2010 Vol. 19, No. 3

Display Method:
Multiple Linear Cryptanalysis of Reduced-Round SMS4 Block Cipher
Liu Zhiqiang, Gu Dawu, Zhang Jing
2010, 19(3): 389-393.
Abstract(486) PDF(1000)
SMS4 is a 32-round block cipher with 128-bit block size and key size. It has been widely implemented in Chinese WLAN industry. In this paper, we present a modified branch-and-bound algorithm which can be used for searching multiple linear characteristics for SMS4-like block ciphers. Furthermore, we find a series of 5-round iterative linear characteristics of SMS4. Then based on these 5-round iterative linear characteristics, a list of 18-round linear characteristics of SMS4 can be constructed. According to the framework of Biryukov et al from Crypto 2004, a key recovery attack can be mounted on 22-round SMS4 by utilizing the above 18-round linear characteristics. The data complexity of our attack is 2112 known plaintexts. Compared with the previously best cryptanalytic results on 22-round SMS4 (that is, the previously best cryptanalytic results on SMS4), our result has much lower data complexity as well as comparable time complexity and memory complexity.
A Bayesian Reinforcement Learning Algorithm Based on Abstract States for Elevator Group Scheduling Systems
Cheng Yuhu, Wang Xuesong, Zhang Yiyang
2010, 19(3): 394-398.
Abstract(600) PDF(1115)
In order to solve the curse of dimensionality problem encountered by reinforcement learning algorithms for Elevator group scheduling (EGS) systems with large-scale state space, a kind of Bayesian reinforcement learning algorithm based on Abstract states (BRL-AS) was proposed. On one hand, an abstract state space whose size is much smaller than that of the original state space was constructed by analyzing the motion situations of EGS systems. On the other hand, a Bayesian network was used to carry out an inference operation on the abstract states and to obtain discrete real-valued variables, which is not only suitable for numerical computation of neural networks, but also can further reduce the size of the state space. The neural network model used for value-function approximating based on the inference output of the Bayesian network not only can solve the problem of continuous space expression of reinforcement learning system, but also can improve the system learning speed due to its simple topology structure. Simulation results of an EGS system for typical traffic profiles verify the feasibility and validity of the proposed reinforcement learning scheduling algorithm.
A Novel Pauli Evolutionary Quantum Algorithm for Combinatorial Optimization
Xiong Yan, Liang Xiao, Miao Fuyou
2010, 19(3): 399-402.
Abstract(596) PDF(878)
In this paper, a novel evolutionary quantum algorithm with Pauli mutation PEQA is proposed to solve the combinatorial optimization problem. PEQA utilizes quantum bit strings, quantum gate and Pauli mutation to obtain the best solution with only one individual in a short time. The analysis of Markov chain and empirical experiments on 0/1 knapsack problem are carried out. The results show that PEQA can outperform traditional genetic and quantum evolutionary algorithms.
Analysis and Comparison of NAND Flash Specific File Systems
Liu Shu, Guan Xuetao, Tong Dong, Cheng Xu
2010, 19(3): 403-408.
Abstract(552) PDF(776)
NAND flash memory becomes one of the most popular storage devices in embedded system and mobile computers. Efficient flash file system designs are important for system designers and users. In this paper, we study the design issues and performance of flash-specific file systems and define four performance metrics to evaluate flash file systems. Then, detailed comparisons of three mainstream flash file systems are conducted, including JFFS2, YAFFS2 and UBIFS. Taking techniques used in the three file systems and evaluation results into account, flash file system design space is discussed. This paper can provide users a comprehensive understanding of NAND flash file system design, present guidelines for measurement of flash file systems and help users determine which file system best meets their need.
Credit-HC: An I/O-friendly CPU Scheduler for Xen
Xia Yubin, Yang Chun, Niu Yan, Cheng Xu
2010, 19(3): 409-413.
Abstract(648) PDF(928)
Recent advances in virtualization technologies make the VM (Virtual machine) based server consolidation attractive for reducing cost and improving efficiency in enterprise computing. However, on a Xen-based platform, the I/O performance of a VM degrades significantly as the degree of consolidation increases, even if the VM is configured to have enough CPU share. This paper analyzes this phenomenon and identifies the reason as the mismatch between the CPU scheduler of Xen and its I/O architecture. We therefore present four enhancements for the CPU scheduler, including preempt-back, no-preemption of driver domain, block-bonus, and more fine-grained accounting. These enhancements are applied into our newly developed I/O-friendly CPU scheduler, namely Credit-HC (Credit-based high-consolidation-oriented) scheduler. The evaluation results show that with Credit-HC, one VM's I/O performance is nearly irrelevant to other domains' CPU workload, while the overhead is negligible. Moreover, the fairness of CPU share is kept as well.
A Sequence Kernel Method for Chinese Subcategorization Analysis
Han Xiwu, Yu Mo, Zhu Conghui, Zhao Tiejun
2010, 19(3): 414-418.
Abstract(589) PDF(935)
There have been a lot of researches focusing on large-scaled automatic acquisition of subcategorization frames, and many achievements have been made for lexicon building in quite a few languages, but subcategorization analysis for individual sentences still remains in a rarely touched field. This paper proposed to analyze Chinese subcategorization as a classification task by means of sequence kernel methods, which exploited the potential relations among the respective sentential constituents. Our final classification with word sequence kernel congregation and Part-of-speech (POS) sequence kernel C-support vector machine (C-SVM) achieved a very promising accuracy ratio of 92.36% on the testing set, which is 13.51% higher than the baseline performance of the existing Chinese subcategorization hypothesis generator.
Research on a Synchronization Algorithm of Look-up Table in Open Reconfigurable Router
Wu Xiaochun, Wu Chunming, Jia Fenggen
2010, 19(3): 419-422.
Abstract(522) PDF(748)
Reconfigurable router with fast look-up table synchronization mechanism is necessary for Next generation network (NGN), which facilitates open and fast deployment of new services. Based on an open architecture, standard and highly credible interfaces among modules, a synchronization mechanism of the routing table and FIB (Forwarding information base) is put forward in this paper which is applicable to other look-up tables. This synchronization mechanism overcomes the inconsistency of look-up tables brought by the dynamic loading or unloading of forwarding planes. Anomalies can be rapidly discovered and eliminated by adding the appropriate synchronization messages to multi-queue, calculating the 16-bit Checksum in look-up table and resending parts of look-up table entries to the forwarding planes. A reconfigurable router prototype is built to simulate the scene. The results show that the proposed algorithm can realize high consistency and quick recovery in look-up tables, which improve stability and reliability of the reconflgurable router.
Combined Effects of the Structural Deformation and Temperature on Magnetic Characteristics of the Single-walled Chiral Toroidal Carbon Nanotubes
Zhang Zhenhua, Li Qiaohua
2010, 19(3): 423-426.
Abstract(617) PDF(782)
The effects of the structural deformation on magnetic characteristics of the single-walled chiral Toroidal carbon nanotube (TCNT) at a given temperature are investigated theoretically by using the tight-binding model. The results show that the persistent currents in a TCNT are very sensitive to the deformations. When the strain reaches 2% at T = 10K, the persistent currents in the (2,5, 360,480) metallic TCNT and the (2,5, 300,400) semi-conducting TCNT decline by about six and five orders of magnitude, respectively. It suggests that at a finite temperature the TCNT electromechanical system may possess important potential applications for making physical sensors (e.g. pressure sensors).
Topological Characterization of Consistency of Logic Theories in n-valued Lukasiewicz Logic Luk(n)
She Yanhong, Wang Guojun, He Xiaoli
2010, 19(3): 427-430.
Abstract(613) PDF(586)
Let (F(S),p) be the n-valued logic metric space, the present paper characterizes consistency of logic theories in the propositional logic system Luk(n) by means of topological concepts in the n-valued logic metric space. It is proved that a closed theory Gamma is consistent iff it contains no interior points, iff it possesses the truth-forgotten property, iff it contains no non-empty regular sphere.
Access Control Lists for Object-Based Storage Systems
Niu Zhongying, Zhou Ke, Feng Dan, Yang Tianming
2010, 19(3): 431-436.
Abstract(580) PDF(719)
We developed an Access control list (ACL) mechanism for object-based storage systems. The proposed ACL mechanism affords Object-based storage devices (OSDs) much more flexibility in managing who can and how she accesses the object and makes it possible to implement completely distributed security for object-based storage systems. By enabling the ACL capability of inheritance and sharing, the mechanism reduces the number of ACLs needing to be stored and maintained. And by allowing the use of public key certificates as identifications of remote users, our ACL mechanism allows access control to extend beyond the local machine's realm to acrossorganizational users. Experimental results show that the overhead of access control is sufficiently small, with a bandwidth overhead of no more than 5%.
A Novel Measure on Inversion Degree of Undoped Symmetric Double-Gate MOSFETs
2010, 19(3): 437-440.
Abstract(552) PDF(729)
The relation between the surface potentials of undoped SDG (Symmetric double-gate) MOSFET (Metal-oxide-silicon field effect transistor) and SG (Single-gate) MOSFET is carefully examined. A new quantity, called coupling potential, is introduced. It can be shown that the coupling potential offers an excellent measure on the inversion degree of undoped SDG MOSFET.
Arbitrary-Order Approximate Solution to Integral State Equation for Generalized Affine Nonlinear Systems
Cao Shaozhong, Li Yang, Tu Xuyan
2010, 19(3): 441-445.
Abstract(530) PDF(834)
Compared with affine system, the generalized affine system is one more universal nonlinear control system, in which both state variables and control variables are nonlinear. In this paper, from the differential equation of generalized affine nonlinear system, the solution of its homogeneous equation is obtained. The differential equation is converted to the fully equivalent integral equation by the method of variation of parameters. Therefore, the recursion formula of the approximate solution to integral equation is given by heuristic method. And then based on the recursion formula, the arbitrary-order approximate series solution to integral equation is obtained. And the theory of integral equation is employed to prove the convergence.
A Real-time Compensation Strategy for Non-contact Gaze Tracking Under Natural Head Movement
Huang Ying, Wang Zhiliang, Tu Xuyan
2010, 19(3): 446-450.
Abstract(600) PDF(752)
Accompany with the development of the computer vision, non-contact gaze tracking is getting more mature. As a new interactive way for the human-computer interaction, promoting the usability of the technique has become the focus of research. The technique proposed in this paper is designed for enhancing the gaze tracking's adaptability for the natural head movement and also retaining its nice performance in real time. A head movement compensation strategy is presented for the gaze tracking based on single camera with fixed wide view. The head movement and eyeball rotation are calculated by the unified vision system, which can avoid time consuming on adjusting the view of the camera. And the effects of head movement and eyeball rotation are considered simultaneously for rectifying the gaze direction calculation. According to the evaluations in practice, the compensation strategy makes the accuracy achieve about 10 with the head moving over a field of 20 x 15 x 15cm(3). And its performance in real time can basically meet the requirement for everyday interaction.
Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation
2010, 19(3): 451-456.
Abstract(585) PDF(968)
Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.
Efficient System Combination for Chinese Spoken Term Detection
Gao Jie, Shao Jian, Zhao Qingwei, Yan Yonghong
2010, 19(3): 457-462.
Abstract(563) PDF(753)
This paper examines system combination issue for Syllable-confusion-network (SCN) -based Chinese Spoken term detection (STD). System combination for STD usually leads to improved accuracy but suffers from increased index size or complicated index structure. But in the scenarios where the index size and search speed are critical, a single compact index is highly desirable. Therefore we explore methods for efficient combination of a word-based system and a syllable-based system while keeping the compactness of the indices. First, a composite SCN is generated using two approaches: lattice combination and confusion network combination. Then a simple compact index is constructed from this composite SCN by merging cross-system redundant information. The experimental result on a 60-hour corpus shows that a relative accuracy improvement of 16.20% is achieved over the baseline syllable-based system. Meanwhile, it reduces the index size by 22.3% compared to the commonly adopted score combination method under comparable accuracy.
FRFT Based Parameter Estimation of the Quadratic FM Signal
2010, 19(3): 463-467.
Abstract(627) PDF(962)
This paper generalizes the Fractional Fourier transform (FRFT) to estimate the parameters of the Quadratic frequency modulated (QFM) signal. Firstly, the proposed algorithm transforms the QFM signal into the Linear frequency modulated (LFM) signal by means of the instantaneous autocorrelation function, and then the parameter estimation of the QFM signal is performed by the FRFT and dechirping method. In order to calculate discrete sampling values of the FRFT, an adaptive FRFT algorithm based on the Least mean square (LMS) is proposed. Extension to the multicomponent and higher order frequency modulated signals is also discussed. Finally, the effects of delay parameter on estimation performances are investigated through Monte Carlo simulations and the results of simulations verify the effectiveness of the proposed algorithm.
A Novel Analog and Digital Weighting Approach for Sum and Difference Beam of Planar Array at Subarray Level
Hu Hang, Liu Weihui
2010, 19(3): 468-472.
Abstract(572) PDF(658)
Aim at planar array radar, this paper investigated an approach which only applies one kind of analog weighting at element level to suppress sidelobes of sum and difference beam simultaneously. Consequently, sum and difference channels were constructed, and the analog weights were determined by making optimal adaptive filtering for the supposed interferences within the sidelobe area. In order to improve sidelobe suppression effect, digital weighting at subarray level was adopted, which was used to approximate the patterns obtained by the Taylor or Bayliss weight. The proposed approach reduces the hardware cost and complexity. Simulation results demonstrate its validity.
Measuring Method of Eyes Diopter Based on Image Measuring Technology
2010, 19(3): 473-476.
Abstract(581) PDF(1786)
Measuring system of eyes diopter is designed with diopter adjustment theory of visual optics and image measuring technology. Measuring methods of presbyopia, myopia, hyperopia and astigmatism are discussed. A link image is projected to the measured eye ground, and then the reflection image is measured from eye ground by CCD device. Finally, size and shape of the image are automatically recognized by computer. Far point diopter and near point diopter are measured according to the method. Far point diopter is defined as the fitting glasses parameters of hyperopia, myopia and astigmatism. Fitting glasses parameters of presbyopia are related to far point diopter and near point diopter. Calculation methods of fitting glasses parameters are given. Because measuring methods utilize advantages of subjective optometry and objective optometry, fitting glasses parameters may be quickly and accurately measured.
Recursion Subspace-based Method for Bearing Estimation: A Comparative Study
Huang Lei, Wu Siliang, Mao Erke
2010, 19(3): 477-480.
Abstract(548) PDF(810)
In many practical applications of sensor array processing, accurate bearing estimation with low complexity is of significant interest. In this paper, we present a Recursion subspace-based method (RSM) to estimate the bearings of incident signals impinging on a Uniform linear array (ULA), and perform the comparison between the RSM method and the signal Subspace method without eigendecomposition (SUMWE). Numerical results are presented to compare the performance the RSM method with that of the SUMWE method.
A Digital Interface-based Digital Rights Management Scheme for Digital Cinema
2010, 19(3): 481-485.
Abstract(564) PDF(675)
Digital rights management (DRM) is indispensable to prevent various kinds of illegal content usage. In this paper, we present a Digital interface-based DRM scheme (DI-DRM) for digital cinema, which can provide a new multi-interfaces oriented DRM solution for digital cinema. The authentication protocol and the encryption algorithm are described in detail. The two kinds of digital interfaces-based DRM prototype system are developed. Security and performance analysis show the proposed scheme has several advantages. First, it is more secure than the existing scheme. Second, it is supported more rights, including the downstream devices. Finally, the cost of the chip based on DI-DRM is low. The scale of SOC application scheme is only 1/3 to 1/6 of the existing DTCP.
Degree-Based Replica Placement Algorithms for P2P Data Grids
Ren Xunyi, Wang Ruchuan, Kong Qiang, Chen Danwei
2010, 19(3): 486-490.
Abstract(569) PDF(627)
Replica placement, which decides when and where to create replicas, is an important technique for improving the efficiency of data grids. In this paper, degree is employed for replica replacement in P2P data grids. Two replica placement algorithms, Degree-based algorithm (DA) and Degree-frequency-based algorithm (DFA), are proposed. In DA and DFA we set a degree threshold p and a frequency threshold v to choose the candidate replica locations and a replica is placed in the candidate node which gives the minimum access cost. Simulation results showed that DA and DFA both can keep smaller Makespan and reduce the number of replicas compared with Simple, AlwaysReplica, and Ecomodel-Zipf. DFA proves to be superior to Frequency algorithms in reducing replica numbers, but DA can reduce Makespan more. In addition, we have studied the optimal parameters for the proposed algorithms.
A Network Layer Mechanism Perceiving AP-ID for PFMIPv6
2010, 19(3): 491-494.
Abstract(514) PDF(725)
All radio access technologies can not ensure that the Previous mobile access gateway (PMAG) can retrieve the identifier of the New access point (N-AP-ID) as required by the current predictive PFMIPv6. Neither can they ensure that the New MAG (NMAG) can obtain the identifier of the Previous access point (P-AP-ID) as required by the current reactive PFMIPv6. To tackle this problem, a network layer mechanism perceiving AP-ID for PFMIPv6 is proposed. It employs API for the Mobile node (MN) network layer to acquire the information of AP-ID and reuses the existing ICMP messages to convey the information to MAG. Minimum required extension of messages is defined and detailed message sequence charts are elaborated for both predictive and reactive PMIPv6. Technical features and performance analysis are provided. Finally it is concluded that the proposed mechanism is future proof in that it can be used in conjunction with any possible radio access technologies.
Symbolic Computation and Lie Symmetry Groups for Two Nonlinear Differential-Difference Equations
Xuan Hengnong, Sun Mingming, He Tao
2010, 19(3): 495-498.
Abstract(561) PDF(712)
Based on the symbolic computation system-Maple, the symmetry group direct method is extended to investigate Lie symmetry groups of two differential-difference equations. Through analysis and tedious calculation, the full symmetry groups of the well-known D Delta-KP equation and Toda lattice equation are obtained. From them, both the Lie point symmetry groups and a group of discrete transformations can be obtained. Furthermore, based on the full symmetry groups and some simple solutions of these two equations, some general solutions are constructed.
A Grid-based Routing Algorithm with Cross-level Transmission to Prolong Lifetime of Wireless Sensor Networks
Liu Wenwei, Zhu Yihua, Pan Jian
2010, 19(3): 499-502.
Abstract(616) PDF(697)
In a Wireless sensor network (WSN) with multi-hop communications, nodes close to a sink drain more battery energy than others in relaying packets, which causes lifetime of the WSN to be shortened. To solve the uneven energy expenditure problem, we present a novel cluster-based routing algorithm, called Grid-based routing algorithm with cross-level transmission (GRACT), in which sensing field is divided into grids constituting several levels, a Cluster head (CH) is elected in each grid, and clusters are formed by letting each non-CH node join the closest CH. Under GRACT, a CH is only allowed to delivers its packets to the neighboring level and the cross level with ratios p and 1-p, respectively. Additionally, two Optimization models are presented to prolong lifetime of the WSN. Simulation results show that GRACT can balance the energy consumption among nodes and improve network lifetime.
Robust Design for Generalized Vector Precoding by Minimizing MSE with Imperfect Channel State Information
Geng Xuan, Jiang Lingge, He Chen
2010, 19(3): 503-506.
Abstract(544) PDF(712)
A robust design for Generalized vector precoding (GVP) is proposed in multi-user Multiple input multiple output (MIMO) downlink system. When the transmitter has imperfect Channel state information (CSI) due to channel estimation errors, the optimum perturbation vector and precoding matrix are derived based on Minimizing mean square error (MMSE) criterion by use of statis .ical information of channel errors. Simulation results show that the proposed precoder is more robust to imperfect CSI than conventional precoders.
Time-Variant Channel Estimation and Symbol Detection for MIMO/OFDM Systems Using Superimposed Training
2010, 19(3): 507-514.
Abstract(539) PDF(584)
Channel estimation for Multiple-input multiple-output/Orthogonal frequency-division multiplexing (MIMO/OFDM) systems in Time-varying (TV) wireless channels using Superimposed training (ST) is considered. The TV channel coefficients are firstly modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the TV channel over multiple OFDM symbols and the optimal training sequence is derived. We also present a performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to Information-pilot power ratios (IPPR). For the case that the training power is limited, we provide an iterative joint channel symbol detection scheme, where the recovered data symbol is utilized to enhance the performance by iteratively mitigate the information sequence interference to channel estimation. Simulations confirm that the proposed approach significantly outperforms the conventional ST, and compares well with that of frequency-division multiplexed trainings-based schemes.
Evolution Dynamic Behavior of Weighted Networks with Disadvantaged Long-Range Connection
Hu Jin, Wei Jiaolong, Huang Shuanglin, Peng Fuyuan
2010, 19(3): 515-520.
Abstract(581) PDF(688)
Complex networks have established themselves as being particularly suitable and flexible for representing and modeling several complex natural and society systems. In this paper, a model for the growth of weighted networks that couples the establishment of new edges and vertices and weights' dynamical evolution was proposed by analyzing the disadvantaged long-range connection behavior in weighted networks. In the model, we introduced the concepts of field strength and interaction-force in classic charge field theory to construct a simple field theory in networks. Based on interactive-force-driven network evolution dynamics, the model integrates the strength, topology, and distance. In order to present the networks generated by the model, a method to construct weighted networks on lattices was suggested. The networks generated by the model on lattices exhibit the statistical properties observed in several real-world systems. In particular, the model yields the spatial collectivization phenomenon, small world property, and scale-free behavior simultaneously.
Applying Chaotic Maps to Interleaving Scheme Design in BICM-ID
Zou Xuelan, Liu Weiyan, Feng Guangzeng
2010, 19(3): 521-524.
Abstract(539) PDF(1027)
Bit-Interleaved coded modulation with Iterative decoding (BICM-ID) is a bandwidth efficient transmission scheme which is suitable for next-generation wireless communication systems. In this paper we focused on the interleaver design based on the chaotic maps to further improve the performance of BICM-ID. We used the dispersion and correlation to analyze the performance of the interleavers. The chaotic interleaving schemes generated from the Logistic map, the Henon map and the Lozi map are provided which have better performance than the random interleaver when applied to BICM-ID. It shows that the inclusion of a chaotic vector increases the dispersion of the golden interleaver and improves the system performance. Simulation results in both Additive white Gaussian noise (AWGN) channel and Rayleigh fading channel are provided which demonstrate the effectiveness of the proposed approaches.
Active Location Detection of Adversaries in 802.11 wireless LAN (WLAN)
2010, 19(3): 525-531.
Abstract(588) PDF(789)
The growing interest in location based service and wireless security in WLAN necessitates the development of an effective scheme which can locate an attacker in a WLAN to make him account for his misdemeanors and expel him out of the network. On the other hand, while localization has been an active area of research recently, current research of secure localization mostly focuses on getting correct locations of legitimate users despite the existence of malicious attacks. There is little effort on how to locate an attacker who is equipped with advanced radio technologies to distort traditional localization system's location estimation. To fill in this challenging technical void, in this paper, a novel localization scheme is proposed, called ALD, which can locate the attacker with traditional range-free localization equipments. The main idea here is to use coordination of multiple APs to locate the attacker and optimize the process with a finite horizon discrete Markov decision process (MDP). An approximation algorithm is proposed to pre-compute the MDP efficiently. The solution then can be stored in APs without requiring any strong computation capability and special hardware. The ALD scheme can be supported by IEEE 802.11 and many other wireless network standards.
Network Utility Maximization for Mapping from Services to Paths
Li Shiyong, Zhang Hongke, Qin Yajuan
2010, 19(3): 532-537.
Abstract(560) PDF(706)
This paper investigates bandwidth allocation for services on multiple connections/paths in networks, and presents the mapping models from services to paths via connections based on Network utility maximization (NUM). Elastic services with concave utilities are firstly considered and the optimum of model can be obtained. Inelastic services with nonconcave (e.g., sigmoidal or discontinuous) utilities are also analyzed and the Models with certain QoS guarantee for these services are presented. These models are significant to QoS guarantee for inelastic services transferred over multiple paths. Numerical examples verify optimization of the models with QoS guarantee for inelastic services.
A New Method for Target Tracking with Debiased Consistent Converted Measurements in Direction Cosines
Zhang Boyan, Qu Hongquan, Li Shaohong
2010, 19(3): 538-542.
Abstract(630) PDF(1085)
In tracking applications, target dynamics is usually modeled in the Cartesian coordinates, while target measurements are got in the sensor coordinates, such as polar, spherical and direction cosine coordinates. Many well-known measurement-conversion techniques for polar and spherical measurements in mechanical rotating/scanning radars have been developed. However, they are not applicable to direction cosine measurements in electronic scanning radars, such as phased array radars. A new method directed to direction cosines measurements for target tracking with debiased consistent conversion (abb. CMKFDcos) is proposed. The converted measurements bias and covariance are explicitly derived. The consistency of converted measurements errors and the covariance is outlined. The simulation results validate that the converted measurements completely capture the true mean and covariance of the original measurements reported in direction cosines. The performance of CMKFDcos is superior to Extended Kalman filter (EKF) and Linear converted measurements KF (CMKFL) in accuracy and consistency for all practical situations. The proposed procedure can be employed in the cross-range errors being significantly large relative to the range errors with the efficiency and modest computational load.
Multipath Effects on the Performance of DLL in a GNSS Receiver
Jiang Yi, Zhang Shufang, Zhang Jingbo, Hu Qing, Sun Xiaowen
2010, 19(3): 543-547.
Abstract(586) PDF(914)
In order to improve the performance of a GNSS (Global navigation satellite system) receiver, multipath effects on common DLLs (Delay locked loops) are approached through comparisons with one coherent and three noncoherent DLLs under non-fading and fading conditions. The characteristics of multipath errors in DLL discriminators are analyzed and evaluated. Furthermore, the performance of DLL in the multipath fading environment is investigated and the methods to reduce multipath errors are derived. Finally, the method to select a proper DLL for a specialized multipath environment is provided which is helpful to design a high performance GNSS receiver.
Curvelet-Based Iterative Regularization and Inverse Scale Space Methods
2010, 19(3): 548-552.
Abstract(573) PDF(692)
For regularization theory of inverse problem in image processing, a challenge is to find a proper space in which the image is well characterized and hence restorable faithfully. Therefore, one contribution of this paper is to propose a novel variational regularization model with the help of decomposition space theory. Furthermore, as an development of it two models for image denoising are given, namely, Curve let-based Iterative regularization method (C-IRM) and Inverse scale spaces (C-ISS) method. Finally, experimental results on some standard test images as well as comparisons with some available methods show that the proposed methods work well in image edge preservation while achieving pleasant performance in terms of Signal-to-noise ratio (SNR).
Subsample Time Delay Estimation Based on Weighted Straight Line Fitting to Cross-Spectrum Phase
Bai Yechao, Zhang Xinggan, Qiu Xiaojun
2010, 19(3): 553-556.
Abstract(540) PDF(1039)
Time delay estimation (TDE) lies at the heart of signal processing algorithms, however, the accuracy of conventional TDE algorithms is limited by the sampling interval. An algorithm for TDE with accuracy less than one sampling period is presented in this paper. This algorithm estimates the integral time delay (taking sampling period as a unit) by locating the maximum of Cross-correlation function (CCF), and the fractional part by calculating the slope of the straight line obtained by applying weighted fitting to the cross-spectrum phase. The weight is deduced from Best linear unbiased estimator (BLUE). Estimating the integral part first can avoid phase wrapping. The simulations show that the algorithm outperforms other algorithms for wideband signals.
Towards Optimal Control Problems of Hybrid Impulsive and Switching Systems with Free Terminal States
Gao Rui
2010, 19(3): 557-562.
Abstract(523) PDF(686)
The global optimal control problem with free system terminal states is proposed for a special class of hybrid dynamical systems, Hybrid impulsive and switching systems (HISS). The necessary condition of the above problem, the HISS' minimum principle is given. In the proof of the above theorem, the general variational method and the matrix cost functional structure expression are employed. Based on this result, a special linear HISS is illustrated and the optimal control algorithm is derived. Moreover, the cases of pure impulsive systems and pure switched systems are considered in this paper.
Design and Implementation of Real-time High Squint Spotlight SAR Imaging Processor
Sun Jinping, Wang Jun, Hong Wen, Mao Shiyi
2010, 19(3): 563-568.
Abstract(606) PDF(1429)
For high squint mode spotlight Synthetic aperture radar (SAR) system without dechirp-on-receive function, a new imaging algorithm and the real-time processor implementation are presented. In this algorithm, high squint mode imaging processing is treated as broadside mode processing with special motion compensation. After the fast time delay correction and the phase compensation to echo data in azimuth time domain, conventional range Doppler method for broadside mode is applied to accomplish range curvature correction. Then, azimuth compression is achieved by azimuth scaling and Spectrum analysis (SPECAN) with non-uniform interpolation. Based on this algorithm, a practical real-time imaging processor is introduced. The effectiveness of the algorithm and the real-time processor is validated by point target simulations and real-time imaging result of real raw data.
“Time-Phase Derivatives” Distribution for Regular Signal with the Application in the Parameters Estimation of Polynomial Phase Signal
Wang Yong, Jiang Yicheng
2010, 19(3): 569-573.
Abstract(520) PDF(591)
A new concept-"Time-phase derivatives" distribution (TPDD) for the regular signal is presented and investigated in this paper. The TPDD is the extension form of the time-frequency distribution. The definitions of TPDD are given by the Exponential matched-phase transform (EMPT) and the High order bilinear matched-phase transform (HPT), and the corresponding TPDD illustrates the relationships of the phase derivatives, the time and the energy of the signal. Furthermore, the application of TPDD in the parameters estimation of Polynomial phase signal (PPS) is investigated. The results of Monte-Carlo simulations demonstrate that, the new approach can estimate the parameters with little computation and high precision.
Improved Way to Generate Multicarrier Complementary Phase-coded (MCPC) Radar Signal with Higher Resolution and Immunity
Gu Cunfeng, Law, Choi Look
2010, 19(3): 574-578.
Abstract(564) PDF(1058)
The contradictory requirements for Multicarrier complementary phase-coded (MCPC) radar signal parameters setting to improve delay/Doppler resolution and DC offset influence on MCPC radar performance had been analyzed. An improved way to generate MCPC signal and a Doppler resisted signal detection method were proposed. The proposed approach improved MCPC radar performance by modifying modulation sequences to adjust subcarrier spacing dynamically. Analysis and simulation result shows the new MCPC radar signal with the proposed detection approach has several properties including unchanged Doppler resolution, unchanged signal peak-to-mean envelope power ratio, improved delay resolution, higher Doppler tolerant and more immunity to phase noise. Furthermore, DC offset effects can be eliminated by adjusting subcarrier spacing to avoid signal modulation on zero frequency and around. By comparison with multicarrier bi-phase radar signal, which has large pulse compression ratio, the new MCPC radar signal has better delay resolution and auto-correlation properties with less subcarriers and bits.
Fast Converging Estimator for Covariance Matrix Structure of Compound-Gaussian Clutter
Jian Tao, He You, Su Feng, Ping Dianfa, Gu Xinfeng
2010, 19(3): 579-582.
Abstract(551) PDF(653)
In order to estimate the covariance matrix structure of compound-Gaussian clutter, a Fast converging estimator (FCE) is proposed. Moreover, for the match case, the FCE is independent of the clutter power levels. Furthermore, the simulation results show that the estimation accuracy of FCE improves as the one-lag correlation coefficient or the number of secondary data increases, but it is degraded as the number of pulses increases. In addition, the FCE is very robust with respect to different subsets. Compared to the existing estimators, the FCE accelerates convergence rate and improves estimation accuracy with moderate computational burden.