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Article Dans Une Revue Sensors Année : 2017

DOA Finding with Support Vector Regression based Forward-Backward Linear Prediction,

Résumé

Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and limited number of snapshots. The forward-backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This paper proposes to combine together the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots and signal-to-noise ratios (SNRs). Simulation results show the effectiveness of the proposed method.

Dates et versions

hal-01527219 , version 1 (24-05-2017)

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Jingjing Pan, Yide Wang, Cédric Le Bastard, Tianzhen Wang. DOA Finding with Support Vector Regression based Forward-Backward Linear Prediction,. Sensors, 2017, 17 (6), pp.1225. ⟨10.3390/s17061225⟩. ⟨hal-01527219⟩
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