Multiple-input multiple-output (MIMO) radar is getting more and more applications over the last decade. In near field imaging using a linear MIMO array, the azimuth sampling is non-uniform, resulting in spatially variant point spread function (PSF) over a large imaging zone. In this work, an azimuth sidelobe suppression technique is proposed where apodization or complex amplitude weighting is applied to the multiple channel data prior to image reconstruction. For best sidelobe suppression, the optimal channel weights w_opt are obtained through mathematical optimization. The overall process mainly includes three steps. Firstly, the expression of PSF in azimuth is acquired by the azimuth focusing process; Secondly, based on the fact that, for an ideal PSF the maximum value of the mainlobe should be one and the values of sidelobes should be zeros, the problem of finding w_opt is mathematically fomulated as an optimization problem; Lastly, by setting proper mainlobe width and sidelobe level, the optimal weights can be solved through convex optimization algorithm. Simulations of a MIMO radar system where channel amplitude-phase error and antenna elements position deviation exist are presented and the performance of the proposed technique is studied.

Date Published: 15 October 2015
PDF: 8 pages
Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 96431E (15 October 2015); doi: 10.1117/12.2194474

Published in SPIE Proceedings Vol. 9643:
Image and Signal Processing for Remote Sensing XXI
Lorenzo Bruzzone, Editor(s)