Artigo Revisado por pares

Track-before-detect for multiframe detection with censored observations

2014; Institute of Electrical and Electronics Engineers; Volume: 50; Issue: 3 Linguagem: Inglês

10.1109/taes.2013.130148

ISSN

2371-9877

Autores

Emanuele Grossi, Marco Lops, Luca Venturino,

Tópico(s)

Indoor and Outdoor Localization Technologies

Resumo

In this work, we address the problem of target detection from multiple noisy observations produced by a generic sensor. A two-step approach is considered, wherein a censoring stage retains the significant measurements (i.e., those whose likelihood ratio exceeds a primary threshold) in each frame, while a multiframe detector elaborates the preprocessed observations and takes the final decision through a generalized likelihood ratio test. A dynamic programming algorithm to form the decision statistic, which exploits the sparse nature of the censored observations, is proposed. A closed-form complexity analysis is provided, and a thorough performance assessment is undertaken to elicit the tradeoffs among censoring level, system complexity, and achievable performance.

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