Diffraction of a plane wave by a multiserial lattice located in a dielectric layer

A modified zero field method is applied to solve the 2D problem of scattering by a multiserial lattice. The lattice consists of perfectly conducting elements and is situated in a homogeneous dielectric layer. The system of integral equations is derived and formulas for calculating the reflection and transmission coefficients are obtained for various geometries of the lattice elements. To increase the efficiency of the algorithm work, both polar and elliptic coordinates are applied to choose the auxiliary contour on which the zero field condition is stipulated.     

One-dimensional normal-incidence inversion: A solution procedure for band-limited and noisy data

In this paper we present a one-dimensional normal-incidence inversion procedure for reflection seismic data. A lossless layered system is considered which is characterized by reflection coefficients and traveltimes. A priori knowledge for the unknown parameters, in the form of statistics, is incorporated into a nonuniform layered system, and a maximum a posteriori estimation procedure is used for the estimation of the system's unknown parameters (i.e., we assume a random reflector model) from noisy and band-limited data. Our solution to the inverse problem includes a downward continuation procedure for estimation of the states of the system. The state sequences are composed of overlapping wavelets. We show that estimation of the unknown parameters of a layer is equivalent to estimation of the amplitude and detection of the time delay of the first wavelet in the upgoing state sequence of the layer. A suboptimal maximum-likelihood deconvolution procedure is employed to perform estimation and detection. The most desirable features of the proposed algorithm are its layer-recursive structure and its ability to process noisy and band-limited data.     

Reconstruction of multilayered lossy dielectrics from one-sidedplane wave impulse reflection responses: the bistatic case

Motivated by numerous scattering problems where the media is lossy and yet can only be investigated from a single side, the authors discuss algorithms for reconstructing a lossy, stratified dielectric from one-sided plane wave impulse reflection responses. Novel features of these algorithms include: 1) solving the lossy media problem using only one-sided reflection response data; 2) exploiting oblique probing angles; 3) having origins in digital signal processing (DSP) theory; 4) employing fast algorithms that have been modified to solve the forward scattering problem; and 5) solving the scattering problems exactly, including accounting for multiple reflections. A new algorithm is introduced that reconstructs such a media from one-sided transverse electric (TE) and transverse magnetic (TM) impulsive plane wave reflection responses from a single oblique angle. The oblique-probing angle necessitates a bistatic measurement configuration. New probing constraints are developed for a previously presented algorithm based on probing at two angles of incidence. Algorithm stability and data correction are addressed. Numerical examples illustrate the new algorithm in synthesizing the media transient response and reconstructing the media     

One- and two-dimensional minimum and nonminimum phase retrieval bysolving linear systems of equations

The discrete phase retrieval problem is to reconstruct a discrete time signal whose support is known and compact from the magnitude of its discrete Fourier transform. We formulate the problem as a linear system of equations; our methods do not require polynomial rooting, tracking zero curves of algebraic functions, or any sort of iteration like previous methods. Our solutions obviate the stagnation problems associated with iterative algorithms, and our solutions are computationally simpler and more stable than alternative noniterative algorithms. Furthermore, our methods can explicitly accommodate noisy Fourier magnitude information through the use of total least squares type techniques. We assume either of the following two types of a priori knowledge of the signal: (1) a band of known values (which may be zeros) or (2) some known values of a subminimum phase signal (whose zeros lie inside a disk of radius greater than unity). We illustrate our methods with nonminimum-phase one-dimensional (1-D) and two-dimensional (2-D) signals     

Observer of autonomic cardiac outflow based on blind source separation of ECG parameters

We present a novel method which provides an observer of the autonomic cardiac outflow using heartbeat intervals (RR) and QT intervals. The model of the observer is inferred from qualitative physiological knowledge. It consists in a problem of blind source separation of noisy mixtures which is resolved by a simple and robust algorithm. The robustness of the algorithm has been assessed by numerical simulations in adverse noisy environments. In clinical applications, we have validated the observer on subjects exposed to experimental conditions known to elicit sympathetic or parasympathetic response.     

A Survey of Approaches to Solving Inverse Problems for Lossless Layered Media Systems

In this paper, we survey approaches to solving inverse problems for lossless layered systems. Such systems can be modeled in two different ways, by nonparametric or parametric models. We review both models, but concentrate our attention on inverse and estimation procedures for parametric models. Algebraic inverse procedures are described for determining the reflection coefficient parameters when measurements are noise free. An extension of these procedures to the case of noisy data is also discussed; but, resulting reflection coefficient values are suboptimal. Finally, we describe two procedures for estimating reflection coefficients from noisy data. One of these, which is very promising, is a maximum-likelihood procedure, which is not only able to provide estimates of reflection coefficients, but is also able to provide estimates of another set of parameters, layer travel times. These maximum-likelihood estimates are optimal.     

Transmitter optimization and optimality of beamforming for multiple antenna systems

We solve the transmitter optimization problem and determine a necessary and sufficient condition under which beamforming achieves Shannon capacity in a linear narrowband point-to-point communication system employing multiple transmit and receive antennas with additive Gaussian noise. We assume that the receiver has perfect channel knowledge while the transmitter has only knowledge of either the mean or the covariance of the channel coefficients. The channel is modeled at the transmitter as a matrix of complex jointly Gaussian random variables with either a zero mean and a known covariance matrix (covariance information), or a nonzero mean and a white covariance matrix (mean information). For both cases, we develop a necessary and sufficient condition for when the Shannon capacity is achieved through beamforming; i.e., the channel can be treated like a scalar channel and one-dimensional codes can be used to achieve capacity. We also provide a waterpouring interpretation of our results and find that less channel uncertainty not only increases the system capacity but may also allow this higher capacity to be achieved with scalar codes which involves significantly less complexity in practice than vector coding.     

A blind adaptive decorrelating detector for CDMA systems

The decorrelating detector is known to eliminate multiaccess interference when the signature sequences of the users are linearly independent, at the cost of enhancing the Gaussian receiver noise. We present a blind adaptive decorrelating detector which is based on the observation of readily available statistics. The algorithm recursively updates the filter coefficients of a desired user by using the output of the current filter. Due to the randomness of the information bits transmitted and the ambient Gaussian channel noise, the filter coefficients evolve stochastically. We prove the convergence of the filter coefficients to a decorrelating detector in the mean squared error (MSE) sense. We develop lower and upper bounds on the MSE of the receiver filter from the convergence point and show that with a fixed step size sequence, the MSE can be made arbitrarily small by choosing a small enough step size. With a time-varying step size sequence, the MSE converges to zero implying an exact convergence. The proposed algorithm is distributed, in the sense that no information about the interfering users such as their signature sequences or power levels is needed. The algorithm requires the knowledge of only two parameters for the construction of the receiver filter of a desired user: the desired user's signature sequence and the variance of the additive white Gaussian (AWG) receiver noise. This detector, for an asynchronous code division multiple access (CDMA) channel, converges to the one-shot decorrelating detector     

An optimization approach to the frequency-domain inverse problemfor a nonuniform LCRG transmission line

The inverse problem for a nonuniform LCRG transmission line is considered in the frequency domain. Imbedding equations for the reflection and transmission coefficients are derived through the concept of wave-splitting. An optimization approach is applied to reconstruct the line parameters as functions of the position using band-limited reflection and/or transmission data. Exact and explicit expressions for the gradients are derived, and the reconstruction algorithm (based upon a conjugate gradient method) is tested with both clean and noisy data, The problem of the nonuniqueness is also discussed     

Closed-form solutions for one-dimensional inhomogeneous anisotropicmedium in a special case. I. Direct scattering problem

An analytical formulation is presented for the direct scattering problem of one-dimensional (1-D) inhomogeneous anisotropic medium in a special case. This method gives nonlinear differential equations for the reflection coefficients of the anisotropic medium. Applying the discontinuity condition of the dielectric parameters at the interface of the medium with free space, approximate closed-form solutions for the reflection coefficients are obtained. Numerical examples show the validity of the method     

Inverse scattering method for one-dimensional inhomogeneous lossymedium by using a microwave networking technique

The formulation of reflection coefficients from an inhomogeneous lossy medium illuminated by TE and TM waves is approximately derived, in closed form, by using a microwave network method. From the formulation, a novel inverse scattering scheme to reconstruct simultaneously the permittivity and conductivity profiles, is proposed. This scheme is suitable for both continuous and discontinuous profiles, under both the weak scattering and strong scattering conditions. It has also been shown that when the conductivity of the medium equals zero, the reconstructed result of this scheme will reduce to the one formulated by Ladouceur and Jordan (1985). Numerical and closed-form reconstruction examples show the validity of the scheme     

Reconstruction of multilayered lossy dielectrics from plane waveimpulse responses at two angles of incidence

Motivated by the radioglaciology inverse problem, the authors present new algorithms for reconstructing a lossy, stratified dielectric from its impulsive plane wave reflection responses at two different angles of incidence. Novel features of these algorithms include: 1) a digital signal processing formulation that does not require discretization of continuous equations; 2) use of the asymmetric Levinson algorithm for rapid solution of the forward and inverse problems; 3) a novel use of layer stripping ideas, featuring iteration between the forward and inverse problems, with each iteration recursively determining another layer of the medium; and 4) another recursive algorithm for determining the bottom lossy half-space from reflection data only. Numerical examples illustrate the new algorithms on the reconstruction of a synthetic but realistic layered ice shelf from both noiseless and noisy radar reflection data     

电磁波在正负折射率介质界面上的传输特性

为了研究负折射率介质这种新型复合材料的电磁性质，利用麦克斯韦电磁理论对电磁波在正、负折射率介质交界面上的反射和透射特性进行了分析。得到了Snell反射定律和折射定律，反射系数和透射系数随入射角的关系（Fresnel公式）。结果发现Snell反射定律和折射定律仍然适用。但折射线与入射线位于法线的同侧；不论是腰波还是TM波，当以某一入射角入射时，反射系数都有可能变为零。这些结果对于设计新型的电磁学和光学器件具有指导性的意义。     

Scattering Parameter Approach to the Design of Narrow-Band Amplifiers Employing Conditionally Stable Active Elements (Short Papers)

In terms of scattering parameters, the equation transducer power gain is shown to be capable of representation as a family of circles of constant gain from which the design of load and source terminations to achieve a restricted bandwidth can be obtained. This is an extension of an earlier approach which only allowed either load reflection coefficient or source reflection coefficient to be considered in a given design. Through the use of a specification statement of VSWR, it is shown how a marginal stability factor can be derived. From the study of the interaction between the input and output reflection coefficients, a detuning factor is analytically derived to correlate the interaction between the input and output reflection coefficients. Either of these factors can be chosen and used to select optimum input and output reflection coefficients which provide stable operation for an amplifying stage that is to employ a conditionally stable active element. An example using these factors is given.     

Recursive least-squares quadratic smoothing from measurements with packet dropouts

The least-squares quadratic filtering and fixed-point smoothing problems of discrete-time stochastic signals from observations with multiple packet dropouts are addressed. It is assumed that the packet dropouts occur randomly and the latest measurement received successfully is processed for the estimation in case that the current measurement is dropped-out. This situation is modelled by introducing in the observation model a sequence of Bernoulli random variables whose values - one or zero - indicate if the current measurement is received or dropped-out, respectively, and whose probability distributions are known. A recursive estimation algorithm is deduced without requiring full knowledge of the state-space model generating the signal process, but only information about the dropout probabilities and the moments of the signal and noise processes involved. Defining a suitable augmented observation model, the quadratic estimation problem is reduced to the linear estimation problem based on the augmented observations, which is solved by using an innovation approach.     

Closed-form solutions for one-dimensional inhomogeneous anisotropicmedium in a special case. II. Inverse scattering problem

For pt. I see ibid., vol.45, no.5, p.936, 1997. An analytical method is presented for the inverse scattering problem of a one-dimensional (1-D) inhomogeneous anisotropic medium in a special case. Using the closed-form formulations for the reflection coefficients derived in the first part of this paper, reconstruction formulas are obtained for the wave impedance profiles, permittivity profiles or permeability profiles of the anisotropic medium, all of which are given in closed form. In the meantime, a partial inverse scattering method for the electric parameters at the interface of the medium with free space is also investigated by using a Wedtzel-Kramers-Brillouin (WKB) approximation. Numerical examples show the validity of the methods     

Recovery of correlated row sparse signals using smoothed L0-norm algorithm

Distributed compressed sensing(DCS) is an emerging research field which exploits both intra-signal and inter-signal correlations.This paper focuses on the recovery of the sparse signals which can be modeled as joint sparsity model(JSM) 2 with different nonzero coefficients in the same location set.Smoothed L0 norm algorithm is utilized to convert a non-convex and intractable mixed L2,0 norm optimization problem into a solvable one.Compared with a series of single-measurement-vector problems,the proposed approach can obtain a better reconstruction performance by exploiting the inter-signal correlations.Simulation results show that our algorithm outperforms L1,1 norm optimization for both noiseless and noisy cases and is more robust against thermal noise compared with L1,2 recovery.Besides,with the help of the core concept of modified compressed sensing(CS) that utilizes partial known support as side information,we also extend this algorithm to decode correlated row sparse signals generated following JSM 1.     

Scattering Coefficients for Wall Impedance Changes in Waveguides

The Wiener-Hopf tectilque is used to obtain an exact solution to a two-dimensional scattering problem. In the problem solved, an incident TE/sub 10/ mode, traveling from z= -/spl infin/ in the positive z direction, is confined by infinite bounding planes; these planes have infinite conductivity for z<0 and an impedance Z/sub 1/, for z>0. The scattering from the junction at z=0 gives rise to reflection and transmission coefficients that are exactly determined. An approximate solution for the reflection coefficients is also given when the TE/sub 10/ mode is incident from the opposite direction. Finally, a table is presented which lists some transmission and reflection coefficients for rectangular and circular waveguides with discontinuities in the wall impedances.     

Blind chip-level equalizer for the downlink of cyclic-prefix CDMA systems

The authors present a chip-level blind frequency domain equalizer (FEQ) for the forward-link channel of a cyclic-prefix code division multiple access system. The FEQ coefficients are obtained without the need of training symbols or knowledge of channel state information. The coefficients are instead acquired by solving a constraint energy minimization problem involving the subspace spanned by the active and passive spreading codewords. They also prove that the random scrambling code sequences is required for the operation of the proposed equalization algorithm. Results from computer simulations are provided to verify the performance of the proposed FEQ.     

On the feasibility of impulse reflection response data for thetwo-dimensional inverse scattering problem

Layer stripping algorithms for inverse scattering problems are very fast but have the reputation of being numerically unstable, especially when applied to noisy data. The goal of this paper is to provide an explicitly discrete framework for layer stripping algorithms for the two-dimensional (2-D) Schrodinger equation inverse scattering problem. We determine when 2-D layer stripping algorithms are numerically stable, explain why they are stable, and specify exactly the (discrete) problem they solve when they are stable. We reformulate the 2-D Schrodinger equation as a multichannel two-component wave system by Fourier transforming the Schrodinger equation in the lateral spatial variable. Discretization results in new 2-D layer stripping algorithms which incorporate multichannel transmission effects; this leads to an important new feasibility condition on impulse reflection response data for stability of these algorithms. A 2-D discrete Schrodinger equation is defined, and analogous results are obtained. Numerical examples illustrate the new results, especially how rendering noisy data feasible stabilizes layer stripping algorithms