Considering the the strict electromagnetic concealment requirement for stealth fighters in combat, we proposed a virtual target tracking method based on network information.State model of virtual tracking was established based on the measurement transformation process, in which the network information precision and fighter state estimate error were taken into consideration.The state model was revised based on unbiased transformation principle.In order to improve the precision of target state estimation, Unscented Kalman Filter of Interacting Multiple Mode (IMM-UKF) algorithm based on current statistical mode was proposed.Finally, simulation was made for maneuvering target tracking under different error conditions.The result showed that “virtual tracking” method can get a stable target state estimation with fast convergence speed and high precision.

The method of collision detection for temporal constraint on air formation coordinated operation against ground was studied using graph theory.The characteristics of temporal constraint in air formation coordinated operation against ground were presented, the Simple Temporal Constraint Network (STCN) theory was discussed, and a STCN model on mission was established.Then the model was translated into a weight matrix resulted from references to graph theory.The correspondence between values of cycles and weight matrix element was analyzed, and then a weight matrix algorithm, which was a new method for consistency testing, was put forward.Theoretic analysis showed that:all values of cycles could be calculated synchronously, moreover, the time complexity was reduced effectively and testing efficiency was improved remarkably, and it satisfied the requirement of dynamic coordination.The simulation result showed that the method was effective and feasible.

Since the images of an aircraft target are much different from each other under various conditions of different observed angle, locality and illumination, many classical dimensional reduction and feature extracting methods are not effective to recognize the aircraft target.A recognition method of radar target is proposed based on two-dimensional locality sensitive discriminant analysis (2DLSDA).Firstly, two graphs respectively representing intra-class and inter-class neighbor relationship are constructed.Then, weight matrixes are calculated out.Finally, two orthogonal transform matrixes are computed out based on Schur decomposition.The projection matrix is obtained and then the dimensionality of the image is reduced.Thus the small-sample-size problem can be overcome.The recognition results on radar targets show that the proposed method is very effective and feasible.

The problem of parameter recursive identification for minimum variance control was studied from the point of system identification.For the unknown parameter vector of the ARMAX model in the minimum variance closed loop control, we proposed a multi-innovation recursive least-squares identification method and a separable iterative recursive least-squares identification method to identify and estimate the unknown parameters vector in the ARMAX model on line.When excited by the white noise, both the methods could give the unbiased estimation about the unknown parameter vector.When excited by the colored noise, only the separable iterative recursive least-squares identification method could give the unbiased estimation.Finally, the effectiveness and feasibility of the proposed strategy was verified by the simulation results.

An improved method is presented to overcome the drawbacks of the original NAS-RIF algorithm.To deal with the noise sensitivity of NAS-RIF, higher order statistics denoising was introduced.To solve the problem that the NAS-RIF requires square support region, the image segmentation based self-estimation of image support region was used.At last, simulation was made to various PSNR images and backgrounds.The improved algorithm was compared with the original one.The simulation results show that the improved algorithm solves the problems of the original algorithm, and can improve the quality of recovery image observably.

Quick, accurate, and anti-disturbance roll attitude control is one of the key technologies of automatic landing control system design for air buses.Based on nonlinear mathematical model of Boeing707 under constant crosswind disturbance, the linear model was obtained by trim and linearization, and the attitude control law for approach and landing was designed.Considering that it's difficult to realize rapid and stable response of roll angle with PID control method, we designed a robust H∞ control law.The two methods were analyzed on their capability of tracking roll attitude command and anti-crosswind disturbance.Simulation results indicated state feedback H∞ controller can achieve quick, accurate and no overshoot roll attitude control, and has ability of faster recovery, better riding quality and larger control redundancy of restraining crosswind disturbance.