Compressive Direction Finding Based on Amplitude Comparison

TL;DR

This paper introduces a compressive sensing-based method for direction finding using amplitude comparison, leveraging antenna pattern characteristics and sparse data properties to improve efficiency and accuracy over traditional peak-searching techniques.

Contribution

The paper presents a novel CS-based approach for direction finding that reduces pulse requirements and enhances performance compared to conventional methods.

Findings

Outperforms traditional peak-searching methods in simulations

Requires fewer pulses for accurate direction estimation

Utilizes antenna pattern unimodality and data sparsity effectively

Abstract

This paper exploits recent developments in compressive sensing (CS) to efficiently perform the direction finding via amplitude comprarison. The new method is proposed based on unimodal characteristic of antenna pattern and sparse property of received data. Unlike the conventional methods based peak-searching and symmetric constraint, the sparse reconstruction algorithm requires less pulse and takes advantage of CS. Simulation results validate the performance of the proposed method is better than the conventional methods.