Abstract
This paper describes an approach to detect, localize, and track moving, non-cooperative objects by exploiting multipath propagation. In a network of spatially distributed transmitting and receiving nodes, moving objects appear as discrete mobile scatterers. Therefore, the localization of mobile scatterers is formulated as a nonlinear optimization problem. An iterative nonlinear least squares algorithm following Levenberg and Marquardt is used for solving the optimization problem initially, and an extended Kalman filter is used for estimating the scatterer location recursively over time. The corresponding performance bounds are derived for both the snapshot based position estimation and the nonlinear sequential Bayesian estimation with the classic and the posterior Cramér–Rao lower bound. Thereby, a comparison of simulation results to the posterior Cramér–Rao lower bound confirms the applicability of the extended Kalman filter. The proposed approach is applied to estimate the position of a walking pedestrian sequentially based on wideband measurement data in an outdoor scenario. The evaluation shows that the pedestrian can be localized throughout the scenario with an accuracy of m at 90% confidence.
Highlights
With the trends of increasing urbanization and increasing automation in road transportation, the demand for improvements in vehicular safety technologies is steadily growing
For illustrating the localization performance of the measurement setup, the root mean square error (RMSE) is calculated for the considered observation area according to the Cramér-Rao lower bound (CRLB) as defined in Equation (24)
The high localization performance can be explained by the received signal strength of the backscattered signal, since the RMSE strongly depends on the SNR
Summary
With the trends of increasing urbanization and increasing automation in road transportation, the demand for improvements in vehicular safety technologies is steadily growing. To safely route through vehicular environments, timely and reliable information about other road users is required In this regard, the exchange of user specific information, like position and velocity, enhances safety on roads by supporting mutual awareness [1,2,3]. Thereby, signals from Wi-Fi access points with comparatively large bandwidths are beneficial for localization, since lower integration times are required [7,13] In this regard, the authors of [16] propose to use even ultra-wideband signals for PCL. The authors of [16] propose to use even ultra-wideband signals for PCL They introduce different target tracking algorithms and analyze the algorithms in simulations.
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