- document
-
Romero, Daniel (author), Viet, Pham Q. (author), Leus, G.J.T. (author)Mobile base stations on board unmanned aerial vehicles (UAVs) promise to deliver connectivity to those areas where the terrestrial infrastructure is overloaded, damaged, or absent. A fundamental problem in this context involves determining a minimal set of locations in 3D space where such aerial base stations (ABSs) must be deployed to provide...conference paper 2022
- document
-
Ajorloo, Abdollah (author), Amini, Arash (author), Tohidi, Ehsan (author), Bastani, Mohammad Hassan (author), Leus, G.J.T. (author)Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in recent years. Unlike traditional MIMO radar, detection/estimation of targets in a CS-based MIMO radar is accomplished via sparse recovery. In this article, for a CS-based colocated MIMO radar with linear arrays, we attempt to improve the target...journal article 2020
- document
-
Tohidi, E. (author), Coutino, Mario (author), Chepuri, S.P. (author), Behroozi, Hamid (author), Nayebi, Mohammad Mahdi (author), Leus, G.J.T. (author)Multiple-input multiple-output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. Although higher angular resolution, improved parameter identifiability, and better target detection are achieved, the hardware costs (due to multiple transmitters and multiple receivers) and high-energy...journal article 2019
- document
-
Roy, V. (author), Simonetto, A. (author), Leus, G.J.T. (author)We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary as well as non-stationary component of the...journal article 2018
- document
-
Coutino, Mario (author), Chepuri, S.P. (author), Leus, G.J.T. (author)Detection of a signal under noise is a classical signal processing problem. When monitoring spatial phenomena under a fixed budget, i.e., either physical, economical or computational constraints, the selection of a subset of available sensors, referred to as sparse sensing, that meets both the budget and performance requirements is highly...journal article 2018