A numerical procedure for recovering scattering coefficients frommeasurements with wide-beam antennas

A numerical procedure for estimating true scattering coefficients, σ⁰, from measurements made using wide-beam antennas is discussed. The use of wide-beam antennas results in an inaccurate estimate of σ⁰. To reduce this error, the authors propose a correction procedure that estimates the error resulting from the use of narrow-beam approximation and utilizes the error to obtain a more accurate estimate of σ⁰. An exponential model is assumed to take into account the variation of σ⁰ with incidence angles, and the model parameters are estimated from measured data. Based on the model and knowledge of the antenna pattern, the procedure calculates the error due to the narrow-beam approximation. The procedure is shown to provide a significant improvement in the estimation of σ⁰ obtained in wide-beam antennas. The proposed procedure is also shown to be insensitive to the assumed σ⁰ model     

A method to dramatically improve subcarrier tracking

A method is presented for achieving a considerable improvement in phase tracking of square-wave subcarriers or other square waves. The amplitude of the phase quadrature reference signal is set to zero, except near the zero crossings of the input signal. Without changing the loop bandwidth, the variance of the phase error can be reduced by approximately Wσ₀² where σ ₀² is the phase error variance without windowing and W is the fraction of cycle in which the reference signal has a nonzero value. Simulation results confirm the results of the analysis and establish minimum W versus SNR (signal-to-noise ratio). Typically, the window can be made so narrow as to achieve a phase error variance of 1.5 σ₀⁴     

Optimal data-based kernel estimation of evolutionary spectra

Complex demodulation of evolutionary spectra is formulated as a two-dimensional kernel smoother in the time-frequency domain. First, a tapered Fourier transform, y_v(f, t), is calculated. Then the log-spectral estimate, is smoothed. As the characteristic widths of the kernel smoother increase, the bias from the temporal and frequency averaging increases while the variance decreases. The demodulation parameters, such as the order, length, and bandwidth of spectral taper and the kernel smoother, are determined by minimizing the expected error. For well-resolved evolutionary, spectra, the optimal taper length is a small fraction of the optimal kernel halfwidth. The optimal frequency bandwidth, w, for the spectral window scales as w²~λ/τ, where τ is the characteristic time and λ_F is the characteristic frequency scalelength. In contrast, the optimal halfwidths for the second stage kernel smoother scales as h~1/(τλ_F )¹(p+2)/ where p is the order of the kernel smoother. The ratio of the optimal-frequency halfwidth to the optimal-time halfwidth is determined     

Stochastic gradient adaptation under general error criteria

Examines a family of adaptive filter algorithms of the form W_k+1=W_k+μf(d_k-W_k^t X_k)X_k in which f(·) is a memoryless odd-symmetric nonlinearity acting upon the error. Such algorithms are a generalization of the least-mean-square (LMS) adaptive filtering algorithm for even-symmetric error criteria. For this algorithm family, the authors derive general expressions for the mean and mean-square convergence of the filter coefficients For both arbitrary stochastic input data and Gaussian input data. They then provide methods for optimizing the nonlinearity to minimize the algorithm misadjustment for a given convergence rate. Using the calculus of variations, it is shown that the optimum nonlinearity to minimize misadjustment near convergence under slow adaptation conditions is independent of the statistics of the input data and can be expressed as -p'(x)/p(x), where p(x) is the probability density function of the uncorrelated plant noise. For faster adaptation under the white Gaussian input and noise assumptions, the nonlinearity is shown to be x/{1+μλx²/σ_k ²}, where λ is the input signal power and σ_k² is the conditional error power. Thus, the optimum stochastic gradient error criterion for Gaussian noise is not mean-square. It is shown that the equations governing the convergence of the nonlinear algorithm are exactly those which describe the behavior of the optimum scalar data nonlinear adaptive algorithm for white Gaussian input. Simulations verify the results for a host of noise interferences and indicate the improvement using non-mean-square error criteria     

Theoretical analysis of word-level switching activity in thepresence of glitching and correlation

This paper presents a novel analytical approach to compute the switching activity in digital circuits at the word level in the presence of glitching and correlation. The proposed approach makes use of signal statistics such as mean, variance, and autocorrelation. It is shown that the switching activity α_f at the output node f of any arbitrary circuit in the presence of glitching and correlation is computed as α_f=Σ_i=1^S-1α(f _i,i+1)=Σ_i=1^{S- 1}p(f_i+1)(1-p(f_i))(1-ρ(f_i,i+1 )) (1) where ρ(f_i,i+1)=ρ(f_i,i+1)=(E[f_i(Sn)f _i+1(Sn)]- p(f_i)p(f_i+1))/(√(p(f _i)-p(f_i)²)(p(f_i+1)- p(f_i+1²))) (2). S number of time slots in a cycle; ρ(f_i,+1) time-slot autocorrelation coefficient; E[x]=expected value of x; p_x=probability of the signal x being “one”. The switching activity analysis of a signal at the word level is computed by summing the activities of all the individual bits constituting the signal. It is also shown that if the correlation coefficient of the higher order bits of a normally distributed signal x is ρ(x_c), then the bit P₀ where the correlation begins and the correlation coefficient is related hy ρ(x_c)=erfc{(2(P₀-1)-1)/(√2σ_x )} where erfc(x)=complementary error function; σ_x=variance of x. The proposed approach can estimate the switching activity in less than a second which is orders of magnitude faster than simulation-based approaches. Simulation results show that the errors using the proposed approach are about 6.1% on an average and that the approach is well suited even for highly correlated speech and music signals     

Quadratic detectors for energy estimation

The estimation of signal energy is an important part of physics and signal processing. A commonly used energy estimate in signal processing is instantaneous energy that is defined by the square of the signal magnitude at time t, i.e., |x(t)|². For a noisy signal, a standard energy detector, which consists of a linear time-invariant (LTI) filter followed by a magnitude-squared operator, is commonly used to reduce noise and extract signal energy in a certain frequency band. However, due to the temporal response of the LTI filtering, this energy estimate is smeared in time. In addition, it is unclear how this estimate relates to the physical energy in the system that produced the signal. e propose simple quadratic systems producing frequency-selective energy estimates and effective noise reduction with little or no smearing in time. We introduce the new concept of quadratic detectors, discuss desirable time and frequency resolution properties of a general quadratic detector, and study five different applications to demonstrate the simplicity of quadratic detector design and implementation     

Capacity of the Gaussian arbitrarily varying channel

The Gaussian arbitrarily varying channel with input constraint Γ and state constraint Λ admits input sequences x=(x₁,---,X_n) of real numbers with Σx_i²⩽nΓ and state sequences s=(S₁,---,s_n ) of real numbers with Σs_i²⩽nΛ; the output sequence x+s+V, where V=(V₁,---,V_n) is a sequence of independent and identically distributed Gaussian random variables with mean 0 and variance σ². It is proved that the capacity of this arbitrarily varying channel for deterministic codes and the average probability of error criterion equals 1/2 log (1+Γ/(Λ+σ²)) if Λ<Γ and is 0 otherwise     

Maximum likelihood DOA estimation and asymptotic Cramer-Rao boundsfor additive unknown colored noise

This paper is devoted to the maximum likelihood estimation of multiple sources in the presence of unknown noise. With the spatial noise covariance modeled as a function of certain unknown parameters, e.g., an autoregressive (AR) model, a direct and systematic way is developed to find the exact maximum likelihood (ML) estimates of all parameters associated with the direction finding problem, including the direction-of-arrival (DOA) angles Θ, the noise parameters α, the signal covariance Φ_s, and the noise power σ². We show that the estimates of the linear part of the parameter set Φ_s and σ² can be separated from the nonlinear parts Θ and α. Thus, the estimates of Φ_s and σ² become explicit functions of Θ and α. This results in a significant reduction in the dimensionality of the nonlinear optimization problem. Asymptotic analysis is performed on the estimates of Θ and α, and compact formulas are obtained for the Cramer-Rao bounds (CRB's). Finally, a Newton-type algorithm is designed to solve the nonlinear optimization problem, and simulations show that the asymptotic CRB agrees well with the results from Monte Carlo trials, even for small numbers of snapshots     

On a new cylindrical harmonic representation for spherical waves

An exact series representation is presented for integrals whose integrands are products of cosine and spherical wave functions, where the argument of the cosine term can be any integral multiple n of the azimuth angle φ. This series expansion is shown to have the following form: I(n)=e^-jkR0/R₀ δ_no-jk Σ_m=1^∞ C(m,n)(k ²ρρ0)/m! h_m⁽²⁾(kR₀)/(kR₀)^m . It is demonstrated that in the special cases n=0 and n=1, this series representation corresponds to existing expressions for the cylindrical wire kernel and the uniform current circular loop vector potential, respectively. A new series representation for spherical waves in terms of cylindrical harmonics is then derived using this general series representation. Finally, a closed-form far-field approximation is developed and is shown to reduce to existing expressions for the cylindrical wire kernel and the uniform current loop vector potential as special cases     

Adaptive smoothing of the log-spectrum with multiple tapering

A hybrid estimator of the log-spectral density of a stationary time series is proposed. First, a multiple taper estimated is performed, followed by kernel smoothing the log-multiple taper estimate. This procedure reduces the expected mean square error by (π²/4) ^4/5 over simply smoothing the log tapered periodogram. A data-adaptive implementation of a variable-bandwidth kernel smoother is given     

Reconciliation of different gate-voltage dependencies of 1/f noisein n-MOS and p-MOS transistors

We have examined the 1/f noise of 3 μm×16 μm, n- and p-MOS transistors as a function of frequency (f), gate-voltage (V_g ) and temperature (T). Measurements were performed for 3 Hz⩽f⩽50 kHz, 100 mV⩽|V_g-V_th|⩽4 V, and 77 K⩽T⩽300 K, where V_th is the threshold voltage. Devices were operated in strong inversion in their linear regimes. At room temperature we find that, for n-MOS transistors, S(V_d)∝V_d²/(V_g-V_th )², and for p-MOS transistors, we generally find that S(V_d)∝V_d²/(V_g-V_th , consistent with trends reported by others. At lower temperatures, however, the results can be very different. In fact, we find that the temperature dependence of the noise and the gate-voltage dependence of the noise show similar features, consistent with the idea that the noise at a given T and V_g is determined by the trap density, D_t(E), at trap energies E=E(T,V_g). Both the T- and V_g-dependencies of the noise imply that D_t (E) tends to be constant near the silicon conduction band edge, but increases as E approaches the valence band edge. It is evidently these differences in D_t(E) that lead to differences in the gate-voltage dependence of the noise commonly observed at room temperature for n- and p-MOS transistors     

Optimality property of the Gaussian window spectrogram

It is shown that for any signal x(t) the minimum of ∫_-∞^∞∫_-∞ ^∞ [(t-t_x)²+(f-f _x)²] S_x^(w)(t , f) dt df over all normalized time-windows w(t) is achieved by the Gaussian window w(t)=2^1/4 exp (-πt²). Here (t_x, f _x) is the center of gravity of the signal x(t ), S_x^(w) (t, f) is the spectrogram of x(t) due to the window w( t), and the double integral is a measure of the spread of S _x^(w) (t, f) around (t _x, f_X) in the time-frequency plane     

Measuring soil moisture with imaging radars

An empirical algorithm for the retrieval of soil moisture content and surface root mean square (RMS) height from remotely sensed radar data was developed using scatterometer data. The algorithm is optimized for bare surfaces and requires two copolarized channels at a frequency between 1.5 and 11 GHz. It gives best results for kh⩽2.5, μ_υ⩽35%, and &thetas;⩾30°. Omitting the usually weaker hv-polarized returns makes the algorithm less sensitive to system cross-talk and system noise, simplifies the calibration process and adds robustness to the algorithm in the presence of vegetation. However, inversion results indicate that significant amounts of vegetation (NDVI>0.4) cause the algorithm to underestimate soil moisture and overestimate RMS height. A simple criteria based on the σ_hv⁰/σ_vv⁰ ratio is developed to select the areas where the inversion is not impaired by the vegetation. The inversion accuracy is assessed on the original scatterometer data sets but also on several SAR data sets by comparing the derived soil moisture values with in-situ measurements collected over a variety of scenes between 1991 and 1994. Both spaceborne (SIR-C) and airborne (AIRSAR) data are used in the test. Over this large sample of conditions, the RMS error in the soil moisture estimate is found to be less than 4.2% soil moisture     

Generation-recombination noise in GaN/AlGaN heterostructure fieldeffect transistors

Local levels with a large activation energy E_a~0.8-1.0 eV have been observed in low-frequency noise measurements of GaN/AlGaN heterostructure field effect transistors (HFETs and MOS-HFETs) grown on 4N-SiC substrates. The noise might come from the thin (30 nm) AlGaN barrier layer. The estimates of the level parameters based on this assumption resulted in reasonable values of capture cross section σ_n≈(10^-12-10^-13) cm² and trap concentration N_t≈5-10¹⁶ cm^-3     

Emission cross sections and spectroscopy of Ho3+ laserchannels in KGd(WO4)2 single crystal

The spectroscopic properties of Ho³⁺ laser channels in KGd(WO₄)₂ crystals have been investigated using optical absorption, photoluminescence, and lifetime measurements. The radiative lifetimes of Ho³⁺ have been calculated through a Judd-Ofelt (JO) formalism using 300-K optical absorption results. The JO parameters obtained were Ω₂=15.35×10^-20 cm², Ω ₄=3.79×10^-20 cm², Ω₆ =1.69×10^-20 cm². The 7-300-K lifetimes obtained in diluted (8·10¹⁸ cm^-3) KGW:0.1% Ho samples are: τ(⁵F₃)≈0.9 μs, τ( ⁵S₂)=19-3.6 μs, and τ(⁵F₅ )≈1.1 μs. For Ho concentrations below 1.5×10²⁰ cm^-3, multiphonon emission is the main source of non radiative losses, and the temperature independent multiphonon probability in KGW is found to follow the energy gap law τ_ph ^-1(0)=βexp(-αΔE), where β=1.4×10^-7 s^-1, and α=1.4×10³ cm. Above this holmium concentration, energy transfer between Ho impurities also contributes to the losses. The spectral distributions of the Ho³⁺ emission cross section σ_EM for several laser channels are calculated in σ- and π-polarized configurations. The peak a σ_EM values achieved for transitions to the ⁵I₈ level are ≈2×10^-20 cm² in the σ-polarized configuration, and three main lasing peaks at 2.02, 2.05, and 2.07 μm are envisaged inside the ⁵I₇→⁵I₈ channel     

Low-frequency noise in TFSOI lateral n-p-n bipolar transistors

Low-frequency (1/f) noise is characterized as a function of base current density (J_B) on thin-film-silicon-on-insulator (TFSOI) lateral bipolar transistors. In the low injection region of operation, the noise power spectral density was proportional to J_B ^1.8 for J_B<0.4 μA/μm², which suggest that the noise in these devices is primarily dominated by a uniform distribution of noise sources across the emitter-base area. However in the high current region of operation (J_B>0.4 μm²), the noise bias dependence shifts to J_B ^1.2, indicating current crowding effects, alter the contribution of noise sources near the extrinsic base link region of the device. In addition to the expected 1/f noise and shot noise, we have observed a bias dependent generation-recombination (Gm) noise source in some of the devices. This G/R noise is correlated to random-telegraph-signal (RTS) noise resulting from single trapping centers, located at or near the spacer oxide and/or the Si to SIMOX interface, which modulate the emitter-base space charge region     

New-user identification in a CDMA system

We present three detector/estimators (DEs) which allow multiuser detection and parameter estimation without a side channel in a dynamic asynchronous code-division multiple-access (CDMA) system in which users are entering and leaving the system. These DEs optimally detect a new user given only the chip rate and the spreading factor of the new user. Two of these DEs, the maximum-likelihood detector/estimator (MLDE) and the generalized maximum-likelihood detector/estimator (GMLDE), produce maximum-likelihood estimates of the new user's signature sequence, delay, and amplitude, which are then incorporated into a multiuser detector. The third DE, the cyclic detector/estimator (CDE), is the most computationally efficient of the three processors. This DE detects the new user by testing for cyclostationarity and then uses suboptimal schemes to estimate the new user's signature sequence, delay, and amplitude. Simulations indicate that all three DEs reliably detect a new user for an E_s/σ² (symbol-energy-to-noise ratio) of 5 dB. The MLDE and GMLDE produce signature sequence and delay estimates with probability of error less than 0.07 for an E_s/σ² of 10 dB, and the CDE produces signature sequence and delay estimates with probability of error less than 0.13 for an E_s/σ² of 15 dB     

A rail-to-rail ping-pong op-amp

A rail-to-rail ping-pong op-amp achieves offset cancellation and 1/f noise reduction without folding of the input spectrum. The clocking scheme minimizes the clock feedthrough and the residual offset due to charge injection. With a clock frequency of 100 kHz, the residual offset is less than 100 μV, and the input referred noise is about 225 nV/Hz ^1/2. The rail-to-rail distortion at 1 kHz is lower than -71 dB. The total silicon area is 610×420 μm², and the circuit dissipates 1.5 mW from a single 5 V supply     

Exact analytic solutions to the nonlinear wave equation for asaturable Kerr-like medium: modes of nonlinear optical waveguides andcouplers

Exact analytic solutions to the nonlinear wave equation for a lossless saturable Kerr-like medium are found. The nonlinearity is an intensity-dependent refractive index which saturates according to the model n²=n₀²±a|E|²/(1+b|E| ²). The solutions to the wave equation are used to determine the TE power-dependent dispersion relations, and therefore the guided modes, of a single waveguide structure and of a directional coupler whose coupling medium is the nonlinear saturable material. Although the interaction between the sinh- and cosh-like modes of the coupler, and therefore the coupling length, is not treated in this work, it is shown that the critical power, defined in the literature to be the level of input power above which 100% of the power cannot be switched between the guides of a coupler, is a mathematical misinterpretation in both saturable media as well as in nonsaturable Kerr media. The absence of a critical power in single waveguide structures is also demonstrated. Parameters of GaAs-based waveguides and of a GaAs-GaAlAs MQW coupling medium are used in the numerical analysis     

Impact of nitrogen (N2+) implantation intopolysilicon gate on thermal stability of cobalt silicide formed onpolysilicon gate

A novel process which uses N₂⁺ implantation into polysilicon gates to suppress the agglomeration of CoSi₂ in polycide gated MOS devices is presented. The thermal stability of CoSi₂/polysilicon stacked layers can be dramatically improved by using N₂⁺ implantation into polysilicon. The sheet resistance of the samples without N₂⁺ implantation starts to increase after 875°C RTA for 30 s, while the sheet resistance of CoSi₂ film is not increased at all after 950 and 1000°C RTA for 30 s if the dose of nitrogen is increased up to 2×10¹⁵ cm^-2 and 6×10¹⁵ cm², respectively, and TEM photographs show that the agglomeration of CoSi₂ film is completely suppressed. It is found that the transformation to CoSi₂ from CoSi is impeded by N₂⁺ implantation such that the grain size of CoSi₂ with N₂⁺ implantation is much smaller than that without N₂⁺ implantation. As a result, the thermal stability of CoSi₂ is significantly improved by N₂⁺ implantation into polysilicon