Considering the calibrating requirements for the carrier landing system, we deduce a model for truth-value calculation of the angle and distance by using photoelectric calibration devices according to the coordinates transformation principle. The impact of the attitude changes of the ships and the measurement error of the equipments on the calibration accuracy is analyzed, and the error computational formula of the theoretical truth-value of the distance and angle of the device is deduced based on the error propagation theory. The numerical simulation results of Matlab verify that the proposed method meets the requirements of the calibration accuracy of the system.

The type of military UAV route planning has a close relationship with combat tasks, and the fixed route-planning methods are commonly used for long-distance reconnaissance tasks. Firstly, in order to quantitatively analyze the advantages and disadvantages of the quality of fixed route planning and detect the restraining factors of the route quality enhancement, the evaluation index and calculation model of the route quality are built, whose main parts are the completion of tasks, air safety and the perforance of the functions. Then, a new fixed route-planning method is proposed taking the loop route planning as an example. The battle dividing line is taken as the reference for route creating, including the three stages of route approaching, forward exploration and backward optimizing. Three kinds of results of route planning are obtained, i. e. , conventional route, radical route and conservative route, which could satisfy the needs for different battle backgrounds and tasks. The application of it in the operational simulation system has proved the effectiveness of the route planning method, and the quality evaluation of the route planning can clearly reflect the advantages and disadvantages of the routes, which can be used as a reference for the decision-making of the commander.

The traditional detection algorithms have poor adaptability and weak anti-interference ability, which are vulnerable to the interference of the noise of clouds or mutation in dim target detection, and may lead to inaccurate detection results. To solve the problem, this paper puts forward an algorithm for dim target detection in the air based on information fusion. First of all, the image down-sampling is carried out to reduce the processing data, and the image is pre-processed by two kinds of filtering methods. Then, the traditional centroid detection and saliency detection are fused by model superposition. Finally, with the detection method based on the inter-frame information correlation in this paper, the “target-like” point is eliminated, so as to further improve the accuracy of the detection algorithm for small targets, and enhance the anti-interference ability of the detection algorithm. The algorithm is verified by simulations and contrast experiments. The experimental results show that the proposed algorithm has better detection effects and a stronger anti-interference ability.

Considering the poor effect of current quad-rotor maneuvering control methods, we proposed a maneuvering motion control model based on Nonlinear Programming Genetic Algorithm (NPGA) to optimize the change rate of control variables. Firstly, the nonlinear dynamic equation of the quad-rotor was established. Secondly, the optimal control model of the maneuvering action was designed, and the control model of the somersault action was established taking the somersault action as an example. Then, the NPGA algorithm was used to solve the model, and the change rate sequence of the optimal control variable was obtained. Finally, the obtained control instruction sequence was imported to the quad-rotor mathematic model for simulation. The experimental results show that, the quad-rotor can complete the expected somersault action according to the control instruction sequence, and the maneuvering control model is effective and reliable.

To solve the problem of signal mixing of interference sources in the research of electromagnetic environmental effects of the equipment, the application of the blind-source-separation algorithm in the signal separation of mixed interference sources is discussed. Usually, the number of source signals should be estimated before using the blind-source-separation algorithm. In this paper, the dimensions of the initialized unmixed matrix are set based on the number of observed signals, and then the signals whose number is the same as that of observed signals can be obtained by separation. Through the correlation detection of the separated signals, the source signals are separated at last. Thus the prior estimation of the number of the source signals can be avoided. The feasibility of the proposed method is proved by the simulation experiment.

Aiming at the multi-target tracking with unknown clutter intensity, we proposed an Accelerated Expectation Maximization Probability Hypothesis Density (AEM-PHD) smoothing filter algorithm. Firstly, the model of clutter intensity was established, and the number of clutters was estimated according to clutter measurements. Then, the clutter density function was modeled by using Gaussian finite mixture model. AEM algorithm was proposed on the basis of EM algorithm, which was used for estimating the parameters of the Gaussian finite mixture model, and the clutter density function was obtained. Finally, the estimated clutter information was applied to multi-target tracking, and the target states were smoothed. Simulation results showed that, under clutter with unknown intensity, the proposed method can estimate clutter parameters accurately with high target tracking precision and accurate estimation of the target number.

As to the task allocation of multiple UAVs to multiple targets, an improved Adaptive Mutation Particle Swarm Optimization (AMPSO) algorithm was used to seek the optimal allocation scheme. The problem of task allocation would be relatively complex if it is related to league formation, and it is impossible to obtain the optimal solution effectively right now. The mechanism of allocation priority was used to deal with the uncertainty about the remaining resources of the league members. The mapping relation between the population particles and the task-allocation scheme was established. The simulation verified that: by using AMPSO algorithm, the optimal scheme can be quickly obtained for multi-UAV to multi-target task allocation.

In order to solve the inaccurate detecting problem in the long-time target tracking process, an AdaBoost multi-target detection algorithm is proposed based on superpixel segmentation and mixed weight. In the dynamic model, the mixed weight of AdaBoost algorithm is calculated out, the moving targets are detected, and the search area is determined, so as to improve the multi-target tracking and detecting capabilities. At the training stage, the superpixel segment is formed by using the SLIC segmentation and the Mean-Shift clustering, and the appearance model of the targets is built. At the tracking stage, the histogram and the confidence map of the template are created by using the superpixel feature pool, and the observation model and the motion model are built. The maximum posterior estimation is computed by using the particle filter and Bayes model, so as to realize the detection of sheltered moving targets. Experimental results show that: The proposed algorithm can effectively deal with the problems of varying-number, multi-target detecting and sheltered target detecting, and improve the real-time performance of the detection.

The problems of existing ways in identifying the key parameters of quad-rotor UAVs in the frequency domain are that it is hard to guarantee the bandwidth and accuracy at the same time and the identification process is inefficient. To solve these problems, an improved identification algorithm in the frequency domain was proposed. Firstly, the system model of the quad-rotor UAVs under hovering conditions was built. Then, based on the measured data obtained from the quad-rotor UAV platform, the frequency response was obtained by the composite-window disposal. Finally, a kind of pattern search algorithm, K-means clustering algorithm, was applied to the identification process, and the state-space model of the quad-rotor UAVs was obtained. The result showed that, the proposed method could balance the accuracy and complexity of the identification, and the frequency response of the identified model could fit the actual model of the quad-rotor UAVs well.

Based on the tightly-coupled SINS/GPS integrated navigation model, a delay spoofing signal was applied to the GPS, and the influence of the spoofing signal on the navigation parameters was observed. The simulation results showed that, the spoofing signal can affect the performance of tightly-coupled navigation, and it is necessary to detect in real time whether the GPS signal is spoofed or not. And then, the Chi-Square verification method was applied to the GPS spoofing recognition, and the residual Chi-Square verification method and the state Chi-Square verification method were simulated and analyzed. The simulation results showed that both the two Chi-Square verification methods can effectively identify the slope and the step-type GPS spoofing signals.

In simulation systems of radar and jammer established with conventional methods, the systems are often difficult to expand and have low efficiency due to the close coupling. An improved method is proposed to solve this problem from three aspects. Firstly, the signals transmitted from the radar and jammer, instead of the received signals, are used as the signals transferred between them. Secondly, the radar publishes the transmitting signals one period earlier than the event time stamp and postpones the processing of signal for one period. Thirdly, the signal descriptors, rather than the digital signals, are transferred between radar and jammer. An analysis is made to the parameter setting of simulation time step and lookahead time. The effectiveness of the improved method has been verified by simulation experiment. The proposed method decreases the information dependency between radar and jammer, reduces the times of data interaction between them, saves the network overhead and improves the expandability and efficiency of the simulation system.

To solve the problems of current methods in processing the uncertain nonlinear system with input constraints, such as complicated computation and the large errors, we proposed a step-by-step controller-designing method with finite-time stability. In the process of the control design, an unsaturated finite-time controller of the system was designed by adding a power integrator. Then, when the output of the controller exceeded the bounded upper-limit output, the functional knowledge was used to prove that the system was finite-time stable at that time and that the segment point was existed, and the selection rules of the corresponding parameters were given. As a result, the segment handling of the input-constraint problem was realized. Simulation results proved the effectiveness of the proposed method.

As the state dimension increases, the amount of calculation of Unscented Kalman Filter (UKF) algorithm increases rapidly. Besides, UKF is sensitive to the model error, and is not suitable for the system model whose noise doesn't subject to Gaussian distribution. In order to solve these problems, a new robust model-predictive UKF algorithm is proposed. This method incorporates the driving noise into the system state through the augmentation of state dimensions to add the system state information. The model error is restrained by Model Predictive Filter (MPF), and the robustness of the system is enhanced by the robust estimation. Thus the limitation of the traditional UKF algorithm which is sensitive to the model error is overcome. The proposed algorithm is applied to the new integrated SINS/BNTS/CNS navigation system for simulation, and is compared with the adaptive EKF algorithm and the robust adaptive UKF algorithm. The results show that the proposed algorithm can effectively restrain the attitude error and the velocity error, and its filtering capability is superior to that of the adaptive EKF and the robust adaptive UKF.

Nowadays, the electrical interconnection interface of the miniature unmanned aerial vehicles and the micro munitions are becoming miniaturized. Firstly, the development and evolution process of the Aircraft/store Electrical Interconnection System(AEIS) standard cluster is studied. Then the functions and requirements of the micro munitions interface signal set defined by AS5726A, including three kinds of signals, i. e. , the digital data bus, the discrete magnitude and the power, are expounded and analyzed. Furthermore, new features of micro munitions interface are researched, with comparison to MIL-STD-1760 interface and the miniature mission store interfaces. Finally, preliminary solutions are presented to solve such engineering application problems as the isolation network of the micro munitions interface, the mated status interface circuit and the control flow.

In the hose-type air-to-air refueling of Unmanned Aerial Vehicles ( UAVs), the bow wave of the receiver-aircraft has an important impact on the docking phase in the air. To meet the urgent requirements of bow-wave modeling, the velocity field data around the nose of the receiver-aircraft is obtained through Computational Fluid Dynamics ( CFD) simulation, based on which the change laws of velocity w让h the coordinated point are analyzed ? Based on the polynomial function, the regularities of distribution of the velocity along the %, y and z axis are fitted by using the least square method, the two-dimension analytical expression of the velocity on the intersecting surface is speculated according to the laws above, and the two- dimension fitting is done by using the polynomial. Then, the analytical expressions of the velocity and the three -dimensional position coordinates are solved by using the plane interpolation, which meets the precision requirements. Finally, the interpolating along the %, y and z axis are conducted respectively, and an area is selected for validation. The simulation results prove the effectiveness of this model, and show that the error is the minimum when interpolating along y axis.

In the hose-type air-to-air refueling of Unmanned Aerial Vehicles (UAVs)the bow wave of the receiver-aircraft has an important impact on the docking phase in the air.To meet the urgent requirements of bow-wave modelingthe velocity field data around the nose of the receiver-aircraft is obtained through Computational Fluid Dynamics (CFD) simulationbased on which the change laws of velocity with the coordinated point are analyzed.Based on the polynomial functionthe regularities of distribution of the velocity along the xy and z axis are fitted by using the least square methodthe two-dimension analytical expression of the velocity on the intersecting surface is speculated according to the laws aboveand the two-dimension fitting is done by using the polynomial.Thenthe analytical expressions of the velocity and the three-dimensional position coordinates are solved by using the plane interpolationwhich meets the precision requirements.Finallythe interpolating along the xy and z axis are conducted respectivelyand an area is selected for validation.The simulation results prove the effectiveness of this modeland show that the error is the minimum when interpolating along y axis.

An avionics software distributed testing platform based on Integrated Modular Avionics (IMA) is described. There are two types of the platform nodes, Server and Client. They are connected by using the Internet. Using Java technologies, Client constructs the submission of the test assignments and the result access. Coordinating w让h the target machine, Server can realize the dispatching management of the test assignments, the automatic compiling, linking, loading, and executing of the test programs, and the storage and collection of the test results. Resource sharing of the limited IMA hardware can be realized on this platform. The resources utilization rate and the testing efficiency are increased, and an effective and complete test of the configuration 让ems or the system of IMA software can be carried out. The testing platform supplies an effective solution to the long-distance testing of IMA avionics software.

An avionics software distributed testing platform based on Integrated Modular Avionics (IMA) is described.There are two types of the platform nodesServer and Client.They are connected by using the Internet.Using Java technologiesClient constructs the submission of the test assignments and the result access.Coordinating with the target machineServer can realize the dispatching management of the test assignmentsthe automatic compilinglinkingloadingand executing of the test programsand the storage and collection of the test results.Resource sharing of the limited IMA hardware can be realized on this platform.The resources utilization rate and the testing efficiency are increasedand an effective and complete test of the configuration items or the system of IMA software can be carried out.The testing platform supplies an effective solution to the long-distance testing of IMA avionics software.

In the quality condition assessment of equipment, a diamond frame model of the index system is put forward in order to shorten the time for the condition assessment aiming at missions while improving the quality management efficiency, combat preparation efficiency, and the level of combat readiness. Then, the characteristics of index convergence methods are analyzed. After that, the index optimization model is built and the quality condition is preliminarily assessed based on Principal Component Analysis ( PCA). Finally, a numerical example is given to verify the feasibility of the method. The analysis shows that: PCA has strong superiority in original index feature transformation and incremental index processing, which can improve the evaluation efficiency, and achieve optimized distinguishing of the state assessment indexes between normal state and state of combat preparation .

In the quality condition assessment of equipmenta diamond frame model of the index system is put forward in order to shorten the time for the condition assessment aiming at missions while improving the quality management efficiencycombat preparation efficiencyand the level of combat readiness.Thenthe characteristics of index convergence methods are analyzed.After thatthe index optimization model is built and the quality condition is preliminarily assessed based on Principal Component Analysis (PCA).Finallya numerical example is given to verify the feasibility of the method.The analysis shows that:PCA has strong superiority in original index feature transformation and incremental index processingwhich can improve the evaluation efficiencyand achieve optimized distinguishing of the state assessment indexes between normal state and state of combat preparation.

A new method of antenna aperture sharing for communication and radar system is presented on the basis of the sparse array antenna and staggered sub-array theory. An analysis is made to the key indicators of the radar and communications with a shared aperture. Two key indicators are chosen as optimization objectives: the maximum peak side-lobe level of the radar array pattern, and the communication channel capacity of Multiple-Input Multiple-Output (MIMO) communication system. The array element position optimization problem under given array element number and aperture size is put forward. After setting a preference degree, the optimization problem is transformed into a single-objective optimization problem, and a solving method based on genetic algorithm is given. Simulations and analysis prove the feasibility of the proposed optimization method, and the optimization curves for different preference degrees are given.(2015JM6306);武警工程大学基础研究项目(WJ20160132)

A new method of antenna aperture sharing for communication and radar system is presented on the basis of the sparse array antenna and staggered sub-array theory.An analysis is made to the key indicators of the radar and communications with a shared aperture.Two key indicators are chosen as optimization objectives:the maximum peak side-lobe level of the radar array patternand the communication channel capacity of Multiple-Input Multiple-Output (MIMO) communication system.The array element position optimization problem under given array element number and aperture size is put forward.After setting a preference degreethe optimization problem is transformed into a single-objective optimization problemand a solving method based on genetic algorithm is given.Simulations and analysis prove the feasibility of the proposed optimization method,and the optimization curves for different preference degrees are given.

In order to improve the proximity fuse target identification capacity of Anti-radiation Missile (ARM)a method of target identification based on the fusion of seeker information and laser proximity fuse information was proposed.An analysis was made to the consistency and conflict between the seeker information and the fuse information.Thenwith Dempster-Shafer(D-S) evidence theorythe seeker information was used together with the proximity fuse information to distinguish whether ARM would pass by above or contact the ground in front of the radar target.In the case of ARM passing by above the targetDempster rules were used to fuse the information from the passive seeker and the laser proximity fusethus to identify the real radar target.The research results show that:the D-S theory based information fusion method can discriminate efficaciously the missile-target intersection,and has high target recognition probability.

In order to improve the proximity fuse target identification capacity of Anti-radiation Missile (ARM), a method of target identification based on the fusion of seeker information and laser proximity fuse information was proposed. An analysis was made to the consistency and conflict between the seeker infonnation and the fuse infonnation. Then, with Dempster-Shafer ( D-S) evidence theory, the seeker information was used together with the proximity fuse information to distinguish whether ARM would pass by above or contact the ground in front of the radar target. In the case of ARM passing by above the target, Dempster rules were used to fuse the information from the passive seeker and the laser proximity fuse, thus to identify the real radar target. The research results show that: the D-S theory based information fusion method can discriminate efficaciously the missile-target intersection, and has high target recognition probability.

Considering the development of the cockpit human-computer interaction display technology and the development requirements of the cockpit display softwarewe proposed a development-and-verification method of the model-driven cockpit display software based on existing model development ideas.Hierarchical design was used in the software architecture to clearly separate the bottom driver from the model operation.The graphical modelingintegration and simulation of the software were realized in its full life circle to construct a reusableconfigurable and loosely-coupled software architectureso as to build an integrated model development and verification scheme.Through the practice of several software projectsand the comparison with the traditional “code-centric” development modelit has been proved that the proposed method can achieve high-quality development and verification of the display software more effectivelywhich can be used widely in the area of cockpit display.

Considering the development of the cockpit human-computer interaction display technology and the development requirements of the cockpit display software, we proposed a development-and-verification method of the model-driven cockpit display software based on existing model development ideas. Hierarchical design was used in the software arch lecture to clearly separate the bottom driver from the model operation. The graphical modeling, integration and simulation of the software were realized in its full life circle to construct a reusable, configurable and loosely-coupled software arch lecture, so as to build an integrated model development and verification scheme. Through the practice of several software projects, and the comparison with the traditional “ code-centric ” development model, it has been proved that the proposed method can achieve high-quality development and verification of the display software more effectively, which can be used widely in the area of cockpit display.

As a new achievement in the field of pattern recognition and machine learning, deep learning has broad prospects in the field of equipment fault diagnosis and health management. In this paper, a new method of fault diagnosis is proposed based on the characteristics of equipment fault big data and the advantages of deep learning theory. According to the principle of the denoising auto-encoder, the unsupervised feature learning of the training network is achieved, and the structuring of the whole neural network is completed. According to the type of fault, the output layer is determined. Using the BP algorithm, the supervised fine-tuning of the whole network is carried out, and thus the accuracy of fault classification is enhanced. By means of the above methods, the module-level fault diagnosis of a communications station is completed through experiments.

As a new achievement in the field of pattern recognition and machine learningdeep learning has broad prospects in the field of equipment fault diagnosis and health management.In this papera new method of fault diagnosis is proposed based on the characteristics of equipment fault big data and the advantages of deep learning theory.According to the principle of the denoising auto-encoderthe unsupervised feature learning of the training network is achievedand the structuring of the whole neural network is completed.According to the type of faultthe output layer is determined.Using the BP algorithmthe supervised fine-tuning of the whole network is carried outand thus the accuracy of fault classification is enhanced.By means of the above methodsthe module-level fault diagnosis of a communications station is completed through experiments.

To overcome the defects of the slow convergence speed and precocity of Discrete Differential Evolution (DDE)-MRR algorithm, a new DDE algorithm is proposed to solve the Cooperative Jamming Resource Allocation (CJRA) problem in electronic countermeasures. Firstly, the samples of the species group are reconstructed based on the inequality of D/N in CJRA problem. Secondly, the DE/best/1 strategy is used for mutation operation. Finally, the sample refreshment is implemented by greedy strategy. Three experiments are designed to analyze the convergence and numerical performance, and the results show that the proposed algorithm is more efficient and has practical value for solving the CJRA problem.