Uncertainty Propagation for Inertial Navigation with Coning, Sculling, and Scrolling Corrections.

James D Brouk,Kyle J Demars

doi:10.3390/s21248457

Abstract

This paper investigates the propagation of estimation errors through a common coning, sculling, and scrolling architecture used in modern-day inertial navigation systems. Coning, sculling, and scrolling corrections often have an unaccounted for effect on the error statistics of inertial measurements used to describe the state and uncertainty propagation for position, velocity, and attitude estimates. Through the development of an error analysis for a set of coning, sculling, and scrolling algorithms, mappings of the measurement and estimation errors through the correction term are adaptively generated. Using the developed mappings, an efficient and consistent propagation of the state and uncertainty, within the multiplicative extended Kalman filter architecture, is achieved. Monte Carlo analysis is performed, and results show that the developed system has favorable attributes when compared to the traditional mechanization.

Highlights

Inertial navigation describes the technique whereby the integration of non-gravitational specific force and total angular rate measurements are used in conjunction with a gravity model to produce estimates for the vehicle states: i.e., the inertial position, velocity, and attitude
The introduction of strapdown inertial navigation systems (SINSs) significantly reduced the mass and complexity of the INS, as compared to the inertially stabilized platforms (ISPs), by removing auxiliary components required for the housing and stabilization of ISPs
As seen in Equations (8), (10), and (14), the output of each algorithm can be expressed as a function of the measurement accumulation and the correction terms, while the error dynamics for covariance propagation must be expressed as a function of the estimate and the error in each quantity

Summary

Introduction

Inertial navigation describes the technique whereby the integration of non-gravitational specific force and total angular rate measurements are used in conjunction with a gravity model to produce estimates for the vehicle states: i.e., the inertial position, velocity, and attitude. Before the introduction of strapdown sensors, inertially stabilized platforms (ISPs) were used to maintain the vehicle’s navigation frame and isolate the necessary sensors from the body’s rotation and any present vibration. The introduction of strapdown inertial navigation systems (SINSs) significantly reduced the mass and complexity of the INS, as compared to the ISPs, by removing auxiliary components required for the housing and stabilization of ISPs. An early adoption of the SINS for space missions includes the Apollo Abort Guidance System in 1969 as a backup to the PGNCS, where the added mass of a second ISP became a significant consideration [5]. With the adoption of the SINS, it became necessary to computationally maintain the transformation to the inertially fixed navigation frame as the SINS is not mechanically isolated from the vehicle rotation

Methods

Results

Conclusion