HIGH RESOLUTION PARAMETRIC MODELLING FOR TWO-DIMENSIONAL RADAR TARGET USING PRONY ALGORITHM

On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.

Two-dimensional cross entropy multi-threshold image segmentation based on improved BBO algorithm

In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.When using BBO algorithm to optimize threshold,firstly,the elitist selection operator is used to retain the optimal set of solutions.Secondly,a migration strategy based on fusion of good solution and pending solution is introduced to reduce premature convergence and invalid migration of traditional migration operations.Thirdly,to reduce the blindness of traditional mutation operations,a mutation operation through binary computation is created.Then,it is applied to the multi-threshold image segmentation of two-dimensional cross entropy.Finally,this method is used to segment the typical image and compared with two-dimensional multi-threshold segmentation based on particle swarm optimization algorithm and the two-dimensional multi-threshold image segmentation based on standard BBO algorithm.The experimental results show that the method has good convergence stability,it can effectively shorten the time of iteration,and the optimization performance is better than the standard BBO algorithm.

Design of a Two-dimensional Recursive Filter Using the Bees Algorithm

This paper presents the first application of the bees algorithm to the optimisation of parameters of a two-dimensional （2D） recursive digital filter. The algorithm employs a search technique inspired by the foraging behaviour of honey bees. The results obtained show clear improvement compared to those produced by the widely adopted genetic algorithm （GA）.

A Two-dimensional Genetic Algorithm Based on the Eno-Haar Wavelet Transform

A two-dimensional genetic algorithm of wavelet coefficient is presented by using the ENO wavelet transform and the decomposed characterization of the two-dimensional Haar wavelet. And simulated by the ENO interpolation the article shows the affectivity and the superiority of this algorithm.

Vertical two-dimensional non-hydrostatic pressure model with single layer

The vertical two-dimensional non-hydrostatic pressure models with multiple layers can make prediction more accurate than those obtained by the hydrostatic pres- sure assumption. However, they are time-consuming and unstable, which makes them unsuitable for wider application. In this study, an efficient model with a single layer is developed. Decomposing the pressure into the hydrostatic and dynamic components and integrating the x-momentum equation from the bottom to the free surface can yield a horizontal momentum equation, in which the terms relevant to the dynamic pressure are discretized semi-implicitly. The convective terms in the vertical momentum equation are ignored, and the rest of the equation is approximated with the Keller-box scheme. The velocities expressed as the unknown dynamic pressure are substituted into the continuity equation, resulting in a tri-diagonal linear system solved by the Thomas algorithm. The validation of solitary and sinusoidal waves indicates that the present model can provide comparable results to the models with multiple layers but at much lower computation cost.

Aheuristic Algorithm for Berth Scheduling Problem in Container Ports

In this paper,the berth scheduling problem is transformed into a special two-dimensional packing problem with some constraints.A nonlinear programming model for the problem is established,and a heuristic algorithm is proposed to solve the model.Simulation results show that the algorithm can improve the utilization of berths on discrete berth scheduling in the container port.

A reliable algorithm for image matching based on SIFT

A novel algorithm is presented to make the results of image matching more reliable and accurate based on SIFT (Scale Invariant Feature Transform). SIFT algorithm has been identified as the most resistant matching algorithm to common image deformations; however, if there are similar regions in images, SIFT algorithm still generates some analogical descriptors and provides many mismatches. This paper examines the local image descriptor used by SIFT and presents a new algorithm by integrating SIFT with two-dimensional moment invariants and disparity gradient to improve the matching results. In the new algorithm, decision tree is used, and the whole matching process is divided into three levels with different primitives. Matching points are considered as correct ones only when they satisfy all the three similarity measurements. Experiment results demonstrate that the new approach is more reliable and accurate.

Communication Resource Planning Algorithm Based on Time Triggered DIMA Architecture

Traditional scheduling algorithms for avionics communication have the shortcoming of messages accumulation,the efficiency and reliability of the service can be improved by combining the distributed integrated modular avionics(DIMA)system with a time trigger mechanism.To further improve the utilization of system resources,the static scheduling algorithm of time triggered service is studied.By making the time trigger message schedule dispersedly,the stabilities of both the available time slots for the event triggered messages and the system will be improved.An improved two-dimensional bin packing algorithm is also presented to achieve the above-mentioned purpose with an extra benefit of better delay performance.

Modified Omega-K algorithm for processing helicopter-borne frequency modulated continuous waveform rotating synthetic aperture radar data

With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With this capability, ROSAR has extensive potential applications, such as self-navigation and self-landing. Moreover, it has many advantages if combined with the frequency modulated continuous wave （FMCW） technology. A novel geometric configuration and an imaging algorithm for helicopter-borne FMCW-ROSAR are proposed. Firstly, by per- forming the equivalent phase center principle, the separated trans- mitting and receiving antenna system is equalized to the case of system configuration with antenna for both transmitting and receiving signals. Based on this, the accurate two-dimensional spectrum is obtained and the Doppler frequency shift effect in- duced by the continuous motion of the platform during the long pulse duration is compensated. Next, the impacts of the velocity approximation error on the imaging algorithm are analyzed in de- tail, and the system parameters selection and resolution analysis are presented. The well-focused SAR image is then obtained by using the improved Omega-K algorithm incorporating the accurate compensation method for the velocity approximation error. FJnally, correctness of the analysis and effectiveness of the proposed al- gorithm are demonstrated through simulation results.

Frequency modulated weak signal detection based on stochastic resonance and genetic algorithm

Stochastic resonance system is subject to the restriction of small frequency parameter in weak signal detection,in order to solve this problem,a frequency modulated weak signal detection method based on stochastic resonance and genetic algorithm is presented in this paper. The frequency limit of stochastic resonance is eliminated by introducing carrier signal,which is multiplied with the measured signal to be injected in the stochastic resonance system,meanwhile,using genetic algorithm to optimize the carrier signal frequency,which determine the generated difference-frequency signal in the lowfrequency range,so as to achieve the stochastic resonance weak signal detection. Results showthat the proposed method is feasible and effective,which can significantly improve the output SNR of stochastic resonance,in addition,the system has the better self-adaptability,according to the operation result and output phenomenon,the unknown frequency of the signal to be measured can be obtained,so as to realize the weak signal detection of arbitrary frequency.

Genetic Algorithms to the Nesting Problem in the Leather Manufacturing Industry

The nesting problem in the leather manufacturing is the problem of placing a set of irregularly shaped pieces (called stencils) on a set of irregularly shaped surfaces (called leathers sheets). This paper presents a novel and promising processing approach. After the profile of leather sheets and stencils is obtained with digitizer, the discretization makes the processing independent of the specific geometrical information. The constraints of profile are regarded thoroughly. A heuristic bottom-left placement strategy is employed to sequentially locate stencils on sheets. The optimal placement sequence and rotation are deterimined by genetic algorithms (GA). A natural concise encoding method is developed to satisfy all the possible requirements of the leather nesting problem. The experimental results show that the proposed algorithm can not only be applied to the normal two-dimensional nesting problem, but also especially suitable for the placement of multiple two-dimensional irregular stencils on multiple two-dimensional irregular sheets.

Two-dimensional entropy model for video shot partitioning

A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass for the task of video analysis, content-based video understanding. In this paper, a novel scheme based on improved two-dimensional entropy is proposed to complete the partition of video shots. Firstly, shot transition candidates are detected using a two-pass algorithm： a coarse searching pass and a fine searching pass. Secondly, with the character of two-dimensional entropy of the image, correctly detected transition candidates are further classified into different transition types whereas those falsely detected shot breaks are distinguished and removed. Finally, the boundary of gradual transition can be precisely located by merging the characters of two-dimensional entropy of the image into the gradual transition. A large number of video sequences are used to test our system performance and promising results are obtained.

Solving Systems of Transcendental Equations Involving the Heun Functions

The Heun functions have wide application in modern physics and are expected to succeed the hypergeometrical functions in the physical problems of the 21st century. The numerical work with those functions, however, is complicated and requires filling the gaps in the theory of the Heun functions and also, creating new algorithms able to work with them efficiently. We propose a new algorithm for solving a system of two nonlinear transcendental equations with two complex variables based on the Müller algorithm. The new algorithm is particularly useful in systems featuring the Heun functions and for them, the new algorithm gives distinctly better results than Newton’s and Broyden’s methods. As an example for its application in physics, the new algorithm was used to find the quasi-normal modes (QNM) of Schwarzschild black hole described by the Regge-Wheeler equation. The numerical results obtained by our method are compared with the already published QNM frequencies and are found to coincide to a great extent with them. Also discussed are the QNM of the Kerr black hole, described by the Teukolsky Master equation.

A new approach of extracting vegetation points from urban airborne LiDAR data

Urban vegetation has been an important indicator for the evaluation of eco-cities, which is of great significance to promote eeo-city construction. We study and discuss the commonly used urban vegetation extrac-tion methods. The extraction of vegetation points in this study is completed through mathematical statistics, mean-square error, successive differences and iterative algorithm which are based on the analysis of different spatial morphological characteristics in urban point clouds. Linyi, a city of Shandong Province in China, is se-lected as the study area to test this method and the result shows that the proposed method has a strong practicali- ty in urban vegetation point cloud extraction. Only 3D coordinate properties of the LiDAR point clouds are used in this method and it does not require additional information, for instance, return intensity, which makes the method more applicable and operable.

A MODIFIED SIMPLE ALGORITHM FOR 2-D FLOW IN OPEN CHANNEL

For two-dimensional wa ter flow in open channel, by discritizing hydrodynamic differential equation of conservative form, the corresponding algebraic equations were derived which invo lve the relationship between velocity and depth. Based on the relationship, this paper deduced a modified formula of velocity correction for SIMPLE algorithm. A s a test case, the flow in a prismatic channel with two different slopes was com puted and a good result was obtained.

利用双天线商用WiFi信道状态信息估计到达角

商用WiFi接收模块可以提供比接收无线信号强度指示(received signal strength indication,RSSI)更细粒的信道状态信息(channel state information,CSI),利用3根天线获取CSI进行方位到达角(angle of arrival,AOA)估计已成为现实。利用正交频分复用技术(orthogonal frequency division multiplexing,OFDM)将2根天线拓展为60个虚拟天线阵,将前向平滑算法拓展到二维前向平滑算法。利用仿真的非相干信号源和相干信号源数据进行实验,结果表明,在只利用2根接收天线的前提下也能实现基于商用WiFi信号的方位角的AOA估计,所提出的2根天线的虚拟天线阵模型和二维前向平滑算法具有有效性和适用性。

A Rapid and Automatic Optimal Design Method for Six-Stage Axial-Flow Industry Compressor

Existing aerodynamic design systems for multi-stage axial-flow compressor suffer from several limitations,such as experience dependent models and time costly simulations.Few attempts,however,have been devoted to the rapid and automatic optimization of aerodynamic performance at the preliminary design phase,which plays a crucial role in the final aerodynamic performance.In this work,a rapid and automatic aerodynamic optimal design method is developed for the multi-stage axial-flow compressor based on one-dimensional meanline design method,radial-equilibrium equation and genetic algorithm.The one-dimensional performance prediction model includes some popular empirical correlations to calculate the flow loss,incidence angle,deviation angle and flow blockage.The radial-equilibrium equation is solved to obtain the spanwise distribution of aerodynamic and thermodynamic parameters at the inlet and outlet of each blade row.The genetic algorithm is used for an automatic search of the global optimal compressor configuration aiming at maximizing the design efficiency.The developed method is illustrated with the aerodynamic optimal design of a 6-stage axial-flow industry compressor and verified by computational fluid dynamics simulations.The results show that the developed method is capable of improving effectively the design efficiency and predicting accurately the aerodynamic performance of the 6-stage axial-flow industry compressor in a few minutes.This work is of scientific significance to improve the axial-flow compressor design system and of engineering importance to release the designers from the heavy experience dependence especially at the preliminary design phase.

Alternating difference block methods and their difference graphs

The general concept of a class of alternating difference block methods and their difference graphs are introduced.The methods are unconditionally stable,and according to the difference graphs the design of parallel algorithms and programs of the methods are flexible and easy.The traditional alternating explicit-implicit method,the ADI method,the AGE method,the Block ADI method and the ABE-I method are all the special cases of this class of methods.Their difference graphs are presented.

Optimal Nesting for Continuous Shape Stamping Processes

WTFZ] This paper discusses the optimal nesting problem for minimizing the scrap in continuous shape stamping processes. The shape sliding technique is used to propose a new approach, OVERLAP-and-ESCAPE, to solve the problem of continuously nesting shapes onto a metal coil of fixed or selectable width. The approach is used to construct the objective function of the mathematical model of the problem using the Simulated Annealing Algorithm to determine the globally minimal configurations for the nesting problems. Some representative cases are studied and the results are encouraging. An automatic nesting software package for manufacturing bicycle chain link blanks is also described.[