Non-measurable flight parameters multi-stage identification while on-board measuring tools’ signals complexing

Information and measuring and control systems


Аuthors

Lebedev G. N.*, Mikhailin D. A.1**, Roumakina A. V.2***

1. Main research and testing center for robotics Ministry of Defense of the Russian , 5, ul. Seregina, Moscow, 125167, Russia
2. ,

*e-mail: kaf301@mai.ru
**e-mail: tau_301@mail.ru
***e-mail: dolgova-221@mail.ru

Abstract

The problem of non-measurable flight parameters identification, including wind affects and remained fuel weight, appeared necessary information for safety and flight control monitoring. The authors offer a multi-stage procedure of assessment, according to which less precise, but simpler means are implemented at the initial stages of assessment, while more complicated elements are put into operation as may be necessary.

A complexed two-stage identifier of side wind is formed, consisting of a windblast estimation block, a block of its steady state value evaluation and a block of logic switching from one estimation to the other, using aperiodic filtering for the first case and modified Kalman filter for the other.

The identifier, employing optimal Kalman filter prognosis operation, provides the most precise indirect estimation technique of the steady-state wind. The authors offered “freezing” the most significant for evaluation correcting matrix coefficients of optimal Kalman’s filter, and zero the rest coefficients, so as to eliminate variable coefficients and provide offload the onboard computer.

According to the offered multi-stage identification concept, every stage employs different set of sensors. Satellite navigation data appears more useful for the situation of initial wind effect, as well as a group onboard sensors, such as accelerometers and airspeed sensor, reacting faster to wind changes than other sensors. To evaluate the steady-state value, other sensors, controlling the aircraft reaction, mainly, to the constant wind component effect.

Keywords:

multi-stage identification, signals complexing, flight parameters, wind disturbances evaluation

References

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