Abstract. Direction of arrival (DOA) estimation is an important problem in array signal processing. An effective multiple signal classification (MUSIC) method based on the short-time Fourier transform (STFT) and forward/ backward spatial smoothing (FBSS) techniques for the DOA estimation problem of multiple time-frequency (t-f) joint LFM sources is addressed. Previous work in the area e. g. STFT-MUSIC algorithm cannot resolve the t-f completely or largely joint sources because they can only select the single-source t-f points. The proposed method constructs the spatial t-f distributions (STFDs) by selecting the multiple-source t-f points and uses the FBSS techniques to solve the problem of rank loss. In this way, the STFT-FBSS-MUSIC algorithm can resolve the t-f largely joint or
Traditional subspace methods which are based on the spatial time-frequency distribution (STFD) matrix have been investigated for direction-of-arrival (DOA) estimation of linear frequency modulation (LFM) signals. However, the DOA estimation performance may degrade substantially when multiple LFM signals are spectrally overlapped in time-frequency (TF) domain. In order to solve this problem, this paper proposes single-source TF points selection algorithm based on Hough transform and short-time Fourier transform (STFT). Firstly, the signal intersections in TF domain can be solved based on the Hough transform, and multiple-source TF points around the intersections are removed, so that the single-source TF points set is reserved. Then, based on the Euclidean distance operator, the single-source TF points set belonging to each signal can be obtained according to the property that TF points of the same signal have same eigenvector. Finally, the averaged STFD matrix is constructed for each signal, and DOA estimation is achieved based on multiple signal classification (MUSIC) algorithm. In this way, the proposed algorithm exhibit remarkable superiority in estimation accuracy and angular resolution over the state-of-the-art schemes and can achieve DOA estimation in the underdetermined cases. In addition, the proposed algorithm can still perform DOA estimation when multiple LFM signals intersect at one point. Numerical simulations demonstrate the validity of the proposed method.
Abstract-In order to improve the angle measurement precision with a low computational complexity, a 2-D direction of arrival (DOA) estimation algorithm UCA-TF-MI-ESPRIT is proposed in this paper. This algorithm is based on the mode space algorithm and the time-frequency (TF) multiple invariance rotational invariance technique (MI-ESPRIT). Firstly, a uniform circular array (UCA) is equivalent to a virtual uniform linear array (ULA) by utilizing mode-space algorithm. Then, the smoothed pseudo Wigner-Ville distribution (SPWVD) of the ULA output is calculated. The spatial time-frequency matrix can be obtained through the average of multiple time-frequency points in the time-frequency plane, and the signal subspace can also be obtained through using eigen decomposition. Then a simple and effective subarray dividing approach is proposed, and the multiple rotational invariant equation of the array is obtained by using the Bessel function. Finally, the closed-form solution is obtained using multi-leastsquares (MLS) criterion so that the 2-D DOA estimation of LFM signals in UCA is completed. The simulation results verify the effectiveness of the algorithm proposed by this paper.
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