Related papers: Bistatic scattering forward model validation using…
Achieving real-time Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian splatting (3DGS) in large-scale real-world environments remains challenging, as existing methods still struggle to jointly achieve low-latency pose…
4D millimeter-wave (mmWave) radars are sensors that provide robustness against adverse weather conditions (rain, snow, fog, etc.), and as such they are increasingly used for odometry and SLAM (Simultaneous Location and Mapping). However,…
Climate change is intensifying rainfall extremes, making high-resolution precipitation projections crucial for society to better prepare for impacts such as flooding. However, current Global Climate Models (GCMs) operate at spatial…
At millimeter-wave frequencies, diffuse scattering from rough surfaces is an important propagation mechanism. Including this mechanism in radio propagation modeling tools,such as ray-tracing, is a key step towards realizing accurate…
Motivated by the goal of achieving long-term drift-free camera pose estimation in complex scenarios, we propose a global positioning framework fusing visual, inertial and Global Navigation Satellite System (GNSS) measurements in multiple…
Cross-correlation of consecutive Doppler images is one of the most common techniques used to detect surface differential rotation (hereafter DR) on spotted stars. The disadvantage of a single cross-correlation is, however, that the expected…
We report results from the Eddy Experiment, where a synchronous GPS receiver pair was flown on an aircraft to collect sampled L1 signals and their reflections from the sea surface to investigate the altimetric accuracy of GNSS-R. During the…
As one of the key technologies for the sixth generation (6G) mobile communications, intelligent reflecting surface IRS) has the advantages of low power consumption, low cost, and simple design methods. But channel modeling is still an open…
We study a multiple measurement vector (MMV) approach to synthetic aperture radar (SAR) imaging of scenes with direction dependent reflectivity and with polarization diverse measurements. The data are gathered by a moving transmit- receive…
Study Region: Goslar and G\"ottingen, Lower Saxony, Germany. Study Focus: In July 2017, the cities of Goslar and G\"ottingen experienced severe flood events characterized by short warning time of only 20 minutes, resulting in extensive…
We develop a flexible spline-based Bayesian hidden Markov model stochastic weather generator to statistically model daily precipitation over time by season at individual locations. The model naturally accounts for missing data (considered…
We address the feasibility of a GNSS-R code-altimetry space mission and more specifically a dominant term of its error budget: the reflected-signal range precision. This is the RMS error on the reflected-signal delay, as estimated by…
This paper considers an integrated sensing and communication system, where some radar targets also serve as communication scatterers. A location domain channel modeling method is proposed based on the position of targets and scatterers in…
The presented approach aims at estimating the lateral variation of seismic velocities for a seismic timelapse survey. The monitor survey is depth migrated with the known velocity model of the base survey. An analysis is performed to…
The compound Gaussian (CG) family of distributions has achieved great success in modeling sea clutter. This work develops a flexible-tailed CG model to improve generality in clutter modeling, by introducing the positive tempered…
We propose a metric called the bistatic radar detection coverage probability to evaluate the detection performance of a bistatic radar under discrete clutter conditions. Such conditions are commonly encountered in indoor and outdoor…
Geometric environment information aids future distributed radio infrastructures in providing services, such as ultra-reliable communication, positioning, and wireless power transfer (WPT). An a priori known environment model cannot always…
We consider in this work an inverse acoustic scattering problem when only phaseless data is available. The inverse problem is highly nonlinear and ill-posed due to the lack of the phase information. Solving inverse scattering problems with…
This paper introduces warped Gaussian processes (WGP) regression in remote sensing applications. WGP models output observations as a parametric nonlinear transformation of a GP. The parameters of such prior model are then learned via…
Inverse medium scattering is an ill-posed, nonlinear wave-based imaging problem arising in medical imaging, remote sensing, and non-destructive testing. Machine learning (ML) methods offer increased inference speed and flexibility in…