# Location and Orientation Optimisation for Spatially Stretched Tripole Arrays Based on Compressive Sensing

## TL;DR

This paper introduces innovative compressive sensing methods to optimize both the locations and orientations of sparse, spatially stretched tripole arrays, significantly reducing the number of dipoles needed while maintaining performance.

## Contribution

It formulates the joint location and orientation optimization as compressive sensing problems, a novel approach for designing sparse tripole arrays.

## Key findings

- Achieved 67% reduction in dipole count compared to uniform arrays.
- Validated the effectiveness of the proposed methods in approximating reference responses.
- Demonstrated cost reduction in array design.

## Abstract

The design of sparse spatially stretched tripole arrays is an important but also challenging task and this paper proposes for the very first time efficient solutions to this problem. Unlike for the design of traditional sparse antenna arrays, the developed approaches optimise both the dipole locations and orientations. The novelty of the paper consists in formulating these optimisation problems into a form that can be solved by the proposed compressive sensing and Bayesian compressive sensing based approaches. The performance of the developed approaches is validated and it is shown that accurate approximation of a reference response can be achieved with a 67% reduction in the number of dipoles required as compared to an equivalent uniform spatially stretched tripole array, leading to a significant reduction in the cost associated with the resulting arrays.