Related papers: TDOA-based localization with NLOS mitigation via r…
In sparse information recovery, the core problem is to solve the $l_0$-minimization which is NP-hard. On one hand, in order to recover the original sparse solution, there are a lot of papers designing alternative model for…
In the past few decades, the localization literature has seen many models attempting to characterize the non-line-of-sight (NLOS) bias error commonly experienced in range measurements. These models have either been based on specific…
Localizing near-field sources considering practical arrays is important in wireless communications. Array-based apertures exhibit mutual coupling between the array elements, which can significantly degrade the performance of the…
The research presented in this paper is aimed at developing a control algorithm for an autonomous surface system carrying a two-sensor array consisting of two acoustic receivers, capable of measuring the time-difference-of-arrival (TDOA) of…
The vivid success of the emerging wireless sensor technology (WSN) gave rise to the notion of localization in the communications field. Indeed, the interest in localization grew further with the proliferation of the wireless sensor network…
The localization problem in a wireless sensor network is to determine the coordination of sensor nodes using the known positions of some nodes (called anchors) and corresponding noisy distance measurements. There is a variety of different…
Classical methods for acoustic scene mapping require the estimation of time difference of arrival (TDOA) between microphones. Unfortunately, TDOA estimation is very sensitive to reverberation and additive noise. We introduce an unsupervised…
Multi-objective evolutionary algorithms (MOEAs) have become essential tools for solving multi-objective optimization problems (MOPs), making their running time analysis crucial for assessing algorithmic efficiency and guiding practical…
It is an essential technique for the moving user nodes (UNs) with clock offset and clock skew to resolve the joint localization and synchronization (JLAS) problem. Existing iterative maximum likelihood methods using sequential one-way…
The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems. However, low-cost systems often suffer from imperfect factors, such as…
A robust and accurate positioning solution is required to increase the safety in GPS-denied environments. Although there is a lot of available research in this area, little has been done for confined environments such as tunnels. Therefore,…
Out-of-Distribution (OOD) generalization in machine learning is a burgeoning area of study. Its primary goal is to enhance the adaptability and resilience of machine learning models when faced with new, unseen, and potentially adversarial…
This paper presents a non-cooperative source localization approach based on received signal strength (RSS) and 2D environment map, considering both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. Conventional localization…
A recent trend of research on direction-of-arrival (DOA) estimation is to localize more uncorrelated sources than sensors by using a proper sparse linear array (SLA) and the Toeplitz covariance structure, at a cost of robustness to source…
In this paper, a fast algorithm for the Direction Of Arrival (DOA) estimation of radiating sources, based on partial covariance matrix and without eigende- composition of incoming signals is extended to two dimensional problem of joint…
The paper describes an NLOS (Non-Line-of-Sight) mitigation method intended for use in a UWB positioning system. In the proposed method propagation conditions between the localized objects and the anchors forming system infrastructure are…
Node-specific hardware biases represent significant error source in wireless Time of Arrival (ToA) and Time Difference of Arrival (TDoA) positioning. While bias estimation and treatment are well-established in Global Navigation Satellite…
Imbalanced regression occurs when continuous target variables have skewed distributions, creating sparse regions that are difficult for machine learning models to predict accurately. This issue particularly affects neural networks, which…
We present a novel sound localization algorithm for a non-line-of-sight (NLOS) sound source in indoor environments. Our approach exploits the diffraction properties of sound waves as they bend around a barrier or an obstacle in the scene.…
We study time difference of arrival (TDoA)-based algorithms for drone controller localization and analyze TDoA estimation in multipath channels. Building on TDoA estimation, we propose two algorithms to enhance localization accuracy in…