Performance Of Adaptive Array Research Articles

Effect of polarized signals on the performance of adaptive antenna arrays

Effect of polarized signals on the performance of adaptive antenna arrays

Robust Adaptive Beamforming Based on Subspace Decomposition, Steering Vector Estimation and Correction

Considering that the performance of adaptive arrays is sensitive to any type of mismatches, an innovative robust adaptive beamforming method based on covariance matrix reconstruction, subspace decomposition, steering vector estimation and correction is proposed. Based on Capon spatial spectrum, a group of angle sets containing all interfering signals are determined, and the interference covariance matrix can be reconstructed with a smaller integration interval. On the other hand, the sample covariance matrix can be decomposed into signal subspace and interference-plus-noise by using the principle of maximum correlation. Based on the interference-plus-noise subspace and the reconstructed signal-plus-noise covariance matrix, a new convex optimization model is built to estimate the steering vector of the desired signal. Then, an improved projection approach based on signal subspace is designed for correction to improve the robustness against the nominal direction vector mismatches. Simulation results demonstrate that the proposed method achieves better overall performance under multiple mismatches over a wide range of input signal-to-noise ratios.

The effects of mutual coupling and polarization on the performance of steered-beam adaptive arrays

The polarization of the electromagnetic waves impinging on adaptive antenna arrays has a significant impact on their performance. The effects of desired and undesired polarized signals and mutual coupling on the performance of adaptive antenna arrays with an electronically steerable beam are studied based on the ratio of the output signal to the interference plus noise. The performance of adaptive antenna arrays composed of single- versus cross-dipole antenna elements is studied to illustrate the effect of signal polarization. The experimental and simulation results show that, for randomly polarized signals, adaptive antenna arrays using cross-dipole elements provide better performance compared with those using single dipoles. However, if the desired signal polarization is well known, single-dipole antenna arrays offer better performance.

Signal processing by adaptive antenna arrays

This article outlines the basic theory of adaptive antenna arrays. The basic elements of an adaptive antenna array such as a diagramforming device and an adaptive processor are presented. The task of the adaptive processor is to control the diagram forming device, which provides the required processing of the input observation based on the available a priori information on the signal-interference environment. When such information is insufficient, the adaptive processor must have the ability to automatically adjust to the receiving conditions. In other words, the adaptive processor must implement some adaptation algorithm based on the initial data bank and the signal processing efficiency criterion. To quantitatively evaluate the performance of adaptive antenna arrays when receiving a useful signal, one of the ways of quality indicator has been considered: the RMS value of the deviation of the useful signal from the reference.

Impact of Element Pattern on the Performance of GNSS Power-Inversion Adaptive Arrays

Power-inversion (PI) adaptive arrays are widely used in Global Navigation Satellite System (GNSS) receivers for interference mitigation. The effects of element patterns on the performance of PI adaptive arrays are investigated in this paper. To this end, the performance of adaptive arrays is investigated by Monte Carlo simulations, using CST Microwave Studio (Dassault Systems, Vélizy-Villacoublay, France) to calculate the radiation patterns of circular microstrip elements which are used to compute the adaptive weight and the adaptive array gain. It is shown that the performance of PI adaptive arrays is mainly dependent on the gain pattern of the reference antenna element rather than the non-reference elements because the algorithm essentially pushes the elements into an unequal position. Furthermore, the results show that the impact of mutual coupling on the performance of the antenna array can be associated with the radiation patterns of the reference element, which is helpful in selecting the optimum reference element without increasing computational complexity, especially for small GNSS arrays.

Impact of Element Pattern Symmetry on the Effective Degrees of Freedom in Dual-Polarized GNSS Adaptive Antenna Arrays

The effect of element pattern symmetry on the performance of dual-polarized global navigation satellite system adaptive antenna arrays is investigated. To this end, using analytical expressions for the far-fields of circular microstrip antennas, the steady-state beamforming performance of a two-element dual-polarized array with three degrees of freedom (DOFs) is studied through many Monte Carlo simulations. It is shown that in the presence of randomly polarized interferers, regardless of the element pattern symmetry, the dual-polarized array can use all its DOF effectively to suppress up to three interferers and is as effective as a four-element right-handed circularly polarized (RHCP) array. It is, however, shown that if the interferers are RHCP, the dual-polarized array can use its DOF effectively only when the element patterns are asymmetric (unequal in E- and H-planes) and is ineffective in suppressing more than one interferer when the element patterns are symmetric (equal in E- and H-planes). This limitation is important in practice if the interferers are known to be RHCP and the array ground plane is small, since the patterns of microstrip antennas with small ground planes can become nearly symmetric. This finding is verified with a fabricated prototype of a two-element dual-polarized array with a small ground plane.

Investigation of Desired Element Pattern Reconfigurability in Small Adaptive Arrays

Pattern reconfigurable antennas implemented in small adaptive arrays can serve as practical solutions in applications, which are limited by available platform space while providing additional degrees of pattern control. This communication integrates the concept of pattern variability directly into an adaptive array optimization routine with a unique pattern reconfigurable antenna element equivalent model, allowing the algorithm to fully leverage the available reconfigurability—which may include individual pattern beam tilts and pattern nulls. Examples showcase the model’s impact on adaptive array performance via the signal-to-interference plus noise ratio metric. The results establish a pathway specifying the design requirements for pattern reconfigurable antennas to improve small adaptive array performance, demonstrating that designers should focus on the null steering capability of the antenna element in many cases.

Phase centre performance evaluation for GNSS adaptive array

The Global Navigation Satellite System (GNSS) adaptive array suffers from phase distortions owing to beam forming processing which in turn affect the navigation precision. In high precision GNSS applications, the distortions must be evaluated. Traditional phase performance evaluation approach is based on the fixed reception pattern antenna. A new approach to evaluate phase performance of adaptive array is presented. The method takes into account the interfering scenes and the average phase centre variation performance for different adaptive algorithm and array geometry can be obtained.

Evaluation of the Interference and Noise Suppression Capability of Uniform Linear Array Adaptive Beamforming Antenna

This paper evaluates the interference and noise suppression capability of uniform linear array adaptive beamforming antenna, at base stations of WCDMA mobile communication system. The signal-to-interference and noise ratio (SINR) was the performance index used for the evaluation and analysis. SINR was investigated for a conventional narrow band beam former by varying the number of antenna array elements, the inter-element spacing and number of interfering signals or users. The results were compared with that of omni-directional antenna. The graph obtained showed significant improvement in SINR as the number of antenna elements increases in the presence of large interferers for odd numbered array. the most common of all the array geometries employed in cellular and personal communication systems (PCS) (2), and it is the simplest to be used in investigating SINR improvement. In this paper, we provide a detailed presentation of SINR improvement ability of a ULA. In particular, we consider the effect of varying the number of antenna elements, number of interfering users and the inter-element spacing on the SINR improvement with the exclusion of mutual coupling. The performance of omni-directional antenna and adaptive antenna array were compared based on SINR maximization.

Functional Bandwidth Criterion for Adaptive Array Performance

The bandwidth of an interference source affects the performance of an adaptive array. The nature and degree of this effect, however, depends on the application considered. To analyze the bandwidth's effects correctly, therefore, a metric that reflects an adaptive array's performance for that application must be chosen. This paper employs a quantity known as the percentage of available sky (PAS) to analyze the bandwidth's effects on the performance of an adaptive array with a GPS receiver for GPS signal detection and tracking. The PAS, an important performance metric in GPS applications, is the fraction of area on a unit hemisphere where GPS signals are available for detection and tracking. The methodology to obtain the PAS for the minimum variance distortionless response (MVDR) beamformer is outlined. Results are presented that show how various system parameters influence the bandwidth's effect on the PAS. A comparison of the results from the PAS with the currently accepted criterion for bandwidth classification shows that the latter is not a reliable indicator of bandwidth effects on beamformer performance for GPS signal detection and tracking.

Performance of underwater adaptive array including mutual coupling effects

In this paper, the mutual coupling effects on the performance of underwater adaptive arrays are analyzed. This study manifests the discrepancies between cases of considering and ignoring the mutual coupling effects. The least mean square (LMS) based adaptive array is utilized to illustrate the mutual coupling effects. Numerical examples show that the performance of an underwater adaptive array can be improved as mutual coupling effects are considered. The consideration of mutual coupling effects is necessary in analyzing underwater adaptive arrays.

Analysis of Multiantenna Architectures for Non-LOS Mobile-to-Mobile Communications in Cochannel Interference

The performance of multiantenna receivers in cochannel interference is investigated for narrowband links in a non-line-of-sight mobile-to-mobile channel. Channel impairments include Doppler spread and angular spread originating from scatterers in the vicinity of both the transmitter and the receiver. The analysis employs a two-ring scattering model and compares the performance of a sectored system employing selection combining (SC) to the performance of adaptive arrays implemented with both omnidirectional antennas and sectored antennas. Performance is estimated for environments with cochannel interference and is measured in terms of output signal-to-interference-plus-noise ratio (SINR). An ensemble of random scattering realizations is utilized in the analysis to estimate the average output SINR. The results demonstrate the improved performance offered by adaptive arrays over sectored systems with SC. Configurations involving both SC and adaptive array processing were also evaluated and found to yield improvements over conventional adaptive array architectures.

Multipath performance of handset adaptive array antennas in the vicinity of a human operator

This paper examines the performance of the adaptive array antennas used in digital handset systems by studying the minimum mean square error (MMSE) algorithm at 2 GHz. The array is comprised of multiple quarter-wavelength monopole antennas and planar inverted-F antennas (PIFAs). By calculating the spatial correlation between two different directions, we describe how significant enhancement in the capability of reducing interference signals can be achieved, even when the handset is being held in the vicinity of a human operator in the talking position. Secondly, a computer simulation has been carried out under a flat Rayleigh fading environment with multiple cochannel interference signals, in which the average bit error rate (BER) of the handset adaptive array antenna has been characterized for the coherent detection of phase-shift keyed (PSK) signals. The performance of the handset adaptive array is compared to that of an adaptive array comprising plural parallel half-wavelength dipole antennas that are one half-wavelength apart. The performance was also evaluated with regard to the distance between the handset and the human head for different unequal median values and fading correlations of the received signals. The study has revealed that the adaptive array under consideration has substantial potential, not only to reduce the relative power of interference signals, but also to combat multipath fading of the desired signal by using the spatial diversity function of the MMSE, even in close proximity to a human operator.

Effects of antenna element bandwidth on adaptive array performance

The effects of individual antenna element bandwidth on the performance of adaptive arrays is studied when the incident interfering signals are wide-band signals. For these signal scenarios, as expected, the antenna element response over the bandwidth of the system plays an important role. If the individual antenna elements are dispersive, then the mutual coupling between array elements leads to dissimilar and dispersive channels in an adaptive array. This in turn leads to degradation in the performance of the adaptive array in that the adaptive array has to use more degrees of freedom to null a strong wide-band interfering signal. It is shown that by using wide-band antenna elements, one can significantly improve the performance of an adaptive array.

Performance evaluation of decision feedback adaptive arrays based on interarray correlation-neglecting algorithm

This paper presents the performance of a decision feedback adaptive array based on the interarray correlation-neglecting (ICN) algorithm that is suitable for high-speed mobile-communication systems. Although the ICN algorithm is regarded as a means of complexity reduction from the recursive least-square (RLS) algorithm, we present that the ICN algorithm has a superior initial acquisition performance close to the RLS algorithm, theoretically. The requirements for stable convergence are analytically revealed. Moreover, the performance is confirmed by Monte Carlo simulation. Besides, since the decision feedback adaptive array based on the ICN algorithm can be easily implemented with parallel processing, this array can reduce run-time cycles needed for one symbol. Therefore, this array can be applied to high-speed radio communication systems. In addition to this, the low operational complexity of this array makes it easy to apply this for high-speed mobile-communication systems where low complexity is basically required.

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 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.

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

Adaptive beamforming methods are known to degrade if some of underlying assumptions on the environment, sources, or sensor array become violated. In particular, if the desired signal is present in training snapshots, the adaptive array performance may be quite sensitive even to slight mismatches between the presumed and actual signal steering vectors (spatial signatures). Such mismatches can occur as a result of environmental nonstationarities, look direction errors, imperfect array calibration, distorted antenna shape, as well as distortions caused by medium inhomogeneities, near-far mismatch, source spreading, and local scattering. The similar type of performance degradation can occur when the signal steering vector is known exactly but the training sample size is small. In this paper, we develop a new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch. Our approach is based on the optimization of worst-case performance. It turns out that the natural formulation of this adaptive beamforming problem involves minimization of a quadratic function subject to infinitely many nonconvex quadratic constraints. We show that this (originally intractable) problem can be reformulated in a convex form as the so-called second-order cone (SOC) program and solved efficiently (in polynomial time) using the well-established interior point method. It is also shown that the proposed technique can be interpreted in terms of diagonal loading where the optimal value of the diagonal loading factor is computed based on the known level of uncertainty of the signal steering vector. Computer simulations with several frequently encountered types of signal steering vector mismatches show better performance of our robust beamformer as compared with existing adaptive beamforming algorithms.

Compensation for the effects of mutual coupling on the performance of adaptive arrays

Using the Method of Moments(MoM) and the spectral method, the effect of mutual coupling on the performance of adaptive arrays is compensated. First, the MoM is used to compute the behavior of the array, where the accurate analytical model and odd numbers of piecewise sinusoids are applied. Then the covariance matrix with mutual coupling being taken into account is analyzed, and the expression for the weight of the Least Mean Square(LMS) algorithm with mutual coupling being compensated is given. Finally, the method given in this letter is tested on an example.

Using sources of opportunity to compensate for receiver mismatch in HF arrays

The spatial processing performance of adaptive sensor arrays is often limited by the nonidentical frequency responses of the receivers in the array over the passband of interest. Addressed here is the problem of estimating digital compensation for mismatches between receiver passbands in high frequency (HF) antenna arrays using interference sources of opportunity. A mathematical model of ionospherically-propagated multipath HF interference is used to develop an adaptive algorithm which estimates the receiver frequency response corrections for each receiver. The effectiveness of the proposed algorithm is experimentally demonstrated and compared against (1) a commonly used least squares technique, and (2) a highly accurate calibration system using data collected by the receiving antenna array of the Jindalee over-the-horizon radar near Alice Springs in central Australia.

Adaptive antenna array assisted dynamic channel allocation techniques

The performance of base station adaptive antenna arrays (AAAs) is investigated in conjunction with fixed channel allocation (FCA) and dynamic channel allocation (DCA) schemes. Locally distributed DCA arrangements are studied and benchmarked against standard FCA, in the context of both line-of-sight (LOS) and multipath propagation environments. One-, two-, four-, and eight-element AAAs are employed using the sample matrix inversion (SMI) beamforming algorithm, in both the up- and the downlink. In most investigated scenarios, the locally optimized least interference algorithm (LOLIA) exhibited the best overall compromise in terms of a set of combined metrics, such as the forced termination probability, new call blocking probability, and the probability of a low quality access.