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Range dependent clutter rejection using range-recursive space-time adaptive processing (STAP) algorithms

SIGNAL PROCESSING 2010年第1期90卷 57-68页

作者： Beau, Sophie Marcos, Sylvie SUPELEC CNRS LSS F-91192 Gif Sur Yvette France

We here address the issue of ground clutter rejection for the detection of slowly moving targets in a non-side looking (NSL) array configuration airborne radar. The optimum space-time adaptive processing (STAP) filter needs the knowledge of the inverse of the space-time covariance matrix. In practice, it is unknown and has to be estimated. The most popular approximated method is the sample matrix inversion (SMI) method which consists in inverting the covariance matrix estimated by an average of the sample matrix over the secondary range cells. This estimator is unbiased in case of i.i.d. data. In an NSL configuration, the clutter power spectrum is range dependent and the data are consequently not i.i.d. We here present a solution to mitigate this range dependency of the data: the range recursive subspace-based algorithms. They are used in two architectures: a fully and a partially adaptive ones. Then a new range-recursive algorithm using Taylor series expansion is investigated. The performance of these algorithms are compared with that of the conventional STAP algorithms in term of SINR loss. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Airborne radar Space-time adaptive processing Range dependent clutter recursive algorithms

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Convergence analysis of instrumental variable recursive subspace identification algorithms

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AUTOMATICA 2007年第8期43卷 1377-1386页

作者： Mercere, Guillaume Lovera, Marco Politecn Milan Dipartimento Elettr & Informat I-20133 Milan Italy Univ Poitiers Lab Automat & Informat Ind F-86022 Poitiers France

The convergence properties of recently developed recursive subspace identification methods are investigated in this paper. The algorithms operate on the basis of instrumental variable (IV) versions of the propagator method for signal subspace estimation. It is proved that, under suitable conditions on the input signal and the system, the considered recursive subspace identification algorithms converge to a consistent estimate of the propagator and, by extension, to the state-space system matrices. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： subspace methods recursive algorithms linear systems instrumental variable convergence analysis

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Design and Digital Implementation of Fast and recursive DCT II-IV algorithms

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2019年第2期38卷 529-555页

作者： Perera, Sirani M. Madanayake, Arjuna Dornback, Nathan Udayanga, Nilan Embry Riddle Aeronaut Univ Dept Math Daytona Beach FL 32114 USA Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA

Using the proposed factorizations of discrete cosine transform (DCT) matrices, fast and recursive algorithms are stated. In this paper, signal flow graphs for the n-point DCT II and DCT IV algorithms are introduced. The proposed algorithms yield exactly the same results as with standard DCT algorithms but are faster. The arithmetic complexity and stability of the algorithms are explored, and improvements of these algorithms are compared with previously existing fast and stable DCT algorithms. A parallel hardware computing architecture for the DCT II algorithm is proposed. The computing architecture is first designed, simulated, and prototyped using a 40-nm Xilinx Virtex-6 FPGA and thereafter mapped to custom integrated circuit technology using 0.18-m CMOS standard cells from Austria Micro Systems. The performance trade-off exists between computational precision, chip area, clock speed, and power consumption. This trade-off is explored in both FPGA and custom CMOS implementation spaces. An example FPGA implementation operates at clock frequencies in excess of 230MHz for several values of system word size leading to real-time throughput levels better than 230 million 16-point DCTs per second. Custom CMOS-based results are subject to synthesis and place-and-route steps of the design flow. Physical silicon fabrication was not conducted due to prohibitive cost.

关键词： Discrete cosine transforms Fast algorithms recursive algorithms Arithmetic complexity Sparse and orthogonal factors Signal flow graphs Field-programmable gate array (FPGA) Application-specific integrated circuits (ASIC)

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ESTIMATE OF THE RATE OF CONVERGENCE OF recursive ROBUST IDENTIFICATION algorithms

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JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL 1994年第2期32卷 33-38页

作者： KULCHITSKIY, OY MOZGOVOI, AE

The problem of constructing nonasymptotic estimates of the rate of convergence of robust identification algorithms is considered. Estimates are constructed for the class of one-dimensional algorithms that are valid at every step of the algorithm with arbitrary, preassigned probability. Examples of these types of estimates are presented.

关键词： ROBUST IDENTIFICATION algorithms MARTINGALE recursive algorithms

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WELL-CONDITIONED recursive LEAST-SQUARED ESTIMATION algorithms

WELL-CONDITIONED RECURSIVE LEAST-SQUARED ESTIMATION ALGORITH...

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4TH IFAC Symposium on Adaptive Systems in Control and Signal Processing 1992

作者： LEVER, KV DEF SCI & TECHNOL ORG ELECTR RES LABSALISBURYSA 5108AUSTRALIA

ISBN: (纸本)0080417175

This paper explains the inadequacies due to ill-conditioning of classical recursive least squares signal estimation algorithms based on Taylor series expansions, then shows how the algorithms may be restructured using orthogonal expansions, at little cost in extra complexity, to provide well-conditioned versions suitable for implementation in a variety of digital signal processing applications. Several open questions are posed, mainly connected with the incorporation of signal windowing to provide smoothing filters.

关键词： LEAST-SQUARES ESTIMATION recursive algorithms WELL-CONDITIONING

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Well-Conditioned recursive Least-Squared Estimation algorithms

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IFAC Proceedings Volumes 1992年第14期25卷 453-458页

作者： K.V. Lever Electronics Research Laboratory Defence Science and Technology Organisation P.O. Box 1500 Salisbury South Australia 5108 Australia Signal Processing Research Institute University of South Australia Levels Campus South Australia 5095 Australia

关键词： Least-squares estimation recursive algorithms well-conditioning

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CONVERGENCE ANALYSIS OF INSTRUMENTAL VARIABLE recursive SUBSPACE IDENTIFICATION algorithms

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IFAC Proceedings Volumes 2006年第1期39卷 279-284页

作者： G. Mercère M. Lovera Laboratoire d'Automatique et d'Informatique Industrielle 40 avenue du recteur Pineau 86022 Poitiers France Phone: + 33 (0)5 49453509 Fax: +33 (0)5 49454034 Dipartimento di Elettronica e Informazione Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano Italy Phone: + 39 02 23993592 Fax: +39 02 23993412

The convergence properties of a recently developed recursive subspace identification algorithm of the MOESP class are investigated in this paper. The algorithm operates on the basis of an extended instrumental variable (EIV) version of the propagator method for signal subspace estimation. It is proved that, under weak conditions on the input signal and the identified system, the considered recursive subspace identification algorithm converges to a consistent estimate of the propagator and, by extension, of the state space system matrices.

关键词： Subspace methods recursive algorithms Identification algorithms State space models Tracking systems Convergence analysis

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INVERSE KINEMATIC SOLUTION TO A CALIBRATED PUMA-560 INDUSTRIAL ROBOT

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CONTROL ENGINEERING PRACTICE 1994年第2期2卷 239-245页

作者： CHEN, N PARKER, GA Department of Mechanical Engineering University of Surrey Guildford Surrey GU2 5XH UK

Robot calibration techniques provide a practical approach to improve the accuracy of industrial robot manipulators. A problem associated with the calibrated results is that the inverse kinematic solution to the calibrated kinematic model becomes difficult to resolve. This paper presents a method for solving the inverse kinematics problem of an S-model calibrated Puma 560 robot. It is a numerical iterative approach based on the closed-form inverse kinematic solution to the nominal Puma kinematic model. The reported method is accurate, efficient and suitable for real-time applications.

关键词： ROBOTS INVERSE KINEMATICS ROBOT KINEMATIC CONTROL ROBOT CALIBRATION recursive algorithms

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Modified two-dimensional Otsu image segmentation algorithm and fast realisation

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IET IMAGE PROCESSING 2012年第4期6卷 426-433页

作者： Chen, Q. Zhao, L. Lu, J. Kuang, G. Wang, N. Jiang, Y. Natl Univ Def Technol Sch Elect Sci & Technol Changsha 410073 Hunan Peoples R China

Traditional two-dimensional (2D) Otsu method supposes that the sum of probabilities of diagonal quadrants in 2D histogram is approximately one. This studies experiments and theory prove that the sum of probabilities of off-diagonal quadrants in 2D histogram is not always very small and this could not be neglected. Therefore the assumption mentioned above in 2D Otsu method is inadequately reasonable. In this study, an improved 2D Otsu segmentation method and recursive algorithm are proposed. By calculating probabilities of diagonal quadrants in 2D histogram separately, modified method is acquired. Experimental results show that proposed method can obtain better performance of segmentation than the traditional 2D Otsu method. The computation complexity of improved 2D Otsu method is equal to traditional 2D Otsu method.

关键词： recursive algorithms image segmentation algorithm Diagonal Quadrant histograms

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On Completeness of Cost Metrics and Meta-Search algorithms in $-Calculus

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FUNDAMENTA INFORMATICAE 2022年第2期188卷 63-90页

作者： Eberbach, Eugene Rensselaer Polytech Inst Dept Engn & Sci Hartford CT 06120 USA

In the paper we define three new complexity classes for Turing Machine undecidable problems inspired by the famous Cook/Levin's NP-complete complexity class for intractable problems. These are U-complete (Universal complete), D-complete (Diagonalization complete) and H-complete (Hypercomputation complete) classes. In the paper, in the spirit of Cook/Levin/Karp, we started the population process of these new classes assigning several undecidable problems to them. We justify that some super-Turing models of computation, i.e., models going beyond Turing machines, are tremendously expressive and they allow to accept arbitrary languages over a given alphabet including those undecidable ones. We prove also that one of such super-Turing models of computation - the $-Calculus, designed as a tool for automatic problem solving and automatic programming, has also such tremendous expressiveness. We investigate also completeness of cost metrics and meta-search algorithms in $-calculus.

关键词： automatic problem solving automatic programming undecidability intractablity recursive algorithms recursively enumerable but not recursive algorithms non-recursively enumerable algorithms super-Turing computation super-recursive algorithms p-decidability e-decidability a-decidability i-decidability reduction techniques U-completeness D-completeness H-completeness $-calculus cost metrics completeness meta-search algorithms completeness

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