A second-order statistics based dual-linear predictor structure is proposed for blind source extraction from noisy instantaneous mixtures. The noise component is assumed to be spatially and temporally white, but the v...
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ISBN:
(纸本)9781424422401
A second-order statistics based dual-linear predictor structure is proposed for blind source extraction from noisy instantaneous mixtures. The noise component is assumed to be spatially and temporally white, but the variance information of noise is not required. A detailed proof of the proposed approach is provided and an adaptive algorithm is developed. Simulation results show that it can extract the source signals successfully.
In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is obtained by considering a novel range and scanning angle plane different from the...
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ISBN:
(纸本)1424403081
In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is obtained by considering a novel range and scanning angle plane different from the conventional methods. An alternative method is briefly proposed for smoothing the target density function by taking advantage of Walsh functions. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm.
The Manchester Decoding Algorithm (MDA) presented in [1] succeeds in separating Secondary Surveillance Radar (SSR) replies impinging on an array. The final step of the MDA consist of jointly diagonalizing a collection...
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ISBN:
(纸本)1424403081
The Manchester Decoding Algorithm (MDA) presented in [1] succeeds in separating Secondary Surveillance Radar (SSR) replies impinging on an array. The final step of the MDA consist of jointly diagonalizing a collection of several symmetric cubes by a sub-optimal technique. In this article, we demonstrate that it is in fact a PARAFAC problem with an almost symmetric solution. Furthermore, comparisons with other algorithms are carried out, with the help of computer simulations.
The resolving ambiguity of phase interferometer is necessary when the baseline separation between elements exceeds half wavelength since the phase difference between elements can only be measured modulo 2 pi. It is di...
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ISBN:
(纸本)1424403081
The resolving ambiguity of phase interferometer is necessary when the baseline separation between elements exceeds half wavelength since the phase difference between elements can only be measured modulo 2 pi. It is difficult to meet the condition the minimum distance between two antennas is less than half wavelength for avoiding ambiguity in wideband operation. In this paper, we propose a simple and efficient array design method which minimizes the probability of ambiguity. This method adapts NLA (nonuniform linear array) geometry. And there is no need to maintain the distance between antennas less than half wavelength. We also show some numerical examples and experimental results of the 2-D array prototype for airborne application.
We describe a method of tuning a simple detection process of stationary targets in SAR images. The tuning metric accounts for the squared-error performance of prescient estimators of target location and reflectivity. ...
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ISBN:
(纸本)1424403081
We describe a method of tuning a simple detection process of stationary targets in SAR images. The tuning metric accounts for the squared-error performance of prescient estimators of target location and reflectivity. The efficiencies of these prescient estimators are compared to their Cramer Rao bounds (CRBs). The off-line tuning is performed by collecting statistics of scatterer estimation in SAR images created using sparse-array spotlight mode simulations.
This study deals with buried object localization using a towed flexible array of sensors. So, the phases of the received signals deviate from the assumed plane wave model by the phase errors which are due to the rando...
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ISBN:
(纸本)9781424422401
This study deals with buried object localization using a towed flexible array of sensors. So, the phases of the received signals deviate from the assumed plane wave model by the phase errors which are due to the random distortions of the antenna. In this letter, an objective function is defined and a new source steering vector including the acoustic scattering model at each sensor is proposed. The robust DIRECT (DIviding RECTangles) method is applied to minimize this objective function for estimating the bearings and the ranges of objects together with the phase errors. To decorrelate the received signals and to estimate the coherent signal subspace a fast focusing operator is proposed. The performance of the developed method is investigated on experimental data recorded during underwater acoustic experiments.
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. The proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array co...
ISBN:
(纸本)9781424422401
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. The proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array configurations. This is accomplished by employing the recently introduced Manifold Separation Technique (MST) [3], which stems from wavefield modelling [4]. The algorithms process the data in the element-space domain, i.e. no mapping of the data that introduces errors is required. Moreover, coherent sources can be handled. The proposed MST-based MVP algorithm shows a statistical performance close to the Cramer-Rao Lower Bound (CRLB) [5, 6]. The performance is illustrated using calibration data from two real-world arrays.
In this paper we propose an algorithm for angle and polarization estimation of non-coherent sources using real-world polarimetric antenna arrays. In order to construct an accurate model of an antenna array, we exploit...
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ISBN:
(纸本)1424403081
In this paper we propose an algorithm for angle and polarization estimation of non-coherent sources using real-world polarimetric antenna arrays. In order to construct an accurate model of an antenna array, we exploit its Effective Aperture Distribution Function (EADF). This model contains information on the array response for a vertical and horizontal excitation, the directional characteristic of each element, andarray imperfections. Here, we propose a method stemming from the RARE (RAnk-Reduction Estimator) algorithm. It performs fast (search-free) DoAs and polarization coefficients estimation. Throughout simulation results, we verify that the algorithm has close to optimal statistical performance with polarimetric real-world arrays. We present the statistical performance for three different array configurations.
Recently, the authors proposed a miniaturized microphone array not utilizing the phase difference but utilizing the directivity of each microphone, namely aggregated microphones. We have already showed that the phased...
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ISBN:
(纸本)1424403081
Recently, the authors proposed a miniaturized microphone array not utilizing the phase difference but utilizing the directivity of each microphone, namely aggregated microphones. We have already showed that the phased microphone array and the aggregated microphones can be described within the same framework. We have also showed that it is possible to apply the aggregated microphones to the various methods of the phased microphone array. However, the difference of the performance between the phased array and the aggregated microphones has not been evaluated yet. The effect of the directivity and the posture of each microphone on the performance of the aggregated microphones has not also been evaluated yet. In this paper, we evaluate the performance of DCMP (Directionally Constrained Minimization of Power) adaptive array utilizing aggregated microphones.
Local processing on the nodes of a distributed sensing andprocessing system has the benefits of reducing the data volume transferred from the nodes to the fusion center, reducing both transmission power requirements ...
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ISBN:
(纸本)1424403081
Local processing on the nodes of a distributed sensing andprocessing system has the benefits of reducing the data volume transferred from the nodes to the fusion center, reducing both transmission power requirements and the computational burden on the fusion center. The individual nodes obtain measurements from the environment and transmit a quantized detection statistic to the fusion center. Quantization threshold levels need to be found for each sensor that maximize the performance of the system. We propose a global optimization method, the particle filtering optimization method, that uses particle filtering to propagate the values of the thresholds of a distributed detection system to sensor threshold values that are optimal with respect to some measure of system performance. We demonstrate, through simulations, the effectiveness of the particle filtering optimization method in finding the threshold of each of the sensors used in detection scenario.
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