Leonardo Sestrem
Papers
2
Total Citations
18
H-Index
2
About
Leonardo Sestrem is a researcher focused on advancing indoor localization technologies, with key contributions in combining multiple positioning techniques to improve accuracy and reliability in real-world environments. His work primarily addresses the challenges of tracking objects in indoor settings such as retail, logistics, and mobile robotics. Sestrem’s most cited paper, "Low-Cost Indoor Localization System Combining Multilateration and Kalman Filter" (2021), has garnered 14 citations and demonstrates a practical, cost-effective approach to enhancing position estimation by integrating multilateration with Kalman filtering. Building on this, his 2022 study "Hybrid Indoor Localization System Combining Multilateration and Fingerprinting" (4 citations) explores a hybrid indoor positioning system (H-IPS) using Bluetooth Low Energy (BLE) beacons, merging fingerprinting with multilateration to boost robustness in complex indoor environments. These contributions highlight Sestrem’s commitment to developing scalable, real-world solutions that bridge theoretical algorithms with practical deployment, making his work valuable for researchers and engineers seeking to improve indoor navigation and object tracking systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2