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This paper addresses the problem of broadband spatial spectrum estimation using multiple spatially-aliased arrays. Unlike previous approaches using sparse arrays, the signals here are assumed to be uncorrelated between multiple arrays which, in fact, may be receiving the same source during different time intervals. This paper presents an approach which jointly exploits spatial-orientation and broadband...
This paper investigates bias compensation for improving the performance of target tracking using range or range difference measurements. We obtain the Maximum Likelihood estimate of the target position at the current instant and pass it to the Kalman filter as observation to obtain the target track. The nonlinear relationship between the target position and measurements creates bias that can degrade...
Locally Orderless Tracking (LOT) is a visual tracking algorithm that automatically estimates the amount of local (dis)order in the object. This lets the tracker specialize in both rigid and deformable objects on-line and with no prior assumptions. We provide a probabilistic model of the object variations over time. The model is implemented using the Earth Mover's Distance (EMD) with two parameters...
The fitting of a collection of noisy data points to a circle is a nonlinear and challenging problem, and it plays an important role in many signal processing applications. This paper proposes a semi-definite programming solution for the circle fitting problem based on the semi-definite relaxation technique. The relaxation of the maximum likelihood estimation converts a nonconvex problem to an approximate...
Effective denoising is vital for proper analysis and accurate quantitative measurements from Magnetic Resonance (MR) images. Apart from following the general criteria for denoising, the algorithms that deal with MR images should also take into account the bias generated due to the Rician nature of the noise in the magnitude MR images. Maximum Likelihood (ML) estimation methods were proved to be very...
The nonlinear nature of the source localization problem creates bias to a location estimate. The bias could play a significant role in limiting the performance of localization and tracking when multiple measurements at different instants are available. This paper performs bias analysis of the source location estimate obtained by the maximum likelihood estimator, where the positioning measurements...
In this paper, we propose a novel acoustic model adaptation method for noise robust speech recognition. Model combination is a common way to adapt acoustic models to a target test environment. For example, the mean supervectors of the adapted model are obtained as a linear combination of mean supervectors of many pre-trained environment-dependent acoustic models. Usually, the combination weights are...
Probabilistic models of audio spectrograms used in audio source separation often rely on Poisson or multinomial noise models corresponding to the generalized Kullback-Leibler (GKL) divergence popular in methods using Nonnegative Matrix Factorization (NMF). This noise model works well in practice, but it is difficult to justify since these distributions are technically only applicable to discrete counts...
We consider a distributed sensor network in which the single antenna sensor nodes observe a deterministic unknown parameter and after encoding the observed signal with a phase parameter, the sensor nodes transmit it simultaneously to a multi-antenna fusion center (FC). The FC optimizes the phase encoding parameter and feeds it back to the sensor nodes such that the variance of estimation error can...
Cooperative time-of-arrival-based sensor localization in a non-line-of-sight (NLOS) environment is investigated. Cooperative sensor localization plays an important role in indoor networks where GPS is limited. However, indoor networks suffer from NLOS propagation which degrades localization accuracy significantly. In this paper, we assume that the estimator is able to discriminate NLOS connections...
In this paper, we show that a patch-based approach can successfully be applied for impulse noise removal. This requires careful choices for both the distance between patches and for the statistical estimator of the original patch. This method proves to be particularly powerful, especially for the restoration of textured areas, and compares favorably to recent restoration methods.
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum likelihood estimator and is based on a parametric model where the signals in the various channels share the same fundamental frequency but can have different amplitudes, phases, and noise characteristics. This essentially means that the model allows for different conditions in the various channels, like...
The linear dynamic Hammerstein model presents some static nonlinearity. The predominant method to estimate the components of this model is to minimize the error between the simulated and measured outputs. Taking the Gaussian input signals into account, we can estimate the linear part of the Hammerstein model by using the Buss gang's classic theory. Accordingly, considering the case in point with the...
The problem considered in this paper is that of approximating a sample covariance matrix by one with a Toeplitz structure. The importance stems from the apparent sensitivity of spectral analysis on the linear structure of covariance statistics in conjunction with the fact that estimation error destroys the Toepliz pattern. The approximation is based on appropriate distance measures. To this end, we...
A novel equalization technique based on noise predictive maximum likelihood and partial response signaling is proposed to enhance the capacity of WDM-PON using SOA-REAM. We successfully demonstrate 40-Gb/s upstream transmission over 20-km bidirectional fiber.
In this paper, a method for precise tracking of aircrafts based on Time of Arrival (TOA) determination of transponder signals is presented. Target location via multilateration based on Time Difference of Arrival (TDOA) measurements is a well known powerful method. In recent time, methods of target location using direct TOA measurement processing without the indirection of generating TDOA measurements...
In the passive underwater context the presence of two bounding surfaces (i.e., sea surface and seabed) results in several paths between the receiver and the source. In this paper we propose a novel closed-form least-squares (LS) solution by combining the time-delay information with angle measurements. Despite its simplicity, the LS estimator exhibits poor localization performance as a result of ignoring...
While fading, in general, is detrimental to accurately localizing a target, fading correlation between adjacent receivers may be exploited to improve localization accuracy. Therefore, this paper presents a novel wireless localization scheme that employs a combination of cross-correlation between shadow fading noise and copula technique to recursively estimate the location of a transmitter. A stochastic...
In high frequency (HF) skywave over-the-horizon radar (OTHR), radar signals are subjected to phase contamination as they propagate through the ionosphere, leading to severe degradation capability of OTHR radar, so that it needs to be corrected. According to the high spatial correlativity of the ionosphere contamination and the adjacent range cells are subjected to the same contamination, a new approach...
Fitting a compact model to measured data that captures the underlying relationship is a fundamental task in computer graphics and computer-aided design. Low-order implicit curves and surfaces are a practical choice in grasping this relationship since they are closed under several geometric operations (e.g. intersection, union, offset) while they offer a higher degree of smoothness than their parametric...
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