To improve the amplitude limiting efficiency of pendulous gyroscope north-seeker， an improved stepping iterative method is developed.Firstly， based on the introduction of motion equation for the sensitive part as well as the analysis of traditional stepping iterative method， different stepping iterative strategies are put forward according to the initial angular velocity when the sensitive part is put down.Then， the implementation principle of improved stepping iterative method is deduced in details.The feasibility of the proposed method is verified by numerical simulation.The numerical simulation examples show that when the initial angular velocity for putting down the sensitive part is within a certain range， the improved stepping iterative method has a higher limiting efficiency than the traditional one.The improved stepping iterative method can avoid the electromagnetic interference torque problem of the electromagnetic damping method while keeping the traditional stepping method′s advantages， and ensure the limiting reliability， thus providing a theoretical reference for shortening the north-seeking time.

To implement fast tracking control of large angle maneuvering of quadrotor UAVs， a nonsingular fast terminal sliding mode controller with more compact structure is designed on the SO(3)， which eliminates the singularity of Euler angle description and the problem of local linearization.The modified reaching law can accelerate the system approaching speed when far from the sliding state， and eliminate the chattering effectively.The stability of the controller is proved by using the Lyapunov stability theory.The simulation results show that the attitude is tracked quickly with high precision and low chattering.

In Direction-Finding (DF) crossing localization， the standard deviation of DF error is influenced by the nonuniform environment of the target area.To solve the problem， we proposed a Weighted Maximum Likelihood Estimation (WMLE) algorithm.In this algorithm， the effect of the target distance was introduced into Maximum Likelihood Estimation (MLE).A weighted vector was constructed to control and compensate for the standard deviation of the DF error increasing with the target distance.Theoretical analysis showed that the algorithm of WMLE can further improve the accuracy of the multi-station DF crossing localization.

The output frequency of signal in high-precision inertial navigation is limited， which is difficult to meet the accuracy requirement of control system for mobile satellite communications.To solve the problem， an attitude estimation algorithm with Sage-Husa adaptive Kalman filter based on data fitting interpolation is presented.It uses cubic spline interpolation to increase the output frequency of attitude information and increase the system estimation times per unit interval.The adaptive Kalman filter algorithm is used for constantly revising the filtering error and avoiding the possible filter divergence caused by system parameter mismatching.The experiment result shows that:1) Data fitting interpolation can make up for the deficiency of the high-precision inertial navigation in data update frequency， and the adaptive filtering can improve the robustness of the system to different environment;and 2) The attitude estimation and control accuracy of antenna beam attitude are improved significantly， which can satisfy the beam pointing needs of broadband mobile satellite communications.

Relative attitude estimation with the stereo vision method is an important part of the autonomous navigation system for Unmanned Aerial Vehicles (UAVs).An attitude measurement method for visual navigation of UAVs based on coplanarity constraint is proposed.Stereo vision is built for images taken by a single camera at different time， the attitude measurement model based on coplanarity condition is established in accordance with the geometric constraint relations of imaging lights of the camera to the same target at different time， and the precise relative attitude parameters are calculated out.Experimental results of the real UAV image data show that the proposed method has higher measurement accuracy and stronger anti-noise ability.Without the synchronization problem of photography in UAV attitude measurement with two cameras， it is of greater flexibility and practicality.

Under the circumstances of multi-target tracking， due to clutter， missed detection and no-linearity， the Particle Probability Hypothesis Density (P-PHD) algorithm will result in such problems as low filter accuracy and tracking divergence.To overcome these problems， a Quadrature Particle based PHD Filter (QPF-PHD) algorithm is proposed.The Quadrature Particle Filter (QPF) is used to realize PHD;the Quadrature Kalman Filter (QKF) algorithm is applied to generate a better importance density function， from which to sample particles， enabling the distribution of particles to be much closer to the real distribution of PHD.The simulation results demonstrate that：compared with particle PHD and Gizmo particle PHD filter algorithms， the proposed filter algorithm has higher filter accuracy and stability.

As to the issue of predicting real-time aerial target track， grey prediction model is an effective method in the context of limited data.But the accuracy of grey model prediction often fails to meet the requirements in practical engineering applications.Through in-depth study on the modeling mechanism of grey mode， it was found that the selections of initial value and grey parameters are not optimal.Then， by using ant colony optimization for the initial value and grey parameters， the accuracy of track prediction was improved significantly.The effectiveness and precision of the method was verified through case calculation.

The cooperation of manned fighters with Unmanned Combat Air Vehicle (UCAV) for air-to-ground attack will be the main combat mode in the future.How to achieve the manned fighter′s command and control to UCAVs is an important topic for study.According to the manned fighter′s command and control mode to UCAVs， the architecture of the command and control system is established.Based on which， the manned fighter′s interface of command and control is designed.The command and control mode of manned fighter to UCAVs is also discussed in the end.

In midcourse guidance of missile by cooperation of different kinds of aircrafts， abnormal abrupt change of missile overload is easily emerged in the process of guidance handover， which is mainly resulted from the switching of target information and guidance law.Based on the idea of converting the “abrupt change” to a “gradual change”， thus reducing the variable extent of overload， algorithms for the handover laws of target information and guidance law are proposed by adopting the variable weight coefficient method.Of which， the handover law of target information gives the “virtual target” information after weighting on the target information from handover aircrafts， while the handover law of guidance law gives the weighted guidance law of that before and after handover.Both the handover laws gradually change the weight coefficients of two weighted terms， until one weight coefficient is 0， and the other is 1， thus to realize the switching between weighted terms.To ensure the smooth transform of missile overload in the handover phase， it should be satisfied that the derivative of missile acceleration exists in the handover phase.Finally， simulations are carried out to demonstrate the effectiveness of the proposed handover method.

In view of the attack decision-making of fighters with Miniature Air Launched Decoy (MALD) in the process of one-to-one air combat， a new method was proposed based on Chaos Particle Swarm Optimization (CPSO) algorithm.The motion models of the fighter， the MALD， and the target fighter were established.Based on the analysis to air combat capability of the fighter， deceit ability of MALD， and threat level of target fighter， the indicator function of attack decision-making was established.Finally， a model of the attack decision-making based on CPSO algorithm was established.Simulation results show that the new method can make MALD work better and improve the survivability of the fighter.

The long-range targets in the sky appear as dim and small targets in the infrared detector， which have unconspicuous gray scale and area characteristics in the image.Due to the influence of the clouds in the sky， the image background may include large areas with high brightness or complex texture structure， which may affect the detection probability and false alarm rate of the system.Therefore， the background of image must be suppressed.In this paper， Top-Hat transform is used together with the image segmentation algorithm based on Markov random field for image processing.The simulation results show that this method can effectively restrain the background while retaining the real targets.

Tracking and controlling to reaching of arbitrary signals in uncertain chaotic system is realized by nonlinear feedback control.Proper feedback mode is selected according to the characteristic of system structure， and a nonlinear controller is designed.The sliding mode control theory is applied to prove that the error signal is exponentially stable at zero and all variables in controlled system are bounded.Compared with the control laws in current literature， the controller designed here not only takes the uncertainty of the system into consideration， but also guarantees that all the system states are bounded.The proposed method is a physically feasible tracking control strategy.The results of numerical simulation further proved the feasibility of this method.

Box particle filter algorithm， a novel estimation approach based on the combination of sequential Monte Carlo method with interval analysis for processing nonlinear dynamic stochastic systems， is introduced.Within recursive Bayesian estimation theory framework， the core ideas and main principle of box particle filter algorithm are analyzed.The performance characteristics of box particle filter are studied， and the application of the theory is briefly introduced.Finally， several possible research directions of the algorithm in the future are pointed out.

Monitoring network resource can provide effective support for better virtual network service under the environment of network virtualization.The management structure of virtual network resource is built up， then a method based on monitoring agent is used for realizing real-time monitoring of network resource.Considering synthetically the bandwidth， delay of reporting monitoring information and load of network node， a binary combinatorial optimal model for the deployment of monitoring agent is established， which is solved to find the approximate optimal solution by improved particle swarm algorithm.The simulation result indicates that the deployment of monitoring agent generated by proposed method has fine performance.

A DOA (Direction of Arrival) estimation method based on 2D-Unitary ESPRIT algorithm with hexangular star array is proposed.The multiple translation invariance of subarrays from hexangular star array is used to form combinations of each two set of subarrays.2D-Unitary ESPRIT algorithm is used to respectively estimate every combination， obtaining the candidate set of DOA estimation;then the power spectral function of 2D-MUSIC algorithm is adopted for optimization estimation of DOA in the candidate set， obtaining the optimized estimated value of DOA.Simulation experiment is conducted.The proposed method avoids the huge computational cost caused by spectral peak search of 2D-MUSIC algorithm， and DOA estimation error is reduced by applying combinations of multiple translation invariance subarrays.The simulation shows that:Compared with the traditional 2D-Unitary ESPRIT algorithm， the proposed method can reduce the mean square root error of estimated value and improve the spatial resolution.

Taking the airborne power supply system as the background， and considering the function characteristics and composition of Generator Control Unit (GCU)， we established the fault diagnosis dictionary of GCU. The result of Fault Tree Analysis (FTA) and fault diagnosis dictionary are used to determine the fault diagnosis model， thus can determine the fault detection points， reduce the complexity of diagnosis， and improve the efficiency of fault diagnosis.

The detecting coverage is one of the important indexes of radar′s performance and of layout optimization of radar stations.Based on the basic equation of radar， the detecting coverage model of radar network applying different network forms and data fusion methods is derived.Then， visualization simulation analysis is carried out with Matlab.The simulation results show the usability of the model as well as the visualization method.The study has important theoretical significance and application value for the combat ability analysis of radar network and station layout optimization.

The panoramic imaging onboard UAV based on image mosaics or fish eye lenses has the shortages of low real-time performance or high cost.To solve the problems， we designed a UAV real-time panoramic imaging equipment.The catadioptric panoramic imaging based on parabolic reflector was used， and real-time airborne panoramic image was obtained through wireless communication， which was then changed to cylindrical panoramic image through projection transformation.Thus a real-time， large field-of-view image(360° in horizontal and 286° in vertical)was obtained.The method can improve the real-time performance large FOV imaging and decrease the cost， which lays an important foundation for further image interpretation.

For the problem of time-varying multi-target tracking in clutter environment， the Extended Kalman-Gaussian Mixture Probability Hypothesis Density (EK-GMPHD) filter algorithm applicable to non-linear system is presented. In recursion of Gaussian component， the extended Kalman filter is used for local linearization， which solves the non-linear problem of measurement equation and state equation. In reducing the number of Gaussian terms， a new merge criterion is established， which gives consideration to the influence of Gaussian component covariance on the estimation accuracy. The estimated number of targets at the current moment is used to smooth the estimated number of targets at the previous moment， thus can eliminate the influence of outlier. Simulation results show that the proposed algorithm can effectively filter out clutter， and accurately estimate the number and state of multiple targets.

The unknown inertial parameters will result in inaccurate space robot system model and make making the common joint movement trajectory tracking control method become invalid.To solve the problem, a new joint movement trajectory tracking control method based on adaptive fuzzy algorithm is proposed.Based on the universal approximation property of fuzzy system, a parameter adaptive regulation method is used to identify the space robot system model online, solving the problems that space robot does not possess the prior knowledge of inertial parameters and usual linear properties.An adaptive fuzzy controller is designed, to realize joint space trajectory tracking control for dual-arm space robot system;and Lyapunov function is constructed to prove the stability of this fuzzy control system.The numerical simulation result verifies the validity of the proposed control method.

Traditional research on the influence of acoustics environment on dipping sonar detection can hardly come to an effective conclusion of equipment usage.According to the passive sonar equation and submarine noise model, a method for computing submarine noise signal margin is established.Through its relationship with the dipping sonar detection probability, the passive detection region of dipping sonar is simulated, and the distribution law of this detection region and its influence on the submarine searching strategy are studied.On the basis of which, and in combination with such parameters as tasks, environment and equipment, research on the submarine searching strategy for dipping sonar is conducted by simulation experiment.It is concluded that:to improve the detection efficiency, the distance between the detection points of dipping sonar should make the detection space of adjacent dipping points be closed, the positive gradient dipping depth be shallow, and double-dipping depths should be used in combination.The study is of specific guiding significance in optimum usage of dipping sonar for anti-submarine helicopter.

For the problem of reduced positioning accuracy of inertial navigation at high latitudes due to rapid convergence of the Earth's meridians, an inertial navigation method in Cartesian coordinates system is proposed, which is applicable to high-latitude areas. The method for establishing Cartesian coordinates system under spherical projection is presented, and the relationship between Cartesian coordinates and quasi-Cartesian coordinates is analyzed. The newly established inertial navigation method in Cartesian coordinates system is expounded, with reckoning of the ship's velocity, position and error. A switching model between high-latitude navigation mode and traditional navigation mode is established. Theoretical analysis shows that navigation of the inertial system based on the proposed Cartesian coordinates system can provide accurate information on the position and velocity of ships at high-latitude areas.

The measurement to laser scattering characteristics of target is critical for estimation of laser measuring system performance.According to the evaluation requirements to radar scattering cross section of the complex-shape, full-scale large object, we performed an outfield measuring test, and made analysis to the measurement data through measuring experience and simulation calculation.Based on simulation modeling and the modes for target scattering property evaluation, some ideas were proposed for improving outfield measuring accuracy for radar scattering cross section of complex large object, which may be taken as a reference for research on laser scattering characteristics of large object, as well as the establishment of evaluation method for scattering cross section of radar.

Grey theory is an effective method for studying the performance degradation law of inertia device and for predicting its lifetime.To enhannce the value of new information, the non-equal interval GM (1, 1) model is improved with a weighted model.Considering that it is impossible to obtain an exact predictive value to chaotic data sequence, a new method of grey interval prediction is proposed, making use of the whole data trend together with extreme point information, which can overcome the shortage of extracting boundary function by only using the extreme point.Smooth ratio of the parameter sequence is examined firstly before modeling.The parameter sequence meeting the quasi-smooth condition is to be modeled directly with weighted grey model, and otherwise, grey interval prediction is performed.The example shows that:in direct modeling, the weighted model improves the prediction accuracy to level 1 from level 2;in grey interval prediction, the real value lies within the prediction interval, with the average relative error of its upper and lower boundary prediction being 4.88%, and the prediction effect is significantly improved.