Two dimensional sparse array design for wideband signals

Syed A. Hamza; Moeness G. Amin

doi:10.1117/12.2519879

13 May 2019 Two dimensional sparse array design for wideband signals

Syed A. Hamza, Moeness G. Amin

Proceedings Volume 10989, Big Data: Learning, Analytics, and Applications; 109890J (2019) https://doi.org/10.1117/12.2519879
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Recently, thinned arrays and sensor position selections have attracted much attention since they lead to reduced hardware cost and yield effective receiver design. The data is fetched from systematically selected sensor locations for maximizing the Signal-to-Interference plus noise ratio (SINR) in a dynamically changing environment. We ensure that the most pertinent data samples are collected, thereby avoiding data redundancies. In this paper, we examine two dimensional sparse array design for wideband signal models. The data is processed jointly in the temporal and spatial domains. Reducing the number of spatial samples, through sparse array configuration, decreases the overall data processing complexity. The performance of the proposed sparse array design, in terms of maximizing the SINR, is presented and the effectiveness of the proposed algorithm is demonstrated.

Citation Download Citation

Syed A. Hamza and Moeness G. Amin "Two dimensional sparse array design for wideband signals ", Proc. SPIE 10989, Big Data: Learning, Analytics, and Applications, 109890J (13 May 2019); https://doi.org/10.1117/12.2519879

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