A Generalized Coning Correction Structure for Attitude Algorithms

Abstract

A new coning correction structure is presented for attitude update coning correction. Different from the previous rate-based and increment-based coning correction structures, the new structure contains cross-product of angular rates, cross-product of angular increments, and cross-product of angular rate and increment (an angular increment may be approximated from angular rate samples). Two types of optimization methods including time Taylor-series method and frequency Taylor-series method were utilized to design the structure coefficients including the uncompressed and the compressed. Two types of algorithm error models including one applicable to coning environments and the other two applicable to maneuver environments were defined and used for analyzing or evaluating the algorithm performance. The derivation procedure of a rotation vector magnitude extraction method is included. Analysis and simulation results indicate that the new structure-based algorithm with the compressed coefficients designed by using frequency Taylor-series method gives a superior algorithm performance in coning environments and maneuver environments.

Improvement to classical coning algorithms in maneuver performance based on a match correction structure

“…In the SINS attitude updating, the equivalent rotation vector is generally calculated by using the simple approximation form 1,4,7–9,12,15,17 where φl is the equivalent rotation vector, t is the time, ω is the gyro sensed angular rate vector at the t time, αl is the integral of ω in time domain [tl-1,tl], and δφl is the analytical form of the coning correction.…”

“…For modern strapdown inertial navigation system (SINS) algorithm, the core technology is the attitude updating algorithm among which the two-stage 1,2 attitude updating algorithm has been widely used. In high precision SINS, the equivalent rotation vector method 2 is necessary, and it requires the attitude noncommutativity error compensation 3–16 which is commonly referred to as the coning correction of which essence is to numerically approximate the noncommutativity error from gyro data as far as possible. Miller 3 first presented a method of designing a numerical algorithm for the attitude noncommutativity error compensation in the pure coning environment.…”

A Real-Time Structure of Attitude Algorithm for High Dynamic Bodies

“…In general, the performance evaluation of algorithms including the uncompressed and compressed algorithms can be expressed as the drifting error under coning environment. There are several different forms of multisubsample algorithms, but all of them can be summarized as [9,10] =̃− .…”

“…Multisubsample optimized algorithms based on bandwidth of gyroscopes are proposed to restrain drifting of coning error, which are also regarded as uncompressed algorithms. It is found that the more the subsamples are chosen, the smaller the drifting rate of coning error is [6][7][8][9]. To further improve the accuracy of rotation vectors, compressed and half-compressed algorithms have been presented as well [10,11].…”

Cone Algorithm of Spinning Vehicles under Dynamic Coning Environment

“…Li et al divided minor coning correction into a number of subminor intervals and delivered a generalized coning compensation algorithm that is independent of the number of incremental angles [10]. Tang and Chen proposed a coning correction structure containing cross-product of angular rates, cross-product of angular 2 International Journal of Aerospace Engineering increments, and cross-product of angular rate and increment, and it can analyze effect on attitude by basing on time Taylor series and frequency Taylor series [11]. Meanwhile, the gyro frequency response is a primary cause for pseudo-coning error that is another form of coning error, and the traditional coning correction algorithms cannot work to highorder accuracy.…”