The algorithm for Automatic Target Recognition (ATR) is an important part of the current and future weapon systems, and also a research focus of military field. A survey on algorithms used for ATR is presented. Analysis is made to some common algorithms, and the classification of them is given. The methods for evaluating the performance of the ATR algorithms are introduced. In the end, the research status of this area is summarized.

To deal with the uncertain statistics of measurement noise in maneuvering target tracking, a Fuzzy Adaptive Cubature Kalman Filter（FACKF） is proposed based on fuzzy inference system.By on-line judging the degree of compatibility between actual residual and theoretical residual, the measurement noise covariance of cubature Kalman filtering is adjusted in real time by using the fuzzy inference system to make it closer to the real measurement covariance gradually.Accordingly, the adaptability of the tracking algorithm is improved.Simulations using bearing-only tracking and active radar tracking model demonstrate that, compared with regular cubature Kalman filter and unscented Kalman filter, the proposed algorithm provides better filtering accuracy and stability when the observation noise is abnormal.

In order to solve the mission assignment problem of Unmanned Aerial Vehicles (UAVs), the flight time, combat threat, fuel consumption and other indecisive factors are taken into consideration for modeling analysis, and the factors are abstracted into uncertain variables.An Uncertain Multi-Objective Programming (UMOP) model with expert reliability is established, and the corresponding solving methods are given.The validity of the model is verified through an example .

To the problem of random measurement loss in nonlinear systems, the Extend Kalman Filter (EKF) with random measurement loss and with relevance noise is studied.By using correlation coefficient and the transmission factor following Bernouli distribution, an EKF with random measurement loss is proposed for nonlinear systems with relevance noise.Finally, the algorithm is applied in tracking space non-collaborate objects, and its validity is proved.

Tracking of target is easy to be disturbed due to sheltering, changing of illumination, or interference of noise under complex background.To solve the problem, a robust target tracking method based on binary channels of infrared and visible frames was proposed.Multiple features of the two channels were extracted, and the sparse sampling feature of compressed sensing was used to eliminate the non-negative hypothesis in sparse tracking algorithms.A new algorithm of compressed sensing was presented based on particle filter framework, and an adaptive method for target template updating was given, which was based on the Bhattacharyya coefficients.Experiments were made using multiple groups of image sequences with complex terrain.The results show that: the proposed algorithm has better robustness, higher precision and lower computation burden than the other tracking algorithms, which can achieve a stable tracking of the image target in complex environment.

Aiming at segmentation to images with nonuniform gray-level, an image segmentation method adaptive to gray value was proposed.Based on the level set theory, by using the gray value information of target image and the background, adaptive linear fitting was made to the global and local information.Then, image segmentation was conducted to avoid being trapped in the local optimum, which was robust to noise.The experimental results showed that the proposed method can resist noise effectively, is adaptive to the nonuniform gray level information, and can obtain global optimal image segmentation.

Dynamic Allan Variance（DAVAR）is an effective tool for the analysis of non-stationary signal.Since the window function is selected fixed, it has the defects of power leakage and single quantity in the identification of noise.Thus we put forward an improved DAVAR algorithm based on adaptive sliding window taking σ2 ratio (F value) as the criteria.Firstly, the F value is used to reflect the mutation characteristics of stochastic signal.Then, the length of the window function is calculated out according to the real-time change of F value, and stochastic signal is intercepted automatically.Finally, the piecewise Allan value is drawn on 3-D graphics.Analysis is made to the collected gyroscope signal.The result shows that the method can accurately reflect the change of dynamic noise characteristics, and ensure implementation of mutation tracking ability and good degree of confidence, which provides a theoretical reference for the study of inertial navigation system composed by gyroscopes under interference factors.

There are a large number of false intersection points when using multiple passive observation stations for making bearing-crossing localization to multiple targets.To solve the problem, a new algorithm is proposed, which is based on improved K-means cluster and data fusion.The intersection points on the same direction line are clustered, so that the targets in the direction line can be estimated.In this way, the most of false intersection points are eliminated.And then the results of clustering obtained from different stations are fused step by step.In the process of fusion, the algorithm makes full use of the clustering result of each observation station to reduce the influence of the residual false intersection points.Therefore,more accurate results of target location are obtained.The result of simulation show that the algorithm has better locating performance and robustness in multi-station cross positioning.

It is difficult to make quantitative analysis to time efficiency of a system.This paper mainly focuses on the theoretic model of time Petri net.Based on the time equivalent transformation of Petri net model, models for the air defense combat based on the Military Information Service System (MISS) are established with the Petri net.Also, the equivalent delay of the whole operational process is derived.On this basis, analysis is made to the system time efficiency through simulation with Matlab, and the effectiveness of the method is verified.

Considering the adaptive target detection of radar in heterogeneous environments, we proposed a knowledge-aided method for clutter covariance matrix estimation.The clutter in heterogeneous environments was supposed to subject to complex Gaussian distribution with covariance matrix as the random covariance matrix.The inverse Wishart distribution was employed as the priori distribution.According to Bayesian methods, we derived the posteriori probability density function of clutter covariance matrix.Then the maximum a posteriori estimation of covariance matrix was obtained.The simulation results show that the proposed knowledge-aided estimation method can effectively improve the target detection performance of radar under heterogeneous environments.

Considering that the Support Vector Data Description (SVDD) has low efficiency in training large scale samples, we put forward a novel directional greed incremental SVDD algorithm.Firstly, a certain amount of samples are randomly selected to train the original hypersphere by incremental SVDD, and the samples meeting the hypersphere requirement are nibbled away.Secondly, we choose the sample at the farthest distance to the former hypersphere as the new incremental sample at each time, and update the hypersphere model to make incremental SVDD growth step greater than the prior one.Finally, through iterative loop, the final SVDD is estabilished for classifying whole training samples.The simulation results show that, compared with ordinary SVDD and incremental SVDD, the new algorithm has the advantages of lower time-consuming and higher model training efficiency in the premise of guaranteed classifier performance.

Considering that traditional methods can't make accurate predictions to MEMS gyroscope's random drift, we put forward an interval prediction method by using the Support Vector Machine(SVM) model based on fuzzy information granulation. First, the original data is preprocessed with fuzzy information granulation algorithm to divide the sample space into multiple subspaces for reducing the sample size and decreasing the time complexity. Then, the scalar gyroscope random drift time series is embedded to an assistant phase space by the technology of phase construction and the data is normalized. SVM is used to conduct regression analysis, and the optimal regulation parameters of the model are obtained by using cross validation algorithm, thus to avoid over fitting and under fitting phenomenon. At last, we predict the random drifts with the trained model. The results show that the model can effectively predict variation trend and interval. Therefore, the model has a good prospect in engineering.

Modern electronic equipment constantly develops in the direction of integration, smartness and complexity, and the traditional redundant fault-tolerant-based method used for improving electronic system reliability cant meet the development needs of existing electronic equipment anymore. To solve the problem, embryonic hardware has emerged in recent years. It is a novel bio-inspired structure based on multicellular development, with excellent self-adaptive, self-organizing and self-healing properties. Embryonic hardware design-based circuit has high fault tolerance and self-healing capability. In this paper, the basic meaning of Embryonic hardware is introduced, and its self-healing theory is researched. Embryonic hardware self-healing research status and the key technologies of implementation at home and abroad are investigated. Eventually, the main problems of Embryonic hardware self-healing are researched, and the future research directions are prospected.

To solve the problem that the TACAN equipment has limited capacity of field test, a TACAN signal detection system was designed by taking FPGA as the core of the control system, using DSP to implement the secondary information decoding, and a embedded configuration software to build the Human-Machine Interface (HMI).In this paper, the hardware and software composition is presented, and the software flow chart is given.The communication module design and angle/distance detection process are described with the improved algorithms.The system makes full use of capabilities of FPGA in high-speed sampling and parallel processing and of DSP in real-time computing, thus to realize rapid calculation and display control.The experiment result shows that the design has a good test precision, and it can improve the level of the maintenance and service, which is valuable in engineering.

The go-stop mode is not suitable for Frequency Modulated Continuous Wave Circular Synthetic Aperture Radar(FMCW CSAR), the Doppler shifting caused by motion of the carrier aircraft has a great effect on the quality of imaging under large-scale, high-velocity condition.The compensation functions of linear SAR are not applicable due to the continuous change of the velocity direction.To solve the problem, we established an accurate signal receiving model, deduced the Doppler shifting in FMCW CSAR, analyzed the effect of the motion radius and velocity on Doppler shifting, and proposed a new compensation function to revise the Doppler shifting.Simulation results proved that the function can correct the Doppler shifting effectively.

Aiming at the problem that alignment accuracy (especially azimuth misalignment angle) and speed of the Hemispherical Resonator Gyroscope (HRG) platform for multi-location are unsatisfactory due to the poor observability, a platform continuous rotation alignment is put forward.Angular motion equations were derived by using the framework, and HRG INS continuous rotation self-alignment model was established.Experiments were made to verify the designed self-alignment method.The results showed that:the proposed self-alignment method improves the alignment accuracy and speed greatly compared with the conventional static multi-position alignment method, and thus it has the value of engineering applications.

To solve the problem that the guided missile insert-pull mechanism can't act quickly and accurately, we put forward a new control mode for implementing reliable insert-pull action by calibrating the target point through visual control taking a 6-DOF robot as the experimental platform. The information of the socket's location is obtained by using image processing and camera calibration, which is then read out by the CPAC controller, and is used to control the end effector to complete reliable action. The feasibility of the method is verified through experiment.

The survivability design characteristics of typical carrier-based aircraft, such as F/A-18, are introduced. The general considerations for high survivability design are summed up from the aspects of decreasing susceptibility and vulnerability and increasing battle damage repair capability. According to the operational characteristics of carrier-based aircraft, this paper introduces the susceptibility analysis methods under sea clutter and electronic countermeasure, and the vulnerability analysis method under the traditional weapons. Taking a hypothetical carrier-based aircraft as an example, a numerical survivability analysis is carried out. Results show that the survivability of carrier-based aircraft is obviously improved when adopting such survivability measures as electronic countermeasures, explosion suppression of fuel tank, and pipe self-sealing.

In view of the high real-time and multi-task design requirements to UAV simulation system and the problems of complicated manual code development and long design cycle, a design method using RTW and C code on VxWorks platform is proposed.First, Simulink tool is used for developing the UAV simulation system.Then missions of the simulation system are divided into system administration, model solving, scheduling management and interfacing task, which are designed respectively.Then, Real Time Workshop (RTW) is used to compile the Simulink and C code files into an executable file, and thus to implement the construction of the UAV simulation system.Semi-physical simulation results show that:1) The UAV simulation system has proper simulating function and can meet the real-time requirements; and 2) Compared with the traditional manual code development mode, the method based on RTW together with C code reduces system design complexity and accelerates the simulation platform development.

A method for calculating the initial structure of off-axis optical system with three mirrors based on aberration theory is introduced, and a three-mirror off-axis optical system is designed with this method, which is adaptable for space remote sensing system.The system has a wave band of7.7~10.3 μm, effective mirror length of 1000 mm, F-number of 2, and the full FOV is 1°.The detailed optimization process is presented.It shows that the system has the advantages of long focal length, large diameter, high image quality and compact structure, which can meet the requirements of the space remote sensing system.

Lighting system is an important part of the aircraft, and LED technology has been widely used in it.An advanced off-line two-stage LED driver power supply with stable output voltage and constant current is presented in the paper.The power supply has a feedback control scheme with its first stage of Power Factor Correction (PFC) converter implemented by the use of L6562 via primary side feedback only.Unlike the traditional architecture of L6562 based LED driver supply, optocoupler is not required here.The second DC/DC constant current stage is controlled by LM3404HV, and an improved constant drive circuit based on LM3404HV is proposed,thus the constant accuracy does not vary as the input voltage changes, unlike the saturation in the traditional topology.Experimental results show that the scheme can decrease the ripple current of LED effectively.

The actuator plays a very important role in the flight control system of UAVs, so it is necessary to diagnose the fault in real time.Analysis was made to the working principle of the actuator of UAVs, based on which the analytical model of the actuator was established.With this model, we made real-time status monitoring and fault diagnosis to the actuator.Then, a fault diagnosis algorithm based on residual was designed by combining threshold analysis with Improved SPRT.The fault features were extracted from residuals to detect and determine the working status of the actuator.Finally, a mathematical model of actuators fault was established, and fault models were injected to the actuator to verify it.The result shows that this scheme can identify the common faults of the actuator rapidly and effectively.

Aiming at the cross-coupling effect between pitch and yaw channels due to periodic rolling of guided projectiles, we designed a decoupling control algorithm by using feed-forward compensation method together with the PID controller.A mathematical model of the spin-guided projectile was established, and the transfer functions of pitch and yaw direction were obtained.The degree of coupling was determined by using the relative gain, and feed-forward compensation method was used for decoupling.PID control was used together with feed-forward compensator for the design of a guided projectile decoupling control system.This approach simplified the controller, and decoupled the strong coupling system guided projectile.The numerical simulation analysis shows that the control method has rapid response capability, high command tracking accuracy and robustness characteristics under the strong coupling and parameter perturbations.This method achieves the decoupling control system and can satisfy the system performance requirements.