4.6 Article

Optimal State Estimation for Systems Driven by Jump-Diffusion Process With Application to Road Anomaly Detection

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2016.2620062

关键词

Jump-diffusion process (JDP); road anomaly detection; state estimation

资金

  1. Ford Motor Company-The University of Michigan Alliance

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Jump-diffusion processes (JDPs) involve a combination of jumps (Poisson process) and diffusions (Wiener process). JDPs can be used to model large classes of disturbances in engineering applications, such as road disturbances to a car, wind disturbances to an airplane, and system parameter perturbations. This paper develops a road anomaly detector by exploiting an optimal state estimator for systems driven by JDP in combination with the multi-input observer. State estimation with the JDP-based estimator is shown to have better performance than a Kalman filter when jumps, such as potholes and bumps, are present. The road anomaly detector is implemented in an experimental test vehicle and its experimental validation results are reported.

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