Related papers: Background Subtraction with Drift Correction for B…
Large Low Earth Orbit (LEO) constellations (e.g., Starlink and Iridium) significantly increase the likelihood of transient, high-power interference events at ground receivers. This report presents SatTrack, a GUI-driven simulation framework…
Simultaneous Localization and Mapping (SLAM) allows mobile robots to navigate without external positioning systems or pre-existing maps. Radar is emerging as a valuable sensing tool, especially in vision-obstructed environments, as it is…
Dynamic Range Compression (DRC) is a widely used audio effect that adjusts signal dynamics for applications in music production, broadcasting, and speech processing. Inverting DRC is of broad importance for restoring the original dynamics,…
Mobility scenarios involving short contact times pose a challenge for high bandwidth data transfer between autonomous vehicles and roadside base stations (BS). Millimeter wave bands are a viable solution as they offer enormous bandwidth in…
A large network employing integrated sensing and communication (ISAC) where a single transmit signal by the base station (BS) serves both the radar and communication modes is studied. We consider bistatic detection at a passive radar and…
The deep image prior showed that a randomly initialized network with a suitable architecture can be trained to solve inverse imaging problems by simply optimizing it's parameters to reconstruct a single degraded image. However, it suffers…
This paper illustrates the potential of an Integrated Sensing and Communication (ISAC) system, operating in the sub-6 GHz frequency range, for Synthetic Aperture Radar (SAR) imaging via an Unmanned Aerial Vehicle (UAV) employed as an aerial…
The robust estimation of the mounting angle for millimeter-wave automotive radars installed on moving vehicles is investigated. We propose a novel signal processing pipeline that combines radar and inertial measurement unit (IMU) data to…
Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for domain expertise. Expanding datasets with additional sources is a common response to limited…
This research focuses on a coherently driven four-level atomic medium with the aim of inducing a negative index of refraction while taking into consideration local field corrections as well as magnetoelectric cross coupling, i.e. chirality,…
Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most radar SLAM pipelines still rely heavily on frame-to-frame odometry, which leads to…
Due to the robustness in sensing, radar has been highlighted, overcoming harsh weather conditions such as fog and heavy snow. In this paper, we present a novel radar-only place recognition that measures the similarity score by utilizing…
Intelligent reflecting surface (IRS) has emerged as a revolutionizing solution to enhance wireless communications by intelligently changing the propagation environment. Prior studies on IRS are based on an ideal reflection model with a…
In this paper, we propose a novel scheme for sixdimensional (6D) radar sensing and tracking of dynamic target based on multiple input and multiple output (MIMO) array for monostatic integrated sensing and communications (ISAC) system.…
In the envisioned beyond-fifth-generation (B5G) and sixth-generation (6G) scenarios which expect massive multiple-input multiple-output (mMIMO) and high frequency communications in the millimeter-wave (mmWave) and Terahertz (THz) bands,…
Indoor radar perception has seen rising interest due to affordable costs driven by emerging automotive imaging radar developments and the benefits of reduced privacy concerns and reliability under hazardous conditions (e.g., fire and…
Proton radiography has proved increasingly successful as a diagnostic for electric and magnetic fields in high energy density physics experiments. Most experiments use target-normal-sheath-acceleration sources with a wide energy range in…
This paper presents the first machine learning based real-world demonstration for radar-aided beam prediction in a practical vehicular communication scenario. Leveraging radar sensory data at the communication terminals provides important…
Detection of moving objects in videos is a crucial step towards successful surveillance and monitoring applications. A key component for such tasks is called background subtraction and tries to extract regions of interest from the image…
In realistic radar tracking, target measurement uncertainty (TMU) in terms of both detection probability and measurement error covariance is significantly affected by the target-to-radar (T2R) geometry. However, existing posterior…