Proceedings of 2013 3rd International Conference on Computer Science and Network Technology 2013
DOI: 10.1109/iccsnt.2013.6967287
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A novel wideband DOA estimation method using direction-free focusing matrix

Abstract: In this paper, a novel DOA estimation method without angles pre-estimating for Wideband Signals is proposed. The main idea is to design a novel Direction-Free focusing matrix using the decomposed representation of the array manifold matrix, where the angle parameter is separated from the array geometry and the frequency parameter. The focusing matrix is derived using a method similar to RSS. The novel method also uses the Toeplitz approximation algorithm to improve the estimation performance. The proposed meth… Show more

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Cited by 9 publications
(5 citation statements)
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References 12 publications
(13 reference statements)
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“…In CSM, rotational signal subspace (RSS) method is one popular way [2], whose focusing matrices are generated by minimising a Frobenius norm of the array manifold errors right leftthickmathspace.5emtrueminPnA0(bold-italicθ)PnAn(bold-italicθ)Fnormals.normalt.PnPnH=bold-italicIwhere the focusing matrix bold-italicPn should be an unitary matrix. Then, we have [8] bold-italicPn=bold-italicUnnormalrfalse(bold-italicUnnormallfalse)normalHwhere bold-italicUnnormall and bold-italicUnnormalr are the left and right singular vectors of the matrix Z=bold-italicAnfalse(θfalse)bold-italicA0false(θfalse)normalH, respectively. Accordingly, the focusing product at the n th frequency is be expressed bold-italicYn=bold-italicPn<...>…”
Section: A Novel Methods For Wideband Doa Estimationmentioning
confidence: 99%
See 1 more Smart Citation
“…In CSM, rotational signal subspace (RSS) method is one popular way [2], whose focusing matrices are generated by minimising a Frobenius norm of the array manifold errors right leftthickmathspace.5emtrueminPnA0(bold-italicθ)PnAn(bold-italicθ)Fnormals.normalt.PnPnH=bold-italicIwhere the focusing matrix bold-italicPn should be an unitary matrix. Then, we have [8] bold-italicPn=bold-italicUnnormalrfalse(bold-italicUnnormallfalse)normalHwhere bold-italicUnnormall and bold-italicUnnormalr are the left and right singular vectors of the matrix Z=bold-italicAnfalse(θfalse)bold-italicA0false(θfalse)normalH, respectively. Accordingly, the focusing product at the n th frequency is be expressed bold-italicYn=bold-italicPn<...>…”
Section: A Novel Methods For Wideband Doa Estimationmentioning
confidence: 99%
“…Estimation of u :û; 1: Fix the focusing frequency f 0 ; 2: Obtain the focusing matrices (8) and 9; 3: Compute Y n = P n X n ; 4: CalculateR by (15); 5: ComputeR w :R w =R − diag(l W )I;…”
Section: Inputmentioning
confidence: 99%
“…It is known that the CSM, which is a classic way of wideband signal processing [ 31 ], can lead to less complexity and better DOA estimation performance. The key point of CSM is to design focusing matrices , whose purpose are to transform the manifold matrices at frequencies to that at the pre-selected reference frequency as follows [ 32 ] where denotes the virtual array manifold matrix at the referenced frequency . Note that rotational signal subspace (RSS) method is a well known way of CSM [ 13 ], whose focusing matrices are gained through minimizing a Frobenius norm of the obtained virtual array manifold errors where should be a unitary matrix, yielding [ 33 ] …”
Section: Wideband Signal Processing Using Virtual Arraymentioning
confidence: 99%
“…This method can achieve high accuracy in a high SNR, but in a low SNR, the accuracy of the algorithm may be greatly affected, and this method cannot effectively deal with the problem of coherent sources [ 32 ]. Moreover, another algorithm, known as the coherent signal subspace method (CSSM) [ 33 , 34 , 35 , 36 , 37 ], is often proposed, which focuses the signal subspace at multiple frequencies to the signal subspace at the reference frequency by constructing a focus matrix and summing these focused covariance matrices to construct a single correlation matrix, after which a high-precision narrowband DOA estimation algorithm can be applied to this covariance matrix to obtain the final estimated value. This algorithm achieves great performance in the case of low SNR, and the process of averaging after focusing can reduce the coherence coefficient between signals.…”
Section: Introductionmentioning
confidence: 99%