Paper Info
Title
Joint Smoothing And Tracking Based On Continuous-Time Target Trajectory Function Fitting
Abstract
This paper presents a joint trajectory smoothing and tracking framework for a specific class of targets with smooth motion. We model the target trajectory by a continuous function of time (FoT), which leads to a curve fitting approach that finds a trajectory FoT fitting the sensor data in a sliding time-window. A simulation study is conducted to demonstrate the effectiveness of our approach in tracking a maneuvering target, in comparison with the conventional filters and smoothers.Note to Practitioners-Estimation, such as automatically tracking and predicting the movement of an aircraft, a train, or a bus, plays a key role in our daily life. In this paper, we provide a new approach for the online estimation of the target trajectory function by means of fitting the time-series observation, which accommodates the lack of quantifiable knowledge about the target motion and of the statistical property of the sensor observation noise. The resulting trajectory function can be used to infer either the past or the present state of the target. Engineering-friendly strategies are provided for computationally efficient implementation. The proposed approach is particularly appealing to a broad range of real-world targets that move in smooth courses, such as passenger aircraft and ships.
Year
DOI
Venue
2017
10.1109/TASE.2018.2882641
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
Keywords
Field
DocType
Filtering, smoothing, target tracking, trajectory fitting, weighted least squares
Data modeling,Continuous function,Curve fitting,Computer science,Algorithm,Control engineering,Sensor observation,Smoothing,Hidden Markov model,Trajectory
Journal
Volume
Issue
ISSN
16
3
1545-5955
Citations 
PageRank 
References 
2
0.37
17
Authors
4
Name
Order
Citations
PageRank
Tiancheng Li1157761.01
Huimin Chen250.75
Shudong Sun336128.11
Juan M. Corchado42899239.10