Two-Stage Point Mass Filter on Terrain Referenced Navigation for State Augmentation

Park, Yong-gonjong; Park, Chan Gook

doi:10.2514/1.g003936

Cited by 5 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The TAN algorithm based on TERCOM and particle filter proposed by [9] can effectively solve the problem of filter divergence caused by inaccurate mathematical model, improve the accuracy of parameter estimation and make the system more robust. The two‐stage filters are used for state estimation, which not only improves the estimation performance, but also improves the computational efficiency [10, 11]. However, for more than three state estimation, it will produce more computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Optimal selection and adaptability analysis of matching area for terrain aided navigation

Chen

Zhang

Zhao

2021

IET Radar Sonar & Navi

View full text Add to dashboard Cite

The existing terrain aided navigation (TAN) has the disadvantage that the navigation performance is limited by the size of matching area and terrain features. Therefore, this study proposes a method of optimal selection and adaptability analysis of matching area for TAN. According to the heading angle of the carrier, inertial navigation system positioning error and performance index, the optimal matching area is selected in real time. First, the matching area selection and adaptability analysis are carried out, and the influence of the matching area on the positioning performance is analysed by using the Beijing Internal TAN II algorithm. Then, the model parameters of the optimal matching area are determined through theoretical calculation and simulation. Finally, it is compared with the typical matching area selecting method. The test results show that the optimal selection and adaptability analysis method can improve the computational efficiency of TAN system, and improve the positioning accuracy of TAN system.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimal selection and adaptability analysis of matching area for terrain aided navigation

Chen

Zhang

Zhao

2021

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

“…TERCOM technology is relatively mature, but it cannot effectively deal with process noise and observation noise [15,16]. Among the three common regression filtering methods, Kalman filter [17,18], point mass filter [19,20], particle Filter (PF) [21,22], Kalman filter requires the observation to be Gaussian distribution; it is not suitable for the application in non-Gaussian parameter situation. e point mass filter can solve the expression of non-Gaussian observations, but it needs to calculate the whole posterior distribution space, which requires a large amount of calculation.…”

Section: Introductionmentioning

confidence: 99%

Underwater Terrain-Aided Navigation Relocation Method in the Arctic

Liu

Che

2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

To solve the localization failure problem of terrain-aided navigation (TAN) system of the autonomous underwater vehicle (AUV) caused by large area of underwater flat terrain in the Arctic, a navigation system with relocation part is constructed to enhance the robustness of localization. The system uses particle filter to estimate the AUV’s position and reduce the nonlinear noise disturbance, and the prior motion information is added to avoid the mismatching caused by the similar altitude of low-resolution map. Based on the estimate data and the measured altitude data, the normalized innovation square (NIS) is used to evaluate the differentiation of terrain sequence, and the differentiation is used as a judgment of whether the AUV is in the switch location. A simulation experiment is carried out on the 500 m resolution underwater map of the Arctic. The results show that adding the prior motion information can restrain the divergence of the estimator; NIS can accurately reflect the sharp change of terrain sequence. After the relocation process, the AUV can still maintain the positioning accuracy within 2 km after running 50 km in the area including flat and rough terrain. This research solves the problem of localization errors in the Arctic flat terrain in the system level and provides a solution for the application of underwater navigation in the Arctic.

show abstract

Robust Two-Stage Filtering for INS/Gravity Matching Passive Integrated Navigation Systems

Luo

Cai

et al. 2022

IEEE Sensors J.

View full text Add to dashboard Cite

Two-Stage Point Mass Filter on Terrain Referenced Navigation for State Augmentation

Cited by 5 publications

References 14 publications

Optimal selection and adaptability analysis of matching area for terrain aided navigation

Optimal selection and adaptability analysis of matching area for terrain aided navigation

Underwater Terrain-Aided Navigation Relocation Method in the Arctic

Robust Two-Stage Filtering for INS/Gravity Matching Passive Integrated Navigation Systems

Contact Info

Product

Resources

About