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The safety valve is the core component of the pressure-relief protection device for pressure-bearing special equipment. When the safety valve leaks, the medium of the pressure vessel will be lost and wasted, which may cause safety accidents. With the aim to solve the problem of accurately locating the multiple leakage sources of safety valves, a localization method combining a uniform circular array acoustic emission detection and an improved multiple signal classification (MUSIC) algorithm is proposed. First, an improved wavelet threshold function denoising method is introduced to extract acoustic emission signals with high SNR, thereby reducing the rank of the covariance matrix, weakening the noise dispersion caused by eigenvalue reconstruction, avoiding signal and noise cross-confusion, and improving positioning accuracy. By introducing a windowed fast Fourier transform (FFT) frequency division processing link to obtain narrowband signal, the premise of using MUSIC positioning algorithm is established. In addition, a forward/backward spatial smoothing algorithm is introduced in the decoherence link to reduce co-channel interference, reduce the rank loss of the signal covariance matrix, and improve the positioning accuracy of the algorithm. The results show that when the working pressure is 0.70 MPa, 0.75 MPa, and 0.80 MPa, the deviation between the azimuth angle and elevation angle positioning results of each leakage source obtained by the improved MUSIC algorithm and the actual angle does not exceed 2°, and the relative error does not exceed 3.5%. Therefore, the improved MUSIC algorithm can accurately locate multiple leakage sources of the safety valve, and as the working pressure of the safety valve increases, the positioning accuracy of the improved MUSIC algorithm also increases accordingly.

In order to improve the quality of the received signal and system spectral efficiency, accurate beamforming using a given antenna array is essential for multiple-input multiple-output (MIMO) systems. To obtain desired MIMO transmission performance, construction of codebooks which are composed of matching beamforming vectors to the array structure is important. To effectively cover different types of mobile traffic, the base station for 5G new radio employs antenna arrays in various sizes and shapes. Nevertheless, the codebooks adopted by the 3GPP standard so far are based on the uniform linear array and the uniform planar array, necessitating design techniques for a wider class of antenna arrays. In this paper, we propose codebook construction methods for the uniform circular array with parameters to flexibly set the initial phase and step size based on the channel characteristics of the user equipment (UE). When tested over the 3GPP spatial channel model, the proposed codebooks show a substantial amount of gain over the conventional codebooks in all UE locations within the cell.

Physical layer security is a cross research hotspot of information security and wireless communications. Recently, orbital angular momentum (OAM) technology has attracted widespread attention due to its potential of improving capacity and spectrum efficiency. However, there are few researches on system security based on OAM technology. In this work, we studied the security of the proposed OAM wiretap system by applying physical layer security theory to OAM communications. Firstly, we proposed a uniform circular array-based multi-mode OAM system and derived the secrecy capacity. Secondly, the phase profiles, channel capacity and received power of OAM beams are analyzed in terms of various system parameters in oblique scenarios at 30GHz. Thirdly, we discussed the security of the proposed OAM wiretap system. The results show that the system using vortex waves is superior to conventional communication systems using planar electromagnetic waves in terms of system security due to the inherent divergence and spiral phase structure of OAM beams. Moreover, we found that the distortion of OAM beams during transmission and the center shift at receiving end will occur and that system is more stable for high-mode OAM propagation in oblique scenarios. This work can provide an effective guidance for the research and application of OAM communications.

In recent years, orbital angular momentum (OAM) waves have been applied to improve the performance of radar target detection and imaging. However, the phase singularity of conventional OAM beams and the doughnut-shaped intensity distribution will degrade the performance of target detection. To solve the divergence problem in OAM multiplexing systems, the generation method of OAM beams propagating along a transverse plane is proposed using a uniform circular array, which is validated by full-wave simulation. Compared with conventional OAM beams, simulation results indicate that the generated beams with different OAM modes all propagate along the transverse plane while maintaining the regular wavefront shapes. This work can provide the development of new radar paradigm with technical support.

In this paper, we present a low complexity sparse beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA). In the proposed method, we firstly use the beamspace transformation (BT) to transform the signal model of UCA in element-space domain to that of virtual uniform linear array (ULA) in beamspace domain. Subsequently, by applying the vectoring operator on the virtual ULA-like array signal model, a novel dimension-reduction sparse beamspace signal model is derived based on Khatri-Rao (KR) product, the observation data of which is represented by the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. And then, the DOA estimation is formulated as a convex optimization problem by following the concept of a sparse-signal-representation (SSR) of the SMVs. Finally, simulations are carried out to validate the effectiveness of the proposed method. The results show that without knowledge of the number of signals, the proposed method not only has higher DOA resolution than the subspace-based methods in low signal-to-noise ratio (SNR), but also has far lower computational complexity than other sparse-like DOA estimation methods.

In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains. We propose a covariance matrix completion algorithm for 2D-DOA estimation in a SUCA. The proposed algorithm estimates the complete covariance matrix of a fully sampled UCA (FUCA) from the sample covariance matrix of the SUCA through a neural network. Afterwards, the MUSIC algorithm is performed for 2D-DOA estimation with the completed covariance matrix. We conduct Monte Carlo simulations to evaluate the performance of the proposed algorithm in various scenarios; the performance of 2D-DOA estimation in the SUCA gradually approaches that in the FUCA as the SNR or the number of snapshots increases, which means that the advantages of a FUCA can be preserved with fewer RF chains. In addition, the proposed algorithm is able to implement underdetermined 2D-DOA estimation.

Nowadays all the research about the estimation of MIMO (multiple input and multiple output) radar's DOA (direction of arrival) is based on traditional algorithm. Therefore, it cannot estimate the cyclostationary signal's DOA and this kind of signals are widely used in the fields of signal processing. Hence, this paper proposes a new estimation algorithm of MIMO radar's DOA which based on cyclic statistics; Uniform circular array can do a 360-degree non-fuzzy DOA estimation and also provide azimuth and angle of pitch information. Therefore, the theoretical derivation of the new algorithm in a uniform circular array can estimate pitch angle and azimuth at the same time in the non-stationary signal environment.

This study presents the conception, simulation, realisation and characterisation of a patch antenna for Wi-Fi. The antenna is designed at the frequency of 2.45 GHz; the dielectric substrate used is FR4_epoxy which has a dielectric permittivity of 4.4.this patch antenna is used to estimate the direction of arrival (DOA) using 2-D Multiple Signal Classification (2-D MUSIC) the case of the proposed uniform circular arrays (UCA). The comparison between Uniform circular arrays and Uniform Linear arrays (ULA) demonstrate that the proposed structure give better angles resolutions compared to ULAs.

Smart antennas have recently received increasing for improving the performance of wireless radio systems. In this research article, we have used a patch antenna using uniform circular arrays (UCA) with central element for direction of arrival (DOA). A central element was added to arrays in order to increase steering capability of the proposed array. This geometry is used to determine the elevation and azimuth based on two famous algorithms of high resolution method: Matrix Pencil method (MP) and MUltiple Signal Classification (MUSIC).The comparison results demonstrate clearly that the matrix pencil is more accurate and stable to estimation of direction of arrival compared to the MUSIC algorithm.

In this paper, the methods and analysis for estimating the location of a three-dimensional (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using information in the covariance matrix obtained by the sensors' outputs, equations of the source location (azimuth angle, elevation angle, and range) are obtained. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the lossy medium. By analyzing the characteristics of the proposed methods and the multiple signal classification (MUSIC) method, the computational complexity and the valid scope of these methods are given. From the results, whether the loss is known or not, we can choose the best method for processing the issues (localization in lossless medium or lossy medium).

Under fixed uniform circular array (UCA), 3-D parameter estimation of a source whose half-wavelength is smaller than the array aperture would suffer from a serious phase ambiguity problem, which also appears in a recently proposed phase-based algorithm. In this paper, by using the centro-symmetry of UCA with an even number of sensors, the source’s angles and range can be decoupled and a novel algorithm named subarray grouping and ambiguity searching (SGAS) is addressed to resolve angle ambiguity. In the SGAS algorithm, each subarray formed by two couples of centro-symmetry sensors can obtain a batch of results under different ambiguities, and by searching the nearest value among subarrays, which is always corresponding to correct ambiguity, rough angle estimation with no ambiguity is realized. Then, the unambiguous angles are employed to resolve phase ambiguity in a phase-based 3-D parameter estimation algorithm, and the source’s range, as well as more precise angles, can be achieved. Moreover, to improve the practical performance of SGAS, the optimal structure of subarrays and subarray selection criteria are further investigated. Simulation results demonstrate the satisfying performance of the proposed method in 3-D source localization.

Beamforming using uniform circular arrays of microphones can be used, e.g., for localization of environmental noise sources and for conferencing. The performance depends strongly on the characteristics of the array, for instance the number of transducers, the radius and whether the microphones are mounted on a scatterer such as a rigid cylinder or a sphere. The beamforming output improves with increasing frequency, up to a certain frequency where spatial aliasing occurs. At low frequencies the performance is limited by the radius of the array; in other words, given a certain number of microphones, an array with a larger radius will perform better than a smaller array. The aim of this study is to improve the performance of the array at low frequencies without modifying its physical characteristics. This is done by predicting the sound pressure at a virtual and larger concentric array. The propagation of the acoustic information captured by the microphones to the virtual array is based on acoustic holography. The predicted pressure is then used as input of the beamforming procedure. The combination of holography and beamforming for enhancing the beamforming output at low frequencies is examined with computer simulations and experimental results.