To improve the robustness and computational efficiency of underwater direction-of-arrival (DOA) estimation in complex marine noise environments, this study proposes an improved sparse Bayesian off-grid DOA estimation method under mixed noise. Within...
In practical array signal processing applications, direction-of-arrival (DOA) estimation often suffers from degraded accuracy under low signal-to-noise ratio (SNR) and limited snapshot conditions. To address these challenges, we propose an off-grid D...
A common challenge in traditional three-dimensional grid-free localization is the struggle to balance computational efficiency with localization accuracy. To address this trade-off, a Bayesian grid-free framework with global optimization (BGG) for th...
In the application of Compressive Sensing (CS) theory for sidelobe suppression in Random Frequency and Pulse Repetition Interval Agile (RFPA) radar, the off−grid issues affect the performance of target parameter estimation in RFPA radar. Theref...
Recently, deep unfolding networks have been widely used in direction of arrival (DOA) estimation because of their improved estimation accuracy and reduced computational cost. However, few have considered the existence of a nested array (NA) with off-...
Off-grid direction-of-arrival (DOA) estimation based on sparse Bayesian learning (SBL) can alleviate angular discretization mismatch, but its practical performance may be affected by unreliable posterior relevance statistics, sensitivity of effective...
Comparisons of Bayesian log-odds and Dempster’s combination rule for occupancy grid mapping typically parameterize the two sensor models independently, so that observed performance differences confound the fusion rule with the sensor parameteri...
For the traditional uniform linear array (ULA) direction of arrival (DOA) estimation method with a limited array aperture, a non-circular signal off-grid sparse Bayesian DOA estimation method based on nested arrays is proposed. Firstly, the extended...
Direction-of-arrival (DOA) estimation is a fundamental task in array signal processing and is widely used in radar, sonar, wireless communications, and acoustic localization. Although classical methods such as MUSIC and ESPRIT can achieve high resolu...
Space-time adaptive processing (STAP) algorithms based on sparse recovery (SR) have been researched because of their low requirement of training snapshots. However, once some portion of clutter is not located on the grids, i.e., off-grid problems, th...
In recent years, the development of compressed sensing (CS) and array signal processing provides us with a broader perspective of 3D imaging. The CS-based imaging algorithms have a better performance than traditional methods. In addition, the sparse...
Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to re...
With the rapid development of the Internet of Things (IoT), autonomous vehicles have been receiving more and more attention because they own many advantages compared with traditional vehicles. A robust and accurate vehicle localization system is crit...
Sound source identification technology based on a microphone array has many application scenarios. The compressive beamforming method has attracted much attention due to its high accuracy and high-resolution performance. However, for the far-field me...
The substation grounding grid, as the primary path for fault current dissipation, is crucial for ensuring the safe operation of the power system and requires regular inspection. The pulsed eddy current method, known for its non-destructive and effici...
Background: Unlike most cancers, breast cancer poses a persistent risk of distant recurrence—often years after initial treatment—making long-term risk stratification uniquely challenging. Current tools fall short in predicting late metast...
Power grid technical renovation projects are implemented through project-based supply chains involving equipment procurement, logistics coordination and on-site construction under market, delivery and carbon constraints. Their final cost is jointly a...
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 natur...
Broadband direction-of-arrival (DOA) estimation using a single acoustic vector sensor (AVS) is an important problem in passive underwater source localization and underwater acoustic signal processing, especially for compact underwater platforms and p...
Modern power transmission grids are increasingly operated under volatile load, variable generation, and near-limit line-flow conditions. In such environments, deterministic line-flow forecasting is insufficient for operational decision support becaus...
A new short-term probabilistic forecasting method is proposed to predict the probability density function of the hourly active power generated by a photovoltaic system. Firstly, the probability density function of the hourly clearness index is foreca...
The propeller tip vortex cavitation (TVC) localization problem involves the separation of noise sources in proximity. This work describes a sparse localization method for off-grid cavitations to estimates their precise locations while keeping reasona...
Direction of arrival (DOA) estimation is an essential and fundamental part of array signal processing, which has been widely used in radio monitoring, autonomous driving of vehicles, intelligent navigation, etc. However, it remains a challenge to acc...
As an important research focus in radar detection and localization, direction-of-arrival (DOA) estimation has advanced significantly owing to deep learning techniques with powerful fitting and classifying abilities in recent years. However, deep lear...
Indoor positioning systems for smartphones are often based on Pedestrian Dead Reckoning, which computes the current position from the previously estimated location. Noisy sensor measurements, inaccurate step length estimations, faulty direction detec...
When the transmitter is in motion, the airborne passive bistatic radar (PBR) has a complex clutter geometry and lacks independent and identically distributed training samples in clutter estimation and suppression. In order to solve these problems, th...
Off-grid algorithms for direction of arrival (DOA) estimation have become attractive because of their advantages in resolution and efficiency over conventional ones. In this paper, we propose a grid reconfiguration direction of arrival (GRDOA) estima...
Genomic prediction is revolutionizing plant breeding since candidate genotypes can be selected without the need to measure their trait in the field. When a reference population contains both phenotypic and genotypic information, it is trained by a st...
While genomic selection (GS) began revolutionizing plant breeding when it was proposed around 20 years ago, its practical implementation is still challenging as many factors affect its accuracy. One such factor is the choice of the statistical machin...
Wi-Fi round-trip time (RTT) ranging has proven successful in indoor localization. Here, it is shown to be useful outdoors as well—and more accurate than smartphone code-based GNSS when used near buildings with Wi-Fi access points (APs). A Bayes...
This study explores the application of a Long Short-Term Memory (LSTM) model for river water level forecasting, emphasizing the critical role of hyper-parameters optimization. Similar to physical and numerical rainfall-runoff models, LSTM relies on p...
“Not In My Back Yard” (NIMBY) conflicts have emerged as a significant challenge in the siting and construction of power grid projects. Traditional risk management methods are often inadequate for addressing the complex interactions betwee...
Online identification of grid-side wideband impedance is of great significance for stability assessment and the formulation of coordinated suppression strategies. Bayesian estimation mitigates the influence of background harmonics on grid-side wideba...
The IEEE 802.11mc WiFi standard provides a protocol for a cellphone to measure its distance from WiFi access points (APs). The position of the cellphone can then be estimated from the reported distances using known positions of the APs. There are sev...
In passive sonars, distance and depth estimation of underwater targets is often limited by the accuracy of time delay estimations. The estimation accuracy of the existing methods of time delay estimation is limited by the uniform discrete grid (signa...
This paper presents a power smoothing strategy for wave energy converters (WECs) by means of energy storage systems (ESS) with integrated forecasting filtering algorithms applied to their control. The oscillatory nature of wave energy leads to high v...
Distributed multiple-input multiple-output (MIMO) is a promising architecture for future wireless systems because cooperation among geographically separated base stations (BSs) improves coverage, spectral efficiency, and link reliability. However, th...
As a result of the deepening of China’s power system reform, the market-oriented business development of power grid enterprises is in full swing. However, most of the existing research has focused on the regulatory risks of the regulatory busin...
This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian fi...
Terrain-aided navigation (TAN) enables autonomous positioning through fusing prior terrain databases with real-time sensor measurements in GNSS-denied environments. Typical factors, including wide beam width and terrain elevation variations, introduc...
To enhance frequency and active power control performance, this research proposes a decentralized robust optimal tuning approach for power grid frequency regulation support using energy storage systems (ESSs) as the primary source of grid-forming (GF...
The reliability of petroleum offshore platform systems affects human safety and well-being; hence, it should be considered in plant design and operation in order to determine its effect on human fatality risk. Methane Vapour Cloud Explosions (VCE) in...
To face the impact of climate change in all dimensions of our society in the near future, the European Union (EU) has established an ambitious target. Until 2050, the share of renewable power shall increase up to 75% of all power injected into nowada...
Off-grid issues and high computational complexity are two major challenges faced by sparse Bayesian learning (SBL)-based compressive sensing (CS) algorithms used for random frequency pulse interval agile (RFPA) radar. Therefore, this paper proposes a...
Socio-economic development is undergoing changes in China, such as the recently proposed carbon peak and carbon neutral targets, new infrastructure development strategy and the Coronavirus disease 2019 (COVID-19) pandemic. Meanwhile, the new-round ma...
Intermittency in the grid creates operational issues for power system operators (PSO). One such intermittent parameter is load. Accurate prediction of the load is the key to proper planning of the power system. This paper uses regression analyses for...
With the fast expansion of intermittent renewable energy sources in the upcoming smart grids, simple and accurate day-ahead systems for residual load forecasts are urgently needed. Machine learning strategies can facilitate towards drastic cost minim...
Second-hand housing transactions constitute a significant segment of the real estate market and are vital for its robust development. The dynamics of these transactions mirror the housing preferences of buyers, and their spatial and temporal analysis...
Due to their distinctive presence in everyday life and the variety of available built-in sensors, smartphones have become the focus of recent indoor localization research. Hence, this paper describes a novel smartphone-based sensor fusion algorithm....
The accurate forecasting of wind power has become a crucial task in renewable energy due to its inherent variability and uncertainty. This study addresses the challenge of predicting wind power generation without meteorological data by utilizing mach...
of 7