Abstract
For real-time solution of inertial navigation system (INS), the high-degree spherical harmonic gravity model (SHM) is not applicable because of its time and space complexity, in which traditional normal gravity model (NGM) has been the dominant technique for gravity compensation. In this paper, a two-dimensional second-order polynomial model is derived from SHM according to the approximate linear characteristic of regional disturbing potential. Firstly, deflections of vertical (DOVs) on dense grids are calculated with SHM in an external computer. And then, the polynomial coefficients are obtained using these DOVs. To achieve global navigation, the coefficients and applicable region of polynomial model are both updated synchronously in above computer. Compared with high-degree SHM, the polynomial model takes less storage and computational time at the expense of minor precision. Meanwhile, the model is more accurate than NGM. Finally, numerical test and INS experiment show that the proposed method outperforms traditional gravity models applied for high precision free-INS.
Highlights
Inertial navigation systems (INSs) are employed throughout all branches of the military and in many civil platforms, due to their significant advantages of providing continuous position, velocity and attitude information, and being invulnerable to external interference [1]
The updating of coefficients and the switch of navigation area are executed in an external gravity computer, where the polynomial model (PM) is fitted to nodal gravity information calculated by spherical harmonic gravity model (SHM)
We propose that two-dimensional coordinate in the vertical direction to be constant here) of low order could be used to fit to any polynomials
Summary
Inertial navigation systems (INSs) are employed throughout all branches of the military and in many civil platforms, due to their significant advantages of providing continuous position, velocity and attitude information, and being invulnerable to external interference [1]. The modeling method, effectively a trade-off between speed and memory, stores nodal gravity field information on an equivalent spherical grid. This information is previously calculated with SHM on a computer. The updating of coefficients and the switch of navigation area are executed in an external gravity computer, where the PM is fitted to nodal gravity information calculated by SHM. This design is superior to data-based compensation methods that occupy several times the memory resources (see [8]).
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