Results 71 to 80 of about 2,027 (176)

Direction-of-Arrival Estimation in Coprime Array Using the ESPRIT-Based Method

Sensors, 2019
Coprime arrays have shown potential advantages for direction-of-arrival (DOA) estimation by increasing the number of degrees-of-freedom in the difference coarray domain with fewer physical sensors.
Zhen Meng, Weidong Zhou
doaj   +1 more source

A Review of Sparse Sensor Arrays for Two-Dimensional Direction-of-Arrival Estimation

IEEE Access, 2021
Two-dimensional (2D) arrays are fundamental to localization applications. Specifically, sparse arrays can provide superior direction-of-arrival (DoA) estimation performance with limited number of sensors. There has been increased interest in the research
Ibrahim Aboumahmoud, Ali Muqaibel, Mohammad Alhassoun, Saleh Alawsh   +3 more
doaj   +1 more source

Virtual array interpolation for coprime arrays: a signal reconstruction perspective

Electronics Letters, 2020
Coprime arrays can highly increase degree‐of‐freedom by operating the second‐order virtual signal. However, the corresponding virtual array is discontiguous, and thus most existing direction‐of‐arrival estimation approaches fail to utilise all received information.
Zhen Chen, Chongyi Fan, Xiaotao Huang
openaire   +1 more source

Research on Three‐Dimensional Autonomous Obstacle Avoidance Path Planning Methods for UAVs

Transactions on Emerging Telecommunications Technologies, Volume 37, Issue 2, February 2026.
This study presents a three‐dimensional autonomous obstacle‐avoidance path planning method for unmanned aerial vehicles (UAVs) based on a deep reinforcement learning (DRL)‐enhanced Mayfly Algorithm. The traditional Mayfly Algorithm suffers from issues such as random initial population generation and slow convergence.
Chong Wu, Hao Cheng, Hua Wang
wiley   +1 more source

A Hole-free Shifted Coprime Array for DOA Estimation

Journal of Telecommunications and Information Technology
Coprime arrays have recently become a popular trend in estimating the direction of arrival in array signal processing, as they increase the degree of freedom (DOF).
Fatimah Abdulnabi Salman, Bayan Mahdi Sabbar   +1 more
doaj   +1 more source

Derangements in intransitive groups

Journal of the London Mathematical Society, Volume 113, Issue 2, February 2026.
Abstract Let G$G$ be a nontrivial permutation group of degree n$n$. If G$G$ is transitive, then a theorem of Jordan states that G$G$ has a derangement. Equivalently, a finite group is never the union of conjugates of a proper subgroup. If G$G$ is intransitive, then G$G$ may fail to have a derangement, and this can happen even if G$G$ has only two ...
David Ellis, Scott Harper
wiley   +1 more source

Near-Field Localization With Coprime Array

Proceedings of the 30th Annual International Conference on Mobile Computing and Networking
Large-aperture coprime arrays (CAs) are expected to achieve higher sensing resolution than conventional dense arrays (DAs), yet with lower hardware and energy cost. However, existing CA far-field localization methods cannot be directly applied to near-field scenarios due to channel model mismatch.
Hongqiang Cheng, Changsheng You, Cong Zhou   +2 more
openaire   +2 more sources

An asymptotic local–global theorem on heights of some Kleinian group orbits

Journal of the London Mathematical Society, Volume 113, Issue 2, February 2026.
Abstract We prove an asymptotic local–global theorem on the heights of point orbits of thin subgroups of Bianchi groups in H3$\mathbb {H}^3$.
Xuanxuan Xiao, Xin Zhang
wiley   +1 more source

Random Lie bracket on sl2(Fp)

Random Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT We study a random walk on the Lie algebra sl2(Fp)$$ {\mathfrak{sl}}_2\left({\mathbf{F}}_p\right) $$ where new elements are produced by randomly applying adjoint operators of two generators. Focusing on the generic case where the generators are selected at random, we analyze the limiting distribution of the random walk and the speed at which it
Urban Jezernik, Matevž Miščič
wiley   +1 more source

Reinforcement Learning for Robust Modulation Classification in Non‐Orthogonal Multiple Access (NOMA) Systems

IET Communications, Volume 20, Issue 1, January/December 2026.
This paper proposes a reinforcement learning–based framework for robust modulation classification and resource management in non‐orthogonal multiple access (NOMA) systems. By integrating Q‐learning, deep reinforcement learning, and proximal policy optimisation, the approach enhances spectral efficiency, mitigates interference, and improves ...
Mohammed M. Alammar, Abdulrahman Al Ayidh, Muneer Parayangat, Mohamed Abd Elhamid Abbas   +3 more
wiley   +1 more source