Analog Beamforming for Active Imaging Using Sparse Arrays

Rajamaki, R and Chepuri, SP and Koivunen, V (2019) Analog Beamforming for Active Imaging Using Sparse Arrays. In: 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 3-6 Nov. 2019, Pacific Grove, CA, USA, pp. 1202-1206.

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Abstract

This paper studies analog beamforming in active sensing applications, such as millimeter-wave radar or ultrasound imaging. Analog beamforming architectures employ a single RF-IF front end connected to all array elements via inexpensive phase shifters. This can drastically lower costs compared to fully-digital beamformers having a dedicated front end for each sensor. However, controlling only the element phases may lead to elevated side-lobe levels and degraded image quality. We address this issue by image addition, which synthesizes a high resolution image by adding together several lower resolution component images. Image addition also facilitates the use of sparse arrays, which can further reduce array costs. To limit the image acquisition time, we formulate an optimization problem for minimizing the number of component images, subject to achieving a desired point spread function. We then propose a gradient descent algorithm for approximately solving this problem. We also derive an upper bound on the number of component images needed by the analog beamformer to achieve the conventional digital beamforming solution.1 © 2019 IEEE.

Item Type:	Conference Paper
Publication:	Conference Record - Asilomar Conference on Signals, Systems and Computers
Publisher:	IEEE Computer Society
Additional Information:	cited By 0; Conference of 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 ; Conference Date: 3 November 2019 Through 6 November 2019; Conference Code:158954
Keywords:	Computer circuits; Gradient methods; Millimeter waves; Optical transfer function; Ultrasonic imaging, Digital beam forming; Gradient descent algorithms; High resolution image; Image acquisition time; Millimeter wave radar; Minimizing the number of; Number of components; Optimization problems, Beamforming
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	11 Sep 2020 05:44
Last Modified:	11 Sep 2020 05:44
URI:	http://eprints.iisc.ac.in/id/eprint/65259

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