Flight Test Results for a Multi Sensor Obstacle Detection and Tracking System for Sense and Avoid Applications

Abstract

This paper presents the development process of an airborne multi-sensor system for autonomous detection and tracking of flying obstacles. The hardware/software prototype integrating Detect, Sense, and Avoid capability, has been designed and realized by the Italian Aerospace Research Center and the Department of Aerospace Engineering of the University of Naples “Federico II”. First of all, system architecture is described. The sensing subsystem is comprised of a Ka-band airborne pulsed radar, a visible panchromatic high-resolution camera, a visible color high-resolution camera, two thermal infrared cameras, and a processing unit for sensor data fusion. Estimated performance of radar/electro-optical sensor fusion is reported. Then the ground segment developed to monitor test flight in real time is described and data from preliminary flight tests are presented and discussed

Autonomous Platform to Protect Maritime Infrastructure Facilities

“…This sometimes creates problems because radar-visual observation systems can produce significant noise in cases of windy weather and rippled sea. As a result, noise filtration algorithms have to be implemented, both in radar and camera systems [2,3].…”

Real Flight Application of a Monocular Image-Based Aircraft Collision Decision Method

“…In this field, the most critical question is the case of noncooperative S&A for which usually complicated multisensor systems (see [3][4][5][6] for example) or radar-based solutions (see [7,8] for example) are developed. However, in the case of small UAVs, the size, weight, and power consumption of the onboard S&A system should be minimal.…”

Estimation of Relative Direction Angle of Distant, Approaching Airplane in Sense-and-Avoid

“…Provided that the size and the energy consumption of the Unmanned Aerial Vehicle (UAV) are limited, a camera based avoidance system would provide cost and weight advantages against radar based solutions [2,3]. Furthermore near airfields, because of a great density of aircrafts and the limited frequency resources of air traffic controllers the camera-based approach seems to be more feasible then others.…”