Digital Signal Processing and System Theory

Talk Hamza Bakkari

 
Zwei Studenten und eine Tasse Kaffee   Automotive Patched Array Sensor Model for Self-Calibration and a Precise DoA Estimation

Date: 19.09.2013, 13:30 h - 14:30 h
Room: Aquarium

Hamza Bakkari
CAU, Kiel, Germany,

 
 
 

Details

 
 

In the automotive safety context, radar sensors evaluate the environment to assist the driver. This framework compels a need of precise and consistent estimates of the relative angular positions of present targets in the sensor Field of View. To enable accurate estimation, sensor calibration is compulsory.

Calibrating a radar sensor is or is based over the estimation of its array manifold. The array manifold is the collection of ar- ray responses to signals impinging from all possible Directions of Arrival (DoA).

The purpose of this study is to model the given automotive patched array to enable a blind (e.g. without calibration data) online manifold estimation after a rough initializa- tion (using calibration data) in the scope of a high resolution DoA estimation.

The proposed array model is based on the projection of the complex phase error over the Fourier basis appearing as a nat- ural extension of an antenna spacing mis- estimation concept. After a rough initialization, the defined array parameters are further estimated jointly to the DoA –through conventional beamforming – considering different fil- ters : the recursive least square, the sequential Kalman filter and its single precision adapted version according to Potter´s equations.