Related papers: Accurate and Robust Indoor Localization Systems us…
A Magnetic field Aided Inertial Navigation System (MAINS) for indoor navigation is proposed in this paper. MAINS leverages an array of magnetometers to measure spatial variations in the magnetic field, which are then used to estimate the…
This work describes the implementation of a simple and computationally efficient Intelligent Navigation System (INS) for autonomous systems used in areas where human access is impossible. The system uses Laser Range Finder (LRF) readings as…
We examine the usability of deep neural networks for multiple-input multiple-output (MIMO) user positioning solely based on the orthogonal frequency division multiplex (OFDM) complex channel coefficients. In contrast to other indoor…
Absolute position accuracy is the key performance criterion of an Indoor Localization System (ILS). Since ILS are heterogeneous and complex cyber-physical systems, the localization accuracy depends on various influences from the…
Spatial wideband effects are known to affect channel estimation and localization performance in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Based on perturbation analysis, we show that the spatial…
Accurate localization and perception are pivotal for enhancing the safety and reliability of vehicles. However, current localization methods suffer from reduced accuracy when the line-of-sight (LOS) path is obstructed, or a combination of…
Localization in outdoor wireless systems typically requires transmitting specific reference signals to estimate distance (trilateration methods) or angle (triangulation methods). These cause overhead on communication, need a LoS link to…
Wireless indoor localization using predictive models with received signal strength information (RSSI) requires proper calibration for reliable position estimates. One remedy is to employ synthetic labels produced by a (generally different)…
Indoor localization in challenging non-line-of-sight (NLOS) environments often leads to poor accuracy with traditional approaches. Deep learning (DL) has been applied to tackle these challenges; however, many DL approaches overlook…
Locating a target is key in many applications, namely in high-stakes real-world scenarios, like detecting humans or obstacles in vehicular networks. In scenarios where precise statistics of the measurement noise are unavailable,…
Reliable positioning services are extremely important for users and devices in mountainous environments as it enables a variety of location-based applications. However, in such environments, the service reliability of conventional wireless…
Ultra-wideband (UWB) ranging has emerged as a key radio technology for robot positioning and relative localization in multi-robot systems. Multiple works are now advancing towards more scalable systems, but challenges still remain. This…
This paper investigates the robust wideband channel estimation problem in the millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In such a scenario, the beam squint effect that the array response vectors vary…
In this paper, we investigate a non-lineof-sight (NLOS) sensing problem at terahertz frequencies. To be able to observe the targets shadowed by a blockage, we propose a method using reconfigurable intelligent surfaces (RIS). We employ a…
Received Signal Strength (RSS) is considered as a promising measurement for indoor positioning. Lots of RSS-based localization methods have been proposed by its convenience and low cost. This paper focuses on two challenging issues in…
Ray tracing (RT) simulations require accurate transmitter (TX) and receiver (RX) location information from real-world measurements to accurately characterize wireless propagation behavior in an environment. Such wireless propagation…
Smartphones have become a popular tool for indoor localization and position estimation of users. Existing solutions mainly employ Wi-Fi, RFID, and magnetic sensing techniques to track movements in crowded venues. These are highly sensitive…
Long-term scene changes present challenges to localization systems using a pre-built map. This paper presents a LiDAR-based system that can provide robust localization against those challenges. Our method starts with activation of a mapping…
Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a…
The Global Navigation Satellite Systems (GNSS) like GPS suffer from accuracy degradation and are almost unavailable in indoor environments. Indoor positioning systems (IPS) based on WiFi signals have been gaining popularity. However, owing…