Search Results (70)

This paper presents a wideband pattern-reconfigurable antenna designed for 360° horizontal sensing with angle-of-arrival (AoA) estimation capability. The antenna features a unique three-layer planar architecture, where a microstrip circular array is integrated between two metallic plates to enhance radiation stability and bandwidth. By employing a single-pole four-throw (SP4T) switching circuit, the array generates four steerable beams covering the entire azimuthal plane. Experimental results show that the prototype achieves a 10 dB return loss impedance bandwidth of 50% (4.0–6.0 GHz) and a peak gain of 8.3 dBi. Based on this antenna, a correlation-coefficient-based AoA estimation approach is implemented. The measured results demonstrate reliable estimation performance, with a mean angular error of less than 1.5° over the 360° horizontal plane across the operating frequency range. The proposed design provides a compact and low-complexity solution for practical wideband direction-finding applications in next-generation wireless systems. Full article

Integrated optical phased array (OPA) chips enable high-speed beam steering via electronic phase control, providing a promising solution for compact pointing, acquisition, and tracking (PAT) systems. However, OPA-PAT systems must simultaneously achieve wide-field-of-view (FOV) coverage and high-precision angle-of-arrival (AOA) detection. To address this challenge, a cascaded AOA detection method based on a multi-sensor collaborative architecture is proposed. This approach utilizes a distributed detector array (DA) for coarse incident angle estimation over a wide-FOV, which then guides a two-dimensional (2D) galvanometer to steer the beam into a quadrant detector (QD) for fine measurement within a narrow-FOV. A prototype system is developed to validate the proposed cascaded algorithm. Experimental results show that within a ±20° FOV, the proposed system achieves root-mean-square errors (RMSEs) of 0.007° in azimuth and 0.01° in elevation. When integrated into an OPA-PAT terminal, static 2D closed-loop tracking is maintained with an overall tracking error better than 0.016° (RMSE). These results demonstrate that the proposed cascaded detection method can simultaneously provide wide-FOV coverage and high-precision AOA measurement, offering a practical solution for wide-FOV OPA-PAT systems. Full article

Waveguide-like propagation in elongated underground environments—utility corridors, logistics tunnels—generates dense multipath that can cause the earliest or strongest resolvable channel impulse response (CIR) component to originate from a specular reflection rather than the direct line-of-sight (LOS) path. In the single-anchor CIR-tap-based implementations common to practical ultra-wideband (UWB) systems, baseline estimators such as phase-difference-of-arrival (PDOA) and MUSIC rely on selecting a single dominant CIR component, producing large angle-of-arrival (AoA) errors whenever the selected path is a reflection. We propose a multipath credibility selection (MCS) AoA estimator, MCS-AoA, that does not require explicit LOS/NLOS classification. The algorithm scores each resolvable CIR component with four credibility factors—amplitude significance, time-of-flight (TOF) consistency, inter-baseline phase–geometry agreement, and cross-baseline coherence—and fuses retained candidates into a credibility-weighted spatial covariance matrix for 2D MUSIC search. Field experiments on a custom five-channel coherent UWB platform compare MCS-AoA against six baselines—PDOA, MUSIC, MVDR/Capon, TLS-ESPRIT, PwMUSIC, and DNN-AoA. In an underground corridor (5–40 m), MCS-AoA achieves an azimuth/elevation MAE of 1.00°/1.46°, outperforming all baselines (PDOA: 2.26°/2.49°; MUSIC: 1.76°/2.40°; next-best PwMUSIC: 1.44°/2.17°); in a logistics tunnel (5–80 m), it achieves a 1.19° overall azimuth MAE. Simulations corroborate these gains, with a 0.71° azimuth RMSE at 80 m (69.3% reduction over PDOA) and 86.6% of estimates falling within 1°. Full article

Microwave wireless power transfer (MWPT) for space solar power stations (SSPS) requires high-precision beam pointing in order to maintain effective aperture coupling and transmission efficiency under platform motion and disturbances. This paper proposes a dual-link beam pointing estimation framework that integrates guidance-link interferometric angle-of-arrival (AoA) measurements with power-link energy-field reconstruction. The interferometric chain provides high-rate azimuth and elevation observations for dynamic tracking, while the energy-field reconstruction estimates the energy-centroid displacement from the received-aperture power distribution to correct steady-state pointing bias. A Kalman filter (KF) is developed to fuse the asynchronous multi-rate measurements, yielding continuous and robust pointing estimates for closed-loop beam control. Simulation results show that the proposed fusion method achieves azimuth and elevation RMSEs of ${0.0069}^{°}$ and ${0.006}^{°}$ with interferometric and energy-centroid error levels of approximately ${0.05}^{°}$ and ${0.02}^{°}$, respectively, significantly reducing high-frequency fluctuations. In addition, a sensitivity model is established to quantify the impact of angular errors on capture efficiency. The expected efficiency improves from approximately 0.988 and 0.998 for the individual methods to nearly unity for the fusion output. Quantitative accuracy thresholds corresponding to different efficiency requirements are further derived, providing practical guidelines for SSPS MWPT system design. Full article

This paper investigates Direction-of-Arrival (DOA) estimation of Long-Range Navigation-C (Loran-C) signals using an Ultra-Short Baseline (USBL) receiving array. Two least-squares angle estimation approaches based on inter-element delay measurements are examined, including Correlation-based Least-Squares (Corr-LS) and a Zero-Crossing-based Least Squares (ZC-LS). In both methods, relative delays are extracted only within the local array and subsequently mapped to azimuth through a geometric least squares formulation; the approach is, therefore, distinct from distributed time difference-of-arrival (TDOA) localization. For comparison, the Multiple Signal Classification (MUSIC) algorithm is implemented as a covariance-based DOA estimator that operates without explicit delay extraction. Experiments were conducted using Loran-C transmissions from the Xuancheng, Xi’an, and Rongcheng stations, with 100 valid pulse groups collected for each station. Statistical analysis using boxplots shows that Corr-LS exhibits the largest variance due to broadened or shifted correlation peaks, particularly under skywave–groundwave interference. ZC-LS reduces both variance and bias by exploiting the deterministic zero-crossing structure of the Loran-C waveform. MUSIC produces the most concentrated azimuth estimates but requires a well-conditioned covariance matrix and substantially higher computational costs. The results demonstrate that ZC-LS achieves a favorable balance among angular accuracy, robustness, and real-time feasibility, making it suited for compact Loran-C receivers and complementary navigation applications in GNSS-challenged environments. Full article

Unmanned aerial vehicles (UAVs) have been extensively deployed across a range of applications thank to their flexibility and low cost. While this expansion has significantly improved their operational efficiency and service capacity, it has also posed challenges for UAV supervision and management systems. To address these issues, this paper proposes a three-dimensional (3D) localization method that integrates time difference of arrival (TDOA) and angle of arrival (AOA) measurements based on the extended Kalman filter (EKF). Specifically, for AOA-based positioning, a uniform circular array (UCA) is employed to capture spatial signal characteristics, and the multiple-signal classification (MUSIC) algorithm is applied to precisely estimate the azimuth and elevation angles of incoming signals. In TDOA-based localization, a multipath signal separation and identification algorithm is implemented to enhance robustness against multipath propagation in complex environments. Subsequently, the TDOA and AOA measurements are fused using the EKF, where nonlinear measurement models are linearized via Jacobian matrices to improve computational efficiency and estimation accuracy. Finally, simulation results demonstrate that the proposed hybrid localization method outperforms existing positioning methods that rely solely on AOA or TDOA, achieving a positioning accuracy of approximately 5 m and an angular error within $3°$, which is suitable for applications in multipath environments such as urban areas. Full article

This study focused on determining the conditions leading to variance in the measurements of an antenna array capable of measuring the direction of electromagnetic waves. The payload of the study is a cross-array of antennas that is able to measure direction through array beamforming and angle of arrival (AOA) technology. Starting from the modeling of satellite kinematics (in terms of the satellite’s position and attitude combined with its relative position with respect to an electromagnetic wave emitter located on Earth’s surface), this study provides the mathematical fundamentals to identify potential cases that lead to divergence in the estimation variance for the position of a signal emitter. The numerical and analytical predictions, conducted through an evaluation of the Cramér–Rao lower bound (CRLB) metrics, were on the azimuth, elevation, and broadside angles through the generation of errors in the attitude with Monte Carlo simulations. Recent advancements in the miniaturization of electronics make these studies of particular interest for a new set of technological demonstrators equipped with payloads composed of antenna arrays. Applications of interest include Earth-scanning missions, with exemplary cases of search-and-rescue operations or the spectrum monitoring of jamming in the E1/L1 band for the GNSS. Full article

Based on the Ffowcs Williams–Hawkings equations and the computational fluid dynamics method, the rotor’s aeroacoustic characteristics, considering the influence of the downwash flowfield on the sound propagation process, are calculated and analyzed. First, a set of analysis methods for the aeroacoustic characteristics is developed, and a convection-based propagation time model is developed, where acoustic group velocity along source–observer lines quantifies flowfield effects. Then, the rotor’s aerodynamic and aeroacoustic characteristics are calculated, and the employed numerical analysis method is validated through the comparisons with experimental data. Finally, the aeroacoustic characteristics of the rotor in hover are analyzed, and the sound pressure positive peak point with/without the influence of the flowfield of downwash on the propagation time is discussed in detail. In addition, parameters, such as the rotor’s collective pitch and the azimuthal angle of the sound source, are quantified, and some conclusions are obtained. For those observers below the rotor rotation plane, the downwash flowfield will influence the sound propagation time, resulting in the increase in the sound pressure and the advance of the arrival time. Full article

To address the computational efficiency challenges in two-dimensional (2D) direction-of-arrival (DOA) estimation, a two-stage framework integrating the Nyström approximation with subspace decomposition techniques is proposed in this paper. The methodology strategically integrates the Nyström approximation with subspace decomposition techniques to bridge the critical performance–complexity trade-off inherent in high-resolution parameter estimation scenarios. In the first stage, the Nyström method is applied to approximate the signal subspace while simultaneously enabling construction of a reduced rank covariance matrix, which effectively reduces the computational complexity compared with eigenvalue decomposition (EVD) or singular value decomposition (SVD). This innovative approach efficiently derives two distinct signal subspaces that closely approximate those obtained from the full-dimensional covariance matrix but at substantially reduced computational cost. The second stage employs a sophisticated subspace-based estimation technique that leverages the principal singular vectors associated with these approximated subspaces. This process incorporates an iterative refinement mechanism to accurately resolve the paired azimuth and elevation angles comprising the 2D DOA solution. With the use of the Nyström approximation and reduced rank framework, the entire DOA estimation process completely circumvents traditional EVD/SVD operations. This elimination constitutes the core mechanism enabling substantial computational savings without compromising estimation accuracy. Comprehensive numerical simulations rigorously demonstrate that the proposed framework maintains performance competitive with conventional high-complexity estimators while achieving significant complexity reduction. The evaluation benchmarks the method against multiple state-of-the-art DOA estimation techniques across diverse operational scenarios, confirming both its efficacy and robustness under varying signal conditions. Full article

Reconfigurable Intelligent Surfaces (RISs) are among the key technologies envisaged for sixth-generation (6G) multiple-input multiple-output (MIMO)–orthogonal frequency division multiplexing (OFDM) wireless systems. However, their passive nature and the frequent absence of a line-of-sight (LoS) path in dense urban environments make uplink channel estimation and localization challenging tasks. Therefore, to achieve channel estimation and localization, this study models the RIS-mobile station (MS) channel as a double-sparse angular structure and proposes a hybrid channel parameter estimation framework for RIS-assisted MIMO-OFDM systems. In the hybrid framework, Simultaneous Orthogonal Matching Pursuit (SOMP) first estimates coarse angular supports. The coarse estimates are refined by a novel refinement stage employing a Variational Bayesian Expectation Maximization (VBEM)-based Off-Grid Sparse Bayesian Learning (OG-SBL) algorithm, which jointly updates azimuth and elevation offsets via Newton-style iterations. An Angle of Arrival (AoA)–Angle of Departure (AoD) matching algorithm is introduced to associate angular components, followed by a 3D localization procedure based on non-LoS (NLoS) multipath geometry. Simulation results show that the proposed framework achieves high angular resolution; high localization accuracy, with 97% of the results within 0.01 m; and a channel estimation error of 0.0046% at 40 dB signal-to-noise ratio (SNR). Full article

Lightning Very-High-Frequency (VHF) radiation source mapping technology represents a pivotal advancement in the study of lightning discharge processes and their underlying physical mechanisms. This paper introduces a novel methodology for reconstructing lightning discharge channels by employing the Multiple Signal Classification (MUSIC) algorithm to estimate the Direction of Arrival (DOA) of lightning VHF radiation sources, specifically tailored for both non-uniform and uniform L-shaped arrays (2D-MUSIC). The proposed approach integrates the Random Sample Consensus (RANSAC) algorithm with 2D-MUSIC, thereby enhancing the precision and robustness of the reconstruction process. Initially, the array data are subjected to denoising via the Ensemble Empirical Mode Decomposition (EEMD) algorithm. Following this, the covariance matrix of the processed array data is decomposed to isolate the signal subspace, which corresponds to the signal components, and the noise subspace, which is orthogonal to the signal components. By exploiting the orthogonality between these subspaces, the method achieves an accurate estimation of the signal incidence direction, thereby facilitating the precise reconstruction of the lightning channel. To validate the feasibility of this method, comprehensive numerical simulations were conducted, revealing remarkable accuracy with elevation and azimuth angle errors both maintained below 1 degree. Furthermore, VHF non-uniform and uniform L-shaped lightning observation systems were established and deployed to analyze real lightning events occurring in 2021 and 2023. The empirical results demonstrate that the proposed method effectively reconstructs lightning channel structures across diverse L-shaped array configurations. This innovative approach significantly augments the capabilities of various broadband VHF arrays in radiation source imaging and makes a substantial contribution to the study of lightning development processes. The findings of this study underscore the potential of the proposed methodology to advance our understanding of lightning dynamics and enhance the accuracy of lightning channel reconstruction. Full article

High-precision two-dimensional direction of arrival (2D-DOA) estimation is an important mean of millimeter-wave radar for accurate target location. Aiming at the problems such as limited antenna aperture, signal coherence, and a few snapshots in millimeter-wave radar target detection, this paper proposes a 2D-DOA estimation method by using a joint iterative adaptive approach and rotational invariance technique (IAA-RIT) based on the double-parallel linear array. This method first constructs an iterative adaptive approach spectrum based on subarray 1 in the double-parallel linear array and then calculates the coupling angle estimate with the azimuth and the elevation. Secondly, based on the rotational invariance relationship between the two subarrays, the extended covariance matrices are respectively constructed, and the spatial smoothing technique is employed to decorrelate the signals. Then, the signal direction matrix is reconstructed based on the coupling angle estimate, and the rotational invariance relationship between the two subarrays is calculated to obtain another set of coupling angle estimates. Finally, the azimuth and the elevation are decoupled based on two sets of estimated coupling angles and the spatial geometry relation. Our experimental results show that IAA-RIT can estimate the coherent signal with high-precision 2D-DOA with a few snapshots and no additional angle matching. Full article

The synthetic aperture passive positioning (SAPP) method has attracted the attention of researchers due to its high positioning resolution. However, there are still key technical issues regarding SAPP methods, such as residual frequency offset (RFO) coupling at Doppler frequency leading to decreased positioning accuracy, and non-periodic discontinuous signals emitted by unknown radiation sources (NRSs) causing positioning algorithm failure. Therefore, this paper proposes an ultra-short baseline SAPP method based on interferometer assistance. Firstly, conjugate multiplication is applied to the received signals of the interferometer’s dual antennas to obtain a single frequency received signal corresponding to the straight-line distance. Subsequently, the proposed step search (SS) algorithm based on cross-correlation analysis is used to obtain the receiving frequency of the single frequency signal, and the initial positioning distance is calculated using the corresponding mapping relationship based on this frequency. Finally, NRS positioning is completed in the two-dimensional coordinates of azimuth and range by combining with the signal arrival angle. The positioning results of this method are insensitive to RFO, and even if NRS emits non-periodic discontinuous signals, the proposed method can successfully locate them. In addition, the Cramer–Rao lower bound (CRLB) of the localization for this method is derived. The simulation and unmanned aerial vehicle (UAV) experimental results demonstrate the effectiveness and feasibility of this method. Full article

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

Floating high-frequency surface-wave radar provides an effective solution to widening the range of detection by such radar systems. However, for high-frequency radars with long coherence integration times, the yaw angle variations during this period can have a significant impact on the accuracy of direction-of-arrival estimation. Although adaptive beamforming methods are applicable to yaw angle compensation, their effectiveness can be significantly reduced when the measured distortion of antenna patterns is considered. To solve this problem, an iterative adaptive beamforming of focusing concept is proposed in this paper to compensate for yaw rotation. Firstly, an adaptive beamforming technique, called balanced-focusing pseudo-fixed beamforming, is developed to improve the ability of beam shape control by shortening the constraint range of the azimuth. Then, the shortened focusing range is determined by one iterative strategy that iteratively reduces the focusing length and selects the focusing center. The simulation results demonstrate that the proposed algorithm is applicable to significantly improve the precision and stability of direction-of-arrival estimation. This algorithm is also validated against the results obtained from two cooperative signals and ship echoes in a field experiment. Full article