THE PROPAGATOR METHOD FOR SOURCE BEARING ESTIMATION

This paper investigates the propagator method as a possible alternativ e to the MUSIC method for source bearing estimation with arrays consis ting of a large number of sensors. Indeed, the propagator method (PM) is a subspace-based method which does not require the eigendecompositi on of the cross-spectral matrix (CSM) of the received signals. The pro pagator is a linear operator which only depends on the steering vector s and which can be easily extracted from the data. We here propose a n ew version of the propagator method referred to as the orthonormal pro pagator method (OPM). The performance of the PM and the OPM is theoret ically analysed in terms of the mean squared error on the source beari ng estimates and in terms of computational complexity. The performance results are then compared to those of MUSIC. We find that at high and medium signal-to-noise ratio, the OPM performs quite like MUSIC with a complexity reduced by the ratio of the number of sources to the numb er of sensors. Simulations are presented to strengthen the theoretical results. At low signal-to-noise ratio, the OPM can also perform like MUSIC when the assumed number of sources is slightly overestimated.