On adaptive beamforming in correlated noise

This paper deals with the problem of adaptive beamforming in the presence of fully coherent (correlated) noise sources. Two different techniques are developed for minimizing the effects of coherent interference. The first method employs spatial interpolation of the array aperture, followed by spatial smoothing in order to decorrelate the desired signal and the interference. The second technique is based on a simple algebraic transformation for restoring the rank of the array signal correlation matrix, which is normally rank deficient in such situations. This technique is shown to work for nonuniform adaptive arrays as well. Extensive computer simulation results are presented to illustrate the effectiveness of the proposed techniques.This week was supported by the N.R.C., Resident Research Associateship Programme.     

Tamed adaptive antenna array

The adaptive array under directionaily constrained minimization of power (DCMP) algorithm is improved by adding a "pseudonoise." It is effective to protect the desired signal from cancellation or distortion in such cases as 1) where a coherent interference is incident, or 2) where the desired signal direction for the constraint contains some pointing error, or 3) when the desired signal is broad band, The optimum amount of pseudonoise to be added is also discussed and its formula is given. This system is named "tamed adaptive antenna" since its killing capability is somewhat moderated so as not to hurt the desired signal.     

A solution to the adaptive nulling problem with a look-direction constraint in the presence of coherent jammers

A new adaptive technique is presented that is capable of nulling coherent, as well as incoherent, jammers while maintaining a fixed gain in the look direction. The technique depends on the use of new kind of correlation matrix and a subtractive preprocessor. It does not require any spatial smoothing. It requires2Melements to nullM-1coherent jammers in the presence of noise. The matrix used in the technique is such that its unbiased estimate in the presence of noise can be obtained. This helps making the algorithm robust to noise in finding the desired weight vector to be used by the array.     

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。     

On the coherent interference suppression using a spatiallysmoothing adaptive array

The behavior of a spatially smoothing adaptive array is examined. An expression for the weight vector is first derived. Using the array gain on the desired signal and the coherent interference is obtained. Then the expression for output signal-to-noise (SNR) is derived. It shows that the performance of the spatially smoothing array depends on the number of the subarrays, the angle separation, relative power and initial phase difference between the desired signal and the coherent interference. For good interference suppression it is found that the magnitude of the phase difference of the incident and interference signals must be greater than the beamwidths of both the subarray and the equivalent array. There is also a tradeoff between increasing the groups of subarrays and decreasing the number of elements in the subarrays. Computer simulation results are given that validate the analysis     

Eigenstructure based partially adaptive array design

A procedure is presented for designing partially adaptive arrays having nearly fully adaptive performance under steady-state conditions. Theory predicts that the required adaptive dimension is less than or equal to the rank of the spatially/temporally correlated portion of the interference correlation matrix for arbitrary linearly constrained minimum-variance beamformers. Knowledge of the eigenstructure of the interference correlation matrix is required to implement a beamformer with this adaptive dimension. To avoid adaptive estimation of the eigenstructure, the eigenstructure of an averaged correlation matrix (which spans the interference scenarios of interest) is utilized, and the adaptive dimension is given by the rank of the averaged correlation matrix. Construction of a transformation for reducing adaptive dimension is addressed. Simulations illustrating the utility of the eigenstructure approach are provided     

Robust adaptive beamforming for general-rank signal models

The performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the actual and presumed array responses to the desired signal. Such mismatches may frequently occur in practical situations because of violation of underlying assumptions on the environment, sources, or sensor array. This is especially true when the desired signal components are present in the beamformer "training" data snapshots because in this case, the adaptive array performance is very sensitive to array and model imperfections. The similar phenomenon of performance degradation can occur even when the array response to the desired signal is known exactly, but the training sample size is small. We propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary-type mismatches of the desired signal array response. Our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both the rank-one (point source) and higher rank (scattered source/fluctuating wavefront) desired signal models. The proposed robust adaptive beamformers are based on explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst-case performance optimization. Simple closed-form solutions to the considered robust adaptive beamforming problems are derived. Our new beamformers have a computational complexity comparable with that of the traditional adaptive beamforming algorithms, while, at the same time, offer a significantly improved robustness and faster convergence rates.     

An improved blind adaptive MMSE receiver for fast fading DS-CDMAchannels

Blind adaptive minimum mean-squared errors (MMSE) receivers for multiuser direct-sequence code-division multiple access (DS-CDMA) systems that assume knowledge of the steering vector, i.e., the cross-correlation between the desired output and the input signal, are known for their robustness against channel fading as they do not attempt to explicitly track the channel of the user of interest. However, these receivers often have higher excess mean squared error and, hence, poorer performance than training-sequence based adaptive MMSE receivers. In this paper, an improved correlation matrix estimation scheme for blind adaptive MMSE receivers is provided. The new scheme takes advantage of the fact that the desired linear receiver can be expressed as a function of the interference correlation matrix only, rather than the total data correlation matrix. A theoretical analysis is performed for the flat fading case which predicts that the new estimation scheme will result in significant performance improvement. Blind adaptive MMSE receivers with the new estimation scheme appear to achieve performance comparable to the training-sequence based adaptive MMSE receivers. Detailed computer simulations for the fast multipath fading environment verify that the proposed scheme yields strong performance gains over previous methods     

On the performance of a polarization sensitive adaptive array

The ability of a least mean square (LMS) adaptive array to adapt to the electromagnetic polarization of incoming signals is considered. An array of two pairs of crossed dipoles is studied. A desired signal and an interference signal are assumed to arrive from arbitrary directions with arbitrary elliptical polarizations. The output signal-to-interference-plus-noise ratio (SINR) from the array is computed as a function of the signal angles of arrival and polarizations. It is shown that as long as certain special desired signal polarizations are avoided, the array is difficult to jam with a single interference signal. To produce a poor SINR, an interference signal must both arrive from the same direction and have the same polarization as the desired signal.     

Blind adaptive multiuser detection for DS/SSMA communications withgeneralized random spreading

A new spreading scheme and an accompanying blind adaptive receiver structure are proposed for direct-sequence spread-spectrum multiple-access communications in a slowly-varying, frequency-selective fading channel. Each user's spreading sequence is given by the Kronecker product of a long-period pseudonoise (PN) sequence, which is accurately modeled by a random sequence, and a short-length deterministic signature code. This spreading scheme bridges the gap between pure PN spreading and pure short-code spreading schemes. It is shown that with this spreading scheme, the channel response to the desired signal component is easily estimated without relying on the spectral decomposition of the signal correlation matrix. With the estimate of the channel response, the receiver suppresses interference based on the maximum signal-to-interference ratio criterion. The blind adaptive receiver requires only coarse timing information and a priori knowledge of the desired user's PN sequence for adaptation. Numerical results show that the adaptive receiver significantly suppresses interference by successfully estimating the channel response and the interference statistics with a low computational complexity. An extension to spatio-temporal processing using an array antenna is also discussed     

Co-channel interference canceller using CMA adaptive array antenna

A co-channel interference canceller that uses a constant modulus algorithm (CMA) adaptive array antenna is presented. In this canceller, when a CMA adaptive array antenna captures a co-channel interference signal, a replica of this signal is generated and then eliminated from a received signal, thus a desired signal can be obtained. Computer simulation results show that the proposed canceller can effectively reduce co-channel interference     

Adaptive beam forming using split-polarity transformation forcoherent signal and interference

Split-polarity transformation (SPT), which is incorporated into conventional linearly constrained minimum variance (LCMV) beamformers to decorrelate the desired signal from interference, is presented. The SPT processor does not distort the direction vectors associated with wave fronts impinging on the array, but it does reverse the phase of the signal coming from a specified direction. With the aid of SPT processing, the signal cancellation due to correlation between the desired signal and interference is almost eliminated. The design of a robust SPT processor for combating the effects of mismatch between idealized array model and actual scenario arising from causes such as sensor location, amplitude, and phase errors is discussed. A detailed performance study of the SPT-LCMV beamformer shows it to be robust against direction uncertainty in the assumed look direction. Numerical results are presented to demonstrate the effectiveness of the SPT-LCMV beamforming scheme is a coherent interference environment     

The tripole antenna: An adaptive array with full polarization flexibility

The performance of an adaptive array using three mutually perpendicular dipoles (a "tripole") is studied. A desired signal and an interference signal, each with arbitrary angle of arrival and polarization, are assumed incident on the array. Uncorrelated thermal noise is also assumed present on each element signal. The output desired signal-to-interference-plus-noise ratio (SINR) is computed as a function of the signal arrival angles and polarizations. It is shown that for most angles of arrival and polarizations, the array has an excellent ability to protect a desired signal from interference. Certain special cases where the performance is not good are discussed in detail.     

Initial weight computation method with rapid convergence for adaptive array antennas

This paper presents a rapid initial weight computation method for adaptive array antennas. The proposed method estimates a correlation matrix and a correlation vector, where the correlation matrix is estimated using not only received samples with the desired signal, but also those before starting the transmission of the desired signal. The proposed method reduces the number of known symbols required for weight convergence. Furthermore, the combined use of the proposed method and the decision-feedback minimum mean square error combining method significantly improves weight convergence. Numerical results show that the combined method converges an array with sixteen antennas by using less than ten known symbols.     

Power optimization in adaptive arrays: A technique for interference protection

A weight control algorithm that may be used in a two-element adaptive array to protect a desired signal from an interference signal is described. The algorithm is a constrained gradient technique that either maximizes or minimizes array output power. It is shown that by choosing appropriately between minimization and maximization, a useful desired signal-to-interference-plus-noise ratio can be maintained at the array output over a wide range of signal powers.     

A π/4 crossed cascaded adaptive array for mobile satellite communications

Adaptive arrays in mobile communications based on any arbitrary performance criteria have many problems in tracking the desired signal at different interference angles relative to the desired one. To use the adaptive arrays efficiently in mobile communications, we need a system which is independent of interference angles. In this paper a system nominated as π/4 crossed cascaded adaptive array (π/4 CC) based on (for example) the well-known constant modulus algorithm (CMA) is suggested. It is a four elements adaptive array, each two elements are controlled by the CMA and they are crossed by 45° angle in the vertical plane. The proposed system is examined by computer simulation and compared with the conventional system. It is found that the conventional two elements array is suffering from the capture problem and its performance is degraded at certain interference angles e.g. 25, 50, 55°,…. When the interference power is equal to the desired signal, the proposed system outperforms the conventional one. Therefore, the suggested system is more suitable in mobile communications which employs CM modulation techniques such as FM, QPSK, GMSK,…. In this article the analysis of the CMA and the proposed system are considered in detail. The system under consideration can be used also for all other adaptive arrays employing LMS, PI, and Applebaum, etc. Copyright © 1999 John Wiley & Sons, Ltd.     

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.     

An orthogonalized blind algorithm for hybrid of adaptive array and equalizer

The problems generated by the interference will be more complicated in the future. A combination of adaptive array and equalizer has been employed to solve the problems of interference when an adaptive array alone cannot suppress all the interferences. A constant modules algorithm (CMA) of the combination system was proposed to solve the problems of insufficient degrees of freedom and main‐beam multipath interference when no training signal is transmitted. The limitation of the CMA for combination systems is due to its slow rate of convergence. In this paper, an orthogonalized blind algorithm for hybrid of array and equalizer (OBHAE) is proposed to combat the problems of the interference. Because the modified input vector of the adaptive array is orthogonalized by the OBHAE in advance, the convergent rate of the CMA system can be improved by the OBHAE. When the coherent interference presents, the performance of the system will be degraded. In this paper, an orthogonalized spatial smoothing blind (OSSB) algorithm is proposed to further enhance the cancellation of the coherent interference. In the OSSB, we combine the OBHAE with the spatial smoothing method to combat the coherent interference problem. Simulation results are presented to demonstrate the merits of the OBHAE and the OSSB. Copyright © 2012 John Wiley & Sons, Ltd.     

基于IAA的协方差矩阵重构稳健波束形成方法

针对小样本背景下,存在相干信号、相位及阵元位置误差,传统波束形成方法性能不佳的问题,提出了基于迭代自适应法(IAA)的协方差矩阵重构稳健波束形成方法。该方法利用IAA估计出精确的功率谱,并进一步利用IAA估计的功率重构干扰协方差矩阵。重构过程中,将积分区域缩小到三维立体环域,减少无用信息的影响,提高了干扰协方差矩阵的重构精确度。最后通过波束形成抑制干扰信号。由于IAA不依赖于信号的非相干假设,解决了相干信号存在下的方位估计和功率估计。仿真表明,所提出的方法在相干信号、少快拍、相位及阵元位置误差同时存在的情况下,相对于其他波束形成方法,具有最优的信干噪比(SINR)输出,表明该方法具有优良的抑制干扰性能。     

Robust cyclic adaptive beamforming using a compensation method

This paper deals with the problem of robust adaptive array beamforming using signal cyclostationarity. The constrained cyclic adaptive beamforming (C-CAB) algorithm presented by Wu and Wong (1996) [6] has been shown to be effective in performing adaptive beamforming without requiring the direction vector or the waveform of the desired signal. However, this algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequency of the desired signal. In this paper, we first evaluate the performance degradation of the C-CAB algorithm in the presence of cycle frequency error (CFE). A novel compensation method in conjunction with the subspace projection is then proposed to tackle the problem due to CFE. We reconstruct the required cyclic conjugate correlation matrix by using a compensation matrix to cope with the deterioration of its dominant singular value when CFE exists. Finally, several simulation examples are provided to show the effectiveness of the proposed algorithm.