Beamforming-based signal enhancement technologies in passive sonar array processing often have poor performance due to array distortion caused by rapid tactical maneuvers of the towed platform, oceanic currents, hydrodynamic effects, etc. In this paper, an enhanced data-driven shape array estimation formulation is proposed using passive underwater acoustic data. Beamforming based on a hypothetically ideal array is firstly employed to perform the detection of narrow-band components from sources of opportunity, and the corresponding phases of these detected narrow-band components are subsequently extracted to acquire time-delay differences. Then, a weighted outlier-robust Kalman smoother is proposed to acquire enhanced estimates of the time-delay differences, since the underlying properties of slowly changing time-delay differences in the hydrophone array and diverse signal to interference and noise ratios in multiple narrow-band components are explored; and its Cramer–Rao Lower Bound is also provided. Finally, the hydrophone array shape is estimated based on the estimated time delay differences. The proposed formulation fully exploits directional radiated noise signals from distant underwater acoustic targets as sources of opportunity for real-time array shape estimation, and thus it requires neither the number nor direction of sources to be known in advance. The effectiveness of the proposed method is validated in simulations and real experimental data.
With respect to the frequency estimation of a real-valued single-tone, a direct frequency estimation method is proposed to acquire fine-resolution parameter by only utilizing three discrete Fourier transform (DFT) samples around the peak. Inspired by the Quinn, Rife and Candan methods, a novel Candan combined Quinn Rife estimator (CCQRE) is proposed, and the theoretical analysis of the corresponding MSE is also given. It has been verified that the proposed method is more robust to the interbin frequency and has better performance than these existed state-of-the-art methods. Both simulations and real data experiments demonstrate the effectiveness of the proposed method. In addition, the proposed methods are suitable for real-time applications due to the simplicity, efficiency and low computational burden.
This paper presents an iterative method for estimating the starting frequency and period slope of hyperbolic frequency modulated (HFM) signals with underwater acoustic platform colored noise. The method involves, firstly, whitening of the colored noise and, secondly, instantaneous frequency (IF) estimation of HFM signals based on the peak of short-time Fourier transform (STFT) and taking reciprocal of the estimated IF to get the zero crossing interval (ZCI). Parameters estimation of HFM signals is then achieved by using iteratively reweighted least squares (IRLS) linear fitting method to fit the ZCI. The main contributions of our work are threefold: (1) A simple and effective method is proposed to whiten the underwater acoustic platform colored noise; (2) A complex nonlinear problem is transformed into a linear one by the proposed parameters estimation method; (3) The proposed method is applicable for the practical engineering applications.
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