An adaptive array utilizing an adaptive spatial averaging technique for multipath environments

When the interference is coherent with the desired signal, the conventional adaptive arrays working under the guiding principle of output power minimization tend to cancel the desired signal by using the coherent interference. A technique is described which enables the adaptive array to function even under such an environment. The array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal. The averaged matrix is now free from correlation terms between the desired signal and interference, and therefore may be used to derive the optimum weight for the array element just as in the ordinary radio environment of incoherent interference. Numerical examples show that the new adaptive array is highly capable to suppress the coherent interferences as well as incoherent ones.     

一种稳健的多径估计和抑制算法

针对通信系统中多径干扰难以估计和抑制的问题,提出了一种地面采用智能天线自适应跟踪的方法。以均匀直线阵为基础,采用前后向空间平滑算法对阵列接收相干信号进行预相干处理,再利用MUSIC(Multiple Signal Classification)算法实现信号来波方向(Direction of Arrival,DOA)估计,应用一种新的对角加载稳健波束形成技术减小主峰偏移,实现多径干扰抑制。仿真分析验证了所提算法的正确性和有效性,系统具有良好的稳健性,具有较高的工程实践价值。     

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.     

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.     

一种新型自适应天线的空间谱估计性能分析

利用菲涅尔区相位修正聚焦结构和馈源阵列构成一种新型的多波束自适应天线。本文深入分析了基于该天线的阵列输出特性，与基于均匀线形阵的空间谱估计技术比较的基础上，揭示了其良好的去相关性能。最后应用极大似然估计算法实现了相干信号源在大角度入射的情形下，菲涅尔平板天线对来波方向的有效估计，从而避免了应用MUSIC算法进行来波方向估计时所遇到的观察区域的限制问题。仿真计算的结果表明菲涅尔平板天线良好的空间谱估计性能。     

An interference-tolerant algorithm for localization ofcyclostationary-signal sources

A method for detecting the number of cyclostationary signals radiated by remote sources and for estimating their directions of arrival by a linear and uniform array is presented. Whereas the traditional techniques exploit the spatial coherent properties, the new method locates the signal sources using the spectral coherence properties as well. This approach eliminates the need to know the characteristics of the noise and the interference, regardless of the extent of their spectral overlap. Moreover, the method applied equally well to environments containing more interferers than sensors. The conditions of applicability of the method are the existence and the knowledge of a cycle frequency at which all the signal sources exhibit spectral correlation but the noise and interference signals do not, and the existence and the knowledge of a value of the lag parameter such that the cyclic cross-correlation matrix of the desired signals has full rank     

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。     

MODE SPACE SMOOTHING ALGORITHM TO ESTIMATE DOA OF COHERENT SIGNALS IMPINGING ON UNIFORM CIRCULAR ARRAY

A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.     

Radio-astronomical imaging in the presence of strong radiointerference

Radio-astronomical observations are increasingly contaminated by interference, and suppression techniques become essential. A powerful candidate for interference mitigation is adaptive spatial filtering. We study the effect of spatial filtering techniques on radio-astronomical imaging. Current deconvolution procedures, such as CLEAN, are shown to be unsuitable for spatially filtered data, and the necessary corrections are derived. To that end, we reformulate the imaging (deconvolution/calibration) process as a sequential estimation of the locations of astronomical sources. This not only leads to an extended CLEAN algorithm, but also the formulation allows the insertion of other array signal processing techniques for direction finding and gives estimates of the expected image quality and the amount of interference suppression that can be achieved. Finally, a maximum-likelihood (ML) procedure for the imaging is derived, and an approximate ML image formation technique is proposed to overcome the computational burden involved. Some of the effects of the new algorithms are shown in simulated images     

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     

Adaptive arrays with main beam constraints

Initial applications of adaptive array theory to the radar sidelobe jamming problem ignored the problem of incidental cancellation of the desired signal returns. In more recent applications, longer transmitted waveforms have combined with returns from extended clutter and/or strong targets to create a more serious signal cancellation problem. There are several ways in which the adaptive processor can be constrained from responding to desired main lobe target returns while maintaining good cancellation of interference in the sidelobes. This paper examines the major techniques for constraining the response of the adaptive processor, including methods of controlling the response of the array in the absence of external interference. Time domain and frequency domain techniques are discussed. The majority of the discussion is devoted to angle domain techniques such as pilot signals, preadaption spacial filtering, and control loop spatial filtering. Analysis is presented showing the relationship between these techniques. Finally, examples are given showing the effects of these constraints as well as control of the quiescent array pattern.     

Generalized eigen-combining algorithm for adaptive array systems in a co-channel interference environment

This paper presents a generalized eigen-combining algorithm for an adaptive array system that provides a diversity gain in angular spread, and a maximum signal-to-interference ratio (SIR) in the presence of strong interference. The proposed technique generates the maximum ratio of signal components distributed in the spatial channel subspace using channel bases that span the signal subspace and nullify the interference. Through extensive computer simulations, it is shown that the proposed algorithm represents a breakthrough in preventing performance saturation caused by strong co-channel interference.     

空间平滑自适应阵列的优化

在多路径环境中，空间平滑是消除相干干扰对自适应阵列处理系统影响的有效方法。我们注意到空间平滑自适应阵列的权系数往往是在子阵列上得到的。这意味着存在一些剩余自由度可以用来改善自适应阵列的性能。本文提出了一种新方法，利用阵列自由度使得自适应阵列的响应具有期望的特性。我们指出如何优化空间平滑自适应阵列使得白噪声功率或者阵列的副瓣昼降低。数值结果说明了新方法的有效性。     

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     

基于波束形成跳频系统抗干扰方法研究

本文研究利用波束形成技术与跳频技术相结合,在存在宽带阻塞干扰以及跟踪干扰时,将信号与干扰在空域进行分离,提高跳频系统的抗干扰性能。指出利用空间平滑不仅可以有效抑制相干跟踪干扰,而且提高了波束的收敛速度。仿真结果证明了该方法的有效性。     

Adaptive array with global weighted spatial smoothing

Global weighted spatial smoothing is utilised in adaptive arrays for coherent interference suppression. With the prior knowledge of the directions of coherent sources, signal cancellation is eliminated and the smoothing index can be reduced to the number of sources even for small spatial separation.     

一种基于高阶累计量的相干干扰抑制方法研究

常规的自适应数字波束形成方法仅限于利用信号的二阶统计特性,当其工作在相干干扰环境中时,由于接收信号协方差矩阵的信号子空间的一些向量收敛到噪声空间中,此时二阶统计量方法无法准确提取干扰方位信息,从而导致该波束形成器很难取得较好的抗干扰性能。因为高阶累计量能包含更多的统计信息,运用高阶累计量方法来提取干扰信号方位信息,然后根据最小均方误差准则来形成波束图,试验表明基于高阶累计量的自适应波束形成方法能够较为有效地抑制相干干扰源,并且该方法减少了对阵列流型的依赖,具有较好的容差性。     

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.     

Protection of a Narrow-Band BPSK Communication System with an Adaptive Array

This paper describes the performance of an adaptive array when used with narrow-band BPSK communication signals; A previous paper [11] described the performance of an adaptive array with a standard BPSK signal when the array bandwidth is several times the signal bandwidth. These earlier results are extended to the case where the array bandwidth is as small as possible, equal to the desired signal symbol rate. To realize such a bandwidth reduction, it is necessary to reshape the BPSK signaling waveform before transmission to prevent intersymbol interference. This is done by passing the BPSK signal through a pulseshaping filter at the transmitter. The performance of the optimal detector for the narrow-band BPSK signal is determined when this detector operates behind an adaptive array that is subjected to CW interference. The bit error probability is obtained as a function of the desired signal and interference powers and arrival angles as well as the array bandwidth.     

A subspace-tracking approach to interference nulling for phasedarray-based radio telescopes

Several next-generation radio telescopes, now in the planning stages, are based on phased-array technology. One reason for this is to make use of adaptive nulling techniques to combat radio frequency interference, which is a growing problem for radio astronomy. This paper presents a low-complexity approach to interference nulling which is suitable for use in such systems. The approach uses subspace-tracking to identify interference, followed by spatial projections to place deep nulls in the directions of interferers. This technique overcomes two limitations of power-minimization algorithms (e.g., "minimum variance"), namely power inversion and pattern rumble, which create serious problems for radio astronomy. Furthermore, this technique imposes a lower computational burden and provides side information which is useful in later stages of data processing. Performance results from a phased array demonstrator system and a simulation are presented