Advanced Array Antenna Design and Signal Processing Techniques

Topic Information

Dear Colleagues,

Array antennas and signal processing techniques are of critical importance in modern electronic systems, such as wireless communication system, vehicular system, unmanned aerial system, radar, etc. Firstly, as the front end of an electronic system, an antenna with wide bandwidth, high gain, and compact size is always required to guarantee the high level of system performance. Moreover, a limited and complex electromagnetic environment reserved for an antenna location creates higher requirements for antenna performance. Secondly, signal processing techniques are essential to enhance the desired signal and mitigate nuisance signals, thus improving the system performance. The performance of electronic systems can be further improved by properly utilizing signal processing techniques. The increasing development of radar and communication systems further promotes new technologies in antenna design and array signal processing. A great number of research groups are working on such active and frontier topics. With the in-depth investigations of array antenna, several novel array antenna frameworks are born, including the frequency diverse array, waveform diverse array, massive multiple-input multiple-output array, opportunistic array, and so on. To further promote the innovative development of basic theories and key technologies of antennas and array signal processing techniques, this Special Issue aims to gather the latest advanced research progress in the field of antenna design and array signal processing techniques for various applications, especially for remote sensing. The types of collected papers include academic papers and review articles on the latest technological achievements.

Potential topics include but are not limited to the following:

• Integrated communication and sensing;
• Array signal processing for remote sensing;
• Antenna and array antenna design;
• Wideband/conformal/compact antennas;
• AI-aided antenna design/array antenna synthesis;
• Antenna miniaturization techniques;
• Adaptive digital beamforming;
• Waveform optimization and waveform diversity;
• Target localization and tracking.

Dr. Yanhong Xu
Prof. Dr. Kwai Man Luk
Prof. Dr. Jingwei Xu
Prof. Dr. Warren Paul du Plessis
Dr. Abdul Basit
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400	Submit
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400	Submit
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700	Submit
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600	Submit
Signals signals	-	3.2	2020	28.3 Days	CHF 1000	Submit

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Published Papers (9 papers)

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21 pages, 4334 KiB  

Open AccessArticle

Robust DOA Estimation via a Deep Learning Framework with Joint Spatial–Temporal Information Fusion

by Yonghong Zhao, Xiumei Fan and Jisong Liu

Sensors 2025, 25(10), 3142; https://doi.org/10.3390/s25103142 - 15 May 2025

Viewed by 110

Abstract

In this paper, we propose a robust deep learning (DL)-based method for Direction-of-Arrival (DOA) estimation. Specifically, we develop a novel CRDCNN-LSTM network architecture, which integrates a Cross-Residual Depthwise Convolutional Neural Network (CRDCNN) with a Long Short-Term Memory (LSTM) module for effective capture of [...] Read more.

In this paper, we propose a robust deep learning (DL)-based method for Direction-of-Arrival (DOA) estimation. Specifically, we develop a novel CRDCNN-LSTM network architecture, which integrates a Cross-Residual Depthwise Convolutional Neural Network (CRDCNN) with a Long Short-Term Memory (LSTM) module for effective capture of both spatial and temporal features. The CRDCNN employs multi-level cross-residual connections and depthwise separable convolutions to enhance feature diversity while mitigating issues such as gradient vanishing and overfitting. Furthermore, a customized FD loss function, combining Focal Loss and Dice Loss, is introduced to emphasize low-confidence samples and promote sparsity in the spatial spectrum, thereby improving the precision and overall effectiveness of DOA estimation. A post-processing strategy based on peak detection and quadratic interpolation is also employed to refine DOA estimations and reduce quantization errors. Simulation results demonstrate that the proposed approach achieves significantly higher estimation accuracy and resolution than conventional methods and current DL models under varying SNR and snapshot conditions. In addition, it offers distinct advantages in terms of generalization and computational efficiency. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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23 pages, 4264 KiB  

Open AccessArticle

Efficient 2D-DOA Estimation Based on Triple Attention Mechanism for L-Shaped Array

by Yonghong Zhao, Xiumei Fan, Jisong Liu, Yuxing Li, Lyulong Yao and Junlong Wang

Sensors 2025, 25(8), 2359; https://doi.org/10.3390/s25082359 - 8 Apr 2025

Cited by 1 | Viewed by 329

Abstract

Accurate direction-of-arrival (DOA) estimation is crucial to a variety of applications, including wireless communications, radar systems, and sensor arrays. In this work, we propose a novel deep convolutional neural network (DCN) called TADCN for 2D-DOA estimation using an L-shaped array. The network achieves [...] Read more.

Accurate direction-of-arrival (DOA) estimation is crucial to a variety of applications, including wireless communications, radar systems, and sensor arrays. In this work, we propose a novel deep convolutional neural network (DCN) called TADCN for 2D-DOA estimation using an L-shaped array. The network achieves high estimation performance through a triple attention mechanism (TAM). Specifically, the new architecture enables the network to capture the relationships across the channel, height, and width dimensions of the signal sample features, thereby enhancing the feature extraction capability and improving the resulting spatial spectrum. To this end, the spatial spectrum is processed by the proposed spectrum analyzer to yield high-precision DOA estimation results. An automatic angle matching method based on TADCN is employed for estimating the pairing between the estimated azimuth and elevation DOA sets. Furthermore, the overall efficiency is enhanced through the parallel processing of the angle estimation and matching networks. Simulation results demonstrate that the proposed algorithm outperforms traditional methods and deep learning-based approaches for various noise levels and snapshots while maintaining better estimation performance even in the presence of correlated signal sources. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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28 pages, 1189 KiB  

Open AccessArticle

Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System

by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu and Kaiquan Cai

Remote Sens. 2025, 17(7), 1208; https://doi.org/10.3390/rs17071208 - 28 Mar 2025

Viewed by 226

Abstract

The novel framework of an integrated aeronautical communication and radar system (IACRS) to realize spectrum sharing is investigated. A non-orthogonal multiple access (NOMA)-motivated multi-input–multi-output (MIMO) scheme is proposed for the dual-function system, which is able to detect multiple aircraft while simultaneously transmitting dedicated [...] Read more.

The novel framework of an integrated aeronautical communication and radar system (IACRS) to realize spectrum sharing is investigated. A non-orthogonal multiple access (NOMA)-motivated multi-input–multi-output (MIMO) scheme is proposed for the dual-function system, which is able to detect multiple aircraft while simultaneously transmitting dedicated messages. Specifically, NOMA-inspired technology is utilized to enable dual-spectrum sharing. The superposition of communication and radar signals is facilitated in the power domain. Successive interference cancellation (SIC) is employed at the receiver to effectively mitigate inter-function interference. Subsequently, the regularity of the three-dimensional flight track and attitude is exploited to model the air-to-ground (A2G) MIMO channel. Based on this framework, a joint optimization problem is formulated to maximize the weighted achievable sum rate and the sensing signal–clutter–noise ratio (SCNR) while satisfying the rate requirements for message transmission and ensuring the radar detection threshold. An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. The original problem is decoupled into two manageable subproblems: transmit beamforming of the ground base station combined with power allocation and receiver beamforming at the aircraft. The penalty-based approach and the successive rank-one constraint relaxation (SROCR) method are developed for iteratively handling the non-convex rank-one constraints in subproblems. Numerical simulations demonstrate that the proposed IACRS framework significantly outperforms benchmark schemes. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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23 pages, 12254 KiB  

Open AccessArticle

Adaptively Iterative FFT-Based Phase-Only Synthesis for Multiple Elliptical Beam Patterns with Low Sidelobes

by Yuxuan Ding, Yunhua Zhang and Xiaowen Zhao

Electronics 2025, 14(7), 1310; https://doi.org/10.3390/electronics14071310 - 26 Mar 2025

Viewed by 184

Abstract

In this paper, an adaptive iterative Fourier technique (AIFT) algorithm is developed for the synthesis of multiple circular/elliptical beams with low sidelobe levels (SLLs) through phase-only optimization. The key innovation of the AIFT algorithm is the introduction of an elliptical beam model, which [...] Read more.

In this paper, an adaptive iterative Fourier technique (AIFT) algorithm is developed for the synthesis of multiple circular/elliptical beams with low sidelobe levels (SLLs) through phase-only optimization. The key innovation of the AIFT algorithm is the introduction of an elliptical beam model, which facilitates the adaptive determination of main beam regions and offers additional flexibility in controlling pencil beam shapes. Unlike conventional IFT-based algorithms, the AIFT algorithm eliminates the need for prior knowledge of main beam regions and avoids repetitive adjustments of sidelobe correction thresholds. This not only simplifies the configuration process but also prevents the generation of defective radiation patterns. Extensive synthesis experiments with different beam numbers, distributions, and ellipticities demonstrate that the elliptical beam model consistently outperforms its circular counterpart in multibeam scenarios, achieving lower SLL and higher directivity. These advantages are particularly pronounced in asymmetrical beam distributions, highlighting the elliptical beam’s superior potential for reducing SLLs of multi-spot-beam patterns and offering new insights for advancing the performance of point-to-multi-point communication systems. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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19 pages, 1413 KiB  

Open AccessArticle

Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm

by Yunhe Shi, Xiaofei Zhang and Shengxinlai Han

Sensors 2025, 25(5), 1456; https://doi.org/10.3390/s25051456 - 27 Feb 2025

Viewed by 469

Abstract

This paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Complementary Coprime Planar Array (CCPA) that strategically fills key holes in [...] Read more.

This paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Complementary Coprime Planar Array (CCPA) that strategically fills key holes in the virtual array. This design enhances the array’s continuous Degrees Of Freedom (DOFs) and virtual aperture, achieving improved performance in 2D-DOA estimation with fewer physical elements. The virtualization of the array further increases the available DOFs, while the hole-filling strategy ensures better spatial coverage and continuity. On the algorithmic side, we introduce a dimensionality-reduction root MUSIC algorithm tailored for uniform planar arrays after virtualization. By decomposing the two-dimensional spectral peak search into two one-dimensional polynomial root-finding problems, the proposed method significantly reduces computational complexity while maintaining high estimation accuracy. This approach effectively mitigates the challenges of 2D peak search, making it computationally efficient without sacrificing precision. Extensive simulations demonstrate the advantages of the proposed array and algorithm, including higher DOFs, reduced complexity, and superior estimation performance compared to existing methods. These results validate the effectiveness of the proposed framework in advancing sparse array design and signal processing for 2D-DOA estimation. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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24 pages, 1668 KiB  

Open AccessArticle

Robust Sidelobe Control for Adaptive Beamformers Against Array Imperfections via Subspace Approximation-Based Optimization

by Yang Zou, Zhoupeng Ding, Hongtao Li, Shengyao Chen, Sirui Tian and Jin He

Remote Sens. 2025, 17(4), 697; https://doi.org/10.3390/rs17040697 - 18 Feb 2025

Viewed by 338

Abstract

Conventional adaptive beamformers usually suffer from serious performance degradation when the receive array is imperfect and unknown sporadic interferences appear. To enhance robustness against array imperfections and simultaneously suppress sporadic interferences, this paper studies robust adaptive beamforming (RAB) with accurate sidelobe level (SLL) [...] Read more.

Conventional adaptive beamformers usually suffer from serious performance degradation when the receive array is imperfect and unknown sporadic interferences appear. To enhance robustness against array imperfections and simultaneously suppress sporadic interferences, this paper studies robust adaptive beamforming (RAB) with accurate sidelobe level (SLL) control, where the imperfect array steering vector (SV) is expressed as a spherical uncertainty set. Under the maximum signal-to-interference-plus-noise ratio (SINR) criterion and robust SLL constraints, we formulate the resultant RAB into a second-order cone programming problem, which is computationally prohibitive due to numerous robust quadratic SLL constraints. To tackle this issue, we provide a subspace approximation-based method to approximate the whole sidelobe space, thus replacing all robust SLL constraints with a single subspace constraint. Moreover, we leverage the Gauss–Legendre quadrature-based scheme to generate the sidelobe space in a computationally efficient manner. Additionally, we give an explicit approach for determining the norm upper bound of SV uncertainty sets under various imperfection scenarios, addressing the challenge of obtaining this upper bound in practice.Simulation results showed that the proposed subspace approximation-based RAB beamformer had a better SINR performance than typical counterparts and was much more computationally efficient. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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12 pages, 5498 KiB  

Open AccessArticle

Passive and Battery-Free UWB Sensor with Multiple Digital Bits Based on Spectral–Temporal Joint Coding

by Rong Li, Jian Liu and Xiaojun Huang

Electronics 2025, 14(4), 671; https://doi.org/10.3390/electronics14040671 - 9 Feb 2025

Viewed by 548

Abstract

In this paper, a passive wireless sensor is designed and developed specifically for a wireless sensing system required by multi-bit applications. The proposed sensor is abided by the formula of UWB spectrum ranging from 3.1 GHz to 10.6 GHz band, and the capability [...] Read more.

In this paper, a passive wireless sensor is designed and developed specifically for a wireless sensing system required by multi-bit applications. The proposed sensor is abided by the formula of UWB spectrum ranging from 3.1 GHz to 10.6 GHz band, and the capability of carrying multiple digital bits can be realized by the combination of multiple sensor units that are operated in the principle of Spectral–Temporal Joint Coding and Modulation. A prototype of such a sensor is configured by four such kinds of UWB sensor units, each of which is functionalized by modulating UWB pulse in the time domain and simultaneously modulating UWB spectrum in the frequency domain, forming the spectral–temporal joint modulation coded by 1/0 bits with enhanced deliverables of data capacity up to eight bits. Simulation and measurement have verified the performance of this sensor, validating its effectiveness in the delivery of multiple data information under dangerous and hazardous sensing scenarios where remote, contactless, and battery-free sensors are utterly required. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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16 pages, 951 KiB  

Open AccessTechnical Note

Angle and Range Unambiguous Estimation with Nested Frequency Diverse Array MIMO Radars

by Zhengxi Wang, Ximin Li, Shengqi Zhu, Fa Wei and Congfeng Liu

Remote Sens. 2025, 17(3), 446; https://doi.org/10.3390/rs17030446 - 28 Jan 2025

Cited by 1 | Viewed by 579

Abstract

This paper proposes an unambiguous method for joint angle and range estimation in colocated multiple-input multiple-output (MIMO) radar using the nested frequency diverse array (NFDA). Unlike a conventional phased array (PA), the transmission beampattern of FDA-MIMO radar depends not only on angle but [...] Read more.

This paper proposes an unambiguous method for joint angle and range estimation in colocated multiple-input multiple-output (MIMO) radar using the nested frequency diverse array (NFDA). Unlike a conventional phased array (PA), the transmission beampattern of FDA-MIMO radar depends not only on angle but also on range, which enables the precise identification of ambiguous regions in the two-dimensional frequency space. As a result, we can simultaneously estimate the angle and range of targets using FDA-MIMO radar, even when range ambiguity exists. By employing a nested array configuration, the degrees of freedom (DOFs) of the FDA are expanded. This expansion leads to improved accuracy in parameter estimation and enables a greater number of identifiable targets. In addition, the Cramér–Rao lower bound (CRLB) and the algorithm complexity are obtained to facilitate performance analysis. The simulation outcomes are presented to showcase the superior performance of the suggested approach. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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22 pages, 8285 KiB  

Open AccessArticle

Hole-Free Symmetric Complementary Sparse Array Design for High-Precision DOA Estimation

by He Ma, Libao Liu, Zhihong Gan, Yang Gao and Xingpeng Mao

Remote Sens. 2024, 16(24), 4711; https://doi.org/10.3390/rs16244711 - 17 Dec 2024

Viewed by 656

Abstract

Direction of arrival (DOA) estimation plays a critical role in remote sensing, where it aids in identifying and tracking multiple targets across complex environments, from atmospheric monitoring to resource mapping. Leveraging difference covariance array (DCA) for DOA estimation has become prevalent, particularly with [...] Read more.

Direction of arrival (DOA) estimation plays a critical role in remote sensing, where it aids in identifying and tracking multiple targets across complex environments, from atmospheric monitoring to resource mapping. Leveraging difference covariance array (DCA) for DOA estimation has become prevalent, particularly with sparse arrays capable of resolving more targets than the number of sensors. This paper proposes a new hole-free sparse array configuration for remote sensing applications to achieve improved DOA estimation performance using DCA. By symmetrically placing a minimum redundancy array (MRA) and its complementary MRA on both sides of a sparse uniform linear array (ULA), this configuration maximizes degrees of freedom (DOFs) and minimizes mutual coupling effects. Expressions for calculating sensor positions and optimal element allocation methods to maximize DOFs are derived. Simulation experiments in various scenarios have shown the advantages of the proposed array in DOA estimation, including a strong ability to estimate multi-targets, high angular resolution, low estimation error, and strong robustness to mutual coupling. Full article

(This article belongs to the Topic Advanced Array Antenna Design and Signal Processing Techniques)

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