JOURNAL ARTICLE

Gaussian-sum cubature Kalman smoothers for bearings-only tracking

Abstract

In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.

Keywords:
Kalman filter Robustness (evolution) Gaussian Mathematics Upper and lower bounds Square root Algorithm Computer science Control theory (sociology) Applied mathematics Mathematical optimization Statistics Mathematical analysis Artificial intelligence Geometry Physics

Metrics

1
Cited By
0.48
FWCI (Field Weighted Citation Impact)
21
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering
Maritime Navigation and Safety
Physical Sciences →  Engineering →  Ocean Engineering

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