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27 December 2017, Volume 28 Issue 6
ELECTRONICS TECHNOLOGY
DOA estimation of wideband signals based on iterative spectral reconstruction
Shun He, Zhiwei Yang, and Guisheng Liao
2017, 28(6):  1039-1045.  doi:10.21629/JSEE.2017.06.01
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In order to solve the problem of coherent signal subspace method (CSSM) depending on the estimated accuracy of signal subspace, a new direction of arrival (DOA) estimation method of wideband source, which is based on iterative adaptive spectral reconstruction, is proposed. Firstly, the wideband signals are divided into several narrowband signals of different frequency bins by discrete Fourier transformation (DFT). Then, the signal matched power spectrum in referenced frequency bins is computed, which can form the initial covariance matrix. Finally, the linear restrained minimum variance spectral (Capon spectral) of signals in other frequency bins are reconstructed using sequential iterative means, so the DOA can be estimated by the locations of spectral peaks. Theoretical analysis and simulation results show the proposed method based on the iterative spectral reconstruction for the covariance matrices of all sub-bands can avoid the problem of determining the signal subspace accurately with the coherent signal subspace method under the conditions of small samples and low signal to noise ratio (SNR), and it can also realize full dimensional focusing of different sub-band data, which can be applied to coherent sources and can significantly improve the accuracy of DOA estimation. 

DOA estimation for mixed signals with gain-phase  
Jiaqi Zhen and Yong Liu
2017, 28(6):  1046-1056.  doi:10.21629/JSEE.2017.06.02
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Most of the direction of arrival (DOA) estimation methods often need the exact array manifold, but in actual applications, the gain and phase of the channels are usually inconsistent, which will cause the estimation invalid. A novel direction finding approach for mixed far-field and near-field signals with gain-phase error array is provided. Based on simplifying the space spectrum function by matrix transformation, DOA of far-field signals is obtained. Consequently, errors of the array are acquired according to the orthogonality of far-field signal subspace and noise subspace. Finally, DOA of near-field signals can be estimated. The method merely needs one-dimensional spectrum searching, so as to improve the computational efficiency on the premise of ensuring a certain accuracy, simulation results manifest the effectiveness of the method.

Dual-threshold symbol selective relaying in cooperative networks
Peiyao Yang, Hai Li, and Shujuan Hou
2017, 28(6):  1057-1063.  doi:10.21629/JSEE.2017.06.03
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In order to efficiently mitigate error propagation and reduce computational complexity, this paper proposes a scheme for traditional cooperative networks, named as dual-threshold symbol selective demodulate-and-forward. In the scheme, two log likelihood ratio (LLR)-based thresholds are devised to measure the reliability of received signals for the relay and the destination, respectively. One of the threshold guarantees that the relay only forwards reliable symbols, thus less error will be propagated to the destination. The other threshold is used at the destination for determining the reliability of symbols received from the source. The destination will directly demodulate reliable symbols received from the source. Otherwise, when the symbols received from the source are not reliable, the maximum ratio combiner (MRC) is used to combine symbols received from the source and the relay. Closed-form expression of the bit error probability (BEP) of the proposed scheme is derived and analyzed under binary phase shift keying (BPSK) modulation. Then, the relationship and closed-form solutions of two LLR-based thresholds are derived. Simulation results prove that the theoretical BEP of the proposed scheme closely matches the simulated ones. The proposed scheme can achieve high performance with low computational complexity compared to existing schemes.

Particle filter for nonlinear systems with multi-sensor asynchronous random delays
Junyi Zuo and Xiaoping Zhong
2017, 28(6):  1064-1071.  doi:10.21629/JSEE.2017.06.04
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This paper is concerned with the recursive filtering problem for a class of discrete-time nonlinear stochastic systems in the presence of multi-sensor measurement delay. The delay occurs in a multi-step and asynchronous manner, and the delay probability of each sensor is assumed to be known or unknown. Firstly, a new model is constructed to describe the measurement process, based on which a new particle filter is developed with the ability to fuse multi-sensor information in the case of known delay probability. In addition, an online delay probability estimation module is introduced in the particle filtering framework, which leads to another new filter that can be implemented without the prior knowledge of delay probability. More importantly, since there is no complex iterative operation, the resulting filter can be implemented recursively and is suitable for many real-time applications. Simulation results show the effectiveness of the proposed filters.

DEFENCE ELECTRONICS TECHNOLOGY
Radar cross section of arbitrary polished spheres at terahertz frequencies#br#
Ruijun Wang, Bin Deng, Hongqiang Wang, and Yuliang Qin
2017, 28(6):  1072-1077.  doi:10.21629/JSEE.2017.06.05
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We develop an efficient method for polished metallic sphere’s scattering prediction in terahertz band when its frequency dispersion property is considered. By deducing scattering solution of the lossy metallic sphere, the radar cross section (RCS) of different metallic spheres is given at terahertz frequencies. The investigation of the RCS of polished metallic spheres shows the normalized RCS is always same to the metals’ normal incidence reflectivity when the sphere becomes electrically large. The metals which have high reflectivity (such as Al, Cu, Ag and Au) show that the corresponding RCS of the spheres is almost πa2 in terahertz band. The sphere’s RCS of the transition metal such as Fe begins to decrease obviously since the far infrared. 
Fast ISAR imaging method based on scene segmentation
Mingjiu Lyu, Shaodong Li, Wenfeng Chen, Jun Yang, and Xiaoyan Ma
2017, 28(6):  1078-1088.  doi:10.21629/JSEE.2017.06.06
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Although compressed sensing inverse synthetic aperture radar (ISAR) imaging methods are widely used in radar signal processing, its reconstructing time and memory storage space requirements are very high. The main reason is that large scene reconstruction needs a higher dimension of the sensing matrix. To reduce this limitation, a fast high resolution ISAR imaging method, which is based on scene segmentation for random chirp frequencystepped signals, is proposed. The idea of scene segmentation is used to solve the problems aforementioned. In the method, firstly, the observed scene is divided into multiple sub-scenes and then the sub-scenes are reconstructed respectively. Secondly, the whole image scene can be obtained through the stitching of the sub-scenes. Due to the reduction of the dimension of the sensing matrix, the requirement of the memory storage space is reduced substantially. In addition, due to the nonlinear superposition of the reconstructed time of the segmented sub-scenes, the reconstruction time is reduced, and the purpose of fast imaging is achieved. Meanwhile, the feasibility and the related factors which affect the performance of the proposed method are also analyzed, and the selection criterion of the scene segmentation is afforded. Finally, theoretical analysis and simulation results demonstrate the feasibility and effectiveness of the proposed method. 
Method to reconnoiter pulse amplitude train for phased array radar based on Hausdorff distance#br#
Chuan Sheng, Yongshun Zhang, Wenlong Lu, and Junwei Xie
2017, 28(6):  1089-1097.  doi:10.21629/JSEE.2017.06.07
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This paper presents a method to estimate beam pointing of phased array radar by the pulse amplitude train, which is significant in radar electronic reconnaissance and electronic support measure. Firstly, the antenna patterns modeling of the phased array system is exploited to build the radar sweeping model and the signal propagation model. Secondly, the relationship between the variation of the radiated power and the antenna beam pointing angles in the given airspace is analyzed. Based on the above two points, the sample with obvious amplitude characteristics of the pulse amplitude train can be screened out after detecting the train peaks. Finally, the sample is matched to the subsequent pulse amplitude train based on the Hausdorff distance. The proposed methods have less prior knowledge and higher efficiency and are easier to process. By cross correlating the sample of the pulse amplitude train with the sample data of the antenna follow-up radiation, the probability of detection of the beam pointing direction becomes larger in case that the subsequent antenna beam returns to the specific position. 
Autonomous process collaboration framework for C4ISR system interoperation#br#
Lin Yang, Minggang Yu, and Qingchao Dong
2017, 28(6):  1098-1113.  doi:10.21629/JSEE.2017.06.08
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Interoperability plays an important role in the joint command, control, communication, computer, intelligence, surveillance, reconnaissance (C4ISR) operations. Coordinating and integrating operational processes to fulfill a common mission are challenged by the ever-changing battlefield and hence requires a cross-organizational process management that produces an autonomous, flexible and adaptable architecture for collaborative process evolution. The traditional business process collaboration pattern is based on the predefined “public-view” perspective and cannot meet the requirement of the joint task operations. This paper proposes a flexible visibility control mechanism and a dynamic collaboration framework for modeling and generating collaborative processes. The mechanism allows collaborators to define a set of visibility rules to generate different views of the private processes for different collaborations, which gives a great flexibility for the collaboration initiator to decide on an appropriate collaboration pattern. The framework supports collaborators to dynamically and recursively add a new process or even a new organization to an existing collaboration. Moreover, a formal representation of the processes and a set of generation algorithms are provided to consolidate the proposed theory. 
SYSTEMS ENGINEERING
Temporal evidence combination method for multi-sensor target recognition based on DS theory and IFS#br#
Ju Wang and Fuxian Liu
2017, 28(6):  1114-1125.  doi:10.21629/JSEE.2017.06.09
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In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition (MSTR) system at the decision making level, this paper proposes a Dempster-Shafer (DS) theory and intuitionistic fuzzy set (IFS) based temporal evidence combination method (DSIFS-TECM). To realize the method, the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value (IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor (RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference. 
Analytical measurement method for situation elements’ dynamic characteristics#br#
Huiyun Zhao, Dongge Zhang, Hui Meng, and Jiuyang Tao
2017, 28(6):  1126-1132.  doi:10.21629/JSEE.2017.06.10
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This paper gives an analysis of the dynamic characteristics of situation elements (SEs) in situation awareness (SA) research. The purpose of the discussion is to understand the factors that influence SA and to help in designing the training systems to improve operators’ SA. The status function of SEs is defined and the derivative of the function represents trends of the status of SEs at each moment. Then, Fourier transform (FT) is used to give the frequency-domain function in terms of the time-domain status function. In frequency domain, the bandwidth of the status function is used as a criterion to characterize the notion of “fast” and “slow” of the change of SE’s status, which represents the dynamic characteristic of SEs. The criterion constitutes the first analytical measurement of the dynamic characteristic of SEs, which is one of the important factors that influence the SA process. 
Joint optimization of maintenance inspection and spare provisioning for aircraft deteriorating parts#br#
Jing Cai, Xin Li, and Xi Chen
2017, 28(6):  1133-1140.  doi:10.21629/JSEE.2017.06.11
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With the wide application of condition based maintenance (CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy. Secondly, a combination of the genetic algorithm (GA) and the Monte Carol method is developed to minimize the total cost rate. Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management. 
Marginal optimization method to improve the inconsistent comparison matrix in the analytic hierarchy process#br#
Shihui Wu, Jiang Xie, Xiaodong Liu, Bo He, Minxiang Yang, and Zhengxin Li
2017, 28(6):  1141-1151.  doi:10.21629/JSEE.2017.06.12
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To improve the inconsistency in the analytic hierarchy process (AHP), a new method based on marginal optimization theory is proposed. During the improving process, this paper regards the reduction of consistency ratio (CR) as benefit, and the maximum modification compared to the original pairwise comparison matrix (PCM) as cost, then the improvement of consistency is transformed to a benefit/cost analysis problem. According to the maximal marginal effect principle, the elements of PCM are modified by a fixed increment (or decrement) step by step till the consistency ratio becomes acceptable, which can ensure minimum adjustment to the original PCM so that the decision makers’ judgment is preserved as much as possible. The correctness of the proposed method is proved mathematically by theorem. Firstly, the marginal benefit/cost ratio is calculated for each single element of the PCM when it has been modified by a fixed increment (or decrement). Then, modification to the element with the maximum marginal benefit/ cost ratio is accepted. Next, the marginal benefit/cost ratio is calculated again upon the revised matrix, and followed by choosing the modification to the element with the maximum marginal benefit/cost ratio. The process of calculating marginal effect and choosing the best modified element is repeated for each revised matrix till acceptable consistency is reached, i.e., CR<0.1. Finally, illustrative examples show the proposed method is more effective and better in preserving the original comparison information than existing methods. 
Cartesian product over interval valued intuitionistic fuzzy sets
Jianming Xie and Sanyang Liu
2017, 28(6):  1152-1161.  doi:10.21629/JSEE.2017.06.13
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The intuitionistic fuzzy set (IFS) based on fuzzy theory, which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set (IVIFS). On the basis of fuzzy set (FS), the IFS is a generalization concept. And the IFS is generalized to the IVIFS. In this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are explored. We prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs. 
CONTROL THEORY AND APPLICATION
Optimal midcourse trajectory cluster generation and trajectory modification for hypersonic interceptions#br#
Humin Lei, Jin Zhou, Dailiang Zhai, Lei Shao, and Dayuan Zhang
2017, 28(6):  1162-1173.  doi:10.21629/JSEE.2017.06.14
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The hypersonic interception in near space is a great challenge because of the target’s unpredictable trajectory, which demands the interceptors of trajectory cluster coverage of the predicted area and optimal trajectory modification capability aiming at the consistently updating predicted impact point (PIP) in the midcourse phase. A novel midcourse optimal trajectory cluster generation and trajectory modification algorithm is proposed based on the neighboring optimal control theory. Firstly, the midcourse trajectory optimization problem is introduced; the necessary conditions for the optimal control and the transversality constraints are given. Secondly, with the description of the neighboring optimal trajectory existence theory (NOTET), the neighboring optimal control (NOC) algorithm is derived by taking the second order partial derivations with the necessary conditions and transversality conditions. The revised terminal constraints are reversely integrated to the initial time and the perturbations of the co-states are further expressed with the states deviations and terminal constraints modifications. Thirdly, the simulations of two different scenarios are carried out and the results prove the effectiveness and optimality of the proposed method. 
Finite-time attitude tracking control for spacecraft without angular velocity measurements#br#
Li Yuan, Guangfu Ma, Chuanjiang Li, and Boyan Jiang
2017, 28(6):  1174-1185.  doi:10.21629/JSEE.2017.06.15
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The output feedback control for spacecraft attitude tracking system is investigated in this study. It is assumed that angular velocity measurements are not available for feedback control. A technique named adding power integrator (API) is adopted to estimate the pseudo-angular-velocity. Then we design a finite-time attitude control law, which only utilizes the relative attitude information. The stability analyses of the feedback system are proved as well, which shows the attitude tracking errors will converge into a region of zero even the external disturbances exist. The simulation results illustrate the high precision and robust attitude control performance of the proposed control strategy. 
Sliding mode control and Lyapunov based guidance law with impact time constraints#br#
Xiaojian Zhang, Mingyong Liu, and Yang Li
2017, 28(6):  1186-1192.  doi:10.21629/JSEE.2017.06.16
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This paper analyses the issue of impact time control of super-cavitation weapons impact fixed targets which mainly refer to the ships or submarines who lost power, but still have combat capability. Control over impact time constraints of guidance law (ITCG) is derived by using sliding mode control (SMC) and Lyapunov stability theorem. The expected impact time is realized by using the notion of attack process and estimated time-to-go to design sliding mode surface (SMS). ITCG contains equivalent and discontinuous guidance laws, once state variables arrive at SMS, the equivalent guidance law keeps the state variables on SMS, then the discontinuous guidance law enforces state variables to move and reach SMS. The singularity problem of ITCG is also analyzed. Theoretical analysis and numerical simulation results are given to test the effectiveness of ITCG designed in this paper. 
Improved bias proportional navigation with multiple constraints for guide ammunition#br#
Wei Pang, Xiaofang Xie, and Tao Sun
2017, 28(6):  1193-1202.  doi:10.21629/JSEE.2017.06.17
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According to the infrared guidance ammunition (GA) attacking non-maneuvering targets on the ground or sea level, an improved bias proportional navigation (IBPN) is put forward, which can meet the constraints of the impact angle and the angle of attack (AOA). The motion equations and the collision triangle for the GA and the target are established in the two-dimensional plane. In accordance with the collision triangle, the integral value of the bias term is solved and BPN is designed on the basis of the relative velocity. To ensure the new method can be solved, closedloop equation of the IBPN is deduced. Considering the limitation of the AOA and the seeker angle, a four-phase IBPN is improved by setting different phases of the bias term. At the same time, the guidance law will make the impact angle achieve the desired angle and the normal acceleration also converges to zero. The simulation results show that the improved guidance law can be applied to various flight tasks and has great potential for engineering applications. 
Bio-inspired geomagnetic navigation method for autonomous underwater vehicle#br#
Hong Li, Mingyong Liu, and Kun Liu
2017, 28(6):  1203-1209.  doi:10.21629/JSEE.2017.06.18
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This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle (AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method. 
ADRC based control for a class of input time delay systems
Dongyang Zhang, Xiaolan Yao, Qinghe Wu, and Zhuoyue Song
2017, 28(6):  1210-1220.  doi:10.21629/JSEE.2017.06.19
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This paper is concerned with the control design and the theoretical analysis for a class of input time-delay systems with stable, critical stable or unstable poles. In order to overcome the time delay, a novel feed-forward compensation active disturbance rejection control (FFC-ADRC) approach is proposed. It combines advantages of the Smith predictor and the traditional active disturbance rejection control (ADRC). The tracking differentiator (TD) is designed to predict the control signal, which adds an anticipatory control to the control signal and allows a higher observer bandwidth to obtain better disturbance rejection. The modified extended state observer (ESO) is designed to estimate both system states and the total disturbances (internal disturbance, uncertainties and delayed disturbance). Then the Lyapunov theory and the theory of the input-output stability are applied to prove the asymptotic stability of the closed-loop control system. Finally, numerical simulations show the effectiveness and practicality of the proposed design. 
Enhancing of nominal characteristic trajectory following control for motion systems#br#
Fitri Yakub, Shamsul Sarip, Andika Aji Wijaya, and Yasuchika Mori
2017, 28(6):  1221-1235.  doi:10.21629/JSEE.2017.06.20
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The goal of this paper is to enhance a practical nominal characteristic trajectory following (NCTF) controller that is specifically designed for two-mass point-to-point positioning systems. A nominal characteristics trajectory contained in the NCTF controller acts as movement/motion reference and a compensator is utilized to force the object to detect and follow the reference/desired trajectory. The object must follow and track closely and should be as fast as possible. The NCTF controller is designed with two different intelligent based compensator approaches which are fuzzy logic and extended minimal resource allocation network. The proposed controller which is NCTF are compared with the conventional proportional integral compensator. Then the results of simulation are discussed for the positioning performances. The inertia variations due to the effect of the design parameters are also assessed to see the robustness of controllers. The results show that the NCTF control method designed from an intelligent based compensator has a better positioning performance in terms of percentage of overshoot, settling time, and steady state error than the classical based compensator. 
SOFTWARE ALGORITHM AND SIMULATION
Astronomical image restoration using variational Bayesian blind deconvolution#br#
Xiaoping Shi, Rui Guo, Yi Zhu, and Zicai Wang
2017, 28(6):  1236-1247.  doi:10.21629/JSEE.2017.06.21
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An algorithm is presented for image prior combinations based blind deconvolution and applied to astronomical images. Using a hierarchical Bayesian framework, the unknown original image and all required algorithmic parameters are estimated simultaneously. Through utilization of variational Bayesian analysis, approximations of the posterior distributions on each unknown are obtained by minimizing the Kullback-Leibler (KL) distance, thus providing uncertainties of the estimates during the restoration process. Experimental results on both synthetic images and real astronomical images demonstrate that the proposed approaches compare favorably to other state-of-the-art reconstruction methods.

Learning Bayesian network parameters under new monotonic constraints#br#
Ruohai Di, Xiaoguang Gao, and Zhigao Guo
2017, 28(6):  1248-1255.  doi:10.21629/JSEE.2017.06.22
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When the training data are insufficient, especially when only a small sample size of data is available, domain knowledge will be taken into the process of learning parameters to improve the performance of the Bayesian networks. In this paper, a new monotonic constraint model is proposed to represent a type of common domain knowledge. And then, the monotonic constraint estimation algorithm is proposed to learn the parameters with the monotonic constraint model. In order to demonstrate the superiority of the proposed algorithm, series of experiments are carried out. The experiment results show that the proposed algorithm is able to obtain more accurate parameters compared to some existing algorithms while the complexity is not the highest.