As a new navigation technology on civil aircrafts the Head-Up Display (HUD) plays an important role in such aspects as improving civil aviation transportation safety increasing flight punctuality rate and reducing operation cost.It is finding wider application in civil aviation transportation currently.The paper describes the working principles characteristics and functions of the HUD and presents an analysis to the benefits of using HUD on civil aircrafts.In addition the composition work principles and roles on civil aircrafts of Head-up Flight Guidance System (HFGS) and Enhanced Flight Vision System (EFVS) which are developed from HUD are also analyzed.

The ICD simulation module included in design of the general avionics integrated processing system was improved by taking the Matlab/Simulink co-simulation flight model as simulation stimuli and making it interactive with the integrated processor.This method has the following advantages:1) the physical quantities received by the integrated processor is from the identically simulated flight model which makes the results of actual significance; and 2) the calculation results can be compared with the output of simultaneously algorithm of Matlab/Simulink to ease the debugging and verifying of the processors functional designation.

The modeling technologies of information systems are the key technologies for military simulation system.The modeling technologies of communication system were studied and a new generalized data processing architecture was established which realized the normality and consistency of the battlefield information transmission processing storage and representation.An integrated modeling method was proposed for multi-resolution communication systems which could realize the modeling of communication networks link terminals communication nodes messaging communication plans in the military simulation.The algorithm has been applied in one naval military simulation system.The Simulation result shows that the model of communication system satisfies the operational requirements of the navy military simulation system and improves the authenticity and rationality of military simulation.

Based on the partition of the radiation area of the targets active radar the task model of the dual-aircraft is set up.By using fuzzy theory to make a generalization to the problems state space providing different transition functions according to different detecting stages and properly defining the action space and reward function the problem is formulated as a Markov Decision Process (MDP).Details of the fuzzy Q learning are presented.Simulation studies indicate that the proposed algorithm can provide adaptive strategies for the dual-aircraft to control their flight paths for non-maneuvering or maneuvering target detection.

This paper proposes a new algorithm based on gradient similarity (GSIM).By comparing the original images with the disturbed ones on their luminance contrast and resolution an image quality assessment index system was obtained and a modified GSIM was constructed.Comparison experiments show that the correlation prediction accuracy and consistency of the proposed metric are respectively 8.5% 7.6% and 4.8% higher than the PSNR index and are respectively 1.5% 3.8% and 2.6% higher than the SSIM index.In terms of experiment results, the new algorithm shows better feasibility comparing with MSE PSNR and SSIM image quality assessment methods.GSIM can overcome the influence of the difference in background intensity and it is efficacious to reflect the laser-dazzling effect.

Distributed cooperative control of multi-UAV system based on consensus theory has been used widely in UAV operations in which the consistent state and collaborative demand are achieved through consensus control algorithm.The mathematical description of gathering problem was established the problem was solved under decomposition strategy based on the method of coordination variables and coordination function.To realize optimization of cooperative control average consensus control algorithm was improved the expression of basic optimized consensus control algorithm was given by Hamilton-Jacobi-Bellman equation.The method got better in terms of dynamic response and optimal cost by introducing outdated state difference to control algorithm.The weighted matrix of the cost function was optimized by genetic algorithm the dynamic response and optimal cost was improved further.In the meanwhile the task execution time was shortened.Theoretical analysis and simulation results verify the feasibility and effectiveness of the method.

To improve the observability and locating precision of targets under electronic silence and tactic invisibility the optimal passive target tracking by multiple Unmanned Aerial Vehicles(UAVs) using Receding Horizon Optimization(RHO)was studied.With respect to optimal tracking by dual cooperative UAVs the spacial layout of the UAVs has great effect on the quality of passive target locating and tracking.To realize the optimal target tracking the RHO was used to obtain the optimal control solution and the headings of UAVs were adjusted in real time.Simulation results demonstrate the effectiveness of this method.

The Command and control (C2) system is essential for the implementation of Network-Centric-Warfare (NCW).Based on the research to the C2 system of the NCW we put forward a user-driven C2 system.The desire for greater agility driving the C2 system to rapid composability would be produced by end users rather than engineers.Then a battle model was founded and a detail flow chart was presented.Simulation and verification tests were made based on VStasker platform which provides a useful exploration for the realization of C2 system of the NCW.

To study the rapid penetration trajectory optimization of the hypersonic gliding aircraft considering multiple constrains a multi-phase optimization strategy was put forward based on hp adaptive pseudo-spectral method (hpAPM).The kinetic model of the hypersonic gliding aircraft was built up and the relationship between the lift coefficient and drag coefficient was fitted by using cubic spline interpolation.The models of no-fly zone and waypoint were found considering the constrains of dynamic press overload and heat flux.The principle of the hpAPM was expounded then an idea was proposed which taking the waypoints as the segment points of the trajectory.Simulation was made to the rapid penetration optimization trajectory of the hypersonic gliding aircraft with the objective of minimizing the arrival time.The results of the simulation indicated that the optimized trajectory using the multi-phase method can satisfy all of the constrains and meet the demand of rapid penetration.

There is a lot of uncertain information in target recognition which can be learned and reasoned by the use of BN.However the target recognition problem is of small sample size and there are often some errors due to lack of observational data during parameter learning.Therefore it is needed to introduce monotonic expertise.Focusing on the above problem the minimum unit algorithm was proposed.By use of the minimum unit the monotonic information was translated into priori information which could be directly used in parameter learning.Then based on the thinking of isotonic regression the parameter learning outcomes were optimized and the errors were eliminated.The relatively accurate network parameters were obtained.On the background of aerial target recognition the advantages of minimum unit algorithm compared with the minimum lower sets algorithm in accuracy and complexity are illustrated.

Aiming at the problems such as hysteresis and large calculation amount during path planning of moving targets we put forward a path planning method suitable for moving target in dynamic environments.First of all the Kalman filter algorithm was used to estimate the next position of the target.Then the D* algorithm was used for the path planning of the UAV by taking its current position as a starting point and the targets predicted position as a destination.In order to reduce the prediction error and ensure efficient route planning the dynamic observation periods were used.Since the Kalman filtering algorithm predicts the next state of UAV according to a recursive formula it doesnt need a lot of historical data(one at most).The prediction algorithm can not only reduce the calculation cost but also has strong real-time performance.The simulation results show that the algorithm can effectively shorten the distance and reduce the time needed for getting to the target position.

Aiming at the characteristics of infrared and visible images a novel fusion algorithm is proposed.Firstly the infrared image target region is extracted by using an improved region growing algorithm and is mapped to the visible image for local information fusion.Then the obtained fusion image is fused with the original infrared image by using a wavelet transform method based on edge enhancement to generate the final fusion image.Experimental results show that the fused image obtained by the proposed algorithm can highlight the infrared image target and reserve the clear background with good visual effects.

A method is proposed based on Cramér-Rao Low Bound for multi-sensor assignment of land-based air defense weapon systems.The Cramér-Rao low bound is introduced into the multi-sensor assignment model according to the characteristics of tracking.Therefore it needs not to choose target tracking algorithm during assignment and the model is made more close to actual situation by detailing the constraints.Then the Discrete Particle Swarm Optimization (DPSO) algorithm is used for calculation.The searching strategy the inertia weight and learning factor are improved to increase the accuracy and timeliness.Finally the application example is given and the results show the feasibility of this method and the validity of the improved DPSO algorithm.

The problem existed in the sensor management algorithm based on efficacy function was analyzed.By introducing the idea of centralized sequential Kalman Filter algorithm the covariance self-adaptive sensor management algorithm was applied to the calculation of efficacy function and the automatic updating of sensor-target pairing coefficient was realized.Combined with target priority a self-adaptive sensor allocation algorithm based on efficacy function was presented.The simulation showed that limited sensor resources can not only be distributed dynamically according to the expected precision but also be adjusted based on the target priority which makes the sensor allocation more reasonable and effective.

The luminance and line width of HUD symbols are important for the display performance of a HUD.The symbol characteristics determine the visibility and comfort level in observation under all-weather environment including high intensity light of the outside and dark of the night.The emission spectrum time characteristics luminance distribution line width and other characteristics of the HUD were analyzed and tested.The analysis shows that:1) The HUD symbol is 20 ms cycle pulsed light and the luminance presents Gaussian distribution; and 2) The symbol display luminance of a HUD varies with eye box position and field angle.This article provides a theoretical basis for improvement of the symbol characteristics and test of the symbol display luminance and line width.

To solve the problems of how to simplify the flow of mission planning and how to use tactics in the tactical mission planning system we proposed the concept of tactical templates.First the 6 DOF aircraft model was simplified to a model of 3 DOF and the basic action model was established.Taking the CLIBⅡ maneuvering for avoiding missile attacking as an example the data base of tactical template was designed.The influence diagram was introduced into CLIBⅡ planning and was simulated in Skyview.The results show that this concept is feasible but still needs further improvement and optimization.

To compromise the gap between the linear and nonlinear controllers we made a study on how to design a linear time varying controller using virtual reference feedback tuning strategy.To identify the unknown time varying parameter vectors in the two linear time varying controllers we added a new regularization term about the two unknown time varying parameter vectors to the formal cost function.So we could constrain the time varying parameter vectors jump property in virtue of this regularization term.An iterative separable nonlinear least-squares identification method was proposed to estimate the unknown time varying parameter vectors.Through iterating the global optimum of the time varying parameter vectors could be obtained.By means of the convex optimization theory we derived a critical value and take it as the starting point for finding the appropriate regularization coefficient.Finally the simulation example results verified the validity of the identification method.

A method based on ant colony optimization (ACO) was put forward for solving the problem of multiprocessor task scheduling in Vehicle Management System(VMS).Taking task number task grade task load and the relation between task and flight status into consideration the single processor risk coefficient function was designed.To balance the risk coefficients among the processors the objective function of task scheduling was established.Then the process of ACO for solving VMS task scheduling problem was given.A suboptimal scheduling scheme was obtained through simulation which verified the effectiveness of proposed method.

To solve the problem that the conventional phased array radar waveform takes relative large amount of resources of time we studied the working mode of phased array radar and the traditional timeshare transmitted pulses with different repetition periods.Based on which a search method was proposed based on a novel three-band search waveform the parameter selecting principles and signal forms in time domain and frequency domain were given.The analysis to an example shows that this kind of signal can effectively save the time and improve the search performance.Finally some of the outstanding issues are discussed.

Considering the scenario of air combat in which our two fighters detect and track one fighter coordinately we studied the decision-making of fighter maneuvering and radar activity during the detecting and tracking process based on Receding Horizon Control(RHC).A model of radar detection was established at first.The dynamic characteristics of Radar Cross Section(RCS)and the situation of dual-fighter detecting were studied.The model of dual-aircraft coordinated detecting and tracking was also built up.The function of coordinated detecting and tracking and the decision-making model of particle swarm optimization(PSO) were discussed.Simulation results show that the method can improve the capability of coordinated detecting and tracking effectively.

The association detection of dim small moving object in infrared image sequences was studied.Based on multi-hypothesis “K/N” regulation was adopted and credibility was introduced as noise probability distribution function.Multi-hypothesis and “K/N” regulation were organically combined which could overcome such problems of the former as large computation cost and inability for real-time processing.Credibility is helpful for improving the robustness of detection and the method has high detection probability even when there is noise pulse and cloud coverage.Theoretical analysis and real data test prove the feasibility and effectiveness of the method.

Aiming at the path planning problem of aerial vehicles with unexpected threats a virus-evolutionary particle swarm optimization algorithm (VEPSO) is proposed based on basic particle swarm algorithm.Combined with the theory of the biological virus-evolutionary system a biological virus mechanism is introduced in the basic particle swarm and two kinds of infection-based operation reverse substitution and incorporation operation are executed.The horizontal infection and vertical propagation of virus are used to maintain the individual diversity of the particles in path planning thus the local search capability of the algorithm is enhanced and the problems of local optimum and the slow convergence speed are solved.Simulation results show that the VEPSO algorithm is faster and more effective under the same path constraints.

LFM radar signal has coupling between the range and Doppler frequency.Based on the method of ladder wave jamming a method of random frequency-shift jamming was proposed.Random Doppler frequency-shift component was added in center frequency bandwidth of the positive and negative half and false targets could be generated randomly distributed around the real target.Random frequency-shifting technique has high randomness thus the radar cant obtain the position of the real target through frequency compensation of multi-false-target.The false-target generated by random frequency-shifting is partially adaptive to the radar thus the false-target range can be broadened.When the random frequency-shifting is close to radars center frequency the generated false-targets can even cover the real-target and achieve very good effect.