Aiming at the problems of difficult control and low landing accuracy in landing stage of shipboard aircrafts due to deck motion and ship wake,the direct lift control mode of “magic carpet” is proposed,which can improve the response speed and response bandwidth of flight path.The direct lift is generated co-ordinately by wing flap and elevator,in which the track is mainly controlled by direct lift control surface,while the flat tail assists the track control by maintaining angle of attack.The throttle is controlled by a constant-speed power compensation mode.Finally,simulation is made for comparing the “magic carpet” control law with traditional control law.The simulation results show that,under the interference of the deck motion and the wake of the ship,the trajectory of “magic carpet” control law is repaired more quickly,and the carrier landing accuracy is higher.

In radar ground target recognition,suitable feature selection algorithm contributes to selecting the features with high discrimination in the complex characteristic space for different types of target.On the basis of information theory and cooperative game theory,a novel feature selection algorithm is proposed based on the Owen value.The proposed feature selection algorithm can select the optimal feature subset,in which the features are of high relevance with its class,and have low redundancy and strong dependence with each other,thus can greatly improve the recognition performance of radar target.Experiments conducted on the real data show that:1) The average recognition rate of the proposed method is better than that using the two classical Filter algorithms;and 2) The proposed feature selection algorithm is robust against noise/clutter.

An adaptive control strategy based on Backstepping method is proposed for a class of nonlinear systems with parameter uncertainty and multiple external disturbances.The virtual control function is introduced in the control design,and the unknown boundary of external disturbance is estimated by using the improved adaptive law.By using the updated values of these unknown boundaries,a continuous adaptive robust state feedback controller is synthesized for the uncertain nonlinear system.At the same time,the Lyapunov stability theory is used to ensure the asymptotic stability of the nonlinear system.Finally,an simulation example shows the effectiveness of the proposed controller.

In the combat system of radar,the reasonable scheduling of beam resources has always been a key issue.In this paper,the covariance algorithm and the gray relational algorithm are combined to implement the beam resource allocation of the radar system.It can maximize the utilization of beam resources while satisfying the tracking accuracy of each target.To the multiple targets being tracked,the threat degree of each target is calculated by using gray relational algorithm,and the expected covariance is set according to the target's threat degree.The difference between the expected covariance and the actual covariance is calculated for each target,and all the differences are ranked from large to small.The target with the biggest difference is taken as the object for tracking.If all the targets reach the desired value,the radar will detect new targets.The proposed algorithm can realize the adaptive allocation of the radar system's beam resources.

In order to solve the problem that the actual heading of the UAV in the initial stage of target tracking is inconsistent with the expected direction provided by the guidance vector field,a method of heading error correction based on dynamic inversion is proposed.Firstly,on the basis of UAV kinematics model,Lyapunov vector field guidance method is used to provide the tracking guidance law for UAV in target tracking.Secondly,by constructing the dynamic inverse structure system of UAV heading error correction, the heading error is gradually corrected in the initial stage of UAV flight,and the convergence speed of heading error is controlled.Finally,the initial heading of UAV is classified according to its region,and convergence of heading feedback is proved.The convergence speed and flight path of UAV initial course under different control parameters are simulated and verified,and comparison analysis is made with the arc compensation method.The simulation results show that the dynamic inverse correction method is effective and practical.

In view of the singleness of the implemented task and the large interaction between the chain data in the autonomous formation flight of the UAV cluster,a multi-swarm center UAV cluster formation model based on distributed communication is proposed.Firstly,four flight rules are constructed based on the emerging calculation ideas to build a UAV cluster formation model.Then,the Lyapunov stability theory and the single UAV motion model are combined to design the speed controller independently for each UAV and prove the stability of the controller.The simulation results show that the UAVs with different properties can automatically classify,aggregate and form stable formations with different shapes to fly towards their respective target to execute the tasks under chaotic initial conditions and the flight efficiency of the UAV cluster is improved.

In the information description of intuitionistic fuzzy Bayesian network model to the network evidence node,there is only single membership degree or non-affiliation degree,and the hesitation degree is not taken into full consideration.To solve the problem,a threat assessment method based on dual hesitant fuzzy Bayesian network is proposed.Firstly,the intuitionistic fuzzy set is extended to the dual hesitant fuzzy set,makes the ambiguity and uncertainty of the node information more realistic,more comprehensive and accurate.Secondly,through the improved Dα operator,the dual hesitation of the hesitation of the hesitation is assigned to the membership degree and the non-affiliation degree,which is used as the input of the network evidence node.Then,analysis is made to the factors affecting the threat assessment and a Bayesian network model is established.Finally,based on the real-time battlefield data,the target threat degree is predicted and analyzed.The simulation results show that the method can accurately and effectively evaluate the threat of the enemy.

In view of the limitations of traditional air combat situation assessment method,which only considers the current static situation,is difficult to evaluate the whole air combat situation and has no predictability,a situation assessment method based on improved MGM(1,N) trajectory prediction is proposed.Firstly,according to the deficiency of MGM(1,N) prediction model which is difficult to describe the linear relationship between variables,an improved MGM(1,N) prediction model is established based on background value optimization.Then,the air combat situation preponderance model based on non-parametric method is established to quantitatively describe the influencing factors of air combat situation.The weight of each index is calculated by grey correlation degree,and the method for calculating the sequential weights of multiple moments are considered and established.The result of the simulation to actual air combat data shows that,the prediction accuracy of this method is better than that of the traditional MGM(1,N) method.The situation evaluation results can not only accurately reflect the battlefield situation,but also effectively reflect the changing tendency of air combat situation,with good predictability.

As the main air-to-ground attack weapon of armed helicopters, the airborne gun can effectively destroy ground armed personnel and light armored vehicles.The light armored vehicles have rapid speed and fine maneuverability.In order to improve the precision of airborne gun on attacking the ground target moving at a high speed, a new method for ground moving target attacking is proposed.By fitting the trajectory of the moving target on the ground,and with consideration of the influence of wind and other factors,this new method has the advantages of high accuracy and high calculation speed.

As a network link for information transmission and information sharing,the tactical data link can maximize the effectiveness of the tactical system and improve the operational effectiveness of the weapon platform.This paper studies fusion tracking based on data-link and airborne multiple sensors.According to the characteristics of data-link,radar and photoelectric sensor,the time is firstly registered by using filter extrapolation algorithm,and the centralized expanded-dimension fusion algorithm is used to implement target fusion tracking.Simulation is made for comparing the fusion filtering with separate data-link filtering and separate radar filtering.The results show that the fusion algorithm based on data-link and airborne multiple sensors have a better effect on target tracking.

The attitude tracking control problem of flexible satellites is studied,and a friction compensation sliding mode control algorithm for RBF network is designed.Firstly,the attitude model of flexible satellite attitude is derived based on the imaging mode of the flexible satellite attitude control system.Secondly, according to the tracking error motion model described by the error quaternion,the classical sliding mode control is introduced as the main control framework.Considering the suppression of the observed interference,an Extended State Observer (ESO) is added to observe the total disturbance of the system.Finally,the RBF network friction compensation system is used to approximately estimate the online switching term,and the smoothing of the switching gain in the sliding mode control law is realized,thus to reduce the system vibration.The convergence of the method is proved and deduced theoretically,and simulation is conducted for comparing it with the traditional adaptive method of RBF network approximation,which verifies the theoretical results.

There are already several documents on cooperative launch at home,and this paper focuses on this subject from a new perspective.The earliest public documents on cooperative launch from abroad are introduced,and the contents in these documents are analyzed.The following conclusions can be obtained from the analysis:1) Several technical details on cooperative launch may be omitted or fuzzified in those foreign documents;2) From the definition,it can be seen that the cooperative launch technology effectively enlarges the A pole of the missile rather than the F pole stated in the foreign documents;3) It is necessary to distinguish the technology of separate mutual support,which was put forward together with cooperative launch in those foreign documents,and attach importance to this technology,because it is more than a supporting technology of cooperative launch;4) Although the two tactics of cooperative launch and separate mutual support are devised to develop the inter-aircraft data link,we definitely should not ignore the fact that the guidance data link can be used for guidance by other aircrafts,which is not mentioned in the references;and 5) We should not only focus on the development background,application background and application scenario of cooperative launch,but also consider the potential changes that may occur due to condition change.

The angle measurement of Microwave Landing System (MLS) is studied,and a comprehensive method for improving the accuracy of angle measurement is proposed.In this method,symmetry of the to-and-fro scanning beams is used to suppress multipath interference,the peak detection algorithm based on intersection of straight lines of position is presented to improve angle measurement accuracy,and digital filtering is used to mitigate the impact of noise.The proposed method has been verified by the digital signal processing system based on TMS320F2812 DSP.The testing results show that the method has the advantages of high measurement accuracy,robustness to multipath interference and easy engineering implementation.

The research solves the gathering problem of close formation of multiple UAVs based on consistency theory control.The close gathering strategy can be divided into two steps: loose gathering and close gathering.Considering the problems that the UAVs should arrive at the target point simultaneously and keep a consensus flight state after completing the gathering,and also taking the distributed communication topology used between the UAVs into account,the consistency algorithms for different strategies are proposed.In loose gathering phase,the improved algorithm based on virtual leader is added.In close gathering phase,the consistency algorithm based on virtual leader is designed considering the delay and topology switching.The convergence of algorithm is proved theoretically.Simulation is made for the UAV gathering process.The result shows that: 1) The improved loose gathering algorithm can converge rapidly,and can realize the gathering of UAVs in finite time to some extent; and 2) The close gathering algorithm is validate while keeping the formation stable in conditions of delay and topology switching.

Aiming at the problems of relying on initial value and being easy to fall into local optimal solution when using conjugate gradient method to solve Gaussian process hyperparameters,this paper proposes an improved Particle Swarm Optimization (PSO) algorithm based on parametric nonlinear dynamic adjustment strategy and applies it for hyperparameter solving.Firstly,the parameter dynamic adjustment strategy is proposed,and different parameters are adopted for different search stages.Then,according to the concentration adjustment mechanism of immune thought,the global search ability of the algorithm is improved.The simulation results show that:1) The proposed algorithm can quickly converge to the optimal value of the function in the optimal solution;and 2) At the same time,the algorithm is effective for solving the Gaussian process hyperparameters,which can guarantee the accuracy for the establishment of later prediction model.

With the development of space remote sensing technology,the need for rapid detection and identification of marine vessels is growing.This paper proposes a ship target detection method combined with high- and low-resolution remote sensing images based on deep learning.Firstly,the YOLO v3 model is used to quickly screen out the target ships in wide-range,low-resolution satellite remote sensing images.To the high-resolution satellite remote sensing image information,a RetinaNet model based on attention mechanism is proposed for exact matching and classification of the target ship.Simulation experiments show that the improved RetinaNet model has a good effect in target detection,and the use of the satellites with two kinds of resolution for collaborative work can greatly improve the working efficiency.

In the field of helicopter control,an attitude composite controller based on nonlinear active disturbance rejection and non-singular terminal sliding mode method is designed to solve the problem that the helicopter is susceptible to system uncertainty and most controllers are highly model-dependent.Firstly,the full nonlinear dynamics equation of helicopter is established to obtain each of the attitude channel models with disturbance term.Secondly,the framework of Active Disturbance Rejection Control (ADRC) is adopted to design the nonlinear extended state observer and the global fast non-singular terminal Sliding Mode Controller (SMC),which can reduce the dependence on the model and realize the rapid response of the helicopter attitude with excellent disturbance rejection characteristics.The simulation results show that the proposed composite controller is effective in helicopter attitude tracking and disturbance rejection.

In order to achieve accurate measurement of close range targets and make full use of the excellent characteristics of Linear Frequency Modulated Continuous Wave (LFMCW),a millimeter wave LFMCW radar ranging system is designed based on ARM single chip.The system adopts the structure of “ARM+Phase-Locked Loop (PLL)+RF transceiver”,uses STM32F3 series ARM MCU as the main control chip for controlling the PLL and 77 GHz RF transceiver chip to complete the transmission and reception of the LFMCW signal,and uses the ARM internal ADC to perform IQ dual differential sampling on the intermediate frequency echo.The Fast Fourier Transform (FFT) is implemented inside the ARM to extract the target distance information.When the bandwidth of the modulated signal is 3.2 GHz and the period is 2 ms,the radar system can implement high-precision ranging to the targets within 2 m with an error less than 0.03 m.The experimental results show that the system can effectively detect short-range targets by transmitting broadband LFMCW signals,and has the advantages of high detection accuracy,strong versatility,good reliability and small volume.

In order to reduce the random errors in the MEMS gyroscope,an adaptive compensation method is proposed based on Empirical Mode Decomposition (EMD) and Variational Mode Decomposition (VMD).Firstly,the signal is decomposed into Multiple Intrinsic Mode Functions (IMFs) by EMD,and all the IMFs are divided into noise-dominated IMFs,noise-information mixed IMFs and information-dominated IMFs by using the similarity of probability density functions and the continuous mean square error.Then,the noise-information mixed IMFs are preliminarily de-noised by using the soft threshold interval method (SIT).The number of effective modes is taken as the number of Band-Limited Intrinsic Mode Functions (BLIMF) decomposed by VMD,and the preliminary denoised signal is further denoised by VMD.The correlation coefficient (CC) between each BLIMF and the original signal is used as the basis for whether discarding the mode as the noise mode or not.In order to validate the effectiveness of the proposed method,gyroscope signal under sectional uniform motion is collected and analyzed.The Root Mean Square Error (RMSE) of the denoised signal is 0.0422 of that of the original signal,which is 68.75% of that of EMD-SIT.

With the rapid development of tactical warfare in modern air combat,the new operational modes,represented by cluster operation,cooperative formation operation and saturated attacking,have put forward higher requirements for multi-target tracking and multi-target strike capability of air defense detection and air defense weapon system.To meet the requirements of the multi-target test,the target supply mode of the shooting range must be changed from single target supply mode to multi-target supply mode.The measurement and control system of one station and multiple drone aircrafts can remotely control multiple UAVs simultaneously and receive the telemetry data of multiple UAVs simultaneously,which greatly reduces the test cost and human and material resource consumption in the target supply mode with multiple drone aircrafts.Combined with the characteristics of the drone measurement and control system,a one-station, multi-drone measurement and control system is designed based on Time Division Duplex (TDD) mode and Time Division Multiple Access (TDMA) system under the condition that both airborne and ground stations are equipped with only one set of digital transmission radio.Experiments and flight tests show that the system design is scientific and feasible.

The visual landing procedure of shipboard aircraft is an important part for shipboard aircraft landing and it has strict requirements for the flight route.Based on MBSE method,the realization of visual landing route in the flight management system of shipboard aircraft is studied.Through requirement capture and analysis,the requirement model is established.By studying the relative motion relationship between the carrier and the aircraft during visual landing,the method for calculating the parameters of the visual landing route is presented,and analysis is made to the influence of different factors on the parameters.The aircraft dynamic and kinematics models are established.Finally,the different visual landing routes obtained are inserted into the flight management system for carrying out whole-process tracking and simulation of the three-dimensional trajectory.