A novel wavelet-based generalized sidelobe canceller

This paper presents a novel narrow-band adaptive beamformer with the generalized sidelobe canceller (GSC) as the underlying structure. The new beamformer employs a wavelet-based approach for the design of the blocking matrix of the GSC, which is now constituted by a set of regular M-band wavelet filters. Such a construction of the blocking matrix can not only block the desired signals from the lower path as required provided the wavelet filters have sufficiently high regularity, but it also encompasses the widely used one with ones and minus ones along the diagonals as a special case. In addition, it possesses two advantageous features. First, the eigenvalue spreads of the covariance matrices of the blocking matrix outputs, as demonstrated in various scenarios, are decreased as compared with those of previous approaches. Since the popular least mean squares (LMS) algorithm has been notorious for its slow convergence rate, the reduction of the eigenvalue spreads can, in general, accelerate the convergence speed of the succeeding LMS algorithm. Second, the new beamformer belongs to a specific type of partially adaptive beamformers, wherein only a portion of the available degree of freedom is utilized in the adaptive processing. As such, the overall computational complexity is substantially reduced when compared to previous works. The issues of choosing the parameters involved for superior performance are also addressed. Simulation results are furnished as well to justify this new approach     

Performance analysis of derivative constraint adaptive arrays withpointing errors

The performance of adaptive arrays with arbitrary order derivative constraints to avoid the signal nulling caused by the error in the steering angle is investigated. The generalized sidelobe canceller (GSC) is used to evaluate the bearing responses of adaptive arrays with pointing errors. Under the assumption of equispaced linear arrays, the Legendre polynomial is used to derive a closed-form formula for the sidelobe leakage factor, the ratio in which the signal leaks into the GSC sidelobe cancelling branch. Moreover, the effective beamwidth, the maximum range of pointing inaccuracy allowable to keep the signal loss in array output less than a given value, is derived for the GSC with a delay-and-sum quiescent beamformer. Such adaptive arrays can achieve the maximum output signal-to-noise ratio when the presteering is perfect, and the performance is independent of the location of the phase origin. Numerical results are presented to confirm the analysis     

Adaptive selection combining for soft handover in OVSF W-CDMA systems

In W-CDMA, soft handover is supported at cell boundaries to maintain communication quality. The maximal ratio combining (MRC) and generalized selection combining (GSC) , are two possible approaches. However, soft handover is resource-intensive. In this letter, we propose an adaptive selection combining (ASC) scheme that can switch flexibly between MRC and GSC so as to take care of both channel loading and communication quality. The signal-to-interference-and-noise ratio (SINR) is kept as high as that of MRC while the blocking probability can remain at about the same level as that of GSC.     

一种基于广义旁瓣相消的改进降秩算法

在处理大型阵列时,阵元数较多,通常对阵列采用降秩处理可以较好地解决运算量过大的问题。基于广义旁瓣相消器(GSC)框架的降秩变换自适应滤波是各种降秩自适应滤波算法的统一模型。分析了基于GSC框架的几种降秩自适应滤波算法,针对当降秩阶数大于干扰数时方向图旁瓣过高、波形混乱和系统性能下降问题,提出了一种基于GSC框架的改进降秩算法,该算法利用特征子空间对GSC阻塞矩阵加以改进,使用改进后的阻塞矩阵进行降秩自适应处理,仿真结果证明了改进算法可以降低旁瓣电平,并形成较好的波束形状,提高了GSC性能的稳健性。     

An iterative maximum SINR receiver for multicarrier CDMA systems over a multipath fading channel with frequency offset

A robust iterative multicarrier code-division multiple-access (MC-CDMA) receiver with adaptive multiple-access interference (MAI) suppression is proposed for a pilot symbols assisted system over a multipath fading channel with frequency offset. The design of the receiver involves a two-stage procedure. First, an adaptive filter based on the generalized sidelobe canceller (GSC) technique is constructed at each finger to perform despreading and suppression of MAI. Second, pilot symbols assisted frequency offset estimation, channel estimation and a RAKE combining give the estimate of signal symbols. In order to enhance the convergence behavior of the GSC adaptive filters, a decisions-aided scheme is proposed, in which the signal waveform is first reconstructed and then subtracted from the input data of the adaptive filters. With signal subtraction, the proposed MC-CDMA receiver can achieve nearly the performance of the ideal maximum signal-to-interference-plus noise ratio receiver assuming perfect channel and frequency offset information. Finally, a low-complexity partially adaptive (PA) realization of the GSC adaptive filters is presented as an alternative to the conventional multiuser detectors. The new PA receiver is shown to be robust to multiuser channel estimation errors and offer nearly the same performance of the fully adaptive receiver.     

相控阵雷达数字自适应波束形成技术

本文分析了自适应波束旁瓣起伏机理，从系统要求出发，研究了信号子空间广义旁瓣相消系统（ＧＳＣ）的性能，提出了简化系统结构的级联方法，并分析了Ｂｕｔｌｅｒ网络ＧＳＣ的性能。     

Generalized selection combining based on the log-likelihood ratio

We propose a generalized selection combining (GSC) scheme for binary signaling in which a subset of diversity branches providing the largest magnitude of log-likelihood ratio (LLR) are selected and combined. It is shown that the bit-error probability with maximum ratio combining (MRC) or square-law combining of L branches is identical to that with LLR-based GSC of L/2 branches. We also propose a simple, but suboptimal, GSC based on a noncoherent envelope detection and discuss its potential advantages over the conventional signal-to-noise-ratio-based GSC and MRC.     

Adaptive Volterra filtering using M-band wavelet transform andGram-Schmidt orthogonalisation

A new adaptive Volterra filter with fast convergence is proposed, where the M-band discrete wavelet transform and Gram-Schmidt orthogonalisation are utilised. In particular, the cascade combination of two such procedures reduces the eigenvalue spread of the Volterra input auto-correlation matrix, thus improving the convergence speed of the adaptive nonlinear filtering     

Performance analysis of a wavelet-based generalized sidelobe canceller

In this paper, we carry out a detailed performance analysis of the recently addressed wavelet-based generalized sidelobe canceller (GSC), which employs a set of P-regular M-band wavelet filters in the design of the blocking matrix involved. We begin our analysis by developing a closed-form expression of the output signal-to-interference-plus-noise ratio (SINR) of partially adaptive beamformers with the GSC as the underlying structure under a one jammer or multiple jammer environment. This new expression is shown to encompass several previous works as special cases. We then examine the relationship between the choices of the parameters P and M in the wavelet-based GSC and the corresponding output SINR based on this expression. Some guidelines for the choices of these parameters can thus be induced to achieve superior performance. Simulation results are also furnished to justify these suggestions.     

直接扩频序列系统中IIR格型自适应滤波抗多窄带干扰

介绍了一种直接扩频系统中抗多个窄带干扰的多支路自适应IIR陷波滤波算法。通过频率分离 ,在各个支路通过谱线增强器估计干扰的瞬时频率和功率 ,减少了输入信号特征值扩散程度 ,加快了自适应算法收敛速度。采用一种IIR自适应格型陷波滤波技术 ,调整陷波器的深度 ,提高了输出信号信噪比。     

A Novel Method for Partially Adaptive Broadband Beamforming

In this paper, a novel subband-selective generalized sidelobe canceller (GSC) for partially adaptive broadband beamforming is proposed. The blocking matrix of the GSC is constructed such that its columns constitute a series of bandpass filters, which select signals with specific angles of arrival and frequencies. This results in bandlimited spectra of the blocking matrix outputs, which is further exploited by a subband decomposition prior to running independent unconstrained adaptive filters in each non-redundant subband. We discuss the design of both the blocking matrix using a genetic algorithm for an efficient sum-of-power-of-two coefficient format and the filter bank for the subsequent subband decomposition. By these steps, the computational complexity of our subband-selective GSC is greatly reduced compared to other adaptive GSC schemes, while performance is comparable or even enhanced due to subband decorrelation, as simulations indicate.     

A subband-selective broadband GSC with cosine-modulated blocking matrix

A novel subband-selective generalized sidelobe canceller (GSC) for partially adaptive broadband beamforming is proposed. The columns of the blocking matrix are derived from a prototype vector by cosine modulation, and the broadside constraint is incorporated by imposing zeros on the prototype vector appropriately. These columns constitute a series of bandpass filters, which select signals with specific directions of arrival and frequencies. This results in a high-pass-type bandlimited spectra of the blocking matrix outputs, which is further exploited by subband decomposition and suitably discarding the low-pass subbands prior to running independent unconstrained adaptive filters in each nonredundant subband. By these steps, the computational complexity of a GSC implementation is greatly reduced compared to fully adaptive GSC schemes, while performance is comparable or even enhanced due to subband decorrelation in both spatial and temporal domains.     

基于广义旁瓣相消的机载雷达抗密集转发式干扰方法

密集转发式干扰不仅会引起雷达虚警,而且会抬高其附近单元的恒虚警率检测门限进而导致目标检测性能下降。另外,它还会污染空时自适应处理的训练样本,导致杂波抑制性能下降。针对这些问题,该文提出一种机载雷达抗密集转发式干扰算法。该算法首先估计干扰方向,然后用广义旁瓣相消技术在空域滤除干扰。广义旁瓣相消中的辅助通道为指向干扰方向的和波束,而其协方差矩阵则利用清晰区中挑选的干扰样本估计得到。该算法可以有效抑制密集转发式干扰,减少由其引起的虚警,改善雷达目标检测性能,同时该算法还具有结构简单,易于实现的优点。实验结果验证了该算法的有效性。     

Blind adaptive beamforming based on generalized sidelobe canceller

The generalized sidelobe canceller (GSC) is an efficient implementation of the direction constrained adaptive array. Conventional GSC is designed according to a quiescent weight vector and a blocking matrix. The quiescent weight vector provides the array with specified array response at some direction. The blocking matrix is designed based on a priori knowledge of the direction of arrival (DOA) of the desired signal. In this paper, we propose a new GSC-based adaptive array without a priori knowledge of the DOA of the desired signal. This paper utilizes eigensubspace decomposition and statistically cyclostationary properties of the signals to design the adaptive array. A method for constructing the most efficient blocking matrix for the GSC is developed. Simulation examples illustrate the effectiveness of the proposed method.     

Frequency domain least-mean-square algorithm

Frequency domain adaptive filtering can be performed by Fourier transforming the input-signal vector and weighting the contents of each frequency bin. By reducing the eigenvalue spread of the data autocorrelation matrix, frequency domain filtering promises great improvements in covergence rate over the conventional time-domain adaptive filtering.     

Two-Dimensional Adaptive Array Beamforming With Multiple Beam Constraints Using a Generalized Sidelobe Canceller

This paper deals with the problem of two-dimensional (2-D) adaptive array beamforming with multiple beam constraints (MBC) using a generalized sidelobe canceller (GSC). We present a method for the construction of signal blocking matrix required by the 2-D GSC. The resulting 2-D adaptive beamformer can provide almost the same performance as conventional 2-D adaptive beamformers based on a linearly constrained minimum variance (LCMV) criterion. The effectiveness of the proposed GSC is that the construction of the required signal blocking matrix requires only the computation of a few entries from analytical formulas. In comparison with conventional methods, the proposed technique gets rid of the computational complexity due to the eigendecomposition required for finding the 2-D signal blocking matrix. For dealing with the performance degradation due to coherent interference, we present a 2-D weighted spatial smoothing scheme to effectively alleviate the coherent jamming effect. Several simulation examples are provided for illustration and comparison.     

Performance Evaluation of Generalized Selection Combiners Over Slow Fading with Estimation Errors

In this paper we derive closed-form expressions for the single-user adaptive capacity of generalized selection combining (GSC) system, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. The complex channel estimate and the actual channel are modelled as jointly Gaussian random variables with a correlation that depends on the estimation quality. Three adaptive transmission schemes are analyzed: (1) optimal power and rate adaptation; and (2) constant power with optimal rate adaptation, and (3) channel inversion with fixed rate. In addition to deriving an exact expression for the capacity of the aforementioned adaptive schemes, we analyze the impact of channel estimation error on the capacity statistics and the symbol error rate for GSC systems. The capacity statistics derived in this paper are the moment generating function, complementary cumulative distribution function and probability density function for arbitrary number of receive antennas. Moreover, exact closed-form expressions for M-PAM/PSK/QAM employing GSC are derived. As expected, the channel estimation error has a significant impact on the system performance.     

On eigenvalues, SINR, and element patterns in adaptive arrays

A simple relationship between the output signal-to-interference-plus-noise ratio (SINR) of an adaptive array and the eigenvalues of the associate signal covariance matrix is pointed out. For two simple cases involving continuous wave (CW) signals, it is shown that the eigenvalue associated with the desired signal is equal to the SINR plus one. This relationship is useful for understanding the effects of element patterns and spacings on eigenvalue behavior in adaptive arrays.     

The performance of the least mean squares algorithm combined withspatial smoothing

Many practical signal environments involve correlation between desired and undesired signals, causing narrowband adaptive array beamformers to exhibit signal cancellation. Spatial smoothing is a technique that can perform beamforming in such environments. This method can be incorporated into an adaptive algorithm, such as least mean squares (LMS), possibly altering the well-known performance characteristics of the algorithm. We discuss methods for combining spatial smoothing with the LMS algorithm in an array with a generalized side-lobe canceler (GSC) structure. The first of these methods is an electronic version of mechanically dithering the array. We show that this well-known method obeys a set of nonhomogeneous dynamical equations, resulting in a limit cycle that increases the misadjustment of the algorithm. The previously reported parallel spatial processing algorithm is also shown to have this increased misadjustment. We then introduce two methods that do not suffer from this misadjustment increase. We compare the methods' computational complexity and performance, in terms of stability and steady-state behavior, including weight misadjustment, GSC output power, and signal-to-noise ratio (SNR). In conclusion, we find that the limit cycle of the first method can be avoided without any increase in complexity by using one of the new methods