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.     

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.     

Analysis of the performance and sensitivity of an eigenspace-basedinterference canceler

Eigenspace-based interference cancelers (EICs) possess the advantages of providing maximal suppression of interference with fast convergence over conventional adaptive beamformers. However, the performance and sensitivity to steering angle error of EICs have not been analyzed due to the use of a signal blocking matrix. We first present a technique to construct a positive definite matrix based on the signal blocking matrix and then use this matrix to compensate the effect of the signal blocking matrix on the sensor noise received by an EIC. Therefore, the interference subspace required for finding the optimal weight vector can be obtained using conventional eigenvalue decomposition (EVD). Moreover, the performance and sensitivity to the steering angle error of the EIC can be analyzed. Simulation examples are provided for confirming the theoretical results     

A Robust Space-Time Generalized Sidelobe Canceller

This paper deals with adaptive array beamforming based on a two-dimensional generalized sidelobe canceller (GSC) with robust capability. It has been known that the performance of conventional GSC is quite sensitive even to pointing error. In conjunction with the joint desired user’s code-aid and signal subspace estimating approach, the proper quiescent weight vector and blocking matrix of GSC can be obtained to suppress the leakage of desired signal. However, space signature is estimated by exploiting the knowledge of the spreading code of the user of interest and the orthogonality between noise and signal subspaces. In this paper, the space-time signature estimation can be integrated jointly. Therefore, the desired signal cancellation does not occur; even the pointing error is relatively large. Computer simulation results show the effectiveness of the proposed approach.     

A robust adaptive beamformer for microphone arrays with a blockingmatrix using constrained adaptive filters

This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a new adaptive blocking matrix using coefficient-constrained adaptive filters (CCAFs) and a multiple-input canceller with norm-constrained adaptive filters (NCAFs). The CCAFs minimize leakage of the target-signal into the interference path of the GSC. Each coefficient of the CCAFs is constrained to avoid mistracking. The input signal to all the CCAFs is the output of a fixed beamformer. In the multiple-input canceller, the NCAFs prevent undesirable target-signal cancellation when the target-signal minimization at the blocking matrix is incomplete. The proposed beamformer is shown to be robust to target-direction errors as large as 200 with almost no degradation in interference-reduction performance, and it can be implemented with several microphones. The maximum allowable target-direction error can be specified by the user. Simulated anechoic experiments demonstrate that the proposed beamformer cancels interference by over 30 dB. Simulation with real acoustic data captured in a room with 0.3-s reverberation time shows that the noise is suppressed by 19 dB. In subjective evaluation, the proposed beamformer obtains 3.8 on a five-point mean opinion score scale, which is 1.0 point higher than the conventional robust beamformer     

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。     

Design of two-dimensional rectangular array beamformers withpartial adaptivity

This paper considers the problem of designing a two-dimensional (2-D) rectangular array beamformer with partial adaptivity. Using the eigenstructure of the signal data received by a 2-D rectangular array beamformer, we first show that the optimal weight matrix when using full adaptivity can be obtained from a set of singular vectors. Then the design problem of using partial adaptivity is formulated. As a result, the optimal solution for the partially adaptive weight matrix can be found by solving two basic problems, namely determining the proper dimension of the partially adaptive weight matrix and the set of the singular vectors. We develop the detection formulas for the information theoretic criteria AIC and MDL to find the proper dimension. Next, an efficient method is presented so that the optimal solution for the set of the singular vectors can be found analytically. We also investigate the required computational complexity. It is shown that 2-D partially adaptive beamforming using the proposed technique requires less computational complexity than 2-D fully adaptive beamforming using conventional techniques. Moreover, computer simulations demonstrate that the proposed 2-D partially adaptive technique provides satisfactory array performance when compared with conventional fully adaptive techniques     

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.     

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     

Design of partially adaptive array beamformers based on informationtheoretic criteria

In this paper, two basic problems in designing partially adaptive array beamformers based on the structure of generalized sidelobe canceller (GSC) are considered. The first problem is to decide the proper dimension of the required adaptive weight vector. Using the information of the array output power, we develop the detection formulas for the information theoretic criteria AIC and MDL to decide the proper dimension of the adaptive weight vector. If the input noise power is unknown a priori, efficient methods are proposed for estimating the input noise power in both cases, with and without the desired signal, to make the detection formulas still feasible. The second problem is to find the most appropriate channel signals for weight adaptation for efficiently canceling interference. An efficient method based on the maximum power reduction criterion is presented for selecting the most desired channel signals from the output of the signal blocking matrix. Theoretical analysis concerning the performance of the proposed methods is made. Computer simulations showing the effectiveness of the proposed methods are also provided     

Design and analysis of a 2-D eigenspace-based interferencecanceller

This paper deals with the problem of eigenspace-based interference cancellation using a two-dimensional (2-D) rectangular array. An efficient 2-D signal blocking technique is presented to remove the desired signal from the received array data. In conjunction with the 2-D signal blocking technique, a positive definite matrix is further constructed and used to compensate the effect of the signal blocking operation on the sensor noise received by a 2-D eigenspace-based interference canceller (EIC). Therefore, the interference subspace required for computing the optimal weight vector of the designed 2-D EIC can be obtained by simply using conventional eigenvalue decomposition methods instead of any complicated generalized eigenvalue decomposition methods. The performances of the designed 2-D EIC under finite samples and steering angle error are also evaluated. The developed theoretical results are confirmed by several simulation examples     

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.     

基于多级阻塞的稳健相干自适应波束形成

针对期望信号波达角(DOA)估计误差较大时相干波束形成性能下降的问题,该文提出一种基于多级阻塞的稳健相干自适应波束形成算法。该算法首先定义阻塞矩阵,推导多级阻塞原理,并利用其滤除阵列接收信号中的期望信号;然后给出空间中只存在期望信号时,子阵与全阵间阵列流型的映射关系,据此推导全阵扩展变换,并证明其在干扰信号存在条件下的有效性;最终利用扩展变换获取全阵最优权矢量,实现相干波束形成。该算法对期望信号波达角估计误差稳健,且无需干扰信号来向的先验信息,同时可以有效避免阵列孔径的损失。仿真分析验证了算法的优越性和理论分析的有效性。     

Efficient eigenspace-based array signal processing using multipleshift-invariant subarrays

This paper deals with the construction of eigensubspaces for adaptive array signal processing. An efficient technique for extracting the eigensubspaces spanned by the data vector received by an N-element adaptive array is presented. We first decompose the original array into several subarrays with multiple shift invariances and find the eigensubspaces corresponding to each of the subarrays. By solving a least-squares (LS) or total least-squares (TLS) problem, the signal and noise subspaces corresponding to the original array can be found from the eigensubspaces spanned by the subarray data vectors. Hence, there is no need to perform the eigenvalue decomposition of the N×N correlation matrix of the received data vector. The proposed technique significantly reduces the required computational complexity as compared to the conventional eigenspace-based (ESB) methods. In conjunction with the spatial smoothing scheme or a proposed cross-correlation method, this technique can also deal with the case of coherent signals. The effectiveness of the proposed technique is demonstrated by several computer simulations     

2-D direction finding of coherent signals VIA Temporo-Spatial processing

In most wireless communication systems, two-dimensional Directions-Of-Arrival (DOA) of multipath signals need to be found for spatial selective transmission. However, it is quite difficult to find their DOAs due to the coherent nature of multipath signals and considerable computations when performing 2-D searches. In this paper, a new algorithm to estimate 2-D DOA of multiple narrow-band signals is proposed. A DOA cyclic matrix is constructed whose eigenvalues and eigenvectors can be simultaneously used to extract 2-D DOA without 2-D searches. By exploiting the temporal property of cyclostationarity, the signal detection capability is significantly improved. Besides, based on the decorrelation model for mobile terminal signals, the algorithm can be effectively extended to the coherent case without spatial smoothing and the loss of array aperture. Simulation results are given to illustrate the performance of the new algorithm.     

On the performance of the generalized sidelobe canceller incoherent situations

The convergence rate for the adaptive weights to reach the optimum value in an adaptive array system depends on the eigenvalue spread ratio of the autocovariance matrix. How the eigenvalue spread ratio in a generalized sidelobe canceller (GSC) is affected by the various parameters is studied. Expressions for the output power of the GSC in coherent situations are derived, and numerical results are included     

Sparse LCMV beamformer design for suppression of ground clutter inairborne radar

Cancellation of the ground clutter received at an airborne phased array radar is an inherently two dimensional problem. Clutter returns are Doppler shifted due to platform motion forcing the use of processors that can resolve targets in both velocity (Doppler) and azimuth. Fully adaptive processors that operate in both dimensions require prohibitively large computation so that reduced adaptive dimension, or partially adaptive processors must be considered. In conventional partially adaptive linearly constrained minimum variance (LCMV) beamformer design the approach taken has been to represent the interference subspace with some reduced set of vectors, typically the eigenvectors associated with the largest eigenvalues of the interference covariance matrix. This technique does yield good performance but will not give the optimum performance for a given partially adaptive dimension. In this paper, an off-line method for selecting the “best” degrees of freedom to be retained in a partially adaptive design is presented. The sequential algorithm described selects those degrees of freedom that best minimize the beamformer output mean square error. This approach leads to a sparse structure for the transformation matrix, which when implemented in a generalized sidelobe canceller (GSC) structure results in a reduction in the computational load. This approach also allows a reduction in the required adaptive dimension as compared to the eigenvector based approach. Illustrative examples demonstrate the effectiveness of this method     

二维几种常见阵型阵列的阻塞矩阵构建

针对二维不同阵型,研究其二维阻塞矩阵的建立方法。阻塞矩阵因其常用于抑制干扰以及在GSC阵列中阻塞期望信号,因而在阵列信号处理中得到广泛应用。常用的是二项式对消方法,该方法简单有效且具有运算量小的特点。目前,通过二项式对消来构造阻塞矩阵的方法主要集中在一维线阵,涉及二维以及其它阵型的较少。为此,文中将基于二维具有代表性的阵型做了研究,并推导出具有凡导向矢量首项为1的阵型阻塞矩阵构造方法--一字阶梯累积法。仿真验证了该方法的简单有效。     

相干信号联合波达角-频率估计的 一种新型预处理方法

本文有效地将一维中的前向/后向空间平滑技术扩展到二维中的时-空阵列数据矩阵,提出了一种用于相干信号联合波达角-频率估计的新型预处理方法.本文详细地分析了如何构造前向/后向平滑时-空阵列数据矩阵,导出了确保信号波达角-频率参数可分辨应满足的条件.与仅利用前向空间平滑的现有预处理方法不同,本文的预处理方法同时利用前向和后向空间平滑,因而提高了阵元的利用率,使联合波达角-频率估计的性能明显提高.     

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.