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On-board navigation system for an aerial craft including a synthetic aperture sideways looking radar

  • US 5,485,384 A
  • Filed: 09/03/1993
  • Issued: 01/16/1996
  • Est. Priority Date: 09/03/1992
  • Status: Expired due to Fees
First Claim
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1. An on-board navigation system for an aerial vehicle of the type including an inertial navigation facility (10) delivering an estimation of the position and velocity of the vehicle with respect to the terrestrial surface, a SAR synthetic aperture sideways looking radar (12) producing a SAR radar image of the territory in the vicinity of the point (Mo) overflown by the vehicle, memory means (16) containing a reference map of the territory overflow, means (17) for comparison based on alignment of said SAP, radar image produced in flight with the stored reference map and providing an alignment deviation δ

  • in two perpendicular directions and computing means (18) linked to the memory means (16), to the inertial navigation facility (10) and to the means of comparison (17), which include filter means of the KALMAN type, and which deliver an inceptor to the KALMAN filter for the estimation of the inertial errors in position and in velocity as a function of the alignment deviation δ

    , wherein said computing means (18) express the alignment deviation as a function of the estimation error vector Δ

    U associated with the state vector U consisting of the components of the vectors P, V for the position and relative velocity of the vehicle, in accordance with the following equation;

    ##EQU25## in which;

    η

    is the vector of alignment error in two perpendicular directions η

    x, η

    y;

    Δ

    X and Δ

    Y represent the inertial error in position of the vehicle in two horizontal perpendicular directions;

    Δ

    Z represents the inertial error in altitude of the vehicle;

    Δ

    V represents the vector of inertial errors in velocity of the vehicle; and

    f(Δ

    Z, Δ

    V) and g(Δ

    Z, Δ

    V) are two scalar functions; and

    wherein the filter is a KALMAN-BUCY filter with gain matrix K such that the estimate Δ

    U of the vector of estimation error is equal to Δ

    U=K.δ

    .

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