Angular Estimation Comparison with ISAC PoC

TL;DR

This paper compares different angular estimation methods using minimal DFT-based samples acquired via ISAC beam sweeping, highlighting the effectiveness of interpolation approaches for general scenarios and OMP for specific targets.

Contribution

It evaluates and compares angular estimation techniques based on minimal samples in an ISAC proof of concept, providing insights into their relative performance.

Findings

Interpolation approaches generalize well across scenarios

OMP yields the most accurate estimates for strong, isolated targets

DFT-based interpolation offers the best overall estimation performance

Abstract

The introduction of Integrated Sensing and Communications (ISAC) in cellular systems is not expected to result in a shift away from the popular choice of cost- and energy-efficient analog or hybrid beamforming structures. However, this comes at the cost of limiting the angular capabilities to a confined space per acquisitions. Thus, as a prerequisite for the successful implementation of numerous ISAC use cases, the need for an optimal angular estimation of targets and their separation based on the minimal number of angular samples arises. In this work, different approaches for angular estimation based on a minimal, DFT-based set of angular samples are evaluated. The samples are acquired through sweeping multiple beams of an ISAC proof of concept (PoC) in the industrial scenario of the ARENA2036. The study's findings indicate that interpolation approaches are more effective for generalizing across different types of angular scenarios. While the orthogonal matching pursuit (OMP) approach exhibits the most accurate estimation for a single, strong and clearly discriminable target, the DFT-based interpolation approach demonstrates the best overall estimation performance.