An Approach to Outlier Detection and Smoothing Applied to a Trajectography Radar Data

Authors

  • Aguinaldo Bezerra Batista Jr. Centro de Lançamento da Barreira do Inferno - CLBI
  • Paulo S. Motta Pires Universidade Federal do Rio Grande do Norte - UFRN

Keywords:

Trajectory, Radar, Filtering, Smoothing, Outlier detection.

Abstract

The tracking of aerospace engines is reasonably achieved through a trajectography radar system that generally yields a disperse cloud of samples on tridimensional space, which roughly describes the engine trajectory. It is proposed an approach on cleaning radar data to yield a well behaved and smooth output curve that could be used as basis for instant and further analysis by radar specialists. This approach consists on outlier detection and smoothing phases based on established techniques such as Hampel filter and local regression (LOESS). To prove the effectiveness of the approach, both filtered and unfiltered data are submitted to an extrapolation method, and the results are compared

Author Biographies

Aguinaldo Bezerra Batista Jr., Centro de Lançamento da Barreira do Inferno - CLBI

Aguinaldo Bezerra, M.Sc.

Computer Engineer

Works as systems analyst at the IT Department of CLBI

Paulo S. Motta Pires, Universidade Federal do Rio Grande do Norte - UFRN

Prof. Paulo S. Motta Pires, D.Sc.

Professor at UFRN

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Published

2014-09-13

Issue

Section

Original Papers