# Theoretical Modeling and Experimental Study on Low-Altitude Slow-Small Target (LSS) Detection Based on Broadband Spectral Modulation Imaging

## TL;DR

This paper introduces a new method for detecting small, low-flying objects like drones using broadband spectral modulation imaging, which improves detection accuracy and reduces false alarms.

## Contribution

The novel broadband spectral modulation imaging (BSMI) theory and system design for enhanced low-altitude slow-small target detection.

## Key findings

- The BSMI system achieves over 90% classification accuracy for drone targets.
- The method improves detection probability and suppresses false alarms in complex environments.

## Abstract

The detection of low-altitude slow-small (LSS) targets, such as drones, is challenged by their small radar cross-section (RCS) and low signal-to-clutter ratio (SCR), resulting in short effective range and susceptibility to background clutter in complex environments. To overcome the limitations of conventional radar and electro-optical methods, this paper proposes a novel detection theory based on broadband spectral modulation imaging (BSMI). We analyze the recognition accuracy for drone targets across different zenith angles and detection ranges through numerical simulations. A snapshot-based BSMI detection system was designed and implemented, with experiments conducted under consistent conditions for validation. Results demonstrate that the system achieves over 90% classification accuracy, confirming the theory’s effectiveness. This study significantly enhances detection probability and suppresses false alarms for low-altitude drones, providing a viable technical solution for monitoring unauthorized aerial activities.