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FAST NULL-STEERING algorithm FOR BROAD-BAND POWER INVERSION ARRAY

IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING 1990年第5期137卷 377-383页

作者： KO, CC Department of Electrical Engineering National University of Singapore Singapore Singapore

A fast algorithm for broadband power inversion adaptive arrays is investigated. Essentially, in this algorithm, each broadband jammer is individually tracked by steering a broadband null formed from the use of a set of tapped delay line filters in a Davies beamformer. To steer a particular broadband null to its optimal position, the algorithm first swaps the associated set of null-controlling filters into the last stage of the beam former, and then employs the lms algorithm with a simple time-invariant decorrelation preprocessor to adjust the filter parameters to minimise the output power for a number of iterations. Performing this procedure for each null in turn results in continuous tracking of all the broadband jammers in a cyclical manner. Although the algorithm requires implementation of the broadband tapped delay-line Davies beamformer, only one tapped delay-line filter is being adaptively updated at any instant. Thus, when the number of elements is small, the overall implementation complexity of the proposed algorithm is comparable to that of using the lms algorithm directly. However, since each broadband null is independently steered, the proposed algorithm has a much faster convergence behaviour, particularly under situations of severe jamming.

关键词： broadband power inversion adaptive arrays fast null-steering algorithm adaptive filters correlation methods antenna phased arrays broadband jammer delay lines lms algorithm Signal processing and detection Davies beamformer signal processing jamming Antenna arrays tapped delay line filters time-invariant decorrelation preprocessor

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Auto-calibrating adaptive array for mobile telecommunications

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2000年第2期36卷 729-736页

作者： Wennström, M Strandell, J Öberg, T Linkskog, E Rydberg, A Uppsala Univ Signals & Syst Grp SE-75120 Uppsala Sweden

A major concern for adaptive antennas is the calibration of hardware. Here we consider the calibration of an analog beamformer (ABF), which calculates the weights in a digital signal processor (DSP), but weights the RF signals using a hardware beamformer. Two novel methods are presented of performing a calibration of this adaptive antenna during normal operation. This will mitigate temperature drift and aging of active components. Both methods uses a feedback of the beamformer output signal, to calculate the error in the beamformer output, or to identify the parameters in the temperature drift, The algorithms are transparent to normal antenna operation and are computationally simple. Simulations show that when using these auto-calibration methods, the performance is independent of variation in hardware parameters when a realistic temperature drift is introduced. The proposed algorithms are intended for use in a time-division multiple access (TDMA) mobile telephone system, but the methods are applicable in radar systems also.

关键词： adaptive antenna arrays array signal processing calibration feedback least mean squares methods mobile radio time division multiple access DSP weights calculation lms algorithm SMI algorithm TDMA mobile telephone system adaptive antennas analog beamforme array signal processing mobile communication Mobile radios Feedback time division multiple access temperature drift adaptive antenna arrays Least mean square algorithm adaptive antenna

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Blind adaptive identification of FIR channel in chaotic communication systems

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CHINESE PHYSICS 2004年第3期13卷 329-334页

作者： Wang, BY Chow, TWS Ng, KT Nanjing Univ Posts & Telecommun Dept Informat Engn Nanjing 210003 Peoples R China City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China

In this paper we study the problem of blind channel identification in chaotic communications. An adaptive algorithm is proposed, which exploits the boundness property of chaotic signals. Compared with the EKF-based approach, the proposed algorithm achieves a great complexity gain but at the expense of a slight accuracy degradation. However, our approach enjoys the important advantage that it does not require the a priori information such as nonlinearity of chaotic dynamics and the variances of measurement noise and the coefficient model noise. In addition, our approach is applicable to the ARMA system.

关键词： chaotic communication blind identification lms algorithm extended Kalman filtering

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Experimental study on active vibration control of a gearbox system

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JOURNAL OF SOUND AND VIBRATION 2005年第3-5期282卷 713-733页

作者： Guan, YH Lim, TC Shepard, WS Univ Alabama Dept Engn Mech Tuscaloosa AL 35487 USA Univ Cincinnati Dept Mech Ind & Nucl Engn Cincinnati OH 45221 USA

An active internal gearbox structure is developed and evaluated experimentally to suppress gear pair vibration due to transmission error excitation. The approach is based on an active shaft transverse vibration control concept that was theoretically analyzed in an earlier study and determined to be one of the most feasible methods. The system comprises of a piezoelectric stack actuator for applying control forces to the shaft via a rolling element-bearing, and a highly efficient, enhanced delayed-x lms control algorithm to generate the appropriate control signals. To avoid the aliasing effects of higher frequency signals and reduce the phase delay of conventional filters, a multi-rate minimum-phase low-pass digital filter is also integrated into the controller. The experimental results yield 8-13 dB attenuation in the gearbox housing vibration levels and correspondingly 5-8 dB reduction in measured gear whine noise levels at the first and second operating gear mesh frequencies. (c) 2004 Elsevier Ltd. All rights reserved.

关键词： NOISE-CONTROL SYSTEMS PAIR VIBRATION lms algorithm CANCELLATION STRUTS WAVES MODEL

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Blind identification of sparse Volterra systems

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2008年第7期22卷 652-662页

作者： Tan, Hong-Zhou Huang, Yihua Fu, Jian Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510275 Guangdong Peoples R China

This paper is concerned with blind identification for single-input single-output Volterra systems with finite order and memory with the second-order and the third-order statistics. For the full-sized Volterra system (i.e. all its kernels are nonzero) excited by unknown independently and identically distributed stationary random sequences, it is shown that blind identifiability does not hold in the second-order moment (SOM) and the third-order moment (TOM) domain. However, under some sufficient conditions, a class of truncated sparse Volterra systems, where some kernels are restricted to being zero. can be identified blindly and more Volterra parameters call be estimated in TOM than in S 0 M. Numerical examples illustrate the effectiveness of the proposed methods. Copyright (C) 2007 John Wiley & Soils, Ltd.

关键词： Volterra systems the second-/third-order moments blind identificatiom lms algorithm

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A new gradient-based adaptive algorithm estimating sinusoidal signals in arbitrary additive noise

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1999年第8期E82A卷 1526-1535页

作者： Xiao, YG Takeshita, Y Shida, K Hiroshima Womens Univ Fac Human Life & Environm Sci Hiroshima 7348558 Japan Saga Univ Fac Sci & Engn Saga 8408502 Japan

In this paper, a new gradient-based adaptive algorithm for the estimation of discrete Fourier coefficients (DFC) of a noisy sinusoidal signal is proposed based on a summed least mean squared error criterion. This algorithm requires exactly the same number of multiplications as the conventional lms algorithm, and presents much improved performance in both whits and colored noise environments at the expense of some additional memories and additions only. We first analyze the performance of the conventional lms algorithm in colored additive noise, and point out when its performance deteriorates. Then, a summed least mean squared error criterion is proposed, which leads to the above-mentioned new gradient-based adaptive algorithm. The performance of the proposed algorithm is also analyzed for a single frequency case. Simulation results are provided to support the analytical findings and the superiority of the new algorithm.

关键词： adaptive Fourier analysis lms algorithm noise misadjustment sinusoidal signals colored noise

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A Robust Least Mean Square algorithm for Adaptive Array Signal Processing

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WIRELESS PERSONAL COMMUNICATIONS 2013年第4期68卷 1449-1461页

作者： Ali, Rana Liaqat Khan, Shahid A. Ali, Anum Anis-ur-Rehman Malik, Shahzad A. COMSATS Inst Informat Technol Elect Engn Dept Islamabad Islamabad Pakistan COMSATS Inst Informat Technol CAST Islamabad Pakistan COMSATS Inst Informat Technol Dept Elect Engn Islamabad Pakistan

Least Mean Square (lms) has been the most popular scheme in the realization of adaptive beamforming algorithms. In this paper a Robust Least Mean Square (R-lms) algorithm is proposed which uses ratio parameters to control the contribution of product vectors in the weight upgrading process. The idea behind the proposed scheme is inclusion of previous information in place of relying solely on current sample. The performance enhancement by R-lms algorithm is achieved with insignificant increase in computational complexity of lms algorithm, so the crux of the conventional technique is not lost. Simulation results are also presented which illustrate that R-lms provides relatively fast convergence, less Brownian motion and improved stability.

关键词： Adaptive array signal processing R-lms algorithm Robust beamformer lms algorithm

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Adaptive array antenna using array antennas as element antennas

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IEICE TRANSACTIONS ON COMMUNICATIONS 2002年第10期E85B卷 1921-1926页

作者： Yamasuge, H Kohno, R Yokohama Natl Univ Fac Engn Yokohama Kanagawa 2408501 Japan

An adaptive array antenna should be applied for suppression of CCI in the spatial domain. However, the adaptive array antenna has some problems as follows. Because the adaptive array antenna takes a long time to converge to the optimum antenna weights, it's hard to track in case of quick varying channel. On the other hand, processing burden increases with the number of elements in the array antenna. To solve these problems, we propose an adaptive array antenna using array antenna as element antennas, the so-called "Layered array antenna." At the 1st layer, sector area are defined. We can change the sector areas according to the DOA distribution, because the sector areas are defined by the antenna weights. At the 2nd layer, MMSE is performed. Interference that couldn't be suppressed at the 1st layer is suppressed at the 2nd layer. By the proposed system, we confirmed higher convergence speed while relieving processing complexity.

关键词： adaptive array antenna smart antennas lms algorithm adaptive sectored antennas

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A Newton based adaptive algorithm for IIR ADF using allpass and FIR filter

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1999年第7期E82A卷 1305-1313页

作者： Okello, J Itoh, Y Fukui, Y Kobayashi, M Tottori Univ Fac Engn Tottori 6808552 Japan Ibaraki Univ Fac Engn Hitachi Ibaraki 3160033 Japan

Newton based adaptive algorithms are among the algorithms which are known to exhibit a higher convergence speed in comparison to the least mean square (lms) algorithms. In this paper we propose a simplified Newton based adaptive algorithm for an adaptive infinite impulse response (IIR) filter implemented using cascades of second order allpass filters and a finite impulse response (FIR) filter. The proposed Newton based algorithm avoids the complexity that may arise in the direct differentiation of the mean square error. The analysis and simulation results presented for the algorithm, show that the property of convergence of the poles of the IIR ADF to those of the unknown system will be maintained for both white and colored input signal. Computer simulation results confirm an increase in convergence speed in comparison to the lms algorithm.

关键词： adaptive IIR filter system identification Newton algorithm lms algorithm

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Subband Kalman filtering for speech enhancement

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING 1998年第8期45卷 1072-1083页

作者： Wu, WR Chen, PC Natl Chiao Tung Univ Dept Commun Engn Hsinchu 30050 Taiwan

Kalman filtering is an effective speech-enhancement technique, in which speech signals are usually modeled as autoregressive (AR) processes and represented in the state-space domain. Since AR coefficients identification and Kalman filtering require extensive computations, real-time implementation of this approach is difficult. This paper proposes a simple and practical scheme that overcomes these obstacles. Speech signals are first decomposed into subbands. Subband speech signals are then modeled as low-order AR processes, such that low-order Kalman filters can he applied. Enhanced fullband speech signals are finally obtained by combining the enhanced subband speech signals. To identify AR coefficients, prediction-error filters adapted by the lms algorithm are applied. Due to noisy inputs, the lms algorithm converges to biased solutions. The performance of the Kalman filter with biased parameters is analyzed, It is shown that accurate estimates of AR coefficients are not required when the driving-noise variance is properly estimated. New methods for making such estimates are proposed. Thus, we can tolerate biased AR coefficients and take advantage of the lms algorithm's simple structure. Simulation results show that speech enhancement in the subband domain not only greatly reduces the computational complexity, but also achieves better performance compared to that in the fullband domain.

关键词： AR modeling Kalman filtering lms algorithm speech enhancement subband filtering

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