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25 August 2015, Volume 26 Issue 4
Channel modeling and influenced factor analysis of the broadband dual-orthogonal polarized MIMO land mobile satellite channel
Qingfeng Jing, Jiajia Wu, Yuping Lu, Xin Liu, and Xiaoju Yan
2015, 26(4):  651.  doi:10.1109/JSEE.2015.00073
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An accurate, complete and realistic channel model is required to accurately analyze the system performance of a multiple input multiple output (MIMO) broadband satellite mobile communication system with dual-orthogonal polarized antennas (DPAs). In most current studies, the channel characteristic matrix (CCM) is always formed by an independent identical distribution (i.i.d) model of Rayleigh or Rice distribution and nevertheless incomplete and inaccurate to describe a broadband dual-orthogonal polarized MIMO land mobile satellite (BDM-LMS) channel. This paper focuses on establishing the BDM-LMS channel statistical model, which combines the 4-state broadband LMS channel model, the time selective fading features, the channel covariance information (CCI) channel model and polarization correlations between antennas. The modeling steps of the channel model are introduced. The main emphasis is placed on the effects of the factors, such as antenna numbers, temporal correlations, terminal environments, elevation angles and polarization correlations between the DPAs, on the channel capacity in the BDM-LMS system. Many simulation results are provided to illustrate the effects of these factors through comparisons of the transmit rate, ergodic capacity and outage capacity with different factor values. Besides, the MIMO outage capacity advantages, which indicate the benefits of MIMO compared with a single input single output (SISO) system under the same channel condition, are also studied under i.i.d or BDM-LMS channel.

Application and improvement of wavelet packet de-noising in satellite transponder
Yannian Lou, Chaojie Zhang, Xiaojun Jin, and Zhonghe Jin
2015, 26(4):  671.  doi:10.1109/JSEE.2015.00074
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The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise contained in the transferred signal, and the additional power will be consumed. Therefore, a method based on wavelet packet de-noising (WPD) is introduced. Compared with other techniques, there are two features making WPD more suitable to be applied to satellite transponders: one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especially for wideband signals. Besides, an oscillation detector and an averaging filter are added to decrease the partial oscillation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm can reduce more noises and make less distortions of the signals than other techniques. In addition, up to 12 dB additional power consumption can be reduced at –10 dB signal-to-noise ratio (SNR).

Semidefinite programming approach for TDOA/GROA based source localization
Yanshen Du, Ping Wei, and Huaguo Zhang
2015, 26(4):  680.  doi:10.1109/JSEE.2015.00075
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Time-differences-of-arrival (TDOA) and gain-ratios-ofarrival (GROA) measurements are used to determine the passive source location. Based on the measurement models, the constrained weighted least squares (CWLS) estimator is presented. Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem (SDP), which can be solved by using modern convex optimization algorithms. Moreover, this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good performance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.

Wideband direction-of-arrival estimation based on cubic spline function
Hongqi Yu, David Day-Uei Li, Kun Zhang, Jietao Diao, and Haijun Liu
2015, 26(4):  688.  doi:10.1109/JSEE.2015.00076
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A new direction-of-arrival (DOA) estimation algorithm for wideband sources is introduced. The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation techniques. The narrowband highresolution algorithm is then used to get the DOA estimation. This
technique does not require any preliminary knowledge of DOA angles. Simulation results demonstrate the effectiveness of the method.

Full-duplex prototype based on joint passive and digital cancellation method
Di Wu, Can Zhang, Shaoshuai Gao, and Heping Zhao
2015, 26(4):  694.  doi:10.1109/JSEE.2015.00077
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Recent research shows that it is possible to achieve the full-duplex system by cancelling strong self-interference signals, which can be divided into three classes respectively, i.e., passive cancellation, active cancellation and digital cancellation. This paper tries to achieve the full-duplex system without using active cancellation, thus a full-duplex system using a joint mechanism based on a novel passive cancellation method and a novel digital cancellation method is proposed. Therein, a good antenna placement guided by the theory of the antenna electromagnetic field for the passive cancellation is presented. For the proposed digital cancellation method, unlike previous separate mechanisms, it is designed by using the recursive least square (RLS) algorithm jointly with passive cancellation. The self-interference channel state information (CSI) is transferred as the input of digital cancellation to balance the performance and the complexity. Experimental results show that the proposed self-interference cancellation mechanism can achieve about 85 dB which is better than the previous research. Meanwhile, this design provides a better performance compared with half-duplex with both line-of-sight channel and nonline-of-sight channel.

Adaptive coherence estimator based on the Krylov subspace technique for airborne radar  
Weijian Liu, Wenchong Xie, Haibo Tong, Honglin Wang, Cui Zhou, and Yongliang Wang
2015, 26(4):  705.  doi:10.1109/JSEE.2015.00078
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A novel adaptive detector for airborne radar space-time adaptive detection (STAD) in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator (ACE). It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher probability of detection (PD), especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate (CFAR).

ISAR active jamming method based on sinusoidal modulation
Yu Zhang, Congfeng Liu, and Yan Zhu
2015, 26(4):  713.  doi:10.1109/JSEE.2015.00079
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It is potentially useful to perform deception or cover jamming using the rotating angular reflectors since they can form deception echoes along range and azimuth. Inspired by the coherent jamming and micro-motion modulation, a novel active method is proposed for inverse synthetic aperture radar (ISAR). Radar pulses are sampled and frequency-modulated along azimuth by sinusoidal signal, and then the jamming signals are retransmitted to the radar and the jamming images are induced after ISAR imaging. Therein, the jamming principle, key parameters and the jamming effect are discussed. The simulated data verify the effectiveness of the jamming method.

Target detection and recognition in SAR imagery based on KFDA
Fei Gao, Jingyuan Mei, Jinping Sun, Jun Wang, Erfu Yang, and Amir Hussain
2015, 26(4):  720.  doi:10.1109/JSEE.2015.00080
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Current research on target detection and recognition from synthetic aperture radar (SAR) images is usually carried out separately. It is difficult to verify the ability of a target recognition algorithm for adapting to changes in the environment. To realize the whole process of SAR automatic target recognition (ATR), especially for the detection and recognition of vehicles, an algorithm based on kernel fisher discriminant analysis (KFDA) is proposed. First, in order to make a better description of the difference between the background and the target, KFDA is extended to the detection part. Image samples are obtained with a dual-window approach and features of the inner and outer window samples are extracted by using KFDA. The difference between the features of inner and outer window samples is compared with a threshold to determine whether a vehicle exists. Second, for the target area, we propose an improved KFDA-IMED (image Euclidean distance) combined with a support vector machine (SVM) to recognize the vehicles. Experimental results validate the performance of our method. On the detection task, our proposed method obtains not only a high detection rate but also a low false alarm rate without using any prior information. For the recognition task, our method overcomes the SAR image aspect angle sensitivity, reduces the requirements for image preprocessing and improves the recognition rate.

Application of DFT in bi-static RCS calculation of complex electrically large targets
Kuisong Zheng, Tengjiang Ding, Hui Yu, and Zhaoguo Hou
2015, 26(4):  732.  doi:10.1109/JSEE.2015.00081
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To handle the electromagnetic problems of the bi-static radar cross section (RCS) calculation of scatterer in a wide frequency band, a finite-difference time-domain (FDTD) extrapolation method combining with discrete Fourier transform (DFT) is proposed. By comparing the formulas between the steady state field extrapolation method and the transient field extrapolation method, a novel extrapolation method combining with DFT used in FDTD is proposed when a transient field incident wave is introduced. With the proposed method, the full-angle RCS distribution in a wide frequency band can be achieved through one-time FDTD calculation. Afterwards, the back-scattering RCS distributions of a double olive body and a sphere-cone body are calculated. Numerical results
verify the validity of the proposed method.

Optimal ship imaging for shore-based ISAR using DCF estimation
Ling Wang, Zhenxiao Cao, Ning Li, Teng Jing, and Daiyin Zhu
2015, 26(4):  739.  doi:10.1109/JSEE.2015.00082
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The optimal imaging time selection of ship targets for shore-based inverse synthetic aperture radar (ISAR) in high sea conditions is investigated. The optimal imaging time includes optimal imaging instants and optimal imaging duration. A novel method for optimal imaging instants selection based on the estimation of the Doppler centroid frequencies (DCFs) of a series of images obtained over continuous short durations is proposed. Combined with the optimal imaging duration selection scheme using the image contrast maximization criteria, this method can provide the ship images with the highest focus. Simulated and real data processing results verify the effectiveness of the proposed imaging method.

Tracking a maneuvering target in clutter with out-of-sequence measurements for airborne radar
Weihua Wu, Jing Jiang, and Yang Wan
2015, 26(4):  746.  doi:10.1109/JSEE.2015.00083
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There are many proposed optimal or suboptimal algorithms to update out-of-sequence measurement(s) (OoSM(s)) for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clutter, an interacting multiple model probabilistic data association (IMMPDA) algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed (ECEF) coordinate system where it considers the effect of the platform’s attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the performance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the tracking performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.

Modeling and verifying SoS performance requirements of C4ISR systems
Yudong Qi, Zhixue Wang, Qingchao Dong, and Hongyue He
2015, 26(4):  754.  doi:10.1109/JSEE.2015.00084
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System-of-systems (SoS) engineering involves a complex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capability objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and nonfunctional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnaissance (C4ISR) systems. A domain-specific modeling language is defined by extending unified modeling language (UML) constructed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An efficiency evaluation function is introduced, based on B´ezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic (DL) so that requirements verification can be automated with a popular DL reasoner such as Pellet.

Multi-criteria group decision making with fuzzy data: an extension of the VIKOR method
Wenqi Jiang and Jennifer Shang
2015, 26(4):  764.  doi:10.1109/JSEE.2015.00085
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The VIKOR method is a multi-criteria decision making aid, which employs linear normalization to offer compromise solutions and has been successfully applied to various group decision making problems. However, the conventional VIKOR techniques used to integrate group judgments and the information loss arising from defuzzification are problematic and distort final outcomes. An improved integration method, which is optimization-based, is proposed. And it can handle fuzzy criteria values and weights. The precondition for accurately defuzzifying triangular fuzzy numbers is identified. Several effective defuzzification procedures are proposed to improve the extant VIKOR, and a comprehensive evaluation framework is offered to aid multi-criteria group decision making. Finally, a numerical example is provided to illustrate the practicability of the proposed method.

Entropy measures of type-2 intuitionistic fuzzy sets and type-2 triangular intuitionistic trapezodial fuzzy sets
Zhensong Chen, Shenghua Xiong, Yanlai Li, and Kwai-Sang Chin
2015, 26(4):  774.  doi:10.1109/JSEE.2015.00086
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In order to measure the uncertain information of a type-2 intuitionistic fuzzy set (T2IFS), an entropy measure of T2IFS is presented by using the constructive principles. The proposed entropy measure is also proved to satisfy all of the constructive principles. Further, a novel concept of the type-2 triangular intuitionistic trapezoidal fuzzy set (T2TITrFS) is developed, and a geometric interpretation of the T2TITrFS is given to comprehend it completely or correctly in a more intuitive way. To deal with a more general uncertain complex system, the constructive principles of an entropy measure of T2TITrFS are therefore proposed on the basis of the axiomatic definition of the type-2 intuitionistic fuzzy entropy measure. This paper elicits a formula of type-2 triangular intuitionistic trapezoidal fuzzy entropy and verifies that it does satisfy the constructive principles. Two examples are given to show the efficiency of the proposed entropy of T2TITrFS in describing the uncertainty of the type-2 intuitionistic fuzzy information and illustrate its application in type-2 triangular intuitionistic trapezoidal fuzzy decision making problems.
Comprehensive optimized GM(1,1) model and application for short term forecasting of Chinese energy consumption and production
Ning Xu, Yaoguo Dang, and Jie Cui
2015, 26(4):  794.  doi:10.1109/JSEE.2015.00087
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In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel comprehensively optimized GM(1,1) model, also named COGM(1,1), based on the grey modeling mechanism. First, the relationship of the background value formula and its whitenization equation is analyzed and a new method optimizing background values is proposed to eliminate systemic errors in the modeling process. Second, the solving process of the new model is derived. For parameter estimation, a set of auxiliary parameters are used to change grey equation’s form. Then, original parameters are restored by an equations system. After solving the whitenization equation, initial value in time response function is established by least errors criteria. Finally, a numerical case and comparison with other grey prediction models are made to testify the new model’s effectiveness, and the computational results show that the COGM(1,1) model has a better property and achieves higher precision. The new model is used to forecast China energy consumption and production, and the ability of energy self-sufficiency is further analyzed. Results indicate that gaps between consumption and production in future are predicted to decline.
BTT autopilot design for agile missiles with aerodynamic uncertainty
Yueyue Ma, Jie Guo, and Shengjing Tang
2015, 26(4):  802.  doi:10.1109/JSEE.2015.00088
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The approach to the synthesis of autopilot with aerodynamic uncertainty is investigated in order to achieve large maneuverability of agile missiles. The dynamics of the agile missile with reaction-jet control system (RCS) are presented. Subsequently, the cascade control scheme based on the bank-to-turn (BTT) steering technique is described. To address the aerodynamic uncertainties encountered by the control system, the active disturbance rejection control (ADRC) method is introduced in the autopilot design. Furthermore, a compound controller, using extended state observer (ESO) to online estimate system uncertainties and calculate derivative of command signals, is designed based on dynamic surface control (DSC). Nonlinear simulation results show the feasibility of the proposed approach and validate the robustness of the controller with severe unmodeled dynamics.
Hierarchical structured robust adaptive attitude controller design for reusable launch vehicles
Guangxue Yu and Huifeng Li
2015, 26(4):  813.  doi:10.1109/JSEE.2015.00089
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Reentry attitude control for reusable launch vehicles (RLVs) is challenging due to the characters of fast nonlinear dynamics and large flight envelop. A hierarchical structured attitude control system for an RLV is proposed and an unpowered RLV control model is developed. Then, the hierarchical structured control frame consisting of attitude controller, compound control strategy and control allocation is presented. At the core of the design is a robust adaptive control (RAC) law based on dual loop time-scale separation. A radial basis function neural network (RBFNN) is implemented for compensation of uncertain model dynamics and external disturbances in the inner loop. And then the robust optimization is applied in the outer loop to guarantee performance robustness. The overall control design frame retains the simplicity in design while simultaneously assuring the adaptive and robust performance. The hierarchical structured robust adaptive controller (HSRAC) incorporates flexibility into the design with regard to controller versatility to various reentry mission requirements. Simulation results show that the improved tracking performance is achieved by means of RAC.
Adaptive backstepping finite-time sliding mode control of spacecraft attitude tracking
Chutiphon Pukdeboon
2015, 26(4):  826.  doi:10.1109/JSEE.2015.00090
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This paper investigates the finite-time attitude tracking problem for rigid spacecraft. Two backstepping finite-time sliding mode control laws are proposed to solve this problem in the presence of inertia uncertainties and external disturbances. The first control scheme is developed by combining sliding mode control with a backstepping technique to achieve fast and accurate tracking responses. To obtain higher tracking precision and relax the requirement of the upper bounds on the uncertainties, a second control law is also designed by combining the second order sliding mode control and an adaptive backstepping technique. This control law provides complete compensation of uncertainty and disturbances. Although it assumes that the uncertainty and disturbances are bounded, the proposed control law does not require information about the bounds on the uncertainties and disturbances. Finite-time convergence of attitude tracking errors and the stability of the closed-loop system are ensured by the Lyapunov approach. Numerical simulations on attitude tracking control of spacecraft are provided to demonstrate the performance of the proposed controllers.
Feature extension and matching for mobile robot global localization
Peng Wang, Qibin Zhang, and Zonghai Chen
2015, 26(4):  840.  doi:10.1109/JSEE.2015.00091
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This paper introduces an indoor global localization method by extending and matching features. In the proposed method, the environment is partitioned into convex subdivisions. Local extended maps of the subdivisions are then built by extending features to constitute the local extended map set. While the robot is moving in the environment, the local extended map of the current local environment is established and then matched with the local extended map set. Therefore, global localization in an indoor environment can be achieved by integrating the position and orientation matching rates. Both theoretical analysis and comparison experimental result are provided to verify the effectiveness of the proposed method for global localization.
Task scheduling and virtual machine allocation policy in cloud computing environment
Xiong Fu and Yeliang Cang
2015, 26(4):  847.  doi:10.1109/JSEE.2015.00092
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Cloud computing represents a novel computing model in the contemporary technology world. In a cloud system, the computing power of virtual machines (VMs) and network status can greatly affect the completion time of data intensive tasks. However, most of the current resource allocation policies focus only on network conditions and physical hosts. And the computing power of VMs is largely ignored. This paper proposes a comprehensive resource allocation policy which consists of a data intensive task scheduling algorithm that takes account of computing power of VMs and a VM allocation policy that considers bandwidth between storage nodes and hosts. The VM allocation policy includes VM placement and VM migration algorithms. Related simulations show that the proposed algorithms can greatly reduce the task completion time and keep good load balance of physical hosts at the same time.
Monitoring time property in time-sensitive LSC
Haiyang Xu, Yi Zhuang, and Jingjing Gu
2015, 26(4):  857.  doi:10.1109/JSEE.2015.00093
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In order to accurately describe the software requirements and automatically extract property formulas, the time property of the live sequence chart (LSC) is focused. For the timesensitive LSC (TLSC), the formal syntax and semantic are defined by introducing the formal definitions of clock and timing constraints. The main function of the TLSC is to extract the temporal logic formula, so basic rules and combination rules are proposed to translate the TLSC into the universal fragment of computation tree logic (CTL) formula. To improve the efficiency of model check, transitivity is also used to optimize the formula. The optimization method could reduce the size of the formula under the condition of equivalence. Finally, a case study is introduced to illustrate how to establish the TLSC of requirements. In terms of the proposed transformation rules, the time property formula is extracted from the TLSC, and the design model is assured which is consistent with the property formula. The results show that the method with respect to the automatic extraction of the logic formula from the TLSC can efficiently monitor the time property of software systems.
Numerical differentiation of noisy data with local optimum by data segmentation
Jianhua Zhang, Xiufu Que, Wei Chen, Yuanhao Huang, and Lianqiao Yang
2015, 26(4):  868.  doi:10.1109/JSEE.2015.00094
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A new numerical differentiation method with local optimum by data segmentation is proposed. The segmentation of data is based on the second derivatives computed by a Fourier development method. A filtering process is used to achieve acceptable segmentation. Numerical results are presented by using the data segmentation method, compared with the regularization method. For further investigation, the proposed algorithm is applied to the resistance capacitance (RC) networks identification problem, and improvements of the result are obtained by using this algorithm.
Immune adaptive Gaussian mixture particle filter for state estimation
Wenlong Huang, Xiaodan Wang, Yi Wang, and Guohong Li
2015, 26(4):  877.  doi:10.1109/JSEE.2015.00095
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The particle filter (PF) is a flexible and powerful sequential Monte Carlo (SMC) technique capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. However, the generic PF suffers from particle degeneracy and sample impoverishment, which greatly affects its performance for nonlinear, non-Gaussian tracking problems. To deal with those issues, an improved PF is proposed. The algorithm consists of a PF that uses an immune adaptive Gaussian mixture model (IAGM) based immune algorithm to re-approximate the posterior density. At the same time, three immune antibody operators are embed in the new filter. Instead of using a resample strategy, the newest observation and conditional likelihood are integrated into those immune antibody operators to update the particles, which can further improve the diversity of particles, and drive particles toward their close local maximum of the posterior probability. The improved PF algorithm can produce a closed-form expression for the posterior state distribution. Simulation results show the proposed algorithm can maintain the effectiveness and diversity of particles and avoid sample impoverishment, and its performance is superior to several PFs and Kalman filters.
Approximate trace and singleton failures equivalences for transition systems
Chao Wang, Jinzhao Wu, and Hongyan Tan
2015, 26(4):  886.  doi:10.1109/JSEE.2015.00096
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Established system equivalences for transition systems, such as trace equivalence and failures equivalence, require the observations to be exactly identical. However, an accurate measurement is impossible when interacting with the physical world, hence exact equivalence is restrictive and not robust. Using Baire metric, a generalized framework of transition system approximation is proposed by developing the notions of approximate language equivalence and approximate singleton failures (SF) equivalence. The framework takes the traditional exact equivalence as a special case. The approximate language equivalence is coarser than the approximate SF equivalence, just like the hierarchy of the exact ones. The main conclusion is that the two approximate equivalences satisfy the transitive property, consequently, they can be successively used in transition system approximation.