Unambiguous sparse recovery of migrating targets with a robustified Bayesian model

Stéphanie Bidon, Marie Lasserre, François Le Chevalier

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
51 Downloads (Pure)

Abstract

The problem considered is that of estimating unambiguously migrating targets observed with a wideband radar. We extend a previously described sparse Bayesian algorithm to the presence of diffuse clutter and off-grid targets. A hybrid-Gibbs sampler is formulated to jointly estimate the sparse target amplitude vector, the grid mismatch, and the (assumed) autoregressive noise. Results on synthetic and fully experimental data show that targets can be actually unambiguously estimated even if located in blind speeds.

Original languageEnglish
Article number8387428
Pages (from-to)108-123
Number of pages16
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume55
Issue number1
DOIs
Publication statusPublished - 2019

Keywords

  • Bayesian sparse recovery
  • high range resolution
  • Metropolis-adjusted Langevin algorithm
  • Monte Carlo Markov chain
  • range migration
  • velocity ambiguities
  • wideband radar

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