In-flight performance analysis of a non-cooperative radar-based sense and avoid system

Abstract

This paper discusses the outcome of flight experiments relevant to non-cooperative sense and avoid that were carried out in the framework of a collaboration between the Italian Aerospace Research Center and the University of Naples '‘Federico II’’. Within the project, aimed at full autonomy for medium/large Unmanned Aircraft Systems, an integrated radar/electro-optical system configuration was adopted, and real-time data fusion/automatic decision-making algorithms were developed to estimate intruders’ motion, and generate and follow proper escape trajectories. All the systems were designed to guarantee collision avoidance without any dependence on the command and control link. The hardware/software sense and avoid system was installed onboard an optionally piloted flying laboratory of Very Light Aircraft category, and a single intruder aircraft of the same class was considered for avoidance experiments. In particular, the paper focuses on the results from radar-based autonomous avoidance flight tests. Performance is analyzed in terms of situational awareness before and during the maneuver, and effectiveness in performing safe avoidance maneuvers while generating smooth commands and minimizing the deviation from nominal trajectory. Statistics relevant to several encounters show that in spite of a small number of valid sensor measurements, the tracking algorithm is able to keep a satisfying level of situational awareness, thus enabling safe avoidance. However, the limits deriving from coarse radar accuracy, low scan rate, and interaction between mechanical scanning and aircraft flight dynamics are also pointed out. While these limits did not impact avoidance safety in the considered tests due to the favorable operating environment in terms of time to collision, radar detection range, and ownship maneuverability, they confirm the need of improved sensing concepts in more challenging avoidance scenarios, such as adoption of radar/electro-optical data fusion and electronic scanning technologies

LARUS: an unmanned aircraft for the support of maritime rescue missions under heavy weather conditions

“…In addition, they do need a demanding computation power for their operation [9,10]. Other sensing technologies like radar have been considered in bigger UAS types [9], but mostly as impulse radar systems with larger size and bigger system mass [11]. Preliminary studies have shown that the choice of a miniaturized continuous wave radar system as a possible detection sensor technology offers a promising approach to meet the requirements [12,13] while using only microcontroller resources to compute detection results.…”

“…Regarding classic impulse radar systems like the type used in [11], the utilized sensor has a smaller detection range (2 nautical miles as described in [11] compared to 900 m) but significant lower electrical power consumption and overall sensor system mass (25 kg sensor mass [11] compared to 164 g per continuous wave radar system, which includes the signal processing and hardware interface units).…”

“…Depending on the carrier frequency f 0 and a selected bandwidth B, starting at the lower limit of the selected frequency range, the frequency ramp is traversed within a running time t up to a specific ramp time T. At a descending (11) Fig. 12 Attenuation of electromagnetic waves due to atmosphere and precipitation, according to [15] ramp, the algebraic signs of the second and third terms of the Eq.…”

Research on the Collision Avoidance Algorithm for Fixed-Wing UAVs Based on Maneuver Coordination and Planned Trajectories Prediction

“…Luongo S [5] improved the 3D analytical algorithm by proposing a cylindrical safety bubble that allows different minimum separations of the vertical and horizontal planes with respect to the nominal trajectory to be achieved. The performances of such system, using active obstacle detection through radar, have been discussed in the paper [6]. Geometric algorithm is intuitive with low computing cost and always provides an optimal solution in 3D environments whether the aircraft cooperates or not.…”

UAV Group Formation Collision Avoidance Method Based on Second-Order Consensus Algorithm and Improved Artificial Potential Field

“…The strategic level approach refers to proactively planning collision-free flight paths from the current location to the destination based on the perceptual detection of obstacles under the constraints of the minimum safe separation distance. Among them, the performance of systems using radar to actively detect obstacles is discussed in [19]. The collision avoidance algorithm based on geometric relationship has the characteristics of simple and efficient calculation, but most of the collision avoidance systems based on geometric relationship only support the collision avoidance between a pair of UAVs.…”