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A novel feature extraction method is proposed in this paper. Dislike contour-based or region-based approaches, an object is first converted to a closed curve by extended central projection (ECP). The derived curve not only keeps the affine transform information, but also is very robust to noise. Then whitening transform is performed to the curve such that the affine transformation is simplified to...
A kernel adapted to the spectral dimension of hyperspectral images is proposed in this paper. A distance based on a statistical cluster model is used to construct a radial kernel. This class specific kernel realizes a compromise between a conventional Gaussian kernel and a Gaussian kernel on the first principal components of the considered class. An automatic gradient optimization is used to select...
Common Spatial Pattern (CSP) is widely used in discriminating two classes of EEG in Brain Computer Interface applications. However, the performance of the CSP algorithm is affected by noise and artifacts, and the problem is more pronounced in small training data. To overcome these drawbacks, this paper proposes a new Spatially Sparsed CSP (SS-CSP) algorithm by inducing sparsity in the spatial filters...
Estimating the location of a signal source based on TOA measurements is an important problem in many applications. In the presence of sensor position errors, the accuracy of a source location estimate could be degraded significantly. This paper first derives the CRLB of the source location when sensor position errors are present. It continues to develop the theoretical increase in the mean-square...
In this paper, a fast and accurate algorithm for identifying circular objects in images is proposed. The presented method is a robust, fast and optimized adaption of Circular Hough Transform (CHT), Eigenvalues of Covariance Matrix and K-means clustering techniques. Results are greatly improved by implementing iterative K-means clustering algorithm and establishing an exponential growth instead of...
The situations where particle filtering fails (so-called weight degeneracy) can be detected with the asymptotic variance of the particle approximation. However, this asymptotic variance is in general intractable, and in the case of weight degeneracy, computing it by Monte Carlo sampling is inefficient. We propose to compute the asymptotic variance of the particle approximation via the Laplace method...
This paper considers the angle-only filtering problem in 3D using bearing and elevation angle measurements from a single maneuvering sensor. We develop continuous-discrete extended Kalman filter (EKF) based algorithms using modified spherical coordinates (MSC) and log spherical coordinates (LSC), where the dynamic and measurement models are described in continuous and discrete times, respectively...
A covariance matching approach for estimating the parameters in errors-in-variables systems is analyzed and the asymptotic accuracy of the parameter estimates is derived. The computation of the asymptotic covariance matrix of the parameter estimates is given in an algorithm and it is shown that the approach is asymptotically statistically efficient in a certain sense. An algorithm for computing the...
The location accuracy of Dual-Satellite Geolocation system, that estimates the location of a stationary source using Difference Time Offset (DTO) and Difference Frequency Offset (DFO) measurements of a signal as retransmitted by the two adjacent geostationary satellites and received by two ground stations in the area of visibility of both satellites, is relevant to the accuracy of parameters estimation...
We propose a blind channel estimation method for space-time block-coded single-carrier with frequency-domain equalization (SC-FDE) systems based on a simple, nonredundant precoding. This method of precoding allows us to better structure the relation between the covariance matrices of the received data and the products of channel coefficients. Using this structure, we can easily obtain the products...
Modern electronic tacheometers offer the possibility to capture kinematic processes in real time. In case when the kinematic process is observed with only one measurement system, we have no possibility to perform redundant observations that would enable the accuracy estimation of observations and computed values. The Kalman filter represents a method of advanced geodetic analysis and as such adjusts...
We present a new form of least squares (LS), called "hyper LS", for geometric problems that frequently appear in computer vision applications. Doing rigorous error analysis, we maximize the accuracy by introducing a normalization that eliminates statistical bias up to second order noise terms. Our method yields a solution comparable to maximum likelihood (ML) without iterations, even in...
Despite the apparent spatio-temporal decomposition given by (Probabilistic) Principal Component Analysis ((P)PCA), there is in fact no temporal coupling built into these models. Here we augment PPCA with a temporal model in the latent space by coupling the latent variables in time with an autoregressive model and show that the new model may be viewed as a generalisation of PPCA. We present an algorithm...
Phase unwrapping is the key step in Digital Elevation Model extraction and the measurement of surface deformation of Interferometric Synthetic Aperture Radar (InSAR). When in steep terrain or larger slope, the unwrapping result is bad and causes error transmission using the existing Kalman Filter phase unwrapping algorithm. Considering this situation, this paper presents an improved Kalman Filter...
A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method's error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft...
This paper discusses three algorithms for the problem of asynchronous Track-to-Track Fusion (AT2TF) with track delays, where the information configuration of T2TF with partial information feedback (AT2TFpf) is used. This is the most practical configuration for AT2TF with time delays, since communication delays make full information feedback very complicated. The first algorithm is the optimal memoryless...
Transmit precoding is a key technique for facilitating blind channel estimation at the receiver but the impact due to precoding on the channel capacity is scarcely addressed in the literature. In this paper we consider the single-carrier block transmission with cyclic prefix, in which a recently proposed diagonal-precoding assisted blind channel estimation scheme via covariance matching is adopted...
In this paper, an unscented Kalman filter (UKF) in an interacting multiple models (IMM) algorithm is designed to operate in non-line-of-sight (NLoS) conditions for localisation and tracking manoeuvring mobile. The considered context is that of wideband code division multiple access (WCDMA) mode of the universal mobile telecommunications systems (UMTS) using time of arrival (TOA) estimates in the downlink...
In this paper we show that the variance of estimated parametric models for open loop Multiple-Input Multiple-Output (MIMO) systems obtained by the prediction error method (PEM) satisfies a fundamental integral limitation. The fundamental limitation gives rise to a multivariable `waterbed' effect.
A robust algorithm to model the harmony structure of a music piece is proposed. The harmony structure is extracted directly from a music audio signal using a second-order statistic of chroma feature vectors. The method is experimentally shown to be robust against the degradation of chroma feature vectors due to noisy pitch estimation in our classical music opus identification evaluation. To analyze...
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