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Sources localization is an important theme of antenna and signal processing researches since decades. It has a lot of applications for source characterization, which leads to object detection, used in submarine eld as well as seismic and remote sensing studies. The particularity of array processing is that we are looking at spatio-temporal vector signals which are generated by both radiating sources or reected by buried objects and ambient medium. These signals are generally corrupted by an additive noise. When the number of sources is greater than the number of the sensors of the smart antenna system, classical methods become unusable. Recently, a new subspace method called incoherent sensor by sensor processing (ISSP) for estimation of directions of arrival (DOAs) is proposed. It is based on a study sensor by sensor to estimate rstly times of arrival(TOAs), then the DOAs of the sources are estimated. The main drawback of this method is the computational load needed to estimate accurately the DOAs. In this paper, we propose new faster methods thanks to the numerical complexity reduction of the existing algorithms. This last point is important nowadays to make embedded systems faster.

About Times of Arrival Estimation for Sources and Buried Objects Localization