Software and Algorithms Development for the Perspective Aircrafts Synthetic Vision System Prototype
Dynamics, ballistics, movement control of flying vehicles
Аuthors1*, 2**, 2***, 1****
1. Integration center branch of the Irkut Corporation, 5, Aviazionny pereulok, Moscow, 125167, Russia
This article describes the software development of Synthetic Vision System (SVS) prototype, which provides enhanced situational awareness for flight crew and decision making assistance during approach and landing phases of flight in nonvisual flight conditions for future civil transport aircrafts.
The SVS uses as initial data the known aircraft present position and terrain elevation map database (map size, map grid intervals Δ1 and Δ2, and Х, Y, Z coordinates of grid reference). As the sources of such data in this article respectively appears the flight management system (FMS) and the terrain awareness and warning system (TAWS).
For 3D-modeling of initial data it is necessary to express the coded topographic data in terms of primitive solids. Tin the most simple way the terrain region of consideration could be approximated as set of rectangular parallelepipeds, the bases of which are the terrain elevation map squares and the heights of which are the corresponding maximum terrain elevation.
After 3D-modeling of terrain region of consideration it is also necessary to cut off the unfaced lines and surfaces. To solve this the z-buffer method is chosen by reason of its most suitableness to implement on airborne equipment of civil transport aircraft and central display system architectural features.
The SVS generates an image of the terrain elevation in region of consideration in 3D view for displaying it on the primary flight display combined with the other flight and navigation information in real time mode.
Based on the proposed algorithm the software developed. Simulation results confirms the adequacy and applicability of the proposed approach to improve the situational awareness of the crew during approach and landing phases of flight in nonvisual flight conditions for transport category aircrafts.
Keywords:aircraft, synthetic vision system, 3D-simulation, landing
Lunev E.M. Programmno-algoritmicheskoe obespechenie izmeritel’noi chasti sistemy avtomaticheskoi posadki BPLA. Sbornik tezisov i dokladov. nauchno-prakticheskoj konferencii " Innovatsii v aviatsii i kosmonavtike— 2010″. Mosсow, 2010, pp. 51-52.
Algoritm, ispol’zuyushchii z—buffer, URL: http://compgraph.tpu.ru/zbuffer.htm, 2015.
Sostoyanie i perspektivy razvitiya integrirovannoi modul’noi avioniki. Mezhdunarodnaya nauchno-prakticheskaya konferentsiya (State and prospects of development of integrated modular avionics), Moscow, 2012, 51 p.
Djatlova O.S. Obrabotka informatsii i upravlenie. 2011. no. 4. pp. 24–29.
Evgenov A. V. Aviakosmicheskoe priborostroenie. 2003. no. 3. pp. 48 — 53.
Osnovnye algoritmy komp’yuternoi grafiki. URL: http://bourabai.ru/graphics/02.htm, 2015.
Rodzhers D. Algoritmicheskie osnovy mashinnoi grafiki (Algorithmic foundations of computer graphics), Moscow, Mir, 1989, 512 p.
Sistema sinteticheskogo videniya dlya pilotov. URL: http://www.ato.ru/content/sistema-sinteticheskogo-videniya-dlya-pilotov, 2015.
Shapiro L. Komp’yuternoe zrenie (Computer Vision), Moscow, BINOM, Laboratorija znanij, 2013, 752 p.
McKenna, E. Synthetic Vision Systems // Avionics Magazine. 2012. no. 5. 58 p.
Pro Line 21™ Synthetic Vision System (SVS) | Rockwell Collins. — U. S.: Rockwell Collins, Inc. 2011. 2 p.
Statistical Summary of Commercial Jet Airplane Accidents | 1959 — 2014. — U. S.A.: Boeing Commercial Airplanes. 2015. 24 p.