Performance Evaluation and Hybrid Application of the Greedy and Predictive UAV Trajectory Optimization Methods for Localizing a Target Mobile Device
arXiv:2302.11740 · doi:10.33012/2023.18666
Abstract
This study investigates unmanned aerial vehicle (UAV) trajectory planning strategies for localizing a target mobile device in emergency situations. The global navigation satellite system (GNSS)-based accurate position information of a target mobile device in an emergency may not be always available to first responders. For example, 1) GNSS positioning accuracy may be degraded in harsh signal environments and 2) in countries where emergency positioning service is not mandatory, some mobile devices may not report their locations. Under the cases mentioned above, one way to find the target mobile device is to use UAVs. Dispatched UAVs may search the target directly on the emergency site by measuring the strength of the signal (e.g., LTE wireless communication signal) from the target mobile device. To accurately localize the target mobile device in the shortest time possible, UAVs should fly in the most efficient way possible. The two popular trajectory optimization strategies of UAVs are greedy and predictive approaches. However, the research on localization performances of the two approaches has been evaluated only under favorable settings (i.e., under good UAV geometries and small received signal strength (RSS) errors); more realistic scenarios still remain unexplored. In this study, we compare the localization performance of the greedy and predictive approaches under realistic RSS errors (i.e., up to 6 dB according to the ITU-R channel model).
Submitted to ION ITM 2023
References in corpus (12)
- Optimal Parameter Inflation to Enhance the Availability of Single-Frequency GBAS for Intelligent Air Transportation
- Enhanced Accuracy Simulator for a Future Korean Nationwide eLoran System
- Urban Road Safety Prediction: A Satellite Navigation Perspective
- RSS-based LTE Base Station Localization Using Single Receiver in Environment with Unknown Path-Loss Exponent
- Effect of Outlier Removal from Temporal ASF Corrections on Multichain Loran Positioning Accuracy
- SFOL DME Pulse Shaping Through Digital Predistortion for High-Accuracy DME
- Practical Simplified Indoor Multiwall Path-Loss Model
- Neural Network-Based Ranging with LTE Channel Impulse Response for Localization in Indoor Environments
- Evaluation of RF Fingerprinting-Aided RSS-Based Target Localization for Emergency Response
- Motion Planning by Reinforcement Learning for an Unmanned Aerial Vehicle in Virtual Open Space with Static Obstacles
- Development of Record and Management Software for GPS/Loran Measurements
- GPS Multipath Detection Based on Carrier-to-Noise-Density Ratio Measurements from a Dual-Polarized Antenna