With the development of machine learning technology, research cases for spatial estimation through machine learning approach (MLA) in addition to the traditional geostatistical techniques are increasing. MLA has the advantage that spatial estimation...
This paper proposes a semiparametric spatial lag model and develops a Bayesian estimation method for this model. In the estimation of the model, the paper combines Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm, random walk Metropolis sa...
To estimate the pose of satellites in space, the docking ring component has strong rigid body characteristics and can provide a fixed circular feature, which is an important object. However, due to the need for additional constraints to estimate a si...
Multiscale estimation for geographically weighted regression (GWR) and the related models has attracted much attention due to their superiority. This kind of estimation method will not only improve the accuracy of the coefficient estimators but also...
14 February 2026
This paper proposes a Bayesian estimation method for spatial lagged panel quantile models. The proposed model simultaneously considers spatial lag effects of the dependent variable and the quantile regression framework, enabling effective capture of...
In spatial econometrics, we usually assume that the spatial dependence structure is known and that all information about it is contained in a spatial weights matrix
As urban built-up areas are the main generators of carbon emissions, scientific and accurate estimation of carbon emission levels in urban built-up areas is an important method to help implement the carbon neutrality target. Nowadays, developing a sp...
Accurate estimation of transportation flow is a challenging task in Intelligent Transportation Systems (ITS). Transporting data with dynamic spatial-temporal dependencies elevates transportation flow forecasting to a significant issue for operational...
Online multi-microphone speech enhancement aims to extract target speech from multiple noisy inputs by exploiting the spatial information as well as the spectro-temporal characteristics with low latency. Acoustic parameters such as the acoustic trans...
The accuracy of relative pose estimation is an important foundation for ensuring the safety and stability of autonomous aerial refueling (AAR) of unmanned aerial vehicles (UAV), and in response to this problem, a relative pose estimation method of UA...
In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD)...
Spatial Modulation Technologies (SMTs) are schemes that reduce inter-carrier interference (ICI), inter-channel interference, inter-antenna synchronization (IAS), and system complexity for multiple-input multiple-output (MIMO) communication systems. M...
The received signal of passive radar based on mobile communication signals contains direct and multipath interference (DMI) signals from multiple co-channel base stations (CCBS). The direct signal spatial spectrum of each CCBS should be obtained firs...
Liquid crystal phase retarders are utilized by photonic devices and imaging systems for various applications, such as tunable filtering, light modulation, polarimetric imaging, remote sensing and quality inspection. Due to technical difficulties in t...
Three-dimensional human pose estimation focuses on generating 3D pose sequences from 2D videos. It has enormous potential in the fields of human–robot interaction, remote sensing, virtual reality, and computer vision. Existing excellent methods...
To improve the data utilization of the sensor array and direction-of-arrival-(DOA)-estimation performance for coherent signals, a DOA-estimation method with a modified spatial-smoothing technique is proposed. The covariance matrix of the received dat...
In this paper, the spatial dynamic panel data (SDPD) model is extended to the single-index spatial dynamic panel data (Si-SDPD) model by introducing a nonlinear connection function to reflect the interaction between explanatory variables. The Si-SDPD...
This study addresses the problem of parameter estimation in spatial autoregressive models with missing data and measurement errors in covariates. Specifically, a corrected likelihood estimation approach is employed to rectify the bias in the log-maxi...
How to enhance the desired signal with low signal-to-noise ratio (SNR) is a difficult problem in the estimation process of the direction-of-arrival (DOA) of the target scattering wave signal. In this paper, the feasibility of spatial spectrum estimat...
This paper investigates the direction of arrival (DOA) estimation of coherent signals with a moving coprime array (MCA). Spatial smoothing techniques are often used to deal with the covariance matrix of coherent signals, but they cannot be used in sp...
This study aims to investigate the impact of the spatial size of the study domain on the performance of the triangle method using progressively smaller domains and Moderate Resolution Imaging Spectroradiometer (MODIS) observations in the Heihe River...
Infrared imaging is widely applied in the discrimination of spatial targets. Extracting distinguishable features from the infrared signature of spatial targets is an important premise for this task. When a target in outer space experiences micro-moti...
1 January 2023
The development of urban agglomerations dominated by the service industry is an important driving force for further sustainable economic growth of China. Spatial analysis marked by population density and regional integration is an essential perspecti...
Spatial regression models are widely available across several disciplines, such as functional magnetic resonance imaging analysis, econometrics, and house price analysis. In nature, sparsity occurs when a limited number of factors strongly impact ove...
We present a scheme aimed at estimating daily spatial snow water equivalent (SWE) maps in real time and at high spatial resolution from scarce in-situ SWE measurements from Internet of Things (IoT) devices at actual sensor locations and historical SW...
Accurately estimating the state of charge of a lithium-ion battery plays an important role in managing the health of a battery and estimating its charging state. Traditional state-of-charge estimation methods encounter difficulties in processing the...
It is difficult for lightweight neural networks to produce accurate 6DoF pose estimation effects due to their accuracy being affected by scale changes. To solve this problem, we propose a method with good performance and robustness based on previous...
Vehicle pose estimation is essential in autonomous vehicle (AV) perception technology. However, due to the different density distributions of the point cloud, it is challenging to achieve sensitive direction extraction based on 3D LiDAR by using the...
The rapid development of remote sensing technology provides wealthy data for earth observation. Land-cover mapping indirectly achieves biodiversity estimation at a coarse scale. Therefore, accurate land-cover mapping is the precondition of biodiversi...
In the field of tunnel engineering, the precise determination of the spatial coordinates of karst water-rich pipelines represents a critical area of research for disaster prevention and control. Traditional detection methods often exhibit limitations...
This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subar...
Direction-of-arrival (DoA) estimation methods are highly versatile and find extensive applications in satellite communication. DoA methods are employed across a range of orbits, from low Earth orbits (LEO) to geostationary Earth orbits (GEO). They se...
Accurate snow water equivalent (SWE) products are vital for monitoring hydrological processes and managing water resources effectively. However, the coarse spatial resolution (typically at 25 km from passive microwave remote sensing images) of the ex...
The high-precision estimation of multi-dimensional parameters for spatial targets based on high-resolution range profiles is crucial for target recognition. However, existing estimation methods face difficulties in resolving the strong coupling betwe...
Rapid advancement of wireless communication systems and the increasing need for accurate, real-time signal processing have driven innovations in direction-of-arrival (DoA) estimation techniques. This paper introduces a novel convolutional neural netw...
Transformer-based 2D-to-3D lifting methods have demonstrated outstanding performance in 3D human pose estimation from 2D pose sequences. However, they still encounter challenges with the relatively poor quality of 2D joints and substantial computatio...
In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with...
Spectral unmixing poses a significant challenge within hyperspectral image processing, traditionally addressed by supervised convolutional neural network (CNN)-based approaches employing patch-to-pixel (pixel-wise) methods. However, such pixel-wise m...
The point detections obtained from radars or sonars in surveillance environments include clutter measurements, as well as target measurements. Target tracking with these data requires data association, which distinguishes the detections from targets...
Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observ...
Estimating disaster relief supplies is crucial for governments coordinating and executing disaster relief operations. Rapid and accurate estimation of disaster relief supplies can assist the government to optimize the allocation of resources and bett...
Nighttime light (NTL) data are increasingly used in urban studies and urban planning owing to their strong connection with human activities, although the detection capacity is limited by the spatial resolution of older data. In the present study, we...
This paper proposes a stereo-vision-based method that detects and registers the positions and postures of muti-type, randomly placed miniature circuit breaker (MCB) components within scene point clouds acquired by a 3D stereo camera. The method is de...
Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimat...
In this study, we analyzed the impact of model spatial resolution on streamflow predictions, focusing on high-resolution scenarios (<1 km) and flooding conditions at catchment scale. Simulation experiments were implemented for the Geumho River cat...
The limited surface area and structural constraints of small underwater communication devices necessitate a dense placement of transmitting and receiving array elements in optical multiple-input multiple-output (MIMO) systems. The compact layout lead...
In this paper, we address a class of heterogeneous spatial autoregressive models with all
Information theoretic estimators for the first-order spatial autoregressive model are introduced, small sample properties are investigated, and the estimator is applied empirically. Monte Carlo experiments are used to compare finite sample performanc...
In this paper, a novel two-dimensional direction of arrival (2D-DOA) estimation method with total variation regularization is proposed to deal with the problem of sparse DOA estimation for spatially extended sources. In a general sparse framework, th...
The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unifie...
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