Marinho MA, Da Costa JPC, Antreich F, De Almeida AL, Del Galdo G, De Freitas EP, Vinel A (2016)
Publication Type: Conference contribution
Publication year: 2016
Publisher: IEEE Computer Society
Book Volume: 2016-September
Conference Proceedings Title: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Event location: Rio de Rio de Janeiro, BRA
ISBN: 9781509021031
Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal.
APA:
Marinho, M.A., Da Costa, J.P.C., Antreich, F., De Almeida, A.L., Del Galdo, G., De Freitas, E.P., & Vinel, A. (2016). Array interpolation based on multivariate adaptive regression splines. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. Rio de Rio de Janeiro, BRA: IEEE Computer Society.
MLA:
Marinho, Marco A.M., et al. "Array interpolation based on multivariate adaptive regression splines." Proceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, Rio de Rio de Janeiro, BRA IEEE Computer Society, 2016.
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