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This study presents three distributed beamforming algorithms to address the challenges of positioning and signal phase errors in unmanned aerial vehicle (UAV) arrays that hinder effective beamforming. Firstly, the array's received signal phase error model was analyzed under near-field conditions. In the absence of navigation data, a beamforming algorithm based on the Extended Kalman Filter (EKF) was proposed. In cases where navigation data were available, Taylor expansion was utilized to simplify the model, the non-Gaussian noise of the compensated received signal phase was approximated to Gaussian noise, and the noise covariance matrix in the Kalman Filter (KF) was estimated. Then, a beamforming algorithm based on KF was developed. To further estimate the Gaussian noise distribution of the received signal phase, the noise covariance matrix was iteratively estimated using unscented transformation (UT), and here, a beamforming algorithm based on the Unscented Kalman Filter (UKF) was proposed. The proposed algorithms were validated through simulations, illustrating their ability to suppress the malign effects of errors on near-field UAV array beamforming. This study provides a reference for the implementation of UAV array beamforming under varying conditions. [ABSTRACT FROM AUTHOR]

The target of an unmanned aerial vehicle swarm will present near-field characteristics when it is integrated as an array, and the existence of the unmanned aerial vehicle swarm motion error will greatly deteriorate the beam pattern formed by the array. To solve these problems, a near-field array beamforming model with array element position error is constructed, and the Taylor expansion of the phase difference function is used to approximately simplify the model. The improved Newton maximum entropy algorithm is proposed to estimate and compensate for the phase errors. The maximum entropy objective function is established, and the Newton iterative algorithm is used to estimate the phase error iteratively. To select the proper Newton iteration initial value, based on a single reference source signal, the initial value of the phase error is estimated through the phase gradient information of the received array signal. Beamforming is carried out after phase error compensation regarding the array. In order to assess the mismatch of the phase error compensation function based on the proposed method, when the beam is scanning, the effectively compensated spatial area of the array beamforming is divided, which lays a foundation for subsequent spatial region division and unmanned aerial vehicle swarm path planning. The simulation results show that the beam formed by the method proposed in this paper has a lower sidelobe level, and as the signal-to-noise ratio changes, the robustness of the proposed method is better validated. The proposed algorithm can effectively suppress the adverse influence of array element position error on array beamforming, and when the beam is scanning, the effectively compensated area of the phase error compensation function is divided, based on the proposed method. [ABSTRACT FROM AUTHOR]

This study presents three distributed beamforming algorithms to address the challenges of positioning and signal phase errors in unmanned aerial vehicle (UAV) arrays that hinder effective beamforming. Firstly, the array’s received signal phase error model was analyzed under near-field conditions. In the absence of navigation data, a beamforming algorithm based on the Extended Kalman Filter (EKF) was proposed. In cases where navigation data were available, Taylor expansion was utilized to simplify the model, the non-Gaussian noise of the compensated received signal phase was approximated to Gaussian noise, and the noise covariance matrix in the Kalman Filter (KF) was estimated. Then, a beamforming algorithm based on KF was developed. To further estimate the Gaussian noise distribution of the received signal phase, the noise covariance matrix was iteratively estimated using unscented transformation (UT), and here, a beamforming algorithm based on the Unscented Kalman Filter (UKF) was proposed. The proposed algorithms were validated through simulations, illustrating their ability to suppress the malign effects of errors on near-field UAV array beamforming. This study provides a reference for the implementation of UAV array beamforming under varying conditions.

In this paper we show the equivalence of near-field beamforming and backward-wave reconstruction algorithm. The proof is carried out analytically with two different approaches, using the principle of stationary phase from a signal processing point of view and the angular spectrum representation as an electromagnetic point of view. A comparison of the time complexity of the near-field beamforming and backward-wave reconstruction algorithm is given. A detailed discussion of the constraints required for a digital implementation is presented, leading to limitations for the chosen system parameters, especially for the backward-wave reconstruction approach. An exemplarily scenario is simulated and processed, confirming the found equivalence between the two very different approaches of image reconstruction. An additional measurement with a 120 GHz radar showcases the capabilities of both algorithms and validates our findings.

This work develops a reconfigurable coil array that compensates for the misalignment between coils in magnetic resonance coupled wireless power transfer (WPT) systems. By tuning the magnitude of the currents induced in the coil array with the variable capacitors that load them, the effect of reconfiguring the size and/or shape of the coil can be achieved. Therefore, the near field can be steered in a certain direction to overcome the notorious misalignment problem in WPT systems. For experimental demonstration, a $2\times 1$ array is designed and fabricated for a $60\times 60$ mm2 coil. For a vertical distance between Tx and Rx coils of 10 mm, which is 16.7% of the largest coil dimension, the transfer efficiency maintains more than 40% and up to 141.6% misalignment. This is more than an 81% increase over the conventional coil. For a vertical distance of 30 mm or 50%, the minimum transfer efficiency is 37.1% up to 100% misalignment, which is almost 5.5 times that of the conventional counterpart. The results suggest that the demonstrated technology successfully overcomes the notorious misalignment problem in both short-range and midrange WPT systems and even in asymmetric systems where the reconfigurable coil array technique is applied only on the Rx. [ABSTRACT FROM AUTHOR]

The target of an unmanned aerial vehicle swarm will present near-field characteristics when it is integrated as an array, and the existence of the unmanned aerial vehicle swarm motion error will greatly deteriorate the beam pattern formed by the array. To solve these problems, a near-field array beamforming model with array element position error is constructed, and the Taylor expansion of the phase difference function is used to approximately simplify the model. The improved Newton maximum entropy algorithm is proposed to estimate and compensate for the phase errors. The maximum entropy objective function is established, and the Newton iterative algorithm is used to estimate the phase error iteratively. To select the proper Newton iteration initial value, based on a single reference source signal, the initial value of the phase error is estimated through the phase gradient information of the received array signal. Beamforming is carried out after phase error compensation regarding the array. In order to assess the mismatch of the phase error compensation function based on the proposed method, when the beam is scanning, the effectively compensated spatial area of the array beamforming is divided, which lays a foundation for subsequent spatial region division and unmanned aerial vehicle swarm path planning. The simulation results show that the beam formed by the method proposed in this paper has a lower sidelobe level, and as the signal-to-noise ratio changes, the robustness of the proposed method is better validated. The proposed algorithm can effectively suppress the adverse influence of array element position error on array beamforming, and when the beam is scanning, the effectively compensated area of the phase error compensation function is divided, based on the proposed method.

The inconsistency in the magnitude and phase variations among the receiving array elements in multibeam soundings can seriously affect the beam pattern characteristics, which reduces the array gain, increases the sidelobe level, and deteriorates the direction-of-arrival (DOA) estimation. The accuracy of the beamforming result may be improved by correcting for magnitude and phase variations among the array elements. Therefore, a novel estimation and correction method based on near-field focused beamforming is proposed to overcome deficiencies of the conventional methods. The magnitude and phase variation model and the corresponding influence on the direction-finding accuracy are analyzed. The near-field focused beamforming model is established for multielement systems, and the root-mean-square error (RMSE) method is used to determine the ideal-source incident angle for correction. We construct the receiving signal covariance matrix in the frequency domain and further estimate the magnitude and phase variations in each array element. The performance and effectiveness of the proposed method are verified by simulations and small anechoic tank experiments. The proposed method requires the employment of a rotation platform that provides necessary rotation information and, thus, can accurately and effectively estimate and correct for variations in the magnitude and phase response of elements in the receiving array. The experimental results show that the sidelobe level can be reduced by approximately 3 dB after the array is corrected, and the angle deviation is reduced by approximately 1.0°. [ABSTRACT FROM AUTHOR]

Beamforming (BF) is an array processing technique that has been extensively applied in angular source localization applications such as sonar and radar, mostly from measurement in the far field. However, near-field source resolution performance of BF procedures can be significantly improved by using channel weights that are inversely proportional to the distance from the hypothesized source location to the measurement locations. Visualization of noise radiated from bearings is challenging since the measurement is usually corrupted by scattering and reflection from bearing housings that are located very close to sources even though the measurement may be taken in an anechoic environment. In this article, adaptive weightings are used in near-field BF procedure, and shown to give very good visualization of sound radiation of rolling bearings that are a complex sound source in a highly scattered and noisy environment. It is shown that for a machine made of several components, this adaptive near-field BF technique provides good imaging performance and allows identification of the primary sources of sound radiation at a broad range of frequencies. [ABSTRACT FROM AUTHOR]

A microphone array beamforming system is proposed for multimedia communication applications using four sets of small planar arrays mounted on a computer monitor. A new virtual array approach is employed such that the original signals received by the array elements are weighted and delayed to synthesize a large, nonuniformly spaced, harmonically nested virtual array covering the frequency band [50, 7000] Hz of the wideband telephony. Subband multirate processing and near-field beamforming techniques are then used jointly by the nested virtual array to improve the performances in reverberant environments. A new beamforming algorithm is also proposed using a broadband near-field spherically isotropic noise model for array optimization. The near-field noise model assumes a large number of broadband random noises uniformly distributed over a sphere with a finite radius in contrast to the conventional far-field isotropic noise model which has an infinite radius. The radius of the noise model, thus, adds a design parameter in addition to its power for tradeoffs between performance and robustness. It is shown that the near-field beamformers designed by the new algorithm can achieve more than 8-dB reverberation suppression while maintaining sufficient robustness against background noises and signal location errors. Computer simulations and real room experiments also show that the proposed array beamforming system reduces beampattern variations for broadband signals, obtains strong noise and reverberation suppression, and improves the sound quality for near-field targets. [ABSTRACT FROM PUBLISHER]

This paper proposes a robust near-field adaptive beamformer for microphone array applications in small rooms. Robustness against location errors is crucial for near-field adaptive beamforming due to the difficulty in estimating near-field signal locations especially the radial distances. A near-field regionally constrained adaptive beamformer is proposed to design a set of linear constraints by filtering on a low rank subspace of the near-field signal over a spatial region and frequency band such that the beamformer response over the designed spatial-temporal region can be accurately controlled by a small number of linear constraint vectors. The proposed constraint design method is a systematic approach which guarantees real arithmetic implementation and direct time domain algorithms for broadband beamforming. It improves the robustness against large errors in distance and directions of arrival, and achieves good distance discrimination simultaneously. We show with a nine-element uniform linear array that the proposed near-field adaptive beamformer is robust against distance errors as large as ±32% of the presumed radial distance and angle errors up to ±20°. It can suppress a far field interfering signal with the same angle of incidence as a near-field target by more than 20 dB with no loss of the array gain at the near-field target. The significant distance discrimination of the proposedaear-field beamformer also helps to improve the dereverberation gain and reduce the desired signal cancellation in reverberant environments. [ABSTRACT FROM AUTHOR]

This paper proposes a near-field broadband adaptive beamforming scheme for intelligent computer telephony and teleconferencing applications, namely the nested microphone array with adaptive noise canceller (NMA-ANC). The NMA-ANC scheme incorporates an harmonically nested array with a nonuniformly subbanded multirate filter bank. Each subband array employs several near-field delay-filter-and-sum beamformers and an adaptive noise canceller (ANC). The proposed NMA-ANC is evaluated via a noise rejection experiment and dereverberation experiment performed in an anechoic chamber and a real conference room, respectively. The experiment data are recorded by a multichannel digital recording system developed using commercial off-the-shelf (COTS) equipments. A perceptual analysis/measurement system (PAMS) test is also carried out using a COTS digital speech level analyzer. The results of the experimental evaluation and PAMS test show that the proposed NMA-ANC scheme is able to improve the sound quality by adaptively rejecting multiple interfering signals and attenuating the reverberant noises and avoiding the desired signal cancellation. [ABSTRACT FROM AUTHOR]

This letter presents near-field beamforming using a loop array for selective wireless power transfer. Near-field beamforming is achieved by controlling the loop current. The magnitude and phase of the loop currents are controlled by adjusting the loop capacitances. The appropriate capacitance value of the loop array can be found with a genetic algorithm for maximum efficiency. It is demonstrated that the power is selectively transferred when there are two receivers whose separation is 50 cm from the 1\times4 loop array at the frequency of 6.78 MHz. The experimental results agree with the theoretical results. In addition, the loop array has an advantage of insensitiveness to misalignment of a receiver for power transfer. [ABSTRACT FROM PUBLISHER]

• This study compares topologies of AE sensor arrays for gas leakage localization. • The performances of the sensor arrays are assessed on a flat-surface structure. • The leak localization is based on the principle of near-field beamforming. • The L-shaped sensor array outperforms all other topologies. The topology of the acoustic emission sensor array has an important effect on the performance of the leak localization technique. This paper compares the performances of different topologies of acoustic emission sensor arrays in the localization of gas leakage on a flat-surface structure. The principle of the leak localization is based on the near-field beamforming according to the spherical wave model and the narrowband filtering which can effectively avoid the influence of acoustic dispersion. The effect of different arrangements of the sensing elements in a sensor array on the localization accuracy is investigated and discussed. Eight typical topologies, including line, L-shaped, cross, triangle, star, circular, semi-circular and square shapes, are appraised through computer simulation. Simulation results suggest that all the arrays can perform leak localization but with different accuracies and that the L-shaped array outperforms all other topologies under the similar conditions. Furthermore, the optimal number of sensors in the L-shaped array which can maintain a reasonable accuracy of localization is analyzed. Experimental work was carried out on a laboratory scale test rig to verify and assess the effectiveness of the L-shaped array. The simulation and experimental results demonstrate that the L-shaped array is capable of identifying the location of a leak hole on a plate with a reasonably good accuracy. [ABSTRACT FROM AUTHOR]