GPS-based Tracking over WSNs with Delayed and Missing Data using UFIR Filtering

• Main Authors: Uribe-Murcia Karen, Shmaliy Yuriy S., Andrade-Lucio Amparo
• Format: Article
• Language: English
• Published: EDP Sciences 2018-01-01
• Series: MATEC Web of Conferences
• Online Access: https://doi.org/10.1051/matecconf/201821005002

Vehicles tracking is organized to increase safety in smart cities by localizing cars using the Global Positioning System (GPS). The GPS-based system provides accurate tracking, but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR) filter, which meets these needs as a more robust alternative to the Kalman filter (KF). The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs) with time-stamped discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.