Tensor DoA Estimation With Directional Elements

Abstract

Directivity gain patterns are treated as a physical diversity for tensor array processing, replacing space diversity, in addition to time and space shift diversities. We show that the tensor formulation allows to estimate directions of arrival under the assumption of unknown gain patterns, improving the performance of the omnidirectional case. We propose a trilinear model where one dimension of the multiway data array is fully provided by gain patterns, allowing tensor approaches even when space diversity is missing due to sensor overlap.