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A discussion of methods for identification of dynamic systems is presented. Problems and methods for determining model structures and estimating unknown parameters are considered. The maximum likelihood (ML) formulation for parameter... more
A discussion of methods for identification of dynamic systems is presented. Problems and methods for determining model structures and estimating unknown parameters are considered. The maximum likelihood (ML) formulation for parameter estimation is discussed in detail due to its generality and its success in numerous applications. An outline is given of the steps and the computational considerations involved in a system identification problem. The benefits of identifying the process and observation noise sources and then applying the ML approach as opposed to the classical least-squares technique are discussed. Present and potential applications in the nuclear industry are reviewed.
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The problem of radar target-shape estimation for perfectly conducting complex objects is formulated as an image-reconstruction problem. A convolve-and-backproject algorithm is derived when the measurements are taken by radars located in... more
The problem of radar target-shape estimation for perfectly conducting complex objects is formulated as an image-reconstruction problem. A convolve-and-backproject algorithm is derived when the measurements are taken by radars located in three-dimensional space around the object region. The algorithm can be used directly in that there are no restrictions on the sensor placement; the sensors are not required to lie in a plane, for example, as is often assumed in many applications. Two possible convolving functions with desirable implementation characteristics are described. The algorithm is applicable to the general problem of reconstructing the density function of three-dimensional objects and applies to the radar shape-estimation problem as a special case.
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Considers the problem of finding the directions of narrowband signals using a time-varying array, i.e., an array whose elements move during the observation interval in an arbitrary but known way. The authors derive the Cramer Rao bound... more
Considers the problem of finding the directions of narrowband signals using a time-varying array, i.e., an array whose elements move during the observation interval in an arbitrary but known way. The authors derive the Cramer Rao bound and the maximum likelihood estimator for the direction-of-arrival estimates, for the Gaussian signal model. The single source case is studied in detail. Time-varying arrays are shown to be more robust to ambiguity errors than static arrays of comparable dimensions
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The problem of separating and estimating signals received by an array whose array manifold has an unknown structural form is usually referred to as the blind signal copy problem. In this paper we consider the blind signal copy problem for... more
The problem of separating and estimating signals received by an array whose array manifold has an unknown structural form is usually referred to as the blind signal copy problem. In this paper we consider the blind signal copy problem for polynomial phase signals. By deriving the Cramer Rao bound we evaluate the optimal performance achievable by any unbiased estimator. To gain additional insight into this problem we compare the CRB to the bound for the case where the functional form of the array manifold is known. We derive a computationally efficient approximate maximum-likelihood (ML) algorithm and compare its performance with the bound
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This paper attempts to assess the potential performance gain of spatial-temporal processing relative to conventional spatial processing, for signals obeying a deterministic parametric model. The Cramer-Rao bound (CRB) on the estimates of... more
This paper attempts to assess the potential performance gain of spatial-temporal processing relative to conventional spatial processing, for signals obeying a deterministic parametric model. The Cramer-Rao bound (CRB) on the estimates of the source directions of arrival (DOA) is used to quantify this gain. Spatial-temporal processing does not yield any such gain in the single source case, or for multiple
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For a nonstationary random process, the time-time correlation function, frequency-frequency Loeve spectrum, time-frequency Wigner-Ville distribution, and frequency-time ambiguity function are each complete theoretical descriptions of... more
For a nonstationary random process, the time-time correlation function, frequency-frequency Loeve spectrum, time-frequency Wigner-Ville distribution, and frequency-time ambiguity function are each complete theoretical descriptions of second-order behavior. They are complete in the sense that they determine realizations of the random process according to the Cramer-Loeve spectral representation for a harmonizable process. In this paper we derive estimators for these descriptors by requiring them to have the same covariant dependence on time delay and complex modulation as do their theoretical counterparts
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We consider the problem of separating two constant-amplitude continuous-phase signal components overlapping in time and frequency band. The discrete polynomial-phase transform (DPT) is used to estimate the parameters of the phase function... more
We consider the problem of separating two constant-amplitude continuous-phase signal components overlapping in time and frequency band. The discrete polynomial-phase transform (DPT) is used to estimate the parameters of the phase function of each component. Simulations are used to evaluate the performance of the algorithm
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Synchronous code-division multiple-access (CDMA) techniques possess intrinsic protection against co-channel interference due to the orthogonal spreading codes used. However, in the presence of multipath the signals lose their... more
Synchronous code-division multiple-access (CDMA) techniques possess intrinsic protection against co-channel interference due to the orthogonal spreading codes used. However, in the presence of multipath the signals lose their orthogonality properly leading to increased cross correlation. In these cases channel estimation may be needed in order to improve the detection of the desired symbols. We propose and compare several algorithms for channel estimation of a synchronous CDMA point to multipoint link (downlink) which uses aperiodic spreading waveforms. We compare by simulation and analysis a subspace approach, a pilot-aided approach, and a decision feedback approach
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We consider the problem of estimating signals consisting of one or more components of the form a(t)ejφ(t), where the amplitude and phase functions are represented by a linear parametric model. A maximum likelihood algorithm for estimating... more
We consider the problem of estimating signals consisting of one or more components of the form a(t)ejφ(t), where the amplitude and phase functions are represented by a linear parametric model. A maximum likelihood algorithm for estimating the phase and amplitude parameters is presented, and the corresponding Cramer Rao bound (CRB) is derived. By analyzing the CRB for the single-component case it is shown that the estimation of the amplitude and the phase are decoupled. The performance of the maximum likelihood algorithm is illustrated by Monte-Carlo simulations, and its statistical efficiency is verified
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The Golden code has been proposed as an optimal space-time code for multiple-input multiple-output (MIMO) communication systems. This paper considers a ¿blind¿ MIMO system where the channel is assumed to be unknown. The Golden code is... more
The Golden code has been proposed as an optimal space-time code for multiple-input multiple-output (MIMO) communication systems. This paper considers a ¿blind¿ MIMO system where the channel is assumed to be unknown. The Golden code is unidentifiable under this condition and can not be used directly. A block code modification is described which makes the Golden code usable in the
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... Our simulation results also showed that the approximation of expectation of OSIR, the main result in [5] was not accurate enough even for high SNR, large T and distanced sources. Problem Formulation We considered an M-element array... more
... Our simulation results also showed that the approximation of expectation of OSIR, the main result in [5] was not accurate enough even for high SNR, large T and distanced sources. Problem Formulation We considered an M-element array with an arbitrary geometry. ...
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The problem of estimating the depth of an underwater source from acoustic measurements is considered. The Cramer-Rao bound on the variance of the depth estimate is evaluated for the cases of one and two sensors. The effect of multipath on... more
The problem of estimating the depth of an underwater source from acoustic measurements is considered. The Cramer-Rao bound on the variance of the depth estimate is evaluated for the cases of one and two sensors. The effect of multipath on estimation alccuracy is investigated.
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We present a maximum likelihood (ML) approach for deconvolving a multi-input-multi-output (MIMO) non-dispersive system and recovering its inputs, from observation of its outputs. We apply this approach to the specific problem of... more
We present a maximum likelihood (ML) approach for deconvolving a multi-input-multi-output (MIMO) non-dispersive system and recovering its inputs, from observation of its outputs. We apply this approach to the specific problem of separating several narrowband digital communication signals that share the same frequency band. A computationally efficient adaptive algorithm for solving this problem is presented, and is shown to be
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SUMMARY Recently, there has been a considerable interest in parametric estimation of non-Gaussian processes, based on high-order moments. Several researchers have proposed algorithms for estimating the parameters of AR, MA and ARMA... more
SUMMARY Recently, there has been a considerable interest in parametric estimation of non-Gaussian processes, based on high-order moments. Several researchers have proposed algorithms for estimating the parameters of AR, MA and ARMA processes, based on the ...
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Research Interests: Signal Processing, Convergence, Multidisciplinary, Adaptive Signal Processing, Digital Communication, and 11 moreMean square error, Impulse response, Blind Equalization, TSP, Qam, Filtering, Channel Impulse Response (CIR), Quadrature Amplitude Modulation, Amplitude Modulation, Least-squares Approximation, and Finite Impulse Response Filter
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Abstract-This correspondence proposes an algorithm for detecting moving targets by imaging sensors and estimating their trajectories. The algorithm is based on directional filtering in the frequency do-main, using a bank of filters for... more
Abstract-This correspondence proposes an algorithm for detecting moving targets by imaging sensors and estimating their trajectories. The algorithm is based on directional filtering in the frequency do-main, using a bank of filters for all possible target directions. The di- ...