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A navigation algorithm using measurement‐based extrapolation
Author(s) -
Stubberud Allen R.
Publication year - 1983
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.4660040407
Subject(s) - inertial navigation system , kalman filter , azimuth , estimator , extrapolation , radar , state vector , computer science , range (aeronautics) , control theory (sociology) , algorithm , inertial frame of reference , engineering , aerospace engineering , mathematics , artificial intelligence , physics , mathematical analysis , statistics , geometry , control (management) , classical mechanics , quantum mechanics
An element in the guidance loop of any aircraft is the navigation system. This system derives position (and sometimes velocity) information by combining data from various on‐board and external measurement devices and transmits it to the guidance algorithm. In this paper a navigation algorithm is designed for an aircraft which has on‐board inertial measurements, range measurements from a TACAN station, and range, elevation and azimuth measurements from a ground‐based radar. The basic design philosophy is the predictor‐corrector form for a recursive estimator. State prediction is accomplished by extrapolation of the inertial measurements rather than from Newton's second law. This eliminates major modelling problems caused by the aircraft's aerodynamics. State correction is accomplished using optimal linear stochastic estimation methods. The resulting estimator (navigation algorithm) is essentially an ‘extended Kalman filter’ which processes the above‐mentioned inputs and generates optimal (in a linearized sense) estimates of the aircraft's latitude, longitude and altitude.