the effectiveness of the algorithm is verified.

This paper focuses on the elastic-liquid coupling problem in the rigid-elastic-liquid coupling dynamics. It is an important topic related to researches on mechanism and large-scale modeling and calculation of liquid-solid coupling in the aerospace rigid-elastic-liquid coupling system. Based on the analysis of the function of the quasi-variational principles for the rigid-elastic-liquid coupling dynamics, characteristics for rigid-elastic coupling, rigid-liquid coupling and elastic-liquid coupling in the rigid-elastic-liquid coupling system were illustrated. Inter-element boundary conditions were plugged into the function by Lagrange multiplier method and the mechanization of the elastic-liquid coupling was illustrated step by step through the identification of Lagrange multipliers. Solving stationary values of function shows that inter-element boundary conditions convert from preconditions to stationary value conditions. It realizes the transition from compatible element model to the hybrid element model. Through analysis on stationary value conditions before and after identification of Lagrange multipliers, it is shown that the identified Lagrange multipliers can effectively reduce the degree of freedom for calculation.

With the rapid development of multi-electrification of aircraft and airborne high-energy electronic equipment, the design of fuel heat management system has been paid great attention to. The most critical factor is the thermal load capacity of fuel. For jet propulsion high-speed aircraft, this paper presents a multi-objective optimal allocation method for a large-scale and multi-task fuel heat management system. The thermal carrying capacity of fuel decreases with the increase of flight time, due to the dual effect of airborne thermal load and aerodynamic heating. In this paper, the improved genetic algorithm NSGA-Ⅱ is used to optimize the design of two targets under different flight mission planning. The objective function is heat sink efficiency and fuel compensation loss. The optimization variables are the maximum flow rate of the fuel cycle, the consumption of coolant and the heat load on board. The objective function Pareto optimal solution set is obtained to meet the expected model selection principle of the fuel heat management system. By analyzing the correlation between the optimized variable and the optimization target, the optimization configuration criterion and the minimum fuel compensation loss can be quantified, and the airborne efficient heat management system supporting the multiple heat sink reconstruction is designed.

In the process of signal receiving, global navigation satellite system (GNSS) receiver will be affected by factors such as building blockages and signal interference and will not be able to obtain all the visible satellites; moreover, in order to reduce the processing burden of multi-constellation receivers, the fast satellite selection algorithm using partial visible satellites to achieve positioning solution is investigated, and the BDS/GPS integrated navigation satellite selection algorithm based on chaos particle swarm optimization (CPSO) is proposed. First, the visible satellites are continuously numbered and randomly divided into groups. Each group is regarded as a particle. Then, chaotic maps are used to select several groups from all grouping spaces to form initial population. The geometric dilution of precision (GDOP) is chosen as fitness function to evaluate the particle's quality. In addition, the particle's position is updated by the velocity-displacement model of the PSO algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. Finally, using real navigation data, the algorithm is verified by simulation experiments. The results demonstrate that when the number of selected satellite is more than 5, the time that the proposed algorithm takes to select satellite once is 37.5% of the time that the traversing algorithm takes, and the GDOP error of the selected satellites is between 0 and 0.6. Moreover, the proposed algorithm can be applied to the case of different numbers of selected satellite in BDS/GPS integrated navigation.

Structure is the comprehensive embodiment of aero-engine function, performance, and reliabi-lity design level, and all technical requirements, performance indicators, strength indicators, or structural safety and reliability should be based on reasonable structure layout design. This paper puts forward the viewpoint of the layout and optimization about the aero-engine rotor structure. Taking the structure configuration of the high-pressure rotor of a typical turbofan engine as an example and based on the response surface method of the design of experiment (DOE), the finite element method is used to calculate through multi-objective genetic optimization algorithm. Relevant optimization calculations are carried out from the aspects of deformation resistance, mechanical environment adaptability and rotor structural efficiency respectively. It is demonstrated that reasonable structure layout can greatly enhance the mechanical properties of rotors. The research method is of great guiding significance for the initial structure layout design of the aero-engine rotor system, which can significantly reduce the number of iterations and shorten the design cycle.

The representative volume element (RVE) method is a common numerical modeling method for predicting the material properties of short fiber reinforced composites. The RVE generation efficiency is an important factor affecting the efficiency of the property prediction. For the problem of too many Boolean operation times which cause low efficiency of Boolean operation when the existing random sequential adsorption (RSA) method is used to generate RVE, the centroid distance calculations between the lasted randomly generated fibers and the existing fibers are introduced. Using the centroid distance, some randomly generated fibers, which are intersecting with the existing fibers, are filtered out to reduce the number of Boolean operations. And a filter based random sequential adsorption (FRSA) method for modeling RVE is presented. By comparing the number of Boolean operations and the time cost for generating RVE, the FRSA method has been verified, and the verification is performed with different RVE parameters and method parameters using improved FRSA method and Boolean operation based random sequential adsorption (BORSA).

In order to analyze the effect of input random variables on the failure probability of structural systems more reasonably, a new moment-independent importance measure analysis method is proposed in this paper. The traditional importance measure index can only estimate the influence of input random variables on the output response of structural systems at fixed points, while the new index proposed in this paper can fully reflect the average influence of input random variables on the output response of structural systems when they change in all reduced intervals of their distribution areas, which is more in line with engineering practice. Seeking to find the new index, this paper presents two algorithms:the conventional double-loop-repeated-set Monte Carlo (DLRS MC) method and adaptive radial-based importance sampling (ARBIS) method. The results of DLRS MC method can be used as a reference solution, yet its calculation process is slow and strenuous. Under the condition of the precision of solving the new index is met, the calculation efficiency of ARBIS method is greatly improved. Finally, a numerical example and an engineering example are given to illustrate the significance of the new index and the efficiency of the proposed algorithm.

Considering the nonlinearity, uncertainty and rigid/elastic coupling of elastic hypersonic vehicles, a state/parameter joint estimation method based on QR decomposition and moving horizon estimation is proposed. First, this method transforms the state/parameter estimation problem into an optimization problem with fixed-number variables by introducing moving horizon strategy, and it can deal with the time-varying parameter estimation better than Kalman filter. Second, by utilizing the forward dynamic programming principle, the computation of arrival-cost is converted into a least-square problem that is solved by QR decomposition, and the arrival-cost update algorithm based on QR decomposition is given. In this way, the moving horizon estimation is based on optimization, and the feedback mechanism is introduced to improve the estimation accuracy and speed. The simulation results demonstrate that the accuracy of moving horizon estimation is obviously higher than that of extended Kalman filter, and the arrival-cost update strategy based on QR decomposition is better than the traditional arrival-cost update method based on the estimated error covariance in speed.

Digital phase-locked demodulator is an important method for weak signal processing in electromagnetic non-destructive testing. For its performance optimization, a digital phase-locked demodulator with Kalman filter is designed, which has strong anti-noise ability and good dynamic tracking features. By using the characteristic that the cut-off frequency of Kalman low-pass filter decreases with the number of iterations and combining with the zero frequency, we design a low-pass filter in a digital phase-locked demodulator and then realize very narrow phase-locked bandpass, which improves the ability of strong noise resistance. In addition, using the predictive-update feature of the Kalman filter, the smaller response time of the digital phase-locked demodulator is realized, thereby improving the dynamic tracking characteristics of the digital phase-locked demodulator. Simulation and detection experiments show that the designed digital phase-locked demodulator has high noise immunity and good dynamic tracking response. It can accurately and quickly capture the defect information contained in the detection signal in electromagnetic non-destructive testing.

In order to enhance the contrast, color and brightness constancy of foggy images, an improved Retinex algorithm of foggy image enhancement is proposed. The algorithm uses an improved bilateral filter as a filter function to remove the noise interference while maintaining the edge information. It uses the S-shape function curve to restore image color by subtracting the incident light component from the logarithmic domain in Retinex algorithm, enhances the contrast and the perceptual characteristics of the whole image, and restores the color information of the image. The experimental results show that the improved algorithm proposed in this paper can effectively improve the clarity and contrast of the foggy image. Compared with the original foggy image, the image clarity is raised by about 200%, the standard deviation is raised by about 110%, and the information entropy is raised by about 10%. At the same time, it can maintain more realistic color information, and the computational complexity is low, which meets the real-time requirements.

A lander in the soft landing mode of shutdown at touchdown is taken as the research object, and the dynamic simulation model of its soft landing process is established. Based on the simulation model, the parameters of the worst landing conditions are obtained by combining optimization method and multi-island genetic algorithm (MIGA). The radial basis function (RBF) neural network is used to establish a surrogate model which reflects the mapping relationship between the lander's velocity parameter and the value of stability indicator. The sample points are obtained by discretizing the velocity parameters of the lander, and the soft landing stability performance of each sample point are calculated by using the neural network model. Based on the calculation results, the contour and the three-dimensional velocity stability boundary of each soft landing stability indicator are given, and then a comprehensive stability boundary of lander velocity is obtained. The analysis results can intuitively determine the range of velocity for safe landing, which provides reference for the rational control of lander velocity.

The existing backoff algorithms of the medium access control (MAC) protocols cannot provide the multiple priority differentiation, and the performance declines sharply under heavy loads in flying Ad hoc networks (FANETs), so a novel adaptive backoff algorithm based on multiple priority differentiation is proposed in this paper. The algorithm adopts a busy/idle factor adaptive mechanism and an optimal contention window (CW) adaptive mechanism, so the length of CW for each priority can be adjusted in real time with the busy degree of channels and network state parameters. Meanwhile, the CW can quickly converge to the best state in every backoff stage, and the multiple priority differentiation can be obtained. Furthermore, the best system throughput performance can be achieved by modeling. The three-dimensional Markov chain model of the backoff process for different priorities is established and the adaptive factor under the saturated throughput is solved by theory. In addition, the mathematical expressions of system throughput and mean MAC delay are also deduced. Simulation results show that the algorithm can achieve the multiple priority differentiation and availably enhance the system throughput, and its performance is superior to the priority adaptive backoff (PAB) algorithm and adaptive CW backoff algorithm for QoS (Q-ABACW).

Aimed at the problem that a large number of images need to be scaled in the visual algorithm for the runway detection, recognition and tracking of the unmanned aerial vehicle with high real-time requirement, a new image scaling algorithm suitable for hardware acceleration is proposed based on the mapping relation of the input-output pixel. By simplifying the algorithm structure and using the field programmable gate array to design the hardware function of the module, the algorithm accelerates, and the real-time image processing system is built by the software and hardware cooperative architecture. The experimental results show that the improved scaling algorithm has high precision and less time consumption, and it can speed up by 171 times with the hardware logic. The hardened system can get the image data through the camera, and the real-time processing is displayed in the monitor, which has 30 frame/s processing speed. It can be applied to the image processing algorithm with high real-time requirement.

In order to solve the problem of terrain awareness when helicopters fly at low altitudes, a forward looking terrain avoidance method is presented using terrain matching, which can correct the relative position error between helicopter and terrain. First, the recovery trajectory of a helicopter is predicted by the helicopter flight dynamics model, based on which the alert envelope is generated. The elevation data of terrain database and radar detection are transformed from airspace to frequency domain. Then, by using the terrain matching method, which is based on cross power spectrum algorithm, the relative position error between the helicopter and the terrain is calculated to obtain the accurate relative position. As the effect of terrain matching can be influenced by topographic relief amplitude, the terrain entropy selection method is adopted to remove the matching area with less topographic relief before terrain matching. Then the matching accuracy is improved. Finally, based on the flight dynamics model of the UH-60 helicopter, 1 000 sets of control case simulation are conducted to verify the alert method. According to the results, the proposed alarm method can significantly reduce the nuisance alert rate by about 16% and increase the successful alert rate greatly by nearly 30%, compared with conventional alert methods. It is shown that the forward looking alert method proposed in this paper can effectively achieve the helicopter collision avoidance alert at low altitude.

Aimed at the problem of cooperative search for UAV swarm in an unknown environment without prior information, a cooperative area search algorithm for UAV swarm with coverage rate as real-time search rewards is proposed. First, coverage distribution map (CDM) is established to describe the mission area, and the rapid update of CDM is realized by using Hadamard product. Then, the coverage rate is calculated based on CDM to describe the search results quantitatively. Considering UAV swarm as a control system, a predictive model of the system is established based on the distributed model predictive control theory, and the maximum increment of coverage rate in the predictive period is determined as a reward function. The optimal solution, as the optimal input of system, is obtained by differential evolution algorithm. Simulation results demonstrate that the proposed algorithm can complete the coverage and search of region effectively. In the event of emergencies, its area coverage rate is much higher than that of the parallel search method.

In order to increase the landing efficiency, improvements are made in two aspects:landing velocity vector field and guidance law design. Landing velocity vector field is designed based on ellipse curve for the requirements of shorter flight path and less maneuverability. Meanwhile, the flight path azimuth angle command is generated based on the relationship between the image coordinate system and the body-fixed frame. With reference to the tangential direction of the ellipse, the flight path elevation angle is tuned and combined with the cooperative vector features. Speed command is calculated using image information. Finally, the requirements of the traditional trajectory and the proposed trajectory on the directional maneuverability are compared in theory. The relationship between the trajectory parameters and the UAV turning performance is then shown. The system simulation platform is built based on Simulink, and the required cooperative vector is calculated. The results show that the UAV accurately lands on the target with curved trajectory, which meets the needs in practical applications.

The traditional environmental vibration tests usually assume that the random vibration signal follows Gaussian distribution and power spectral density (PSD) is used as the test conditions, while in practice, lots of vibration excitations to the structure are non-Gaussian distribution and PSD can only describe the low-order statistics of signals but not for the high-order statistics of the non-Gaussian signals such as the kurtosis and skewness. So a method based on amplitude modulation technique (AMT) of window function to generate the non-Gaussian signal with PSD and kurtosis is developed. An approximated simulation method is provided to generate the modulation signal. Two kinds of statistical distribution, Beta and Weibull, are used to construct modulation signal, the relation between target kurtosis and modulation signal distribution parameters is explored, and the suitable kurtosis range of two distributions is discussed. A case study is presented to show that the synthesized non-Gaussian signal has the same PSD, probability density function (PDF), and kurtosis as outfield measured data, which verifies the correctness of the method.

For complex aerospace machinery products, the limit state functions are often implicit and highly nonlinear, and the reliability calculation usually requires time-consuming finite element analysis. In this paper, the particle swarm optimization-simulated annealing (PSOSA) algorithm is applied to the optimization of the correlation parameters of the dynamic Kriging model, which improves the prediction accuracy. At the same time, with the dynamic update mechanism, sample points are gradually added to reduce the number of function callsas much as possible, thereby improving the calculation efficiency. The algorithm is applied to the structural reliability analysis. The Monte Carlo method, response surface and other classic algorithms are compared, and the results of the proposed algorithm are closer to those of Monte Carlo method, and the calculation time is greatly shortened, which shows that the efficiency and accuracy of the algorithm are improved significantly.

Aimed at the problems of complex failure mechanism of interconnected structures in electronic chips, difficulty in obtaining lifetime data, and lack of a theoretically supported life distribution model, a statistical analysis based on degraded experimental data was conducted. First, an electronic chip reliability evaluation testbed is built, and the daisy-chain test chip is used as the test object. Degradation data and lifetime data of interconnected structures are acquired. Then, based on the theory of fracture mechanics, The failure mechanism of interconnection structure is analyzed. The theoretical basis of the two-parameter Weibull distribution of the life distribution of the interconnection structure of electronic chips in BGA package is given. The life distribution model of the interconnection structure of electronic chips based on the life data is established. Next, using the distribution of degradation, a lifetime distribution model of the interconnected structures in electronic chips is established. Finally, the two statistical modeling methods are compared. The results show that the lifetime distribution model based on degradation data is in good agreement with that based on lifetime data.

Aimed at the problem of near-Earth orbit hovering of electromagnetic spacecraft formation, a coordinated control method is proposed in the absence of accurate information of reference orbit. The relative motion between spacecraft is described by the TH equation, and the circular orbit of the same cycle as the reference orbit is selected as the nominal orbit. The deviation of the reference orbit from the nominal circular orbit, the Earth's non-spherical gravity, the atmospheric resistance and the other celestial gravitation are classified separately, and they are considered as uncertain and constitute an uncertain system. By introducing the consistency theory, the robust coordinated control law is designed for the target of spacecraft formation hovering under the condition that the electromagnetic action model and the dynamic equation are all uncertain. Considering the optimal and balanced energy consumption and the decoupling of orbital attitude, a scheme of magnetic moment distribution through optimization is given. The simulation results show that the designed robust coordinated control law can achieve high-precision hovering of electromagnetic spacecraft formation. The proposed magnetic moment configuration scheme can realize the rational distribution of magnetic moments.

In this paper, the semi-codeless based P(Y) code autocorrelation sea surface altimetry method was studied due to the fact that the conventional GPS C/A code delay altimetry method is less precise, and that the signal-to-noise ratio of delay waveform in interference altimetry method is low. First, the height measurement accuracy of the C/A code and P(Y) code was compared and analyzed through theoretical model for describing the height measurement accuracy. Then, the architecture of semi-codeless based P(Y) code autocorrelation processing for L1 and L2 dual-frequency reflected signals was described. Meanwhile, the altimetry model and dual-frequency ionospheric time-delay error correction methods are discussed. Finally, using simulated L1 and L2 reflection signals, the measurement accuracy is compared and analyzed regarding the proposed method, C/A code autocorrelation method and signal cross-correlation method. The results show that the accuracy of the proposed method is 3.97 times and 1.47 times higher than that of the C/A code autocorrelation method and signal cross-correlation method, respectively.

In view of the problem that few researches have been done on the mixed scheduling of unicast and multicast traffic for the combined input and crossbar queued (CICQ) architecture, and there is no research on the head of line (HoL) blocking problem, a new scheduling algorithm for mixed multicast and unicast, i.e. unicast with low HoL blocking (MULHB) algorithm, is proposed, which aims to reduce HoL blocking so that the switch can operate in work-conserving state as much as possible. In addition, to avoid the phenomenon of "starvation", the proposed algorithm considers the difference between unicast traffic and multicast traffic and uses weights to complete the arbitration between unicast and multicast. At the same time, this paper also proposes a dynamic multicast cell assignment algorithm named dynamic muticast queuing (DMQ), which allows the arrival multicast cell to select the appropriate queue without disorder. Simulation results show that the performance in terms of through rate and average packet delay obtained by DMQ-MULHB is much better than that of the existing popular algorithms under the different traffic patterns, and especially under the non-uniform traffic pattern, the performance is close to the output queuing (OQ) scheduling.

Aimed at the decrease of filtering accuracy caused by too many models and competitions between them in interactive multi-model (IMM) algorithm for tracking hypersonic targets, an adaptive variable structure interactive multi-model (AVSIMM) algorithm is proposed based on adaptive grid IMM (AGIMM) algorithm for tracking hypersonic non-powered reentry gliding targets. Based on the angular velocity parameters of the real-time maneuvering state of gliding hypersonic target without power load, AVSIMM algorithm with various dynamitic models is designed to focus on the unicity of models in AGIMM algorithm. AVSIMM algorithm realizes high-precision tracking through adaptive adjustments in both model set parameters and algorithm structure. Simulation results show that, compared with AGIMM algorithm, the designed AVSIMM algorithm not only is more adaptive in structure and parameters but also improves accuracy and efficiency in tracking hypersonic targets.

This paper proposes an improved vehicle dynamics model based on the current situation of mixed-pedestrian-vehicle driving in real life. The model considered the influence of pedestrians, bicycles, etc. on the adjacent lanes or in lateral directions on the driving behavior of the main road vehicles. Based on the classical optimal velocity model, this paper modelled the actual problem and introduced the lateral distance and longitudinal distance between the main road vehicle and the pedestrian as parameters into the optimal velocity model, and expanded to obtain the improved model. In order to verify the stability and effectiveness of the model, this paper used the linear stability theory to derive the stability and non-stable conditions of the model, draw a neutral stability curve, and visually describe the size of the traffic flow stability area. It is shown that the improved model considering the lateral pedestrian interference factor is more stable than the traditional car-following model considering only the single-lane vehicle factor, and the steady-state region caused by the change of different parameters also changes. This paper adopted a more realistic optimization of the velocity equation and described the driving behavior of the vehicle through simulation experiments. The simulation experiment lists two kinds of practical scenarios:when pedestrians are scarce and when pedestrians are more. The velocity-time curve of the vehicle and the space(distance)-time curve of the vehicle were plotted separately. The experimental results show that the lateral pedestrians do interfere with the normal driving of the vehicle; in different scenarios, the number of pedestrians will also affect the driving behavior of the vehicle to varying degrees.