In vehicular applications, both radar and communications play an important role. Safety applications in particular may make use of both systems to perform well: radar imaging can be used to gain information about objects in the vicinity, and communications allow vehicles to exchange traffic or maneuvering information. If both radar and communications are to be performed with a single hardware and signal, OFDM radar becomes an interesting choice. The dual use frees up the spectrum, and less hardware is required for antennas and RF front-ends. For such a dual use, OFDM radar algorithms based on spectral estimation are highly useful. These algorithms make use of the fact that simple linear operations can translate the radar signal into complex sinusoids, which then can be interpreted using spectral estimation methods. The frequencies of these sinusoids correspond to the range and Doppler shift of detected targets. Previously, we have focused on robust FFT-based methods, which use a modified two-dimensional periodogram for estimation. However, given that the estimation problem focuses on sinusoids, we can use eigenvalue-based estimation methods, which are only limited by a machine's computational accuracy and are designed to match this particular spectral estimation problem. In this work, we will therefore explore these algorithms to identify possible uses in the context of OFDM radar.


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    Title :

    High-resolution spectral estimation algorithms in OFDM radar


    Contributors:


    Publication date :

    2011


    Size :

    5 Seiten, 3 Bilder, 1 Tabelle, 9 Quellen


    Remarks:

    (nicht paginiert)


    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English