Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A New Method for Estimating the Number of Harmonic Components in Noise with Application in High Resolution Radar | EURASIP Journal on Applied Signal Processing 2004 8 1177-1188 2004 Hindawi Publishing Corporation A New Method for Estimating the Number of Harmonic Components in Noise with Application in High Resolution Radar Emanuel Radoi Laboratoire E3I2 Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d Armement ENSIETA 2 rue Francois Verny 29806 Brest France Email radoiem@ Andre Quinquis Laboratoire E3I2 Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d Armement ENSIETA 2 rue Francois Verny 29806 Brest France Email quinquis@ Received 18 February 2003 Revised 8 December 2003 Recommended for Publication by Bjorn Ottersten In order to operate properly the superresolution methods based on orthogonal subspace decomposition such as multiple signal classification MUSIC or estimation of signal parameters by rotational invariance techniques ESPRIT need accurate estimation of the signal subspace dimension that is of the number of harmonic components that are superimposed and corrupted by noise. This estimation is particularly difficult when the S N ratio is low and the statistical properties of the noise are unknown. Moreover in some applications such as radar imagery it is very important to avoid underestimation of the number of harmonic components which are associated to the target scattering centers. In this paper we propose an effective method for the estimation of the signal subspace dimension which is able to operate against colored noise with performances superior to those exhibited by the classical information theoretic criteria of Akaike and Rissanen. The capabilities of the new method are demonstrated through computer simulations and it is proved that compared to three other methods it carries out the best trade-off from four points of view S N ratio in white noise frequency band of colored noise dynamic range of the harmonic component amplitudes and computing time. Keywords and phrases superresolution methods subspace
