Novel approach for identifying Z-axis drift of RLG based on GA-SVR model

This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope （RLG） based on ge-netic algorithm （GA） and support vector regression （SVR） in the single-axis rotation inertial navigation system （SRINS）. GA is used for selecting the optimal parameters of SVR. The latitude error and the temperature variation during the identification stage are adopted as inputs of GA-SVR. The navigation results show that the proposed GA-SVR model can reach an identification accuracy of 0.000 2 （？）/h for the Z-axis drift of RLG. Compared with the ra-dial basis function-neural network （RBF-NN） model, the GA-SVR model is more effective in identification of the Z-axis drift of RLG.     

系统可持续发展的评价模型构建——基于模糊语言值逻辑的近似推理方法

基于模糊语言值逻辑的近似推理评价方法能够在一定意义上克服可持续发展概念本身所具有的深刻模糊性及其实现的难度自增值性。该评价模型包括六个步骤：（1）确定系统可持续发展指标体系;（2）评价指标测量值的归一化处理;（3）语言变量及其语言值的选取;（4）模糊推理规则库的建立;（5）模糊推理过程;（6）逆模糊化过程。     

电动汽车用开关磁阻电机有限元分析及仿真

开关磁阻电机（SRM）广泛应用于电动车驱动系统。建立SRM数学模型,对其做深入的仿真分析,对电动车用SRM的设计、控制有着重要的指导意义。SRM具有非线性的工作特征,无法得到统一的数学模型与解析式,利用ANSYS对电动汽车用开关磁阻电机进行有限元分析,得到电机静特性,计算出样机的磁链特性曲线。然后通过ANSYS与SIMULINK之间的数据传递,将有限元分析的数据导入SIMULINK中,以磁链函数为基础建立相对应的SRM驱动系统模型,并对该系统进行动态仿真。通过分析三组不同导通角和关断角组合条件下仿真系统的绕组电流、转矩和转速的仿真曲线,验证SRM的有限元分析结果及所建立的仿真模型的正确性及合理性。     

ECCM scheme against interrupted sampling repeater jammer based on time-frequency analysis

The interrupted sampling repeater jamming（ISRJ） is an effective deception jamming method for coherent radar, especially for the wideband linear frequency modulation（LFM） radar. An electronic counter-countermeasure（ECCM） scheme is proposed to remove the ISRJ-based false targets from the pulse compression result of the de-chirping radar. Through the time-frequency（TF） analysis of the radar echo signal, it can be found that the TF characteristics of the ISRJ signal are discontinuous in the pulse duration because the ISRJ jammer needs short durations to receive the radar signal. Based on the discontinuous characteristics a particular band-pass filter can be generated by two alternative approaches to retain the true target signal and suppress the ISRJ signal. The simulation results prove the validity of the proposed ECCM scheme for the ISRJ.     

Region-based classification by combining MS segmentation and MRF for POLSAR images

Speckle effects on classification results can be suppressed to some extent by introducing the contextual information.An unsupervised classification algorithm is proposed for polarimetric synthetic aperture radar(POLSAR) images based on the mean shift(MS) segmentation and Markov random field(MRF).First,polarimetric features are exacted by target decomposition for MS segmentation.An initial classification is executed by using the target decomposition and the agglomerative hierarchical clustering algorithm.Thereafter,a classification step based on MRF is performed by using the mean coherence matrices obtained for each segment.Under the MRF framework,the smoothness term is defined according to the distance between neighboring areas.By using POLSAR images acquired by the German Aerospace Centre and National Aeronautics and Space Administration/Jet Propulsion Laboratory,the experimental results confirm that the proposed method has higher accuracy and better regional connectivity than other classification methods.     

Evidence for self-organized criticality in unscheduled downtime data of equipment

How to reduce downtime and improve availability of the complex equipment is very important. Although the unscheduled downtime（USDT） issues of the equipment are very complex, the self-organized criticality（SOC） is the right theory to study complex systems evolution and opens up a new window to the investigation of disasters, such as the sudden failure of the equipment. Firstly,SOC theory and its validation method are introduced. Then an SOC validation method for USDT of the equipment is proposed based on the above theory. Case study is done on bottleneck equipment in a factory and corresponding data pre-process work is done. The rescaled-range（R/S） analysis method is used to calculate the Hurst exponent of USDT time-series data in order to determine the long-range correlation of USDT data on time scale;at the same time the spatial power-law characteristic of USDT time series data is studied. The result shows that the characteristics of SOC are revealed in USDT data of the equipment according to the criterion of SOC. In addition, based on the characteristics of SOC,the overall framework of the prediction method for major sudden failure of the equipment is proposed based on SOC.     

Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.     

Survey on nonlinear reconfigurable flight control

An overview on nonlinear reconfigurable flight control approaches that have been demonstrated in flight-test or highfidelity simulation is presented. Various approaches for reconfigurable flight control systems are considered, including nonlinear dynamic inversion, parameter identification and neural network technologies, backstepping and model predictive control approaches. The recent research work, flight tests, and potential strength and weakness of each approach are discussed objectively in order to give readers and researchers some reference. Finally, possible future directions and open problems in this area are addressed.     

基于NCS改进SAR大斜视角RD成像算法

SAR在大斜视时距离向和方位向存在着严重的耦合,为了消除这种耦合,分析了一种基于非线性调频变标NCS的改进RD算法。它充分利用大斜视角回波信号的大距离走动、小距离弯曲的特点,首先在距离向校正距离走动,然后采用非线性调频变标NCS来补偿方位向调频率的空变性,最后通过几何校正完成目标成像。同时仿真模拟场景的原始回波信号并对改进后的算法进行仿真,仿真结果表明,该算法可有效补偿方位向调频率的空变性,具有较高的精度,满足大斜视角下的成像要求。

Abstract：

To eliminate the serious coupling between azimuth and range for SAR in large squint mode,an improved RD imaging algorithm based on nonlinear chirp scaling was proposed,which made full use of the characteristic of SAR echo signal in large squint mode,which featured large range walk and small range curvature.First,range walk was corrected.Second,nonlinear chirp scaling operation was adopted to compensate the azimuth-dependent chirp rate.Finally,geometry correction was used to correct geometric distortion.Meanwhile the raw echo signal of the scene and the improved algorithm was simulated.Simulation results illustrate that it efficiently compensates the azimuth-dependent chirp rate,possesses high precision and satisfies the imaging quality of SAR in large squint mode.     

Reduced bit low power VLSI architectures for motion estimation

Low power and real time very large scale integration(VLSI) architectures of motion estimation(ME) algorithms for mobile devices and applications are presented.The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference(RBSAD) metric for calculating matching error and conversion to full resolution sum of absolute difference(SAD) metric whenever necessary.Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthesized using Xilinx Synthesis Tools(XST),where the ME designs based on reduced bit(RB) algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.     

Evaluation matrix with the speed feature based on double inspiriting control lines

Methods of the comprehensive evaluation have been studied for many years. However, the change speed of evaluated objects was rarely considered by the existing evaluation methods. An evaluation matrix is proposed to remedy this deficiency. Firstly, the change speed state （CSS） of the evaluated objects is analyzed based on double inspiriting control lines （DICLs）, and a matrix of the CSS is constructed. Then, 72 elements in the matrix are analyzed, and formulas describing each CSS are given. The efficiency of the proposed evaluation matrix is proved when the CSS merges with the change speed trend （CST） in the dynamic comprehensive evaluation. Finally, a computing example shows that the proposed evaluation matrix is feasible in the dynamic comprehensive evaluation with the speed feature.     

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.     

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making (GDM) method based on intuitionistic fuzzy sets (IFSs) is developed to evaluate the ergonomics of aircraft cockpit display and control system (ACDCS). The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging (IFSWA) operator is taken to synthesize decision-makers’ (DMs’) preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.     

基于 SD 的 VMI 供需双方利润分配机制研 究简

针对解决实施VMI合作双方因订货主动权的转移所引的责任和利益不统一问题,运用系统动力学的原理和方法,分别构建了传统库存管理和VMI两种模式下的供应商和销售商利润分配系统动力学模型,并通过仿真模拟对实施VMI模式前后各企业的经济效益进行比较,探讨实施VMI且销售商销售价格不变时,供应商的销售价格调整对合作双方利润分配的影响。     

Human activity recognition based on HMM by improved PSO and event probability sequence

This paper proposes a hybrid approach for recognizing human activities from trajectories.First,an improved hidden Markov model(HMM) parameter learning algorithm,HMM-PSO,is proposed,which achieves a better balance between the global and local exploitation by the nonlinear update strategy and repulsion operation.Then,the event probability sequence(EPS) which consists of a series of events is computed to describe the unique characteristic of human activities.The analysis on EPS indicates that it is robust to the changes in viewing direction and contributes to improving the recognition rate.Finally,the effectiveness of the proposed approach is evaluated by data experiments on current popular datasets.     

Radial acceleration estimation of multiple high maneuvering targets

The acceleration of a high maneuvering target in signal processing is helpful to enhance the performance of the tracker and facilitate the classification of targets. At present, most of the research on acceleration estimation is carried out in cases of a single target with time-frequency analysis methods such as fractional Fourier transform （FRFT）, Hough-ambiguity transform （HAT）, and Wigner-Vil e distribution （WVD）, which need to satisfy enough time duration and sampling theorem. Only one reference proposed a method of acceleration estimation for multiple targets based on modified polynomial phase transform （MPPT） in the lin-ear frequency modulation （LFM） continuous-wave （CW） radar. The method of acceleration estimation for multiple targets in the pulse Doppler （PD） radar has not been reported so far. Compressive sensing （CS） has the advantage of sampling at a low rate and short duration without sacrificing estimation performance. There-fore, this paper proposes a new method of acceleration estimation for multiple maneuvering targets with the unknown number based on CS with pulse Doppler signals. Simulation results validate the effectiveness of the proposed method under several conditions with different duration, measurement numbers, signal to noise ra-tios （SNR）, and regularization parameters, respectively. Simulation results also show that the performance of the proposed method is superior to that of FRFT and HAT in the condition of multiple targets.     

Multi-dimensional blind separation method for STBC systems

Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.     

Method of target tracking with Doppler blind zone constraint

Doppler blind zone （DBZ） has a bad influence on the airborne early warning radar, although it has good detection performance for low altitude targets with pulse Doppler （PD） technology. In target tracking, the blind zone can cause target tracking breakage easily. In order to solve this problem, a parallel particle filter （PF） algorithm based on multi-hypothesis motion models （MHMMs） is proposed. The algorithm produces multiple possible target motion models according to the DBZ constraint. Particles are updated with the constraint in each motion model. Once the first measurement from the target which reappears from DBZ falls into the particle cloud formed by any model, the measurementtrack association succeeds and track breakage is avoided. The simulation results show that on the condition of different DBZ ranges, a high association ratio can be got for targets with different maneuverability levels, which accordingly improves the tracking quality.     

New method for detection fusion of MAC based on DCM and NP rule

The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel (MAC) schemes are able to offer high efficiency in bandwidth usage and consume less energy than the parallel access channel (PAC), the MAC scheme is introduced into the underwater target detection field. The model of underwater distributed detection fusion based on MAC schemes is established. A new method for detection fusion of MAC based on deflection coefficient maximization (DCM) and Neyman-Pearson (NP) rule is proposed. Under the power constraint of local sensors, this paper uses the DCM theory to derive the optimal weight coefficients and offsets. The closed-form expressions of detection probability and false alarm probability for fusion systems are obtained. The optimal detection performance of fusion systems is analyzed and deeply researched. Both the theory analysis and simulation experiments indicate that the proposed method could improve the detection performance and decrease the error probability effectively under power constraints of local sensors and low signal to noise ratio.