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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | deu |
| Published: |
Copernicus Publications
2016-09-01
|
| Series: | Advances in Radio Science |
| Online Access: | http://www.adv-radio-sci.net/14/39/2016/ars-14-39-2016.pdf |
| 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.<br><br>
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. |
|---|---|
| ISSN: | 1684-9965 1684-9973 |