A novel autofocusing approach for estimating directions-of-arrival of wideband signals

To solve the problem that the number of signal sources is more than the number of sensors when Gaussian colored noise exists, a fast wideband DOA estimation algorithm based on improved fourth-order cumulant is proposed. The complexity of the traditional fourth-order cumulant algorithm is high which influences the real-time demand. This paper proposes a fast algorithm to improve the traditional methods by eliminating the redundant information of the fourth-order cumulant, and it can reduce the computational complexity and the running time effectively. And the algorithm using the signal subspace method doesn't need angle pre-estimation when constructing the focusing matrix, so it can improve the estimation accuracy obviously. The simulation results show the effectiveness and robustness of the algorithm.

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“…As can be seen from (14),   (13) has no focusing loss, and therefore   l f T is the optimal focusing matrix.…”

Section: Signal Subspace Focusing Algorithmmentioning

confidence: 99%

A fast wideband DOA (direction of arrival) estimation algorithm based on improved fourth-order cumulant

Dou

Zhang

Wang

et al. 2015

2015 4th International Conference on Computer Science and Network Technology (ICCSNT)

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“…In analysing broadband AoA estimation approaches, we first review the parameterised spatial covariance matrix method [6,7] in Sec. 3.1, followed by an auto-focussing approach [5] to coherent signal subspace-based estimation in Sec. 3.2 and polynomial MUSIC [8] in Sec.…”

Section: Broadband Angle Of Arrival Estimationmentioning

confidence: 99%

“…Determining the focussing matrices usually requires a degree of knowledge of the scenario prior to estimation. A recent approach to auto-focussing [5] claims to overcome this problem, and is based on a bin-wise eigenvalue decomposition of covariance matrices.…”

Section: Introductionmentioning

confidence: 99%

Angle of Arrival Estimation for Broadband Signals: A Comparison

Alrmah

Weiss²,

Redif

et al. 2013

IET Intelligent Signal Processing Conference 2013 (ISP 2013)

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This paper reviews and compares three different linear algebraic signal subspace techniques for angle of arrival estimation. These include a polynomial matrix approach to multiple signal classification (MUSIC), a parameterised spatial covariance matrix approach, and an auto-focussing based version of coherent signal subspace estimation applied to MUSIC. These approaches are expressed in the framework of polynomial space-time covariance matrices and their polynomial eigenvalue decomposition, thus highlighting their commonalities and differences. Simulation results comparing the accuracy of these broadband angle of arrival estimation methods are presented.

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“…However, many applications will face a low SNR case inevitably, such as the array sonar which detects the underwater acoustic sources passively. In order to overcome such disadvantages, a class of Coherent Signal-Subspace Method (CSM) has been introduced [3][4][5] , such as RSS [6,7] , MTLS [8] , and so on. The main idea of CSM methods is to transform the components of several decomposed narrowband signals into one narrowband representation at the reference frequency, then the narrowband DOA techniques can be applied to the focused output to get the coherent wideband DOA results.…”

Section: Introductionmentioning

confidence: 99%

A novel wideband DOA estimation method using direction-free focusing matrix

Bo¹,

Xiong²,

Luo³

2013

Proceedings of 2013 3rd International Conference on Computer Science and Network Technology

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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 method combines the RSS method and Toeplitz approximation algorithm, and does not require initial angles, so it can be called Toep-DFRSS method. The performance of Toep-DFRSS and other major methods is compared through computer simulations. The simulations show that Toep-DFRSS method has a better resolution performance and estimation accuracy than conventional RSS method, especially in the case of low SNR.

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A novel autofocusing approach for estimating directions-of-arrival of wideband signals

Cited by 27 publications

References 11 publications

A fast wideband DOA (direction of arrival) estimation algorithm based on improved fourth-order cumulant

A fast wideband DOA (direction of arrival) estimation algorithm based on improved fourth-order cumulant

Angle of Arrival Estimation for Broadband Signals: A Comparison

A novel wideband DOA estimation method using direction-free focusing matrix

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