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ABSTRACT: Joint Doppler shift and time delay estimation is an important topic in radar, sonar and communication applications. Least square (LS) is a classical and effective method for solving the problem. However, the performance degrades severely in the scenario of low ratio of signal-noise (SNR), due to the instability of matrix inversing. In this paper, a high-resolution method is proposed basing on the compressive sampling theory. The 2-dimension channel response can be sparsely recovered, and high-resolution Doppler shift-time delay estimation can be described with an underdetermined equation solving problem. Three categories of algorithms, including diagonal loading least squares, [script-l](1) Regularization, and Greedy Pursuit, are adopt to solve the problem and show outstanding resolving capabilities. The three categories of algorithms are analyzed and compared in different conditions. For the dictionary appears not to have unit norm columns, Greedy pursuit is not good as [script-l](1) Regularization in general, and simulation results demonstrate it.
The Journal of the Acoustical Society of America 04/2012; 131(4):3482. · 1.55 Impact Factor
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ABSTRACT: Acoustic signal processing in shallow water environments is a challenging problem because of the presence of reverberation. Based on some models of reverberation, data from sensors array is pretreated to suppress reverberation. Considering reverberation as a sum of echoes of transmitted signal, the principal component inverse (PCI) algorithm is operated by deleting the largest singulars of data matrix, which is reconstructed by array data. However, the amount of calculation is very large because the construction of data matrices is complex and singular decomposition is needed. In this paper, the construction is simplified. As a result, computing quantity of PCI is reduced. After PCI-pretreatment, broadband direction-of-arrival is estimated by diagonal loading beamforming. According to a simulation which takes broadband linear modulated frequency signal as transmitted signal, with PCI-pretreatment the performance of DOA estimation can be improved.
Image and Signal Processing, 2008. CISP '08. Congress on; 06/2008
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ABSTRACT: Acoustic signal processing in shallow water environments is a challenging problem because of the presence of reverberation. Based on some models of reverberation, data from sensors array is pretreated to suppress reverberation. Considering reverberation as a sum of echoes of transmitted signal, the principal component inverse (PCI) algorithm deletes the largest singulars of data matrix, which is constructed from array data. However, estimating a threshold which is needed in PCI is difficult in practice. In this paper, two new subspace methods, Deleting Big Eigenvalues and Subspace Projection are proposed. The two novel methods, substituting automatic signal-number estimation for threshold estimation, are operated via eigendecomposition. According to a simulation which takes broadband linear modulated frequency signal as transmitted signal, these two methods show a similar performance but smaller computing quantity compared with PCI.
The Journal of the Acoustical Society of America 06/2008; 123(5):3951. · 1.55 Impact Factor
