Optimized 2D CA-CFAR for Drone-Mounted Radar Signal Processing Using Integral Image Algorithm

TL;DR

This paper presents an optimized 2D CA-CFAR algorithm using integral image techniques to enhance radar signal processing efficiency on resource-constrained drone-mounted systems for buried survivor detection.

Contribution

It introduces a novel application of integral image algorithms to optimize 2D CA-CFAR processing in drone-mounted radar systems, reducing computation time.

Findings

Reduced data processing time on single board computer

Effective implementation on resource-limited drone hardware

Potential for real-time buried survivor detection

Abstract

Buried survivor detection in the post-disaster environment by employing radar as sensor is an appealing approach. However, the implementation in the real field is challenging especially for large observation missions. Mounting the radar on the flying drone is the most promising solution. In this case, since the limitations of drones such as low computer specification and limited power resources, an efficient radar data processing is crucially required. Hence, this paper study about the implementation of the integral image technique to optimize the computation of the signal processing step of ultra-wideband impulse radar signatures. The evaluation was held on the single board computer mounted on the developed multisensory drone. The results confirm that the developed method can relatively reduce the data processing time.