Portal de Periódicos da CAPES

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

2371-9877

Emanuele Grossi, Marco Lops, Luca Venturino,

Indoor and Outdoor Localization Technologies

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.