17,812 research outputs found

    Adaptive acoustooptic filter

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    A new adaptive filter utilizing acoustooptic devices in a space integrating architecture is described. Two configurations are presented; one of them, suitable for signal estimation, is shown to approximate the Wiener filter, while the other, suitable for detection, is shown to approximate the matched filter

    Data-Adaptive Wavelets and Multi-Scale Singular Spectrum Analysis

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    Using multi-scale ideas from wavelet analysis, we extend singular-spectrum analysis (SSA) to the study of nonstationary time series of length NN whose intermittency can give rise to the divergence of their variance. SSA relies on the construction of the lag-covariance matrix C on M lagged copies of the time series over a fixed window width W to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components; here W = M Dt, with Dt the time step. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M <= W <= N. Multi-scale SSA varies W, while keeping a fixed W/M ratio, and uses the eigenvectors of the corresponding lag-covariance matrix C_M as a data-adaptive wavelets; successive eigenvectors of C_M correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's covariance matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic and geophysical time series. A real application is to the Southern Oscillation index (SOI) monthly values for 1933-1996. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 4 and 3 years supports the Devil's staircase scenario for the El Nino/Southern Oscillation phenomenon.Comment: 24 pages, 19 figure

    Quantum theory of optical temporal phase and instantaneous frequency. II. Continuous time limit and state-variable approach to phase-locked loop design

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    We consider the continuous-time version of our recently proposed quantum theory of optical temporal phase and instantaneous frequency [Tsang, Shapiro, and Lloyd, Phys. Rev. A 78, 053820 (2008)]. Using a state-variable approach to estimation, we design homodyne phase-locked loops that can measure the temporal phase with quantum-limited accuracy. We show that post-processing can further improve the estimation performance, if delay is allowed in the estimation. We also investigate the fundamental uncertainties in the simultaneous estimation of harmonic-oscillator position and momentum via continuous optical phase measurements from the classical estimation theory perspective. In the case of delayed estimation, we find that the inferred uncertainty product can drop below that allowed by the Heisenberg uncertainty relation. Although this result seems counter-intuitive, we argue that it does not violate any basic principle of quantum mechanics.Comment: 11 pages, 6 figures, v2: accepted by PR

    Interpolated-DFT-Based Fast and Accurate Amplitude and Phase Estimation for the Control of Power

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    The quality of energy produced in renewable energy systems has to be at the high level specified by respective standards and directives. The estimation accuracy of grid signal parameters is one of the most important factors affecting this quality. This paper presents a method for a very fast and accurate amplitude and phase grid signal estimation using the Fast Fourier Transform procedure and maximum decay sidelobes windows. The most important features of the method are the elimination of the impact associated with the conjugate's component on the results and the straightforward implementation. Moreover, the measurement time is very short - even far less than one period of the grid signal. The influence of harmonics on the results is reduced by using a bandpass prefilter. Even using a 40 dB FIR prefilter for the grid signal with THD = 38%, SNR = 53 dB and a 20-30% slow decay exponential drift the maximum error of the amplitude estimation is approximately 1% and approximately 0.085 rad of the phase estimation in a real-time DSP system for 512 samples. The errors are smaller by several orders of magnitude for more accurate prefilters.Comment: in Metrology and Measurement Systems, 201

    Local Ensemble Transform Kalman Filter: a non-stationary control law for complex adaptive optics systems on ELTs

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    We propose a new algorithm for an adaptive optics system control law which allows to reduce the computational burden in the case of an Extremely Large Telescope (ELT) and to deal with non-stationary behaviors of the turbulence. This approach, using Ensemble Transform Kalman Filter and localizations by domain decomposition is called the local ETKF: the pupil of the telescope is split up into various local domains and calculations for the update estimate of the turbulent phase on each domain are performed independently. This data assimilation scheme enables parallel computation of markedly less data during this update step. This adapts the Kalman Filter to large scale systems with a non-stationary turbulence model when the explicit storage and manipulation of extremely large covariance matrices are impossible. First simulation results are given in order to assess the theoretical analysis and to demonstrate the potentiality of this new control law for complex adaptive optics systems on ELTs.Comment: Proceedings of the AO4ELT3 conference; 8 pages, 3 figure

    Optimal motion control and vibration suppression of flexible systems with inaccessible outputs

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    This work addresses the optimal control problem of dynamical systems with inaccessible outputs. A case in which dynamical system outputs cannot be measured or inaccessible. This contradicts with the nature of the optimal controllers which can be considered without any loss of generality as state feedback control laws for systems with linear dynamics. Therefore, this work attempts to estimate dynamical system states through a novel state observer that does not require injecting the dynamical system outputs onto the observer structure during its design. A linear quadratic optimal control law is then realized based on the estimated states which allows controlling motion along with active vibration suppression of this class of dynamical systems with inaccessible outputs. Validity of the proposed control framework is evaluated experimentally

    Efficient detection and signal parameter estimation with applications to high dynamic GPS receivers

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    A novel technique for simultaneously detecting data and estimating the parameters of a received carrier signal phase modulated by unknown data and experiencing very high Doppler, Doppler rate, etc. is discussed. Such a situation arises, for example, in the case of Global Positioning Systems (DPS) where the signal parameters are directly related to the position, velocity and acceleration of the GPS receiver. The proposed scheme is based upon first estimating the received signal local (data dependent) parameters over two consecutive bit periods, followed by the detection of a possible jump in these parameters. The presence of a detected jump signifies a data transition which is then removed from the received signal. This effectively demodulated signal is then processed to provide the estimates of global (data independent) parameters of the signal related to the position, velocity, etc. of the receiver. One of the key features of the proposed algorithm is the introduction of two different schemes which can provide an improvement of up to 3 dB over the conventional implementation of Kalman filter as applied to phase and frequency estimation, under low to medium signal-to-noise ratio conditions
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