A Sound Field Separation and Reconstruction Technique Based on Reciprocity Theorem and Fourier Transform

We show a method to separate the sound field radiated by a signal source from the sound field radiated by noise sources and to reconstruct the sound field radiated by the signal source. The proposed method is based on reciprocity theorem and the Fourier transform. Both the sound field and its gradient on a measurement surface are needed in the method. Evanescent waves are considered in the method, which ensures a high resolution reconstruction in the near field region of the signal source when evanescent waves can be measured. A simulation is given to verify the method and the influence of measurement noise on the method is discussed.

A method for the separation and reconstructions of charged hadron and neutral hadron from their overlapped showers in an electromagnetic calorimeter

The separation and reconstructions of charged hadron and neutral hadron from their overlapped showers in an electromagnetic calorimeter is very important for the reconstructions of some particles with hadronic decays, for example the tau reconstruction in the searches for the Standard Model and supersymmetric Higgs bosons at the LHC. In this paper, a method combining the shower cluster in an electromagnetic calorimeter and the parametric formula for hadron showers, was developed to separate the overlapped showers between charged hadron and neutral hadron. Taking the hadronic decay containing one charged pion and one neutral pion in the final status of tau for example, satisfied results of the separation of the overlapped showers, the reconstructions of the energy and positions of the hadrons were obtained. An improved result for the tau reconstruction with this decay model can be also achieved after the application of the proposed method.

Synthetic aperture radar imaging based on attributed scatter model using sparse recovery techniques

The sparse recovery algorithms formulate synthetic aperture radar （SAR） imaging problem in terms of sparse representation （SR） of a small number of strong scatters＇ positions among a much large number of potential scatters＇ positions, and provide an effective approach to improve the SAR image resolution. Based on the attributed scatter center model, several experiments were performed with different practical considerations to evaluate the performance of five representative SR techniques, namely, sparse Bayesian learning （SBL）, fast Bayesian matching pursuit （FBMP）, smoothed 10 norm method （SL0）, sparse reconstruction by separable approximation （SpaRSA）, fast iterative shrinkage-thresholding algorithm （FISTA）, and the parameter settings in five SR algorithms were discussed. In different situations, the performances of these algorithms were also discussed. Through the comparison of MSE and failure rate in each algorithm simulation, FBMP and SpaRSA are found suitable for dealing with problems in the SAR imaging based on attributed scattering center model. Although the SBL is time-consuming, it always get better performance when related to failure rate and high SNR.

Three-dimensional reconstruction for a large scene of integral imaging based on color-position characteristics

A new large-scale three-dimensional(3D) reconstruction technology based on integral imaging with color-position characteristics is presented.The color of the object point is similar to those of corresponding points.The corresponding point coordinates form arithmetic progressions because integral imaging captures information with a senior array which has similar pitches on x and y directions.This regular relationship is used to determine the corresponding point parameters for reconstructing 3D information from divided elemental images separated by color,which contain several corresponding points.The feasibility of the proposed method is demonstrated through an optical indoor experiment.A large-scale application of the proposed method is illustrated by the experiment with a corner of our school as its object.

An equivalent source method for recovering and reconstructing the target sound field in a non-free field

In a non-free field,the existence of disturbing sources would destroy the free-field condition required by near-field acoustic holography,and confuse the identification of target source due to the scattering effect caused by disturbing sound falling on the target source.To totally remove the influence of disturbing source,a method for recovering and reconstructing the target sound field in a non-free field was proposed based on the equivalent source method and the pressure-velocity measurement.In the proposed method,the sound field separation technique was firstly used to separate the mixed sound field into the outgoing field coming from the target source and the incoming field coming from the disturbing source.Then the scattered component contained in the outgoing field was calculated by using the disturbing sound and the surface impedance of the target source.Finally,the sound field radiated by the target source in a free field was obtained by subtracting the scattered component from the outgoing field and was further used to reconstruct the sound field of the target source.The proposed method was numerically and experimentally testified and the results of both the simulation and the experiment demonstrated the validity of the proposed method.