Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar
A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The und...
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Published in: | Advances in radio science Vol. 14; pp. 39 - 46 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Katlenburg-Lindau
Copernicus GmbH
28-09-2016
Copernicus Publications |
Subjects: | |
Online Access: | Get full text |
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Summary: | A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The underlying sensor platform consists of several homodyne continuous wave (CW) radar modules. Based on In-phase-Quadrature (IQ) processing and down-conversion, they provide only Doppler shift information about the observed target. Localization with Doppler shift estimates is a nonlinear problem that needs to be linearized before the linear KF can be applied. The accuracy of state estimation depends highly on the introduced linearization errors, the initialization and the models that represent the true physics as well as the stochastic properties. The important issue of filter consistency is addressed and an initialization procedure based on data fitting and maximum likelihood estimation is suggested. Models for both, measurement and process noise are developed. Tracking results from typical three-dimensional courses of movement at short distances in front of a multi-sensor radar platform are presented. |
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ISSN: | 1684-9973 1684-9965 1684-9973 |
DOI: | 10.5194/ars-14-39-2016 |