Sculling Compensation Algorithm for SINS Based on Two-Time Scale Perturbation Model of Inertial Measurements

Abstract

In order to decrease the velocity sculling error under vibration environments, a new sculling error compensation algorithm for strapdown inertial navigation system (SINS) using angular rate and specific force measurements as inputs is proposed in this paper. First, the sculling error formula in incremental velocity update is analytically derived in terms of the angular rate and specific force. Next, two-time scale perturbation models of the angular rate and specific force are constructed. The new sculling correction term is derived and a gravitational search optimization method is used to determine the parameters in the two-time scale perturbation models. Finally, the performance of the proposed algorithm is evaluated in a stochastic real sculling environment, which is different from the conventional algorithms simulated in a pure sculling circumstance. A series of test results demonstrate that the new sculling compensation algorithm can achieve balanced real/pseudo sculling correction performance during velocity update with the advantage of less computation load compared with conventional algorithms.

A modified velocity updating algorithm for a strapdown INS

“…where α is the slew rate and the sculling frequency in the typical sculling motion described in (7), and a, b are the magnitudes of the angular rate and specific force vectors, respectively, as defined in (7). In this definition, the projections of the angular rate and specific force vectors in frame B vary at the same frequency and slew about the z-axis with the same slew rate vector.…”

“…In this definition, the projections of the angular rate and specific force vectors in frame B vary at the same frequency and slew about the z-axis with the same slew rate vector. The typical slewing motion can be regarded as a superposition of two sculling motions, that is, the sculling motion described by (7) and the other described as follows:…”

“…More recently, Wu [6] reduced velocity errors using functional iterative integration and angular rate and specific force fitted by Chebyshev polynomials. Wang [7] proposed a new velocity updating algorithm based on the inertial information's twotime scale singular perturbation models. Huang [8] presented two types of novel optimal sculling algorithms using angular rate input without converting the angular rate to the integrated angular rate.…”

Strapdown Sculling Velocity Algorithms Using Novel Input Combinations

“…The discrete algorithm for ΔV , which is usually referred to as sculling algorithm, can be obtained from the coning algorithm using a simple duality formula [4,5,7]. For example, the 2-interval optimal sculling algorithm using incremental angle/specific force increments inputs is [5,[8][9][10]]…”

“…Eqs. (9) and (10) have the identical mathematical forms to (33) and (34), and they equal each other when the terms Δ , f, aH, bH 2 , A, BH, and CH 2 in (9) and (10) are replaced by ΔV, , AH, BH 2 , a, bH, and cH 2 respectively. The 2-interval generalized sculling algorithm using angular rate/specific force increments inputs can therefore be given as…”