A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on...
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ISBN:
(纸本)9781467350518
A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on recursive updating of sample covariance matrix and adaptive diagonal loading. New implementation of robust Capon beam former (RCB) is more robustness to non-stationary interference environment. Simulation results confirm efficiency of recursive robust adaptive beamformer.
This paper focuses on the state estimation problem of a class of systems under binary-valued observations and uncertain dynamics. Firstly, the key idea of the extended state observer is introduced to deal with the unc...
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ISBN:
(纸本)9798350366907;9789887581581
This paper focuses on the state estimation problem of a class of systems under binary-valued observations and uncertain dynamics. Firstly, the key idea of the extended state observer is introduced to deal with the uncertain dynamics. The idea is to regard the uncertain dynamic of the state model as a signal to be estimated, and then take it as an extended state. Secondly, based on the extended binary-valued system, an algorithm gain design method is proposed and an extended state based recursive binary-valued projection filtering algorithm is established. Furthermore, the effectiveness of the proposed algorithm is illustrated via simulations for binary-valued systems with different uncertain dynamics.
In this paper, we propose a simple learning algorithm for non\|linear function approximation and system modeling using minimal radial basis function neural network with high generalization performance. A hybrid algori...
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In this paper, we propose a simple learning algorithm for non\|linear function approximation and system modeling using minimal radial basis function neural network with high generalization performance. A hybrid algorithm is constructed, which combines recursive n \|means clustering algorithm with a simple recursive regularized least squares algorithm (SRRLS). The n \|means clustering algorithm adjusts the centers of the network, while the SRRLS constructs a parsimonious network which makes the generalization performance of the network well. The SRRLS algorithm needs no matrix computing, so it has a lower computational cost and no ill\|conditional problem. Because of the recursive manner, this algorithm is suitable for on\|line applications. The effectiveness of this algorithm is demonstrated by two benchmark examples.
Stream ordering is a useful property of every river network, having a wide range of applications. A method for determining stream orders that quickly and easily addresses various network topologies and magnitudes is t...
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Stream ordering is a useful property of every river network, having a wide range of applications. A method for determining stream orders that quickly and easily addresses various network topologies and magnitudes is therefore needed. This paper introduces a general recursive stream ordering framework for vector hydrography. It also presents a linear, O(n), stream ordering procedure for braided river networks, which is a major improvement to the existing quadratic, O(n(2)), procedure. The discussion includes results and interpretations, and the appendices present procedure pseudocodes and thorough line by line explanations.
This paper presents a comprehensive recursive formulation of dynamic equations for multibody systems with variable-speed control moment gyroscopes. It permits any rigid or flexible body in the system to have a cluster...
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This paper presents a comprehensive recursive formulation of dynamic equations for multibody systems with variable-speed control moment gyroscopes. It permits any rigid or flexible body in the system to have a cluster of variable-speed control moment gyroscopes in a generic configuration as actuators. The detailed dynamics of the actuators is taken into consideration to capture its interactions with the flexibilities of the structures. The recursive algorithm is obtained through analyzing the kinematics and dynamics between two adjacent bodies, both of which can be rigid or flexible, or one of which is rigid and the other is flexible. The orthonormal complement of the projection matrix of the joint is adopted to express the constraint equations for structural loops uniformly. Numerical results of an illustrative example are presented to show the accuracy and efficiency of the proposed method by comparing it with a nonrecursive formulation.
作者：
BarItzhack, IYNASA
GODDARD SPACE FLIGHT CTRFLIGHT MECH BRANCHGREENBELTMD 20771
QUEST is a well-known algorithm for least squares fitting of the attitude quaternion of a spacecraft to vector measurements. QUEST, however, is a single time point (single frame) batch algorithm;thus, measurements tha...
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QUEST is a well-known algorithm for least squares fitting of the attitude quaternion of a spacecraft to vector measurements. QUEST, however, is a single time point (single frame) batch algorithm;thus, measurements that were taken at previous time points are discarded, The algorithm presented provides a recursive routine, which considers all past measurements. The algorithm is based on the fact that the so-called K matrix, one of whose eigenvectors is the sought quaternion, is linearly related to the measured vector pairs and on the ability to propagate K, The extraction of the appropriate eigenvector is done according to the classical QUEST algorithm, This stage, however, can be eliminated, and the computation simplified, if a standard eigenvalue-eigenvector solver algorithm is used.
A new recursive identification algorithm using the cosine basis functions has been developed for the time-varying systems. It is demonstrated that through expanding the time-varying parameters within a sliding time wi...
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A new recursive identification algorithm using the cosine basis functions has been developed for the time-varying systems. It is demonstrated that through expanding the time-varying parameters within a sliding time window into the virtual even periodic functions, the parameters in the window can explicitly be approximated by the cosine series. Following the orthogonality of the trigonometric functions, the parameter estimation and the efficient update of the data matrices are recursively implemented to decrease the computational complexity. Moreover, a smoothing technique is also considered to reduce the estimation error caused by the noise effects. In contrast with the standard RLS, LMS/NLMS, AP/BOP and the conventional methods based on the basis functions, the proposed algorithm has higher tracking performance even for the high series degree, and can reduce the distortion of the Gibbs effect at the window edges.
This paper focuses on the state estimation problem of a class of systems under binary-valued observations and uncertain dynamics. Firstly, the key idea of the extended state observer is introduced to deal with the unc...
详细信息
ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
This paper focuses on the state estimation problem of a class of systems under binary-valued observations and uncertain dynamics. Firstly, the key idea of the extended state observer is introduced to deal with the uncertain dynamics. The idea is to regard the uncertain dynamic of the state model as a signal to be estimated, and then take it as an extended state. Secondly,based on the extended binary-valued system, an algorithm gain design method is proposed and an extended state based recursive binary-valued projection filtering algorithm is established. Furthermore, the effectiveness of the proposed algorithm is illustrated via simulations for binary-valued systems with different uncertain dynamics.
A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on...
详细信息
ISBN:
(纸本)9781467350501
A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on recursive updating of sample covariance matrix and adaptive diagonal loading. New implementation of robust Capon beamformer (RCB) is more robustness to non-stationary interference environment. Simulation results confirm efficiency of recursive robust adaptive beamformer.
Krasker and Welsch proposed an estimator related to GM-estimators for robust estimation in the classical linear model. In this paper we use standard methods for creating recursive algorithms to formulate a recursive v...
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