A review of system safety failure probability objectives for Unmanned Aircraft Systems

Unmanned Aircraft Systems (UAS) are one of a number of emerging aviation sectors. Such new aviation concepts present a significant challenge to National Aviation Authorities (NAAs) charged with ensuring the safety of their operation within the existing airspace system. There is significant heritage in the existing body of aviation safety regulations for Conventionally Piloted Aircraft (CPA). It can be argued that the promulgation of these regulations has delivered a level of safety tolerable to society, thus justifying the “default position” of applying these same standards, regulations and regulatory structures to emerging aviation concepts such as UAS. An example of this is the proposed “1309” regulation for UAS, which is based on the 1309 regulation for CPA. However, the absence of a pilot on-board an unmanned aircraft creates a fundamentally different risk paradigm to that of CPA. An appreciation of these differences is essential to the justification of the “default position” and in turn, to ensure the development of effective safety standards and regulations for UAS. This paper explores the suitability of the proposed “1309” regulation for UAS. A detailed review of the proposed regulation is provided and a number of key assumptions are identified and discussed. A high-level model characterising the expected number of third party fatalities on the ground is then used to determine the impact of these assumptions. The results clearly show that the “one size fits all” approach to the definition of 1309 regulations for UAS, which mandates equipment design and installation requirements independent of where the UAS is to be operated, will not lead to an effective management of the risks.

Design of flight avoidance manoeuvre alphabets for mixed centralised-decentralised separation management

This paper investigates a mixed centralised-decentralised air traffic separation management system, which combines the best features of the centralised and decentralised systems whilst ensuring the reliability of the air traffic management system during degraded conditions. To overcome communication band limits, we propose a mixed separation manager on the basis of a robust decision (or min-max) problem that is posed on a reduced set of admissible flight avoidance manoeuvres (or a FAM alphabet). We also present a design method for selecting an appropriate FAM alphabet for use in the mixed separation management system. Simulation studies are presented to illustrate the benefits of our proposed FAM alphabet based mixed separation manager.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.