Geo-Referenced Mapping through an Anti-Collision Radar Aboard an Unmanned Aerial System

Abstract

Unmanned aerial systems (UASs) have enormous potential in many fields of application, especially when used in combination with autonomous guidance. An open challenge for safe autonomous flight is to rely on a mapping system for local positioning and obstacle avoidance. In this article, the authors propose a radar-based mapping system both for obstacle detection and for path planning. The radar equipment used is a single-chip device originally developed for automotive applications that has good resolution in azimuth, but poor resolution in elevation. This limitation can be critical for UAS application, and it must be considered for obstacle-avoidance maneuvers and for autonomous path-planning selection. However, the radar-mapping system proposed in this paper was successfully tested in the following different scenarios: a single metallic target in grass, a vegetated scenario, and in the close proximity of a ruined building.

Fast Obstacle Detection System for UAS Based on Complementary Use of Radar and Stereoscopic Camera

“…The radar used for this work is an AWR1843BOOST by Texas Instruments [12]. A radar detects the distance of the target by sending and receiving an electromagnetic signal through at least a couple of antennas.…”

“…Under this hypothesis, the map generated using the radar is bi-dimensional. It becomes three-dimensional by changing the drone altitude [12]. In order to reduce the number of false alarms, the radar signal was filtered using two constant false alarm rate (CFAR) algorithms [12].…”

“…It becomes three-dimensional by changing the drone altitude [12]. In order to reduce the number of false alarms, the radar signal was filtered using two constant false alarm rate (CFAR) algorithms [12]. The first CFAR algorithm discriminates the physical targets from the thermal noise and from possible clutter using a moving threshold on range direction.…”

“…As will be explained in Section 2.6, by suitably processing this topic, it is possible to create an obstacle-detection system. The ODS node (obstacle-detection system) implements various functions: in addition to the obstacle-detection task, it is responsible for the creation of the maps [12] explained in Section 2.5, exploiting the absolute paths generated from the GNSS data [12] via the DJI OSDK node and from the SLAM (simultaneous localization and mapping) estimated by the vision process [18][19][20][21].…”

“…Recently, the scientific community has begun to experiment with the use of radar systems, which have multiple advantages, such as longer detection ranges and being insensitive to light and visibility conditions [12,13]. Compared to optical systems, it is important to note that radar technology also has disadvantages, such as a lower spatial resolution and the almost total absence of resolution in height [12,14]. However, the two technologies have complementary characteristics and therefore lend themselves well to being used together; in fact, they are able to compensate for each other's disadvantages.…”