Litcius/Paper detail

A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter

Guangle Gao, Shesheng Gao, Genyuan Hong, Peng Xu, Tian Yu

2020Sensors28 citationsDOIOpen Access PDF

Abstract

In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-based velocity measurement equation in the INS/SRS/CNS system is derived. Furthermore, a new chi-square test-based robust Kalman filter (CSTRKF) is also proposed in order to improve the robustness of the INS/SRS/CNS navigation system. In the CSTRKF, the chi-square test (CST) not only detects measurements with outliers and in non-Gaussian distributions, but also estimates the statistical characteristics of measurement noise. Finally, the results of our simulations indicate that the INS/SRS/CNS integrated navigation system with the CSTRKF possesses strong robustness and high reliability.

Topics & Concepts

Inertial navigation systemNavigation systemRobustness (evolution)Kalman filterCelestial navigationComputer scienceGaussianOutlierExtended Kalman filterControl theory (sociology)Computer visionArtificial intelligencePhysicsInertial frame of referenceChemistryAstronomyControl (management)Quantum mechanicsGeneBiochemistryTarget Tracking and Data Fusion in Sensor NetworksInertial Sensor and NavigationRobotics and Sensor-Based Localization
A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter | Litcius