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For the issue of limited filtering accuracy of interactive multiple model particle filter algorithm caused by the resampling particles don't contain the latest observation information, we made improvements on interactive multiple model particle filter algorithm in this paper based on mixed kalman particle filter algorithm. Interactive multiple model particle filter algorithm is proposed. In addition, the composed methods influence to tracking accuracy are discussed. In the new algorithm the system state estimation is generated with unscented kalman filter (UKF) first and then use the extended kalman filter (EKF) to get the proposal distribution of the particles, taking advantage of the measure information to update the particles' state. We compare and analyze the target tracking performance of the proposed algorithm of IMM-MKPF in this paper, IMM-UPF and IMM-EPF through the simulation experiment. The results show that the tracking accuracy of the proposed algorithm is superior to other two algorithms. Thus, the new method in this paper is effective. The method is of important to improve tracking accuracy further for maneuvering target tracking under the non-linear and non-Gaussian circumstances.

Compared with traditional gear transmission, the multi-branch split-torsion gear transmission system has the advantages of large transmission power, small size and high reliability, so it is more and more used in high-speed heavy load occasions such as ships and aircraft. Since the transmission system of multi-branch split torsional gears belongs to over-constrained configuration, it is necessary to meet strict tooth matching condition in the design process in order to realize the correct synchronous meshing of each branch, which is of great significance to ensure its uniform installation and motion synchronization.Aiming at the coaxial six-branch twisted herringbone gear transmission system, this paper establishes a calculation method for the proper meshing conditions of each branch on the basis of considering the movement synchronization of each branch and preventing geometric interference.In addition, the calculation of gear allocation was carried out for a ship's power transmission system, and a parameter scheme that satisfies the requirements of transmission ratio, concentricity and synchronous meshing was obtained.The correctness of the calculation method of tooth matching in this paper is verified by three-dimensional modeling. This method has universal application value to the tooth matching design of other coaxial multi-branch gear transmissions.

This paper selects SST k-w turbulence model and VOF wave to construct a numerical calculation model of moving body planning on a flat free surface based on STAR-CCM+ numerical simulation software. The construction model is checked through foreign classic literature, and the numerical simulation results are in good agreement with the experimental results. The hydrodynamic numerical errors are less than 5%, which is within the engineering error range. The model can be used for the numerical simulation of the planning cylinder. In this paper, it is used to simulate the planing process of cylinder with different speeds and different submerged depths, and the flow field characteristics and hydrodynamic characteristics in the planing process are obtained. The results show that waves appear at the tail and the tail liquid splashes to form a water splash during the planing process of the cylinder on a flat surface. The higher the speed of the planning cylinder is, and the deeper the submersion depth, the more pronounced waves at the tail. When the cylinder has a Fr number Cv≥8, the hydrodynamic force of the cylinder is almost unchanged, and it is not affected by the speed. But when Cv=3, the hydrodynamic characteristic coefficient is higher. The drag coefficient is 20% higher than that in the high-speed (Cv≥8) planing process. The lift coefficient is 3 times of high-speed planing lift coefficient. It is related to the surface pressure and frictional force distribution of cylinder during the low-speed planing. There is a linear relationship between the drag coefficient and the submerged depth during the cylinder planing at different submerged depths.

The fault detection function of GLT method is approximately proportional to the square of fault value, the value of the fault detection function is lower than the detection threshold when the soft fault is small, which leads to the low sensitivity of soft fault detection and the high rate of missing detection. The IM-SPRT method rapidly increases the value of fault detection function above the threshold of fault detection by accumulating small soft fault values, so it has high sensitivity for soft fault detection, however, the end time of the fault cannot be judged timely, resulting in a high false alarm for fault detection. In view of the above problems, this paper proposes a high-sensitivity fault detection method for redundant systems based on GLT/IM-SPRT. This method uses the IM-SPRT method to detect weak and soft faults and sets the IM-SPRT method fault detection function value to zero by the GLT fault detection result, and isolates the fault with GLT. On this basis, a framework of high-sensitivity fault detection and isolation methods for redundant ADS and INS systems is designed. The simulation results of soft and hard fault detection and isolation of three-redundancy ADS subsystem level and INS sensor level show that the method in this paper can improve the sensitivity of fault detection and reduce the rate of missed detection.

Path planning is the key technology for UAV to achieve autonomous flight. Considering the shortcomings of path planning based on the conventional potential field method, this paper proposes an improved optimization algorithm based on the artificial potential field method and extends it to three-dimensional space to better achieve flight constrained 3D online path planning for UAVs. The algorithm is improved and optimized aiming at the three problems of goal nonreachable with obstacle nearby (GNWON), easy to fall into local minimum, and path oscillation in traditional artificial potential field method. First, an improved potential field function with relative distance is used to solve the GNWON, and an optimized repulsive potential field calculation method based on different obstacles or threat models is proposed to optimize the planned path. Secondly, in order to make the drone jump out of the local minimum trap, a method of setting heuristic sub-target points is proposed. For local path oscillation, a method using memory sum force was proposed to improve the oscillation. The simulation results show that the improved optimization algorithm in this paper effectively makes up for the shortcomings of the traditional artificial potential field method, and the designed 3D online path planning algorithm for the UAV is practical and feasible.

In the case of nonlinear systems with random bias, the Optimal Two-Stage Unscented Kalman Filter (OTSUKF) can obtain the optimal estimation of system state and bias. But it requires random bias to be accurately modeled, while it is always very difficult in actual situation because the aircraft is a typical nonlinear system. In this paper, the faults of the Inertial Measurement Unit (IMU) are treated as a random bias, and the random walk model is used to describe the fault. The accuracy of the random walk model depends on the degree of matching between the covariance of the random walk model and the actual situation. For the IMU fault diagnosis method based on OTSUKF, the covariance of the random walk model is assigned with a constant matrix, and the value of the matrix is initialized empirically. It is very difficult to select a matching matrix in practical applications. For this problem, in this paper, the covariance matrix of the random walk model is adaptively adjusted online based on the innovation covariance matching technique, and an adaptive Two-Stage Unscented Kalman Filter (ATSUKF) is proposed to solve the fault diagnosis problem of the IMU. The simulation experiment compares the IMU fault diagnosis performance of OTSUKF and ATSUKF, and verifies the effectiveness of the proposed adaptive method.

Aiming at the requirement of attitude information module with high precision, small size and low power consumption for the control of miniature UAV, a practical attitude estimation algorithm based on the micro-electro-mechanical sensor is proposed in this paper, which realizes the accurate estimation of the attitude of the UAV under the condition of low acceleration. A low-cost MEMS gyroscope, accelerometer, and magnetometer are used in the system. The Euler angle is obtained by the state observer method based on Direction Cosine Matrix (DCM) which can be got by fusing the sensor data. Firstly, based on the basic idea of TRIAD algorithm, a method to determine the attitude rotation matrix by accelerometer and magnetometric measurement is proposed. Compared with the traditional method, this method does not have to calculate the inverse of the matrix. Secondly, a state observer is intended to estimate the attitude of the system. The state observer doesn't have to observe the bias of the gyroscope, but still ensures the convergence of the Euler angle. Finally, the simulation based on the actual sampling data of the MEMS sensor shows that the output of the state observer designed in this paper still has high accuracy and good dynamic characteristics under the condition of gyroscope noise and bias.

It is crucial to develop an effective controller for the multi-UAV system to contribute to the frontier fields, such as the electronic warfare. To address the dilemma of the cooperative formation with the high dimensional data, a deep neural network(NN) controller is developed in this paper. Firstly, a deep NN model is used to tune parameters of PID controller online. Secondly, this paper introduces an improved deep NN model integrating the momentum to improve the performance of the classical NN model and satisfy the condition for the real time cooperative formation. Lastly, the cooperative formation task is achieved by extending the proposed cooperative controller with an improved NN to the complex multi-UAV system. The simulation result of multi-UAV formation demonstrates the effectiveness of the proposed method, which achieves a faster formation than competitors.

To intercept a higher-speed target in the terminal guidance phase, this paper proposes a generalized relative biased proportional navigation (BPN) law. In order to enlarge the capture domain of the classical proportional navigation (PN) law and make full use of the maneuverability of a missile, the paper designs time-varying navigation coefficients; thus the modified PN guidance law integrates the advantages of the PN guidance law with those of the retro-PN guidance law. In order to intercept high-speed targets with impact angle constraints, the relative BPN law is introduced, and the impact angle is achieved by controlling the relative flight-path angle. In order to improve the performance of the guidance law for intercepting higher-speed maneuvering targets, some compensation measures are designed for guidance commands. Extensive simulations are conducted to verify the design features of the proportional navigation law.

With the development of the more/All electrical aircraft technology, the dual active bridge converter has been applied to the energy storage device to realize the bidirectional power flow in aircraft electrical system. The power loss of power device in DAB converter affects the operational life of the device and the reliability of the converter. So it is an important performance index to keep the temperature balance for power device in DAB converter. In this paper, the operational mode of dual active bridge bidirectional DC-DC converter in extended-phase-shift (EPS) control is analyzed and verified by experiment, find the reasons for difficult to achieve soft-switching under light load conditions, then proposes a novel thermal balance phase-shift control strategy on the basis of EPS. Experimental methods in this paper are alternation control mode and temperature feedback control mode. The thermal image and temperature was analyzed. The efficiency curve was plotted. The switching waveform was observed. the thermal balance was achieved to verify the effectiveness. and finally achieves the goal for improving the converter efficiency, reduces the devices heat stress, improves the reliability of the DAB converters and increases device lifetime.

A research method for multi-echelon inventory allocation of civil aircraft spare parts with lateral transshipments and maintenance ratio is proposed in this paper, and the maintenance rate is considered into the inventory model, aiming at the problem of multi-echelon inventory allocation with lateral transshipments for civil aircraft spare parts. Firstly, the principle of the multi-echelon inventory model with lateral transshipments and maintenance ratio is proposed. Then, by considering the fleet availability and the satisfaction ratio as the constraints, a mathematical model is built with the inventory system total cost as the optimization objective. Secondly, the procedure of solving multi-echelon inventory allocation model considering the influence of lateral transshipments and maintenance ratio is discussed based on the marginal analysis method. Finally, some components of Boeing 737 are selected as the research objects, the multi-echelon inventory allocation is investigated by considering lateral transshipments and maintenance ratio. The analysis results in this paper show the best number of multi echelon inventory allocation, the minimum inventory system total cost and the fleet availability are 1.205 million dollars and 0.9909 respectively. Comparing the traditional inventory model without considering lateral transshipments and maintenance ratio, and the model which only considers the maintenance ratio, the results indicate that the model offered in this paper could reduce the total cost of inventory system significantly, and provides theoretical support and method guidance for the accurate allocation of multi echelon inventory optimization for civil aircraft spare parts.

A quasi-zero-stiffness vibration isolation consists of a pair of oblique springs and a vertical spring, aiming at widening the vibration isolation region, is studied in this paper. The time delay linear displacement feedback control strategy is introduced to improve the performance of the isolator. The characteristics of dynamical response under harmonically forcing excitation is obtained by using averaging method. The force transmissibility of the control isolator is presented in this paper. The influence of the time delay linear displacement control on the force transmissibility is studied theoretically. The results show that the performance of the vibration isolation with time-delay control is better than the equivalent linear isolator in either low or high frequency region and the performance of controlled system is better than uncontrolled system.

The parameter identification of a non-cooperative target is a key problem of on-orbit servicing. Due to poor priori information about the motion and structure of non-cooperative targets, the traditional cooperative estimation architecture is inadequate. In addition, the existing method based on single observation spacecraft is difficult to ensure a good observation state for a long time. This paper proposes a method for observing and estimating attitude kinematic state of a non-cooperative space target based on multi-spacecrafts cooperative observation. The space target's 3D point cloud data is reconstructed based on the data with different viewpoints. The target's attitude change is calculated based on the 3D point cloud matching, and the kinematics information is estimated via EKF filtering. The simulation results demonstrate the efficiency of the proposed approach. As the proposed method does not require priori model, structural information or accurate motion information of the tumbling non-cooperative target, it can avoid the influence of occlusion or date missing in space observation, it is suitable for space on-orbit servicing with non-cooperative target in future.

Considering the precise landing demand for carrier-based aircraft flight control, this paper proposes an adaptive fuzzy landing control method for the strong time-varying, parameter uncertainty and various complex coupling in the actual state aircraft model. This method is applied to the flap channel to achieve direct lift control, and the fuzzy system is utilized to approximate the six-degree-of-freedom nonlinear system model of a carrier aircraft that is difficult to accurately describe, to achieve accurate tracking of the landing glideslope, and improve the landing accuracy. Lyapunov method was used to judge the stability of the adaptive fuzzy control algorithm. During the simulation, the airwake and deck motion disturbance were introduced to simulate the landing environment of the aircraft. The effectiveness of the landing control system was verified by the Matlab software. Monte-Carlo random test was utilized to carry out the landing point accuracy for the conventional control scheme and the adaptive fuzzy direct lift control scheme respectively. Through the response curve and landing point statistical results, it is confirmed that the direct lift control scheme has better control effect, and the landing precision has improvement compared with the conventional control scheme.

Walker constellation is the most effective constellation for global coverage and is often used for earth observation, navigation and internet communication. A scenario that several faulted satellites in a Walker constellation lead to its performance degradation can be quickly repaired to a certain extent by reconstructing the on-orbit satellite configuration. Different from the classical strategies such as adjusting the phase of the adjacent satellites, uniform the on-satellites' phase and adjusting the plane of the adjacent satellites, this paper proposes a bionic reconstruction method which uses the elastic mechanics method of thin film plate to generate the satellite maneuver strategy in the constellation reconstruction process, minimizes the performance degradation between the repaired configuration and the previous configuration. Thus, the maneuver strategy of each satellite can be calculated in reversely. The simulation example shows that the maneuver strategy by the bionic reconstruction method is more harmonious and natural than the classical strategies.

Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterprises continues to increase, distributed databases have gradually replaced stand-alone databases and become the mainstream of applications. However, the current business supported by distributed databases is mainly based on OLTP applications, lacking OLAP implementation. This paper proposes an implementation method of HTAP for distributed database CBase, which provides an implementation method of OLAP analysis for CBase, and can easily deal with data analysis of large amounts of data.

Spaceborne SAR(synthetic aperture radar) imaging requires real-time processing of enormous amount of input data with limited power consumption. Designing advanced heterogeneous array processors is an effective way to meet the requirements of power constraints and real-time processing of application systems. To design an efficient SAR imaging processor, the on-chip data organization structure and access strategy are of critical importance. Taking the typical SAR imaging algorithm-chirp scaling algorithm-as the targeted algorithm, this paper analyzes the characteristics of each calculation stage engaged in the SAR imaging process, and extracts the data flow model of SAR imaging, and proposes a storage strategy of cross-region cross-placement and data sorting synchronization execution to ensure FFT/IFFT calculation pipelining parallel operation. The memory wall problem can be alleviated through on-chip multi-level data buffer structure, ensuring the sufficient data providing of the imaging calculation pipeline. Based on this memory organization and access strategy, the SAR imaging pipeline process that effectively supports FFT/IFFT and phase compensation operations is therefore optimized. The processor based on this storage strategy can realize the throughput of up to 115.2 GOPS, and the energy efficiency of up to 254 GOPS/W can be achieved by implementing 65 nm technology. Compared with conventional CPU+GPU acceleration solutions, the performance to power consumption ratio is increased by 63.4 times. The proposed architecture can not only improve the real-time performance, but also reduces the design complexity of the SAR imaging system, which facilitates excellent performance in tailoring and scalability, satisfying the practical needs of different SAR imaging platforms.

Distributed electric propulsion technology brings new ideas to the design of unmanned aerial vehicle(UAV), such as improving aerodynamic efficiency and propulsive efficiency, and new concept of vertical/short takeoff and landing configurations. However, compared with conventional UAV, the propulsion system of distributed electric propulsion UAV is more complex, which brings difficulties and challenges to the design of distributed electric propulsion UAV. Based on its special aerodynamic/propulsive coupling characteristics, this paper studies the design method and process of primary parameters of distributed electric propulsion UAV. A short takeoff and landing UAV with distributed electric propulsion system is taken as an example for the conceptual design and primary parameter design, and the influence of design parameters on the takeoff mass and endurance is analyzed. Finally, the validity of the established design method is verified by the flight test of the prototype. Results indicate that the distributed electric propulsion system accounts for more than 20% of the takeoff mass; the electric ducted fan efficiency, mass specific power of the motor, mass specific power of the electronic speed controller and the resistivity of power wires are the most significant design parameters that affect the performance of the UAV; with the improvement of technologies, the takeoff mass is expected to be reduced by more than 20%, and the endurance is expected to be increased by more than three times.

During the blisk side milling, the blade is thin and the tool suspension length is large, which is easy to occur milling system chatter. The wavy surface left by chatter has great effect on the surface roughness and service performance of the aero-engine blisk. To accurately predict the stability of the blisk side milling, the influence of random variables on the machining stability was considered. In this paper, the chatter reliability model of the blisk side milling system was established using the first-order second-moment method. The model takes structural parameters and spindle speed as random variables and chatter frequency as intermediate variables. The chatter reliability model was used to draw the reliability lobe diagram, which can be used to divide the machining reliability area. The effectiveness of this method was verified by experiments and compared with Monte Carlo method. The validation results showed that the reliability lobe diagram can be used to determine the stability probability prediction of blisk side milling and can replace the traditional stability lobe diagram.

Aiming at the problem that the current WSoS mission modeling and analysis methods are difficult to describe the property of multi-state of each equipment system, combining with Petri net and Markov process, an O-PPN based mission thread modeling and analysis method is proposed in this paper. Based on the definition of WSoS, the mission of WSoS is formally described. To improve the traditional Petri net, an operation performance Petri net (O-PPN) is constructed, in order to meet the modeling needs of the general mission thread of the WSoS; and aiming at the problems of the performance degradation of the equipment system and the possible "ahead of time" state, the performance degradation model of the equipment system based on Markov is constructed. The corresponding state probability set is obtained by inputting the reliability parameters of each equipment system. And according to the requirements of each operation in the mission thread for the performance level of each equipment system and combined with the mission success and failure criteria of the combat task and operation, the mission success probability of the whole WSoS is calculated. Finally, the feasibility of the proposed method is verified by the simulation of the case.

Aircraft lug joint is the key part of load transfer. In order to improve the safety of lug joint, on the premise of meeting the design requirements of static strength and fatigue, the composite connection lug structure design technology of different metal materials is proposed in this paper. Firstly, the damage safety design and life reliability analysis of the lug structure are studied theoretically. Secondly, based on the concept of damage safety design and the design principle of deformation coordination, the design method of composite connection lug with deformation coordination is proposed, and the thickness ratio of single ear is 0.8:1:0.8. Finally, the reliability of the composite lug is analyzed. The results show that the structural design scheme of aluminum-titanium composite ear piece can meet the requirements of static strength and damage tolerance, and compared with the conventional ear structure, the failure probability of structure mission life is greatly reduced when the weight of the composite connection lug is only increased by 4.9%. The proposed method can effectively guide the structural design of composite ear piece.

The feature image code represented by the two-dimensional code is the key reference for global positioning in the visual navigation of mobile robots. Although reducing the acquired low-resolution image helps to reduce the real-time performance of the algorithm, the acquired feature image is more susceptible to motion blur-based interference and affects the accuracy of recognition, which causes the positioning failure of the whole multi-intelligence, in which the body control system is invalid. In this paper, an optimized low-resolution feature image code recognition method is proposed. In the preprocessing part, the characteristic image is converted into the characteristic signal matrix of Hu invariant moments, and then the characteristic image is added to the characteristic signal matrix as a characteristic component, and then the Hu-DBN neural network signal classifier is used to construct the signal matrix so as to achieve accurate recognition of low-resolution custom image signature images under high motion tolerance conditions. It not only avoids the problem of classical pattern recognition relying on model experience and poor adaptability of the scene, but also avoids the problem of high computational complexity and recognition efficiency of directly deep learning methods such as YOLO. The deployment of the mobile robot instance deployment test shows that the average recognition rate is of 96.3% at a resolution of 640×480@Pixs and motion speed of 0.5 m/s, which proves the effectiveness of the present method.

In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.

The method of using unmanned aerial vehicle (UAV) to obtain aerial image information of target scene has the characteristics of wide coverage, strong mobility and high efficiency, which is widely used in urban traffic monitoring, vehicle detection, oil pipeline inspection, regional survey and other aspects. Aiming at the difficulties of the object to be detected in the process of aerial image object detection, such as multiple orientations, small image pixel size and UAV body vibration interference, a novel aerial image object detection model based on the rotation-invariant deep denoising auto encoder is proposed in this paper. Firstly, the interest region of the aerial image is extracted by the selective search method, and the radial gradient of interest region is calculated. Then, the rotation invariant feature descriptor is obtained from the radial gradient feature, and the noise in the original data is filtered out by the deep denoising automatic encoder and the deep feature of the feature descriptors is extracted. Finally, the experimental results show that this method can achieve high accuracy for aerial image target detection and has good rotation invariance.

The initial satellite telemetry data acquired by ground stations usually contain noise and outlier interference. In order to ensure the accurate analysis of satellite status, the telemetry data need to be filtered. In this paper, a sliding window optimal tracking differentiator filtering (SWOTDF) method for satellite telemetry data is proposed. Aiming at the problem of parameter selection during the filtering of the optimal tracking differentiator, the amplitude-frequency characteristics of the maximum tracking differentiator are analyzed by sine sweep frequency method, and the mapping relationship between tracking factors and filtering effects is established. On this basis, the telemetry data are divided by sliding windows, and the relationship between local stability of data in each window and tracking factors is further analyzed. The calculation method of local data tracking factor is given to realize dynamic optimal tracking differentiator filtering of telemetry data in each window. Experimental results show that the SWOTDF method can effectively avoid the limitations of traditional digital filters in processing nonlinear telemetry data, and can effectively filter out noise and outliers in satellite telemetry data.

In this paper, the full strap-down seeker of rotating bomb is taken as the research object, and the method of extracting the LOS (line-of-sight) angle and angular rate of the full strap-down seeker of the rotating bomb is studied. The structure of the full strap-down seeker is quite different from that of the conventional rate gyro seeker. The measurement system of full strap-down seeker is fixed to the missile, the seeker can only obtain the measurement information in the projectile coordinate system, and the measurement information is coupled with the body posture information, so it cannot be directly used for the control guidance of the rotating projectile. First, based on the conversion relationship between coordinate systems, the mathematical model of the inertial LOS angle of the rotating bomb is established, and the mathematical model of the extraction of the inertial LOS angle and angular rate of the rotating bomb is further established. Then, the Kalman filter is designed by using the unscented Kalman filter method (UKF), and the extracted LOS angle containing noise information is filtered. Finally, the mathematical simulation is carried out to verify the validity of the mathematical model of LOS angle and angular rate extraction. Compared with the Extended Kalman filter method (EKF), the UKF has a higher accuracy for estimating the navigation information of the full strap-down rotating projectile.

Currently developed underwater gliders can be roughly divided into the two types:traditional configuration and unconventional configuration. As a type of underwater gliders with unconventional configuration, a blended-wing-body (BWB) underwater glider has better fluid dynamic performances because of its unique shape. However, it is difficult to design the shape of the BWB underwater glider that has excellent hydrodynamic performances. Therefore, it is of great significance to optimize its shape, which this paper carries out by using the free-form deformation (FFD). The complete and automatic shape optimization framework is established by jointly using FFD parameterization method, CFD solver, optimization algorithm and mesh deformation method. The framework is used to optimize the shape of a BWB underwater glider. The average drag coefficient of the BWB underwater glider during its sinking and floating in one working period is used as the objective function to optimize its shape, with the volume constraints considered. The optimization results show that the gliding performance of the BWB underwater glider is remarkably enhanced.

Under the modern high-tech condition, the demand of air combat has been stricter on the combat performance and the integration of fighter, which impels the application of integrated vehicle management technology and makes it become the core technology of the advanced fighter about the mission management and vehicle management. From an overview of tactical flight management system's technical background and the state of development, this paper systematically introduces the issues, including the development process & history, architecture framework of the integrated vehicle management system (IVMS) which divided into perception layers, decision layer and execution layer, and function system architecture and software system architecture. Through a comprehensive analysis for the functions of each level, comprehensively expounds the basic function and key technology of IVMS which included situation awareness and assessment, mission path planning, integrated navigation, automatic attack guidance, health management and prognostic and intelligent pilot-vehicle interface, and the future development directions are also discussed.

Feature selection is an essential process in the identification task because the irrelevant and redundant features contained in the unselected feature set can reduce both the performance and efficiency of recognition. However, when identifying the underwater targets based on their radiated noise, the diversity of targets, and the complexity of underwater acoustic channels introduce various complex relationships among the extracted acoustic features. For this problem, this paper employs the normalized maximum information coefficient (NMIC) to measure the correlations between features and categories and the redundancy among different features and further proposes an NMIC based feature selection method (NMIC-FS). Then, on the real-world dataset, the average classification accuracy estimated by models such as random forest and support vector machine is used to evaluate the performance of the NMIC-FS. The analysis results show that the feature subset obtained by NMIC-FS can achieve higher classification accuracy in a shorter time than that without selection. Compared with correlation-based feature selection, laplacian score, and lasso methods, the NMIC-FS improves the classification accuracy faster in the process of feature selection and requires the least acoustic features to obtain classification accuracy comparable to that of the full feature set.

Discretization of multidimensional attributes can improve the training speed and accuracy of machine learning algorithm. At present, the discretization algorithms perform at a lower level, and most of them are single attribute discretization algorithm, ignoring the potential association between attributes. Based on this, we proposed a discretization algorithm based on forest optimization and rough set (FORDA) in this paper. To solve the problem of discretization of multi-dimensional attributes, the algorithm designs the appropriate value function according to the variable precision rough set theory, and then constructs the forest optimization network and iteratively searches for the optimal subset of breakpoints. The experimental results on the UCI datasets show that:compared with the current mainstream discretization algorithms, the algorithm can avoid local optimization, significantly improve the classification accuracy of the SVM classifier, and its discretization performance is better, which verifies the effectiveness of the algorithm.

When the target is tracked based on the current traditional reference point guidance method by standoff mode, if the angle between the relative speed of the UAV and the target and the tangential direction of the corresponding point on the circular expected flight path of UAV is close to 90 degrees, and UAV is close to the desired path, the efficiency of the UAV converging to the circular desired path is not high enough. In this paper, the small angle hypothesis for reference point guidance method tracking desired circular path is studied. According to this, we designed a maneuvering entry guiding strategy for UAV standoff tracking fixed/moving target based on reference point guidance method. Simulation results show effectiveness of the guidance strategy. UAV might quickly converge to the circular desired path.

The autonomous security situation awareness on industrial networks communication has been a critical subject for industrial networks security analysis. In this paper, a CNN-based feature mining method for networks communication dataflow was proposed to intrusion detect industrial networks to extract security situation awareness. Specifically, a normalization technique uniforming different sorts of networks dataflow features was designed for dataflow features fusion in the proposed feature mining method. The proposed methods were used to detect the security situation of traditional IT networks and industrial control networks. Experiment results showed that the proposed feature analysis method had good transferability in the two network data, and the accuracy rate of network anomaly detection was ideal and had higher stability.

This paper studies helicopter optimal landing and control procedure after tail rotor control failure (TRCF) in different collective pitch. The optimal control problem of landing after tail rotor control failure was solved numerically by direct multiple shooting method and sequential quadratic programming. A sample helicopter optimal landing procedures after tail rotor control failure in large collective pitch and small collective pitch were investigated respectively. As can be seen from the results, when the tail rotor is stuck at large collective pitch, the tail rotor provides a large lateral force, which facilitates landing with small forward speed and descent rate in a large power state. The pilot can maintain stability of heading by side slipping. When the tail rotor is stuck at small collective pitch, the tail rotor provides a small lateral force, which is favorable for flying near economic speed, but difficult for a safe landing. A normal landing maneuver will cause a high yaw rate at touchdown, which is dangerous. Therefore, autorotation is preferred during touchdown because the landing is more secure with small yaw rate. The trajectory optimization method of helicopter safe landing after tail rotor control failure can provide a reference for flight test.

In order to resolve the problem of joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO array, a dimensional reduced-Capon method based on Taylor series expansion and signal subspace is proposed in this paper. Firstly, the Taylor series expansion of the steering vector is used to reduce the two-dimensional (2D) spectrum peak searching of Capon method to one-dimensional searching. Then, the DOD estimator can be achieved via Lagrange multiplier by one-dimension search. Finally, the steering vector of DOA corresponding to the DOD estimator is achieved and the DOA can be estimated. Hence, the estimated DOD and DOA are obtained automatically paired. And also, the proposed method can avoid the high computational complexity of MIMO Capon method. Simulation results are presented to illustrate the effectiveness of the proposed method.

The construction spectrum(C-spectrum) is often used to exploit the network reliability and importance measure. It depends only on the network structure and hence called structure invariant. Importance measure can be used to quantify the criticality of edge within a network. This paper aim at generalizing the traditional permutation importance measure to accommodate the case of K-terminal network in which all the edges fail with independent and equal probability. A concept for mixture C-spectrum is introduced to evaluate the permutation importance measure of edges. It is proved that the rankings according to the permutation importance measure depend only on the network structure through the mixture C-spectrum when the network has special structure or the reliability of edge is sufficient large. Finally, numerical experiment show that the Monte Carlo algorithm based on the mixture C-spectrum can be efficiently used to evaluate the permutation importance measure.

In order to guarantee the QoS requirements of multiple services in airborne all-domain heterogeneous and flexible networks, we propose a novel multi-priority and multi-path based QoS routing (MP2R) protocol in this paper. In the protocol, in terms of the route effectiveness and reliability, the route cost penalty function is constructed based on the multi-priority M/M/1 queueingqueuing system with the preemptive-resume policy. The minimum value of the function is derived through the optimization theory, and the optimum routing solution is acquired. The simulation results show that the MP2R protocol not only has the capabilities of differentiation services for different kinds of traffic and QoS provision, but also can utilize the network resource rationally, avoid congestion, achieve the load balancing, and meet the requirements of airborne all-domain heterogeneous and flexible networks effectively.

Distributed sources can be regarded as an assembly of point sources within a spatial distribution. In this paper, we explore the estimation of the two-dimensional incoherently distributed sources using double L-shape arrays. The rotational invariance properties of the nominal elevation and nominal elevation are firstly obtained by taking first-order Taylor series expansions with regard to the generalized steering vectors of two pairs of parallel subarrays. The rotation operators can be solved based on signal subspace. Then the nominal elevation and nominal elevation can be obtained from parameters matching method. Estimation of direction of arrival can be used in multi-source scenario and needn't peak-finding search. Lastly the angular spreads can be solved through two-dimensional Capon search based on nominal angles. The simulation experiments show that the proposed method has good performance on the estimation of two-dimensional incoherently distributed sources. Investigating different experimental conditions, sources with different angular spreads, simulations are conducted to validate better estimation accuracy of the proposed method.

Air cushion furnace is widely used in the heat treatment process of aluminum strip, copper strip and silicon steel, and the double slot nozzle is the core part of the air cushion furnace device. Studying the distribution characteristics of the surface pressure coefficient of the strip during the suspension process could provide important theoretical references for the high-efficiency and high-value production of the air-cushion furnace. In this paper, the distribution of pressure coefficients is studied under the conditions of Re=48 194~12 048, high H/D=1~3, spacing L/D=17.2 and sinusoidal amplitude A=0~30 mm. The results show that with the decrease of L/D, the position of the main stop point moves to the center line of the nozzle, and the value of the second stop point increases gradually, and with the increase of the sinusoidal amplitude A, the position of the main stop point moves gradually to x/D=0. The pressure coefficient Cp decreases with the increase of sinusoidal amplitude A, the pressure coefficient Cp decreases with the increase of H/D, and the difference between the pressure coefficient at the stationary point of the double-slot nozzle and the pressure coefficient at the non-stationary point increases with the increase of H/D. This study provides an important theoretical basis for the design of double slot nozzles in air cushion furnace.

In this paper, a practical improved dynamic inverse control method is proposed to solve the large control error and control hysteresis of post stall maneuver under unsteady aerodynamics. Firstly, depending on the wind tunnel experimental data of the advanced fighter aircraft model under biaxial coupled large oscillation, an accurate unsteady aerodynamic model is established by using the improved extreme learning machine (ELM) method. Secondly, in terms of the time scale separation, the control error caused by unsteady aerodynamic is reduced by adding integral in the fast loop, and the control delay caused by unsteady aerodynamic is eliminated by applying the lag correction link in the slower loop. The deflections of conventional aerodynamic surface and thrust vector are allocated by the daisy chain method. Finally, the formula of the reduced frequency, which is the key factor in the unsteady aerodynamic modelling process, is derived by analyzing the wind tunnel data. The effectiveness of the present method for the scaled model is verified by herbst post stall maneuver. The present work provides a practical and reliable way for the flight test of post stall maneuver.

Aiming at the problem of image distortion caused by light refraction during underwater imaging, and the conversion error caused by existing image conversion algorithms due to neglecting the secondary refraction of light, an underwater image conversion algorithm based on the light refraction model is proposed in this paper. The algorithm firstly obtains the pixel information of the underwater image, then calculates the corresponding coordinate information of the pixel points in the equivalent air image through the mapping relationship, and finally obtains the equivalent air image through image interpolation. Experimental results shows, compared with the existing image conversion algorithms, the proposed algorithm reduces the average error ofudirection from 2.289 5 to 1.213 3, which is a decrease of 47.01%. The average error ofvdirection is reduced from 3.252 5 to 1.526 3, which is a decrease of 53.07%. At the same time, the mean value of ranging error was reduced from 58.83 mm to 28.88 mm, a decrease of 50.91%。

The random data loss that occurs during the communication process of multi-agent systems will lead to the dynamic switching of network topology. The time-varying communication delay will cause the agents to update their control inputs irregularly and asynchronously. In this paper, we deal with the cooperative output regulation problem of multi-agent systems with both random data loss and time-varying communication delay. By applying a queuing mechanism, the multi-agent systems with time-varying communication delay can be modeled as the multi-agent systems with constant communication delay and stochastic packet dropout. Based on the queuing mechanism, we designed the distributed state observers of the leader and the followers. Then, a new distributed measurement output feedback control algorithm is proposed. Under some standard assumptions, the proposed algorithm can solve the cooperative output regulation problem of multi-agent systems with both stochastic packet dropout and time-varying communication delay for unstable or stable exosystem. Then, the corresponding conditions for solving the cooperative output regulation problem are given, respectively. The simulation results show that the measurement output feedback control algorithm based on queue mechanism can effectively solve the cooperative output regulation problem of multi agent systems with time-varying delay under dynamic network topology.

A novel kind of underwater transducer with trapezoidal matching layer manufactured by 1-1-3 piezoelectric composite has been proposed to improve the underwater performance of high frequency transducer. In this paper, the finite element method has been used to analyze the influence of the matching layer on the electrical properties of the composite materials and vibration displacement of the radiation area. Two kinds of underwater transducers with and without matching layers have been fabricated. The experimental results show that the transmission voltage response of the underwater transducer with matching layer reaches 169.4 dB at 360 kHz, and the receiving voltage sensitivity reaches-190 dB, the bandwidth is up to 70 kHz and the maximum sound source level is 208 dB. Comparing with transducer without matching layer, the transmission voltage response is increased by 3.8 dB. Meanwhile the sound source level is increased by 6 dB. The received bandwidth is increased by 1.45 times.

The process of disc-mill cutter machining blisk-tunnel is a typical multi-input and multi-output system, therefore multi-objective optimization is applied to improve the process. In this paper, an integrated approach that Grey Relational Analysis(GRA)couples with Radial Basis Function (RBF) neural network and Firefly algorithm (FA) is used to solve the optimization problem. The aim is to satisfy the minimum cutting force and maximum material removal rate simultaneously by optimizing the cutting speed, feed rate per tooth and cutting height. The results for verifying experiment indicated that GRA-RBF-FA method can be applied to optimize the processing parameters of disc-mill cutter machining TC17 blisk-tunnel and the optimization results are superior to the GRA's.

Pressure pipes have broad applications in aviation, space flight, mechanical engineering, industrial and civil architecture etc. Instability destruction is their main failure mode. Firstly, in this paper, a complex fluid-solid coupling problem was simplified as a buckling problem of a pipe under two stresses which were along the pipe wall. The two stresses consisted of a compressive stress which was perpendicular to the pipe wall and a tangential stress which was parallel to the pipe wall. Secondly, the buckling performs of the pressured pipe were discussed by finite element analysis method under a working state and an off-working state, respectively. Some obtained conclusions were drawn as follows by the analysis in this paper.1). Provided the tangential stress is unchanged, by increasing compressive stress eigenvalue buckling critical load increases and nonlinear buckling critical load decreases.2). Provided the compressive stress is unchanged, when the direction of the tangential stress is same as that of the axial pressure, by increasing the absolute value of tangential stress the buckling critical load decreases; provided the compressive stress is unchanged, when the direction of the tangential stress is in the opposite direction of the axial pressure, by increasing the absolute value of tangential stress the buckling critical load increases.

Rapid evaluation of aerodynamic forces is a key technology in conceptual and preliminary performance assessment and design optimization for supersonic/hypersonic vehicles, which is expected to achieve a balance between accuracy and time. In this paper, the preliminary evaluation platform of aerodynamic forces is built based on the physical theories and engineering methods. This platform computes the local velocity vector by using the streamline tracing technology, and extracts the pressure and friction coefficients by calling methods in method database. Furthermore, an example based on HL-20 is brought out. A good agreement is obtained by comparing the calculated results via CFD with the experimental. Also, a good angle of attack compatibility of streamline tracing technology is concluded. This platform has a computation time less than that via CFD and an flight range greater than that via wind tunnel. Finally, the simple flight dynamics simulation is taken out and the synergetic process is verified.

Aim. MRO2 system is a data management platform. It has the ability to manage and store all kinds of data in the product's lifecycle, that is both the mass storage capacity and the scalability are required. For the existing big-data stores for MRO2 systemeither only focus on the storage problem, or only do the scalability issue. In this paper, a two-layer data management model is proposed, in which the top layer uses the memory storage for scalability and the bottom layer uses the distributed key-value storage for mass storage. By adding a middle layer of the key group between the application and the KV storage system, the keys for real-time processing are combined to cache in a node. It satisfies the characteristics of the real-time application and improves the dynamic scalability. The present protocol of the dynamic key groups for real-time distributed computation for MRO2 system is explained in detail. And then the protocol for creating and deleting key groups is introduced. The third topic is an implement of a big-data store for supporting MRO2 system. In this topic, the delay times for creating and deleting the dynamic transaction groups to estimation are used. Finally, the experiments to appraise the present method are done. The response time of the present method is quite efficient in comparison with the other methods to be used inbig data storage systems.

In underwater acoustic target recognition, the target signal is usually complex and the samples which are difficult to obtain also have some uncertain information. In order to effectively solve these problems, the evidence clustering recognition algorithm (TECRA) is presented. In this new method, the k-nearest neighbor are first determined by using the feature distance between the object and its neighbors in each class of the training set, and a reasonable initial basic belief assignments (bba's) for each target data are constructed by the improved k-nearest neighbor classification algorithm. Then the final global bba's of the target is obtained by optimizing the objective function of the algorithm. Finally the object can be recognized by the fusion result and the classification rule presented in the paper. Several experiments based on real underwater acoustic data sets are made to test the effectiveness of TECRA in comparison with some other methods. The results indicate that TECRA can effectively improve the recognition accuracy.