Direction Finding in Partly Calibrated Arrays Exploiting the Whole Array Aperture

TL;DR

This paper introduces a novel single-snapshot direction finding algorithm for partly calibrated arrays that leverages signal orthogonality and blind source separation to achieve high angular resolution despite position errors.

Contribution

It proposes a new method exploiting orthogonality and blind source separation to improve angular resolution with only one snapshot in partly calibrated arrays.

Findings

Achieves high angular resolution comparable to error-free arrays

Effective with only a single snapshot, reducing data transmission and processing delay

Validated through simulations and experiments

Abstract

We consider the problem of direction finding using partly calibrated arrays, a distributed subarray with position errors between subarrays. The key challenge is to enhance angular resolution in the presence of position errors. To achieve this goal, existing algorithms, such as subspace separation and sparse recovery, have to rely on multiple snapshots, which increases the burden of data transmission and the processing delay. Therefore, we aim to enhance angular resolution using only a single snapshot. To this end, we exploit the orthogonality of the signals of partly calibrated arrays. Particularly, we transform the signal model into a special multiple-measurement model, show that there is approximate orthogonality between the source signals in this model, and then use blind source separation to exploit the orthogonality. Simulation and experiment results both verify that our proposed algorithm achieves high angular resolution as distributed arrays without position errors, inversely proportional to the whole array aperture.