GNSS Spoofing Detection Ability of a Loosely Coupled INS/GNSS Integrated Navigation System for two Integrity Monitoring Methods

2017 ◽  
Author(s):  
Yang Liu ◽  
Qiangwen Fu ◽  
Zhenbo Liu ◽  
Sihai Li
Keyword(s):  
Navigation System ◽  
Integrated Navigation ◽  
Monitoring Methods ◽  
Integrity Monitoring ◽  
Detection Ability ◽  
Integrated Navigation System ◽  
Loosely Coupled ◽  
Spoofing Detection

scholarly journals An Improved Adaptive Extended Kalman Filter Algorithm of SINS/GPS Loosely-Coupled Integrated Navigation System

2018 ◽  
Vol 7 (4.27) ◽  
pp. 87
Author(s):  
Yuyan Wang ◽  
Xiuyun Meng ◽  
Jilu Liu
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Navigation System ◽  
Measurement Noise ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Loosely Coupled ◽  
Kalman Filter Algorithm ◽  
Adaptive Extended Kalman Filter

The Kalman Filter algorithm usually cannot estimate noise statistics in real-time, in order to deal with this issue, a new kind of improved Adaptive Extended Kalman Filter algorithm is proposed. Based on residual sequence, this algorithm mainly improves the adaptive estimator of the filter algorithm, which can estimate measurement noise in real-time. Furthermore, this new filter algorithm is applied to a SINS/GPS loosely-coupled integrated navigation system, which can automatically adjust the covariance matrix of measurement noise as noise varies in the system. Finally, the original Extended Kalman Filter and the improved Adaptive Extended Kalman Filter are applied respectively to simulate for the SINS/GPS loosely-coupled model. Tests demonstrate that, the improved Adaptive Extended Kalman Filter reduces both position error and velocity error compared with the original Extended Kalman Filter.  

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