Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

Geoacoustic inversion for sediments in the South China Sea based on a hybrid inversion scheme

We performed a long range acoustic propagation experiment in the South China Sea(SCS) in November 2004.The environment of the experiment was with an isothermal sound speed profile,where influence of water volume fluctuation was small,meaning that bottom parameters can be well estimated from acoustic signals.We inverted the acoustic parameters of sediment by using a hybrid inversion scheme that combines the matched field processing inversion with Hamilton sediment empirical relationship and transmission loss data.The numerical results show excellent agreement with the experiment data,indicating validity of the inverted parameters.

Matched Field Localization Based on CS-MUSIC Algorithm

The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.

Linear theory of beam–wave interaction in double-slot coupled cavity travelling wave tube

A three-dimensional model of the double-slot coupled cavity slow-wave structure （CCSWS） with a solid round elec- tron beam for the beam-wave interaction is presented. Based on the ＂cold＂ dispersion, the ＂hot＂ dispersion equation is derived with the Maxwell equations by using the variable separation method and the field-matching method. Through numerical calculations, the effects of the electron beam parameters and the staggered angle between adjacent walls on the linear gain are analyzed.

Source-Space Compressive Matched Field Processing for Source Localization

Source localization by matched-field processing （MFP） can be accelerated by building a database of Green＇s functions which however requires a bulk-storage memory. According to the sparsity of the source locations in the search grids of MFP, compressed sensing inspires an approach to reduce the database by introducing a sensing matrix to compress the database. Compressed sensing is further used to estimate the source locations with higher resolution by solving the β -norm optimization problem of the compressed Green＇s function and the data received by a vertieal/horizontal line array. The method is validated by simulation and is verified with the experimental data.

Fully automatic DOM generation method based on optical flow field dense image matching

Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.

Study of electrostatic-magnetic deflector for CEPC

Purpose As the key component for the Higgs operating mode of Circular Electron-Positron Collider(CEPC),the electrostatic-magnetic deflectors are required by the double ring collider to separate the electron and the positron beams horizontally in the RF regions.The electric field is required to reach 2 MV/m with the vacuum pressure of less than 2×10^(−10) Torr.The deflectors make use of both electric and magnetic fields to deflect the beams.The incoming beam gets zero deflection,but the outgoing beam is deflected by the combined effect of the electric and magnetic forces.W and Z modes use the same cavities with H mode to save budget.The deflectors are large contributors to the overall beam impedance which is necessary to be reduced as much as possible.Methods The electric and magnetic field optimization has been performed by the Opera.The beam impedance study has been carried out using the Computer Simulation Technology(CST)particle studio.Results The shape of the electrode is optimized for a good electric field homogeneity(±0.05%)in 46 mm×40 mm region.The electric field and the magnetic field could be matched perfectly in the main body of the deflector by bending the elec-trodes and introducing magnetic field clamps and mirror plates.The beam loss factor decreases by about 20%via the intro-duction of ground electrodes and tapering ends.Conclusions The design results successfully meet the physical requirements,and the mechanical design has been finished.

An experimental study on matched field processing in shallow water

Matched field processing (MFP) is a generalized beamforming method which uses the spatial complexities of acoustic field in an ocean waveguide to localize sources in range, depth and azimuth or to infer parameters of the waveguide itself. In the paper, we present simulated and experimental results on narrow-band point source localization in shallow water by the matched field processing of a vertical array. Range-depth ambiguity surfaces are obtained by the spatial correlation of the incident field (modeled or realistic) with a modeled replica of that field. The simulated results indicate that a high-quality ambiguity surface can be obtained in case of perfect match between the 'true' environmental parameters and those used to compute the replica field. The effects of mismatches result in a degraded ambiguity surface and incorrect localization. Examples of localizations obtained with real sea test data are presented. It is shown that the conventional methods have better robustness than the minimum variance distortionless response (MVDR) based method. By employing the reduced minimum variance beamforming (RMVB), we can also get better results.