In this paper, a new general Linearly constrained recursive least squares (RLS) array beamforming algorithm, based on an inverse QR decomposition, is developed for multiple jammers suppression. It is known the LS weig...
详细信息
ISBN:
(纸本)0780367200
In this paper, a new general Linearly constrained recursive least squares (RLS) array beamforming algorithm, based on an inverse QR decomposition, is developed for multiple jammers suppression. It is known the LS weight vector can be computed without back substitution In the inverse Qrd based algorithms and is suitable to be implemented using the systolic array. Also, the problem of the unacceptable numerical performance in limited precision environments, occurred in the "fast" RLS filtering algorithms, can be avoided. To document the advantage of this new constrained algorithm performance, In terms of convergence property of the learning curve and the capability of jammer's suppression, is investigated. We show that our proposed algorithm outperforms the LCLMS algorithm [5] and the linearly constraint fast LS algorithm (LCFLS) and its robust version (LCRFSL) algorithm [4].
Nonparametric Bayesian techniques are considered for learning dictionaries for sparse data representations, with applications in sparse rendering of sensor data. The beta process is employed as a prior for learning th...
详细信息
ISBN:
(纸本)9781424451807
Nonparametric Bayesian techniques are considered for learning dictionaries for sparse data representations, with applications in sparse rendering of sensor data. The beta process is employed as a prior for learning the dictionary, and this non parametric method naturally infers an appropriate dictionary size. The proposed method can learn a sparse dictionary, and may also be used to denoise a signal under test. The noise variance need not be known, and can be non-stationary. The dictionary coefficients for a given sensorsignal may be employed within a classifier. Several example results are presented, using both Gibbs and variational Bayesian inference, with comparisons to other state-of-the-art approaches.
This paper investigates the design choices and implementation schemes for information fusion among cluster heads in a large-scale hierarchical wireless sensor network. Two main issues addressed are: whether to choose ...
详细信息
ISBN:
(纸本)9781424451807
This paper investigates the design choices and implementation schemes for information fusion among cluster heads in a large-scale hierarchical wireless sensor network. Two main issues addressed are: whether to choose centralized processing with aid of a fusion center or decentralized collaboration among cluster heads, and for the latter choice, how to collaborate. Based on a sparse signal recovery problem arising from an environmental monitoring application, we propose a decentralized collaborative decision-making algorithm for cluster heads, and compare it with the centralized scheme. Our observation is: when the number of sensors within each cluster is quite large to induce a large amount of data, and the cluster heads are subject to multi-hop communications due to limited communication range, the collaborative algorithm is superior to the centralized one in terms of communication load and energy efficiency.
Compressive sensing (CS) techniques have shown promise for sparse imaging applications such as ground penetrating radar (GPR). However, CS involves the enumeration of a dictionary which implies huge storage requiremen...
详细信息
Harmonizable processes constitute an important class of non-stationary stochastic processes. In this paper we study the important extension to multivariate harmonizable random fields. We derive the multivariate- multi...
详细信息
In this paper, unitary root-MUSIC algorithm for direction of arrival estimation is proposed for Uniform Circular array. Uniform circular array provides uniform performance in any direction and simultaneous azimuth and...
详细信息
ISBN:
(纸本)0780382927
In this paper, unitary root-MUSIC algorithm for direction of arrival estimation is proposed for Uniform Circular array. Uniform circular array provides uniform performance in any direction and simultaneous azimuth and elevation angle estimates. The proposed algorithm has low computational complexity because eigenvalue decomposition for real number may be used. It also provides low variance estimates because the number of observations is doubled in comparison to conventional MUSIC algorithm. Also, a robust extension to the method is introduced based on multivariate extensions of nonparametric statistics. It gives highly reliable results in the face of heavy-tailed noise and interference. The additional computational cost is negligible.
The presence of measurement noise and model uncertainties in sensorarrays and the lack of statistical information poses several challenges for development of effective and robust algorithms for the Direction-of-Arriv...
详细信息
作者：
Farina, A.Fabrizio, G.A.Melvin, W.L.Timmoneri, L.
Chief Technical Office Radar and Technology Division Via Tiburtina Km. 12.400 00131 Rome Italy
PO box 1500 Edinburgh SA 5111 Australia
7220 Richardson Rd. Smyrna GA 30080 United States
The space-time adaptive processing (STAP) technique was originally conceived to suppress clutter (and jamming) received by radar on board moving platforms such as aircraft;this was so because of the clutter ridge in t...
详细信息
This paper develops a generalized Cauchy density (GCD) based theoretical approach that allows the formulation of challenging problems in a robust fashion. The proposed framework subsumes the generalized Gaussian distr...
详细信息
ISBN:
(纸本)9781424451807
This paper develops a generalized Cauchy density (GCD) based theoretical approach that allows the formulation of challenging problems in a robust fashion. The proposed framework subsumes the generalized Gaussian distribution (GGD) family based developments, thereby guaranteeing performance improvements over traditional problem formulation techniques. This robust framework can be adapted to a variety of applications in signalprocessing. We formulate two particular applications under this framework in this paper: 1) Robust reconstruction methods for compressed sensing and 2) robust estimation in sensor networks with noisy channels.
This paper proposes an architecture for future GNSS receivers, exploiting the planned GPS and Galileo publicly available signals. The use of direct sampling, multiples antennas and Maximum Likelihood array synchroniza...
详细信息
暂无评论