Related papers: Super-resolved Localisation without Identifying Lo…
The landmark multi-dimensional scaling (LMDS) is a leading method that embeds new points to an existing coordinate system based on observed distance information. It has long been known as a variant of Nystr\"{o}m algorithm. It was recently…
Location information will play a very important role in emerging wireless networks such as Intelligent Transportation Systems, 5G, and the Internet of Things. However, wrong location information can result in poor network outcomes. It is…
Wireless sensor networks require accurate target localization, often achieved through received signal strength (RSS) localization estimation based on maximum likelihood (ML). However, ML-based algorithms can suffer from issues such as low…
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach in wireless networks for obtaining position information of transmitters and receivers as well as information on the propagation environment. MP-SLAM…
The accuracy of traditional localization methods significantly degrades when the direct path between the wireless transmitter and the target is blocked or non-penetrable. This paper proposes N2LoS, a novel approach for precise…
Challenging indoor and urban environments with severe multipath propagation and obstructed LoS (OLoS) degrade classical radio frequency (RF) positioning. Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising remedy,…
Recent work has shown impressive localization performance using only images of ground textures taken with a downward facing monocular camera. This provides a reliable navigation method that is robust to feature sparse environments and…
Localization in Wireless Sensor Networks (WSNs) has been a challenging problem in the last decade. The most explored approaches for this purpose are based on multidimensional scaling (MDS) technique. The first algorithm that introduced MDS…
Distributed cooperative localization in wireless networks is a challenging problem since it typically requires solving a large-scale nonconvex and nonsmooth optimization problem. In this paper, we reformulate the classic cooperative…
We consider simultaneously identifying the membership and locations of point sources that are convolved with different low-pass point spread functions, from the observation of their superpositions. This problem arises in three-dimensional…
We propose a Bayesian method for distributed sequential localization of mobile networks composed of both cooperative agents and noncooperative objects. Our method provides a consistent combination of cooperative self-localization (CS) and…
Cooperative geolocation has attracted significant research interests in recent years. A large number of localization algorithms rely on the availability of statistical knowledge of measurement errors, which is often difficult to obtain in…
Addressing the communication and sensing demands of sixth-generation (6G) mobile communication system, integrated sensing and communication (ISAC) has garnered traction in academia and industry. With the sensing limitation of single base…
Localization in GPS-denied outdoor locations, such as street canyons in an urban or metropolitan environment, has many applications. Machine Learning (ML) is widely used to tackle this critical problem. One challenge lies in the mixture of…
When dedicated positioning systems, such as GPS, are unavailable, a mobile device has no choice but to fall back on its cellular network for localization. Due to random variations in the channel conditions to its surrounding base stations…
In this paper, we address the problem of Multiple Transmitter Localization (MTL). MTL is to determine the locations of potential multiple transmitters in a field, based on readings from a distributed set of sensors. In contrast to the…
In this paper, a novel method for sensor node localization under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions based on second order cone programming (SOCP) is presented. SOCP methods have, hitherto, not been utilized in the…
Only the chairs can edit This paper investigates the fundamental limits of target position estimation accuracy of joint sensing and communication (JSC) networks comprising several monostatic base stations (BSs) that cooperate to localize…
Global localization is a critical problem in autonomous navigation, enabling precise positioning without reliance on GPS. Modern global localization techniques often depend on dense LiDAR maps, which, while precise, require extensive…
Localization has been a challenging task for autonomous navigation. A loop detection algorithm must overcome environmental changes for the place recognition and re-localization of robots. Therefore, deep learning has been extensively…