V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
| Autor: | David Bryant, Colin Fox, Matthew Parry, Zhanglong Cao, T. C. A. Molteno |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
piecewise continuous TP1-1185 01 natural sciences Biochemistry cross-validation Article Cross-validation Analytical Chemistry 010104 statistics & probability Acceleration Position (vector) 0502 economics and business 0101 mathematics Electrical and Electronic Engineering Instrumentation adaptive penalty 050210 logistics & transportation Chemical technology 05 social sciences hermite spline basis functions Atomic and Molecular Physics and Optics Term (time) Spline (mathematics) Computer Science::Graphics Piecewise Trajectory Algorithm Smoothing |
| Zdroj: | Sensors Volume 21 Issue 9 Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 3215, p 3215 (2021) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s21093215 |
| Popis: | Trajectory reconstruction is the process of inferring the path of a moving object between successive observations. In this paper, we propose a smoothing spline—which we name the V-spline—that incorporates position and velocity information and a penalty term that controls acceleration. We introduce an adaptive V-spline designed to control the impact of irregularly sampled observations and noisy velocity measurements. A cross-validation scheme for estimating the V-spline parameters is proposed, and, in simulation studies, the V-spline shows superior performance to existing methods. Finally, an application of the V-spline to vehicle trajectory reconstruction in two dimensions is given, in which the penalty term is allowed to further depend on known operational characteristics of the vehicle. |
| Databáze: | OpenAIRE |
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