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Loughborough Antennas and Propagation Conference (LAPC)

作者： Ali, Weal A. E. Mohamed, Darwish A. E. Hassan, Adel H. G. Arab Acad Sci & Technol Dept Elect & Commun Engn Alexandria Egypt

ISBN: (纸本)9781479900916

Beamforming is a signal processing technique that has the ability to direct the main beam toward signal-of-interest and the null toward signal-of-not-interest without moving antenna array. This technique is achieved by using algorithms which change the amplitude and phase of array pattern continuously. This paper presents hybrid algorithm that is a combination of two algorithms, least mean square algorithm and sample matrix inversion algorithm. The hybrid algorithm (least mean square/sample matrix inversion) is applied on an array of dipoles to overcome the shortcomings of existing algorithms for a robust smart antenna system. To focus the main beam toward the desired direction and place the null in the direction of the interference signals, the weights of the inversion matrix in sample matrix inversion are calculated and these weights will be the initial weights in least mean square algorithm. The merit of this approach solves the convergence speed problem of the least mean square algorithm as well as the computation intensive exists in sample matrix inversion algorithm and decreases the least mean square error. The simulation results indicate the analyses of least mean square, sample matrix inversion and hybrid algorithm performances. These techniques are compared and verified using MATLAB.

关键词： smart antenna least mean square algorithm sample matrix inversion algorithm Beamforming

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A Hybrid Least Mean Square/sample matrix inversion algorithm Using Microstrip Antenna Array

A Hybrid Least Mean Square/Sample Matrix Inversion Algorithm...

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Science and Information Conference (SAI)

作者： Ali, Wael A. E. Hassan, Adel H. G. Arab Acad Sci & Technol Elect & Commun Engn Dept Alexandria Egypt

ISBN: (纸本)9780989319317

Adaptive beamforming algorithms is the kind of smart antenna algorithms that have the ability to direct the main beam toward the desired signal and to place a null in the direction of the interference signal. Those algorithms achieve the desired direction by adjusting weights "amplitude and phase" of the array pattern. The proposed hybrid algorithm is presented in this paper that combines between two algorithms to improve the performance of them. This is achieved by utilizing merits of two algorithms and avoiding demerits of them. Those two algorithms are least mean square algorithm and sample matrix inversion algorithm. A hybrid algorithm of least mean square and sample matrix inversion (least mean square/sample matrix inversion) is applied on rectangular microstrip antenna to indicate the performance of the three algorithms. The microstrip antenna covers the range between 1700-1950MHz with resonant frequency 1850MHz. This frequency range is used in many applications such as mobile communication in GSM, IS-95 (CDMA), 3G, and 4G. the conventional algorithms and the hybrid algorithm are compared and verified using MATLAB.

关键词： smart antenna least mean square algorithm sample matrix inversion algorithm beamforming

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Finite sample size effect on minimum variance beamformers:: Optimum diagonal loading factor for large arrays

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2006年第1期54卷 69-82页

作者： Mestre, X Lagunás, MA Ctr Tecnol Telecommun Catalunya ES-08034 Barcelona Spain

Minimum variance beamformers are usually complemented with diagonal loading techniques in order to provide robustness against several impairments such as imprecise knowledge of the steering vector or finite sample size effects. This paper concentrates on this last application of diagonal loading techniques, i.e., it is assumed that the steering vector is perfectly known and that diagonal loading is used to alleviate the finite sample size impairments. The analysis herein is asymptotic in the sense that it is assumed that both the number of antennas and the number of samples are high but have the same order of magnitude. Borrowing some results of random matrix theory, the authors first derive a deterministic expression that describes the asymptotic signal-to-noise-plus-interference ratio (SINR) at the output of the diagonally loaded beamformer. Then, making use of the statistical theory of large observations (also known as general statistical analysis or G-analysis), the authors derive an estimator of the optimum loading factor that is consistent when both the number of antennas and the sample size increase without bound at the same rate. Because of that, the estimator has an excellent performance even in situations where the quotient between the number of observations is low relative to the number of elements of the array.

关键词： diagonal loading G-estimation minimum variance distortionless beamformer (MVDR) random matrix theory sample matrix inversion algorithm

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Suppression of Intermittent Interference using Smart Antenna with Distributed Training Scheme

Suppression of Intermittent Interference using Smart Antenna...

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11th International Bhurban Conference on Applied Sciences and Technology (IBCAST)

作者： Siddiqui, Fayyaz Ahmad Sreng, V. Danilo-Lemoine, F. Falconer, D. CESAT Islamabad Pakistan Carleton Univ Dept Syst & Comp Engn Broadband Commun & Wireless Syst BCWS Ctr Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781479923199

In this paper, an adaptive antenna arrays processing based on sample matrix inversion (SMI) algorithm with a novel training scheme is presented. The training scheme used is known as distributed training scheme [1]. The scheme uses distributed placement of the training symbols throughout the packet. The channel estimation, along with this particular training scheme, is designed to track intermittent interference. This type of interference arises due to an uncontrolled and unpredictable environment such as that of a license-exempted case. In this work, we show the comparison between the performance of distributed scheme with pre-amble training method and also with some iterative based adaptation algorithms like LMS and CMA. A lower bound theoretical analysis is made to compare its result to the simulation results. Moreover, analytical expression for the excess MSE are derived for both distributed and preamble training schemes. Short blocks scenario for the creation of intermittent interference is created by using a batch Poisson traffic model.

关键词： adaptive antenna arrays channel estimation interference suppression iterative methods matrix inversion mean square error methods adaptive antenna arrays processing batch Poisson traffic model channel estimation distributed placement distributed training scheme intermittent interference iterative based adaptation algorithms preamble training method sample matrix inversion algorithm smart antenna training symbols Antenna arrays Correlation Interference Simulation Training Vectors

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Research on robust SMI algorithm for phased antennas

Research on robust SMI algorithm for phased antennas

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International Conference on Microwave and Millimeter Wave Technology

作者： Li Zhenli Han Zhiren Harbin Engn Univ Harbin Heilongjiang Pr Peoples R China Res Inst CSIC Hubei Peoples R China

ISBN: (纸本)9781424418794

This paper introduces the study on adaptive beamforming algorithm for phased Antennas. a modified orthogonal algorithm was put forward in this paper. The formulas were derived and steps of computation were given. The new algorithm had less computation than orthogonal algorithm with the similar performance. The theoretical analysis and computer simulation results showed that the algorithm was effective.

关键词： antennas matrix inversion adaptive beamforming algorithm orthogonal algorithm phased antennas sample matrix inversion algorithm

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Data block processing structure for airship-borne passive bistatic radar

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JOURNAL OF ENGINEERING-JOE 2019年第19期2019卷 6295-6299页

作者： Xu, Feng Liu, Xin Liu, Li Wang, Chao Wang, YiFei Natl Key Lab Sci & Technol Test Phys & Numer Math Beijing 100076 Peoples R China DFH Satellite Co Ltd Beijing 100094 Peoples R China

Serious ground clutter is of significant influence for target detection in an airship-borne passive bistatic radar (ABPBR) using frequency modulated broadcasting signals. The authors propose a data segment processing scheme to recover the direct signal from multi-path clutter and suppress the multi-path in the surveillance channel in an ABPBR. Super exponential (SE) equaliser and sample matrix inversion algorithm are exploited to recover the transmitted signal and suppress the serious multi-path interference, respectively. It is shown that the proposed algorithms can accomplish the target detection task effectively by computer simulations.

关键词： object detection passive radar radar detection radar clutter FM radar airships broadcasting radar interference interference suppression ABPBR sample matrix inversion algorithm data block processing structure airship-borne passive bistatic radar frequency modulated broadcasting signals data segment processing scheme signal transmission multipath interference suppression ground clutter target detection multipath clutter surveillance channel superexponential equaliser SE equaliser

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