OMP-type Algorithm with Structured Sparsity Patterns for Multipath Radar Signals

Tabea Rebafka (1) , Céline Lévy-Leduc (2) , Maurice Charbit (2)

1 LPMA - Laboratoire de Probabilités et Modèles Aléatoires
2 LTCI - Laboratoire Traitement et Communication de l'Information

A transmitted, unknown radar signal is observed at the receiver through more than one path in additive noise. The aim is to recover the waveform of the intercepted signal and to simultaneously estimate the direction of arrival (DOA). We propose an approach exploiting the parsimonious time-frequency representation of the signal by applying a new OMP-type algorithm for structured sparsity patterns. An important issue is the scalability of the proposed algorithm since high-dimensional models shall be used for radar signals. Monte-Carlo simulations for modulated signals illustrate the good performance of the method even for low signal-to-noise ratios and a gain of 20 dB for the DOA estimation compared to some elementary method.

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Tabea Rebafka, Céline Lévy-Leduc, Maurice Charbit. OMP-type Algorithm with Structured Sparsity Patterns for Multipath Radar Signals. 2011. ⟨hal-00580140⟩