The propagator method for source bearing estimation

Marcos, Sylvie; Marsal, A.; Benidir, M.

doi:10.1016/0165-1684(94)00122-g

Cited by 420 publications

(249 citation statements)

References 8 publications

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“…In the noise free case, it can be shown that U o = −V as discussed in [9,20]. So the RMSE in (44a) and (45) differ only by the numerator value.…”

mentioning

confidence: 93%

“…A possible alternative to the MUSIC method for source bearing estimation with arrays consisting of a large number of sensors is the propagator method (PM). Marcos et al [9] have proposed the so-called 'propagator, method for array signal processing without any eigen-decomposition. The propagator is a linear operator based on a partition of the steering vectors, and was found to be a very effective tool for estimating the DOAs.…”

Section: Introductionmentioning

confidence: 99%

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Direction of Arrival Estimation Based on Fourth-Order Cumulant Using Propagator Method

Palanisamy

2009

PIER B

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Abstract-In this paper direction-of-arrival estimation (DOA) of multiple narrow-band sources, based on higher-order statistics using propagator, is presented. This technique uses fourth-order cumulants of the received array data instead of second-order statistics (autocovariance) and then the so-called propagator approach is used to estimate the DOA of the sources. The propagator is a linear operator which only depends on the array steering vectors and which can be easily extracted from the received array data. But it does not require any eigendecomposition of the cumulant matrix of the received data like MUSIC algorithm. Computer simulations are carried out to compare the performance of the proposed method to those of methods based on auto-covariance using MUSIC and propagator algorithms.

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“…In the noise free case, it can be shown that U o = −V as discussed in [9,20]. So the RMSE in (44a) and (45) differ only by the numerator value.…”

mentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Direction of Arrival Estimation Based on Fourth-Order Cumulant Using Propagator Method

Palanisamy

2009

PIER B

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“…We can make a common assumption like many previous works [9][10] that the array manifold B is of full rank and the K rows of B are linearly independent. Then the other (2M-K) rows of B can be expressed as a linear combination of the former K rows.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

“…The work in [8] proposed a low complexity algorithm with an unsatisfied estimation performance. And the work in [11] which also needs 2-D search is based on the OPM algorithm [14], which utilizes the propagator to obtain the noise subspace and estimates nominal DOAs and angular spreads through a similar spectrum search like DSPE-CD [7]. In this letter, a successive propagator method (S-PM) algorithm was proposed to further reduce the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Localization of coherently distributed source using a successive propagator method

Cheng¹,

Yang²,

Liu³

et al. 2017

Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

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Abstract. In this letter, the localization of coherently distributed (CD) is considered. With regard to the direction finding of CD source, the conventional method distributed source parameter estimation (DSPE) can provide stable estimation performance, while it also requires a complex two-dimensional spectral peak search for both nominal direction-of-arrivals (DOAs) and angular spreads. Thus, with rank reduction criterion, we derived a successive propagator method (S-PM) which exploits three decoupled one-dimensional search to replace an extensive one-dimension search to reduce the heavy cost. And the proposed algorithm can avoid the high-complexity eigen-decomposition procedure by using the linear operator-propagator. When compared to the convention ESPRIT-CD [8], S-PM has a better estimation performance with a low complexity. Several simulation results illustrate the effectiveness and improvements of the proposed algorithm.

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“…In [5], a polynomial root-finding-based method was proposed using two parallel ULAs, by decoupling the 2-D problem into two 1-D problems to reduce the computational complexity. Another computationally efficient method was proposed in [6], where the propagator method in [7] was employed based on two parallel ULAs. However, this method requires pair matching between the 2-D azimuth and elevation estimation results and may not work effectively for some situations.…”

Section: Introductionmentioning

confidence: 99%

Direction finding and mutual coupling estimation for uniform rectangular arrays

Hou

Chen

et al. 2015

Signal Processing

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A novel two-dimensional (2-D) direct-of-arrival (DOA) and mutual coupling coefficients estimation algorithm for uniform rectangular arrays (URAs) is proposed. A general mutual coupling model is first built based on banded symmetric Toeplitz matrices, and then it is proved that the steering vector of a URA in the presence of mutual coupling has a similar form to that of a uniform linear array (ULA). The 2-D DOA estimation problem can be solved using the rank-reduction method. With the obtained DOA information, we can further estimate the mutual coupling coefficients. A better performance is achieved by our proposed algorithm than those auxiliary sensor-based ones, as verified by simulation results.

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The propagator method for source bearing estimation

Cited by 420 publications

References 8 publications

Direction of Arrival Estimation Based on Fourth-Order Cumulant Using Propagator Method

Direction of Arrival Estimation Based on Fourth-Order Cumulant Using Propagator Method

Localization of coherently distributed source using a successive propagator method

Direction finding and mutual coupling estimation for uniform rectangular arrays

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