Array Signal Research Articles

Sound delivery to listening point using tangent line method.

In personal audio systems, sounds should propagate toward the listening point and attenuate beyond the listening point. This study deals with controlling directivity and distance attenuation using loudspeaker arrays. The array signal processing is based on tangent line method (TLM), which can generate acoustic beams following arbitrary convex trajectories. A curvilinear acoustic beam is produced as an envelope of tangent lines, i.e., straight acoustic beams. Specifying the envelope length enables controlling distance attenuation while enhancing directivity. In this study, the TLM for arbitrary circular trajectories is formulated. Optimization algorithm is applied to identify the trajectory maximizing acoustic contrast.

A depth discrimination method based on the scintillation of frequency domain

An innovative algorithm of target depth discrimination suitable for passive horizontal array in shallow sea is discussed in this paper. Based on the idea of modal scintillation theory, a new target depth discrimination method of high calculation speed for horizontal array is proposed by analysing the commonness between frequency domain energy of low-frequency broadband signals and modal excitation. This method avoids the mode decomposition of the horizontal array signals, greatly reduces the complexity, improves the stability, has a fast calculation speed and can perform the real-time depth judgment. In this paper, the principle of the algorithm is derived in detail in the theoretical aspect, and then the algorithm is simulated in the shallow sea environment to verify its effectiveness, and the influence of different influencing factors on the performance of the algorithm is explored. At the same time, the algorithm is verified by the actual experimental data and achieves good results, indicating that the algorithm has certain practical application value in the target depth discrimination domain.

Satellite Interference Source Direction of Arrival (DOA) Estimation Based on Frequency Domain Covariance Matrix Reconstruction.

Direction of arrival (DOA) estimation is an effective method for detecting various active interference signals during the satellite navigation process. It can be utilized for both interference detection and anti-interference applications. This paper proposes a DOA estimation algorithm for satellite interference sources based on frequency domain covariance matrix reconstruction (FDCMR) to address various types of active interference that may occur in the satellite navigation positioning process. This algorithm can estimate the DOA of coherent signals from multiple frequency points under low signal-to-noise ratio (SNR) conditions. The signals received from the array are transformed from the time domain to the frequency domain using a fast Fourier transform (FFT). The data corresponding to the frequency point of the target signal is extracted from the signal in the frequency domain. The frequency domain covariance matrix of the received array signals is reconstructed by utilizing its covariance matrix property. The spatial spectrum search method is used for the final DOA estimation. Simulation experiments have shown that the proposed algorithm performs well in the DOA estimation under low SNR conditions and also resolves coherency. Moreover, the algorithm's effectiveness is verified through comparison with three other algorithms. Finally, the algorithm's applicability is validated through simulations of various interference scenarios.

A novel adaptive beamforming scheme for array signal data processing

When the desired signal data exists in the array received data or the steering vector has a mismatch problem, the current traditional adaptive beamformers will suffer from the effect of the desired signal cancelation phenomenon, resulting in a sharp decline in performance. To address the occurrence of desired signal cancelation, an improved matrix projection-based efficient beamforming method is proposed. Firstly, based on spatial partitioning (SP) technology, a significant projection matrix for interference-plus-noise space (INS) is constructed. Secondly, using the constructed key projection matrix, the sample data covariance matrix is projected into the INS to achieve the goal of suppressing the desired signal data information. Finally, the weight data vector is calculated by Capon beamformer. The proposed algorithm does not require an iterative search for the optimal solution, which has the advantage of a small amount of calculation. Simulation experiments have verified that the proposed method has significant advantages in suppressing the desired data signals. Especially when the desired data signal has large power, the signal-to-interference-plus-noise ratio (SINR) of the proposed algorithm is better than that of the compared algorithms under the conditions of random directionality errors or local scattering errors between the desired signal and interference.

Polarization Direction of Arrival Estimation Using Dual Algorithms Based on Time-Frequency Cross Terms

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms’ SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms.

Complex sparse Bayesian learning for guided wave dispersion curve estimation in plate-like structures

This paper proposes a new dispersion curve estimation method that employs the complex sparse Bayesian learning (CSBL). It is well accepted that guided wave packets are distorted because of the differences in propagation velocities at different frequencies; thus, the preceding velocity–frequency curve estimation is beneficial for wave packet recovery, feature recognition and defect localization. Conventional dispersion curve estimation methods, such as two-dimensional Fourier transform and multiple signal classification, are suitable for array signal and are restricted by the transducer aperture, leading to a small application scope. According to the frequency–response model of the guided wave, for each frequency, the responses obtained by the transducers can be sparsely represented based on an overcomplete dictionary matrix constructed using multiple discretized wavenumbers and known distances. A CSBL algorithm was developed to infer the posterior probability density function of the weight vector in the sparse representation. The non-zero elements in the sparse weight vector mean that the corresponding dictionary atoms indicated wavenumbers are contained in the frequency response, and the velocity–frequency curve can be finally derived from the wavenumber–frequency curve. The proposed CSBL method has a satisfactory capability to solve this sparse representation of the complex frequency response because a hierarchical form of the Laplace prior is employed to achieve a high degree of sparsity of the weight vector. This method effectively incorporates the real and imaginary parts of the complex frequency response by employing the same hyperparameter to integrate the known information. This method requires only a few randomly placed transducers; thus, it has a wide range of applications. The effectiveness of the proposed approach was validated using multiple guided-wave signals obtained through numerical simulations and an experimental study on a plate structure.

Design of a Digital Array Signal Processing System with Full Array Element

For the application of a digital array signal processing system with a high sampling rate and large bandwidth, and considering the constraints of limited resources (performance, volume, power consumption, weight, etc.), this paper proposes a design and implementation method of broadband digital array signal processing system based on radio frequency system on a chip. The system focuses on multi-channel synchronization under a high sampling rate and multi-channel amplitude and phase calibration under large bandwidth to form an all-digital, low-power, multi-channel, high-speed, large bandwidth hardware platform suitable for broadband digital array signal processing. Through the implementation of the Multiple-Input Multiple-Output phased-array digital beamforming algorithm, the test conducted verifies that the system has superior signal processing performance of the broadband digital array.

Tensor-Based Joint Beamforming with Ultrasonic and RIS-Assisted Dual-Hop Hybrid FSO mmWave Massive MIMO of V2X

Reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) communication systems relying on hybrid beamforming structures are capable of achieving high spectral efficiency at a low hardware complexity and with low power consumption. Tensor-based joint beamforming with low-cost ultrasonic and RIS-assisted Dual-Hop Hybrid free space optical (FSO) mm Wave massive Multiple Input Multiple Output (MIMO) of vehicle-to-everything (V2X) is proposed. To address the occlusion problem for high-speed mobility of the vehicle, an RIS-assisted mixed FSO-MIMO V2X system is proposed. The low-cost ultrasonic array signal model is developed to solve the accurate direction-of-arrival (DOA) estimation. The ultrasonic-assisted RIS phase shift matrix based on subspace self-organizing iterations is designed to track the beam direction between RIS and vehicle. Specifically, the associated bandwidth-efficiency maximization problem is transformed into a series of subproblems, where the subarray of phase shifters and RIS elements is jointly optimized to maximize each subarray’s rate. The vehicle motion state is transformed into a two-dimensional model for prior distribution to calculate the particle weights of the RIS phase. Multi-vehicle Tucker tensor decomposition is used to describe the high-dimensional beam space. We conceive a multi-vehicle joint optimization method for designing the hybrid beamforming matrix of the base station (BS) and the passive beamforming matrix of the RIS. A cascaded channel decomposition method based on Singular Value Decomposition (SVD) is used to obtain the combined matrix beamforming of BS and vehicle. Our simulation results demonstrate the superiority of the proposed method compared to its traditional counterparts.

Tracking aftershock sequences using empirical matched field processing

SUMMARY Extensive aftershock sequences present a significant problem to seismological data centres attempting to produce near real-time comprehensive seismic event bulletins. An elevated number of events to process and poorer performance of automatic phase association algorithms can lead to large delays in processing and a greatly increased human workload. Global monitoring is often performed using seismic array stations at considerable distances from the events involved. Empirical matched field processing (EMFP) is a narrow-frequency band array signal processing technique that recognizes the inter-sensor phase and amplitude relations associated with wavefronts approaching a sensor array from a given direction. We demonstrate that EMFP, using a template obtained from the first P arrival from the main shock alone, can efficiently detect and identify P arrivals on that array from subsequent events in the aftershock zone with exceptionally few false alarms (signals from other sources). The empirical wavefield template encodes all the narrow-band phase and amplitude relations observed for the main shock signal. These relations are also often robust and repeatable characteristics of signals from nearby events. The EMFP detection statistic compares the phase and amplitude relations at a given time in the incoming data stream with those for the template and is sensitive to very short-duration signals with the required characteristics. Significant deviations from the plane wavefront model that typically degrade the performance of standard beamforming techniques can enhance signal characterization using EMFP. Waveform correlation techniques typically perform poorly for aftershocks from large earthquakes due to the distances between hypocentres and the wide range of event magnitudes and source mechanisms. EMFP on remote seismic arrays mitigates these difficulties; the narrow-band nature of the procedure makes arrival identification less sensitive to the signals’ temporal form and spectral content. The empirical steering vectors derived for the main shock P arrival can reduce the frequency dependency of the slowness vector estimates. This property helps us to automatically screen out arrivals from outside of the aftershock zone. Standard array processing pipelines could be enhanced by including both plane-wave and empirical matched field steering vectors. This would maintain present capability for the plane-wave steering vectors and provide increased sensitivity and resolution for those sources for which we have empirical calibrations.

Comparison of Sub-Scalp EEG and Endovascular Stent-Electrode Array for Visual Evoked Potential Brain-Computer Interface.

Brain-computer interfaces (BCI) have the potential to improve the quality of life for persons with paralysis. Sub-scalp EEG provides an alternative BCI signal acquisition method that compromises between the limitations of traditional EEG systems and the risks associated with intracranial electrodes, and has shown promise in long-term seizure monitoring. However, sub-scalp EEG has not yet been assessed for suitability in BCI applications. This study presents a preliminary comparison of visual evoked potentials (VEPs) recorded using sub-scalp and endovascular stent electrodes in a sheep. Sub-scalp electrodes recorded comparable VEP amplitude, signal-to-noise ratio and bandwidth to the stent electrodes.Clinical relevance-This is the first study to report a comparision between sub-scalp and stent electrode array signals. The use of sub-scalp EEG electrodes may aid in the long-term use of brain-computer interfaces.

Wideband Array Signal Processing with Real-Time Adaptive Interference Mitigation.

Wideband beamforming and interference cancellation for phased array antennas requires advances in signal processing algorithms, software, and specialized hardware platforms. A high-throughput array receiver has been developed that enables communication in radio frequency interference-rich environments with field programmable gate array (FPGA)-based frequency channelization and packetization. In this study, a real-time interference mitigation algorithm was implemented on graphics processing units (GPUs) contained in the data pipeline. The key contribution is a hardware and software pipeline for subchannelized wideband array signal processing with 150 MHz instantaneous bandwidth and interference cancellation with a heterogeneous, distributed, and scaleable digital signal processing (DSP) architecture that achieves 30 dB interferer cancellation null depth in real time with a moving interference source.

Low-Complexity Adaptive Beamforming Algorithm With High Dimensional and Small Samples

A large-scale array (LSA) inevitably encounter scenarios with a small number of samples, and its beamformer suffers from high computational complexity. High computational complexity prevents the system from being used in practical online engineering applications. The complex vector of the beamformer weights can be expressed as the product of training snapshots and the signal steering vector, and a coefficient vector, since the optimal weight vector is a linear combination of basis vectors of the signal-plus-interference subspace. In this study, a new adaptive beamformer is developed on the basis of the minimum variance distortionless response (MVDR) criterion and kernel techniques. The new beamformer only needs to compute the inversion of a low-dimensional Gram matrix instead of the high-dimensional sample covariance matrix, which significantly reduces the calculation cost. Moreover, an efficient loading parameter calculation method (only related to the received matrix and not required user-defined parameters) is derived, which can adaptively suppress the mismatches of the ill-conditioned Gram matrix. Furthermore, a fast version of the new beamformer is formulated for the LSA under the scanning mode. Simulation results demonstrate that the new beamformer achieves better performance and a lower computation load than existing algorithms for a small number of samples. Especially, insufficient samples and high computational complexity problems are more frequently aroused in the space-time broadband array signal processing. Interestingly, the new techniques can be successfully extended to wideband array signal processing and yield satisfactory beam pattern shapes.

Photovoltaic Class‐E Inverter for Resonance Wireless Power Transfer for Electric Vehicle Charging Applications with Optimization Algorithms

A wireless power transfer (WPT) station supplied by an array of solar panels is presented, where solar energy comes from an array of panels with 120 V voltage and 3 A current. It is subjected to maximum power point tracking algorithm optimization on a boost converter, where the duty cycle of the converter is adjusted with an interval chosen between [0.2, 0.8], which is used to iteratively compare between the input and output signals in order to have a maximum power at the output. After regulating the panel array signal through the boost converter, the signal is transferred to an additional middle stage whose role is to raise the frequency until it reaches the resonance frequency of the WPT charger. The device responsible for this task is an inverter based on a class‐E inverter architecture and a GaN transistor technology. The inverter is controlled by a DSP card in a hard‐switch mode and delivers the output signal with a frequency of 10 Mhz, which is the resonance frequency of spiral coils of wireless chargers. Herein, the signal nature can be seen at the terminal of a fixed load with signal optimization through the MPPT algorithm and the HF inverter control mode.

Post-Newtonian-accurate pulsar timing array signals induced by inspiralling eccentric binaries: accuracy, computational cost, and single-pulsar search

Pulsar Timing Array (PTA) experiments are expected to be sensitive to gravitational waves (GWs) emitted by individual supermassive black hole binaries (SMBHBs) inspiraling along eccentric orbits. We compare the computational cost of different methods of computing the PTA signals induced by relativistic eccentric SMBHBs, namely approximate analytic expressions, Fourier series expansion, post-circular expansion, and numerical integration. We show that the fastest method for evaluating PTA signals is by using the approximate analytic expressions, which provides up to ∼50 times improvement in computational speed over the alternative methods. We investigate the accuracy of the approximate analytic expressions by employing a mismatch metric valid for PTA signals. We show that this method is accurate within the region of the binary parameter space that is of interest to PTA experiments. We introduce a spline-based method to further accelerate the PTA signal evaluations for narrowband PTA datasets. The efficient methods for computing the eccentric SMBHB-induced PTA signals were implemented in the GWecc.jl package and can be readily accessed from the popular ENTERPRISE package to search for such signals in PTA datasets. Further, we simplify the eccentric SMBHB PTA signal expression for the case of a single-pulsar search and demonstrate our computationally efficient methods by performing a single-pulsar search in the 12.5 year NANOGrav narrowband dataset of PSR J1909–3744 using the simplified expression. These results will be crucial for searching for eccentric SMBHBs in large PTA datasets.

Coincidence time resolution measurements for dual-ended readout PET detectors

Coincidence time resolution (CTR) is an important performance parameter of clinical positron emission tomography (PET) detectors, which is dependent on the parameters of the scintillation crystal, the timing measurement methods, and the electronics. In this work, CTRs of PET detectors using dual-ended readout of segmented LYSO arrays were measured with different timing measurement methods. The detector modules were composed of LYSO arrays of 8 × 8 with a crystal size of 3.10 × 3.10 × 20 mm3 or 13 × 13 with a crystals size of 1.88 × 1.88 × 20 mm3, coupled at each end to an 8 × 8 Hamamatsu SiPM array (S13361-3050NE-08) with pixel active area of 3.00 × 3.00 mm2 and pitch of 3.20 mm. The signals of the SiPM arrays were individually read out and processed by using the TOFPET2 ASICs. The CTRs of the detectors were measured after the timing alignment of the ASICs was performed. Timing measurement methods of the dual-ended readout detector such as the average time of the two SiPMs, the faster time of the two SiPMs, the time of the back SiPM, and the time of the front SiPM were compared. The average time of the two SiPMs provides the best CTR, which is explained by a simple model about the timing measurement methods of a dual-ended readout detector. The detector with one-to-one crystal-to-SiPM coupling provides better CTR than the detector with a crystal size smaller than the pixel size of the SiPM. The best CTR of 367 ± 6 ps was obtained by using the 8 × 8 LYSO array with unpolished lateral crystal surfaces and ESR reflectors. The CTR of the dual-ended readout detector can be improved if a DOI-dependent timing correction is used.

Evaluation of the noise immunity of the navigation equipment of consumers of the global navigation satellite system with spatial adaptation based on the algorithm of maintaining the level of the useful signal

Problem statement. The use of spatial filtering of signals in adaptive antenna arrays (AAR) of consumer navigation equipment (NAP) of the global navigation satellite system (GNSS) in conditions of intentional interference is an effective means of ensuring stability and continuity of positioning of mobile objects. The specifics of solving this problem is the low level of navigation signals received from the upper hemisphere of space against the background of powerful concentrated interference, significantly exceeding noise. Most compact L-band AARs consist of 4-8 elements, and the algorithms used optimize compensation indicators without the presence of a priori information about the position of useful and interfering signals. At the same time, the formed dips on the sources of interference in width can lead to a loss of the availability of spacecraft signals for subsequent processing. This circumstance determines the relevance and practical orientation of the task of evaluating the effectiveness of the diagram formation algorithm, taking into account the integration of interference attenuation indicators and maintaining the level of the useful signal. Purpose. Investigation of the characteristics of the spatial interference compensation algorithm with a linear restriction on the direction of reception of the useful signal, as well as an assessment of its impact on the performance of the equipment of consumers of the global navigation satellite system. Results. The level of compensation of spatially distributed interference sources is analyzed using a processing algorithm that minimizes the average power of the adaptive antenna array with the exception of the direction of reception of the useful signal to the zenith. The influence of the spatial compensator on the availability of spacecraft signals for subsequent processing, depending on the number, level and angular coordinates of interference sources, is investigated. Practical significance. A model is proposed for evaluating an algorithm that maintains constant gain at the zenith and minima in the interference directions for a four-element L-band antenna array. The given values of interference attenuation depending on the number, level, angle of location and azimuth of the impact make it possible to clarify the indicators of noise immunity of the equipment of consumers of a global navigation satellite system equipped with a spatial compensator.

DOA Estimation With Co-Prime Array by a Combined BNC-PFLOM Method in Presence of Impulsive Noise

Direction of arrival (DOA) estimation with co-prime array is well studied in the field of array signal processing, but most research assumes noise to be Gaussian white noise. In practical scenarios, there might be impulsive noise, which has neither second-order statistics nor high-order cumulant, therefore cannot be processed directly in co-prime array configurations. In addition, the signals received by the co-prime virtual array are of single snapshot, which can be considered as coherent virtual signals coming from the same source and therefore performance degradation in DOA estimation. To solve the above mentioned problems, a combined bounded non-linear covariance (BNC) and phase fractional low-order moments (PFLOM), called BNCPFLOM, is proposed in this paper. The proposed BNC-PFLOM combines the merits of both BNC and PFLOM by constructing equivalent data covariance matrices of the received signal to lower the impact of impulsive noise. Moreover, the proposed BNC-PFLOM can build multiple pseudo snapshots of virtual signals from the co-prime array by using different orders of the proposed method. With the increase of pseudo snapshots, the proposed method is more robust in DOA estimation. Besides, the pseudo snapshots are developed from different methods, which implies different virtual signals coming from different sources. Therefore, the correlation between the virtual co-array signals can be reduced; and the proposed method direct estimates the DOAs of signals without spatial smoothing when the number of incoming signals is small. The proposed method generates multiple pseudo snapshots, which improves the resolution and accuracy in DOA estimation with co-prime array, and can be used for radar, sonar, communication systems, etc. Simulation results demonstrate the effectiveness of the proposed method, which outperforms the conventional BNC, FLOM, and PFLOM with smaller root means square error (RMSE) in terms of the generalized signal to noise ratio (GSNR) and factor of impulsive noise.

Identification of bolt state in lap joint based on propagation model and imaging methods of Lamb waves

Bolts are commonly applied to lap joints in various industrial fields. Harsh environment, low quality of operation, and other unfavorable conditions may result in bolt looseness. Due to the structural complexity, conventional Lamb wave-based methods just extract statistical characteristics for looseness detection, while neglecting the information contained in the propagation process of Lamb waves. To take full advantage of the information on bolt states carried by array signals during the propagation, this study proposes a detection procedure based on propagation model and imaging methods of Lamb waves. Firstly, the contact status on the macro and micro scales is investigated with theoretical analysis and finite element simulation, and the theoretical model of Lamb wave propagation across bolted joints is established deriving from the analysis of contact. Subsequently, three imaging methods, including delay-and-sum, minimum variance, and sparse reconstruction, are adapted for the identification of bolt state. Since Lamb waves are mainly transmitted into another plate through the contact area near the bolts based on the proposed propagation model, pixel values are inclined to be concentrated around the bolts. On this basis, imaging intensity near each individual bolt can reveal its fastening state given that the transmitted energy around its location is associated with its torque. Finally, experiments are carried out in both single-bolt and double-bolt joints. The proposed propagation model is verified in the single-bolt joint and loose bolts can be identified in the imaging results of the double-bolt joint, which demonstrates the effectiveness of the proposed method for bolt state identification.

An Improved Toeplitz Approximation Method for Coherent DOA Estimation in Impulsive Noise Environments.

Direction of arrival (DOA) estimation is an important research topic in array signal processing and widely applied in practical engineering. However, when signal sources are highly correlated or coherent, conventional subspace-based DOA estimation algorithms will perform poorly due to the rank deficiency in the received data covariance matrix. Moreover, conventional DOA estimation algorithms are usually developed under Gaussian-distributed background noise, which will deteriorate significantly in impulsive noise environments. In this paper, a novel method is presented to estimate the DOA of coherent signals in impulsive noise environments. A novel correntropy-based generalized covariance (CEGC) operator is defined and proof of boundedness is given to ensure the effectiveness of the proposed method in impulsive noise environments. Furthermore, an improved Toeplitz approximation method combined CEGC operator is proposed to estimate the DOA of coherent sources. Compared to other existing algorithms, the proposed method can avoid array aperture loss and perform more effectively, even in cases of intense impulsive noise and low snapshot numbers. Finally, comprehensive Monte-Carlo simulations are performed to verify the superiority of the proposed method under various impulsive noise conditions.

Implementation of Real-Time Space Target Detection and Tracking Algorithm for Space-Based Surveillance

Space-based target surveillance is important for aerospace safety. However, with the increasing complexity of the space environment, the stellar target and strong noise interference pose difficulties for space target detection. Simultaneously, it is hard to balance real-time processing with computational performance for the onboard processing platform owing to resource limitations. The heterogeneous multi-core architecture has corresponding processing capabilities, providing a hardware implementation platform with real-time and computational performance for space-based applications. This paper first developed a multi-stage joint detection and tracking model (MJDTM) for space targets in optical image sequences. This model combined an improved local contrast method and the Kalman filter to detect and track the potential targets and use differences in movement status to suppress the stellar targets. Then, a heterogeneous multi-core processing system based on a field-programmable gate array (FPGA) and digital signal processor (DSP) was established as the space-based image processing system. Finally, MJDTM was optimized and implemented on the above image processing system. The experiments conducted with simulated and actual image sequences examine the accuracy and efficiency of the MJDTM, which has a 95% detection probability while the false alarm rate is 10−4. According to the experimental results, the algorithm hardware implementation can detect targets in an image with 1024 × 1024 pixels in just 22.064 ms, which satisfies the real-time requirements of space-based surveillance.