Parallel Subarrays Research Articles

Pruned Distributed and Parallel Subarray Beamforming for 3-D Underwater Imaging With Fine-Grid Sparse Arrays

The development of real-time 3-D underwater imaging systems with large planar arrays involves high hardware costs and great computational burden. This study proposes the concept of fine-grid sparse arrays and the pruned distributed and parallel subarray (P-DPS) beamforming algorithm to achieve 3-D narrowband underwater imaging systems with low complexity. Fine-grid sparse arrays refine traditional half-wavelength grids to improve the freedom of the sparse optimization process and reduce the number of active elements. However, grid refinement increases the computational load of conventional fast beamforming algorithms. To solve this problem, a new pruned fast Fourier transform is proposed to eliminate all the redundant operations in the P-DPS beamforming, which is suitable for fine-grid sparse arrays. The computational load of the P-DPS beamforming seldom increases with grid refinement. The validity of the proposed method is verified with a fine-grid sparse planar array designed in the study. The computational load is then analyzed and compared with those of other methods. Results show the notable improvements in array sparsity rate and computational efficiency relative to those in the literature.

Expectation Propagation Detector for Extra-Large Scale Massive MIMO

The order-of-magnitude increase in the dimension of antenna arrays, which forms extra-large-scale massive multiple-input-multiple-output (MIMO) systems, enables substantial improvement in spectral efficiency, energy efficiency, and spatial resolution. However, practical challenges, such as excessive computational complexity and excess of baseband data to be transferred and processed, prohibit the use of centralized processing. A promising solution is to distribute baseband data from disjoint subsets of antennas into parallel processing procedures coordinated by a central processing unit. This solution is called subarray-based architecture. In this work, we extend the application of expectation propagation (EP) principle, which effectively balances performance and practical feasibility in conventional centralized MIMO detector design, to fit the subarray-based architecture. Analytical results confirm the convergence of the proposed iterative procedure and that the proposed detector asymptotically approximates Bayesian optimal performance under certain conditions. The proposed subarray-based EP detector is reduced to centralized EP detector when only one subarray exists. In addition, we propose additional strategies for further reducing the complexity and overhead of the information exchange between parallel subarrays and the central processing unit to facilitate the practical implementation of the proposed detector. Simulation results demonstrate that the proposed detector achieves numerical stability within few iterations and outperforms its counterparts.

Improved two-dimensional DOA estimation using parallel coprime arrays

The conventional coprime array consists of two uniform linear subarrays to construct an effective difference coarray with desirable characteristics. Such linear coprime arrays only provide one-dimensional (1-D) direction-of-arrival (DOA) estimation. In this paper, we propose a novel coprime array configuration with parallel subarrays, along with an effective method for two-dimensional (2-D) DOA estimation. The 2-D DOA estimation problem is cast as two separate 1-D problems for reduced complexity and is solved using one of the two mechanisms based on the number of sensors and that of sources. When there are less sources than the number of sensors, subspace-based and rank-reduction estimation (RARE) techniques are sequentially applied to the physical array output. On the other hand, when the number of sources is equal to or larger than that of sensors, a virtual difference coarray is formed and group sparse reconstruction and least squares operations are then applied. In both scenarios, the proposed methods automatically pair the corresponding azimuth and elevation angles. The proposed methods resolve up to MN sources using 2M+N−1 sensors, which are the same as in the 1-D DOA estimation using conventional coprime arrays. Simulations results are presented delineating both the accuracy and resolution capability of the proposed method.

Design of Low-Complexity 3-D Underwater Imaging System With Sparse Planar Arrays

The development of a real-time 3-D underwater imaging system with a planar array is restricted by the huge hardware cost and computational burden associated with the large number of elements required. In this paper, a new design of low-complexity 3-D underwater imaging system is proposed, involving two key parts: a special sparse array with low hardware cost and an efficient beamforming with low computational burden. Especially, the simulated annealing algorithm is optimized based on distributed and parallel subarray (DPS) beamforming and results in fewer active elements than existing methods. To improve the computational efficiency especially for sparse arrays, an optimized DPS beamforming is presented with the pruning fast Fourier transform technology. To test the validity of the design, a real system based on the proposed methods was devised and employed in the lake and sea trials. The experiment results demonstrate that the low-complexity 3-D underwater imaging system can provide a satisfactory imaging quality.

Low‐loss frequency scanning planar array with hybrid feeding structure for low‐altitude detection radar

A 1 × 4 low-loss frequency scanning planar array with hybrid feeding structure in Ku-band has been designed. In order to improve the array efficiency, the planar array was designed by four parallel sub-arrays and the waveguide slow-wave line structure with electromagnetic coupled slot on narrow side was used as feed line. The results of simulation show that, except at the centre frequency, the voltage standing wave ratio of the antenna array is below 1.2 at the operation band, the range of the scanning angles is (−30.5°, 29°), the beam width of the antenna is about 5.5°–6.6°, the sidelobe is below −20 dB, and the gain is more than 30 dBi.

Estimation for Two-Dimensional Incoherently Distributed Source in Double L-Shape Arrays

Distributed sources can be regarded as an assembly of point sources within a spatial distribution. In this paper, we explore the estimation of the two-dimensional incoherently distributed sources using double L-shape arrays. The rotational invariance properties of the nominal elevation and nominal elevation are firstly obtained by taking first-order Taylor series expansions with regard to the generalized steering vectors of two pairs of parallel subarrays. The rotation operators can be solved based on signal subspace. Then the nominal elevation and nominal elevation can be obtained from parameters matching method. Estimation of direction of arrival can be used in multi-source scenario and needn't peak-finding search. Lastly the angular spreads can be solved through two-dimensional Capon search based on nominal angles. The simulation experiments show that the proposed method has good performance on the estimation of two-dimensional incoherently distributed sources. Investigating different experimental conditions, sources with different angular spreads, simulations are conducted to validate better estimation accuracy of the proposed method.

A Low-Complexity Real-Time 3-D Sonar Imaging System With a Cross Array

The development of real-time 3-D underwater imaging is restricted by the huge hardware cost and the computational burden associated with a large number of transducers. In this paper, a low-complexity real-time 3-D sonar imaging system with a cross array is proposed. The low complexity, in both hardware cost and computational load, is achieved by an innovative method of signal processing in the far field and the advantages of the cross array in minimal transducer numbers. The method consists of two parts: a multifrequency (MF) algorithm for the transmitting process and a parallel subarray (PS) algorithm for the receiving beamforming. The MF algorithm solves the real-time problem of the cross array by reducing the scanning time that is proportional to the number of transmissions. The PS algorithm improves the computational efficiency using a two-stage parallel and pipeline framework. The PS algorithm is an approximate method, and its precision is analyzed in this paper. The computational efficiency of the proposed method is compared with the direct method (DM) beamforming in both cross and planar arrays. A prototype, based on the innovative method, was designed and tested in pool and lake trials. The results demonstrate that the low-complexity system can satisfy the real-time requirement of 3-D underwater imaging applications with an acceptable imaging quality.

A Real-Time 3-D Underwater Acoustical Imaging System

Real-time 3-D acoustical imaging technique is a key advance to broaden the scope and enhance the feasibility of underwater missions. In this paper, a real-time 3-D underwater acoustical imaging system to handle the actual tasks under a narrowband excitation is presented. The system consists of three parts: a transmitter, a receiving hydrophone array, and a signal processor. In this system, a distributed and parallel subarray (DPS) beamforming algorithm is proposed to process the acquired signals from a scene placed in the far field. The DPS beamforming algorithm is an approximate method for the sonar signal processing with an advantageous computational efficiency. The direct method (DM) and fast Fourier transform (FFT) beamforming are compared with DPS beamforming for the memory and computational requirements. Based on this algorithm, a prototype was developed, which has been extensively employed in the lake and sea trials. The trials demonstrate that the system can achieve the 3-D imaging of the scene and meet the real-time requirement of the underwater operations.