Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between S...

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Main Authors: Yanqiang Yang, Chunxi Zhang, Jiazhen Lu
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/17/1/167
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spelling doaj-9a951367c07d47299c7e622d8793dd722020-11-24T21:13:30ZengMDPI AGSensors1424-82202017-01-0117116710.3390/s17010167s17010167Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight VehiclesYanqiang Yang0Chunxi Zhang1Jiazhen Lu2The Science and Technology on Inertial Laboratory, School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, ChinaThe Science and Technology on Inertial Laboratory, School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, ChinaThe Science and Technology on Inertial Laboratory, School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, ChinaStrapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.http://www.mdpi.com/1424-8220/17/1/167star sensor installation errorslocal observability analysisKalman Filteringnear-earth flight vehicles
collection DOAJ
language English
format Article
sources DOAJ
author Yanqiang Yang
Chunxi Zhang
Jiazhen Lu
spellingShingle Yanqiang Yang
Chunxi Zhang
Jiazhen Lu
Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
Sensors
star sensor installation errors
local observability analysis
Kalman Filtering
near-earth flight vehicles
author_facet Yanqiang Yang
Chunxi Zhang
Jiazhen Lu
author_sort Yanqiang Yang
title Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
title_short Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
title_full Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
title_fullStr Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
title_full_unstemmed Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles
title_sort local observability analysis of star sensor installation errors in a sins/cns integration system for near-earth flight vehicles
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-01-01
description Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.
topic star sensor installation errors
local observability analysis
Kalman Filtering
near-earth flight vehicles
url http://www.mdpi.com/1424-8220/17/1/167
work_keys_str_mv AT yanqiangyang localobservabilityanalysisofstarsensorinstallationerrorsinasinscnsintegrationsystemfornearearthflightvehicles
AT chunxizhang localobservabilityanalysisofstarsensorinstallationerrorsinasinscnsintegrationsystemfornearearthflightvehicles
AT jiazhenlu localobservabilityanalysisofstarsensorinstallationerrorsinasinscnsintegrationsystemfornearearthflightvehicles
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