A 2-D robust high-resolution frequency estimation approach

Berthoumieu, Yannick; Ansari, Mohamed El; Aksasse, Brahim; Donias, Marc; Najim, M.

doi:10.1016/j.sigpro.2004.12.009

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…Q H N is a sparse unitary matrix that transforms v N (ψ) into a realvalued manifold, i.e., d N (ψ) = Q H N v N (ψ). 2) Consider an NM × P real-valued matrix as (10) where vec(·) maps an N × M matrix to an NM × 1 vector by stacking the columns of the matrix. According to the 2-D U-ESPRIT technique, when V(ψ) satisfies (4), the following equations hold true:…”

Section: A Estimation Of the Locations Of The Isolated Scatterersmentioning

confidence: 99%

“…To overcome the limitation of resolutions in FFT-based ISAR imaging algorithms, superresolution imaging algorithms, such as 2-D multiple signal classification (MUSIC) [9] and 2-D ESPRIT [10], have been introduced. The MUSIC algorithm proposed by Schmidt [11] returns the pseudospectrum at all frequency samples; however, it has to involve an additional exhaustive searching procedure, which causes a very large amount of computations.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Cross-Range Scaling Method via Two-Dimensional Unitary ESPRIT Scattering Center Extraction Algorithm

Wang

Zhang

Zhao

2015

IEEE Geosci. Remote Sensing Lett.

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For a better understanding of the inverse synthetic aperture radar (ISAR) image, cross-range scaling is an essential step. To deal with the scaling problem of ISAR image, this letter proposes a novel cross-range scaling algorithm for ISAR image. This method consists of three steps. In the first step, joint time-frequency method is employed to compensate the rotational motion and generate 2-D ISAR images at two selected times. Theoretically, after rotating the angular shift between the two images, they present the same appearance. However, conventional image rotation is computationally inefficient and complex for implementation. Thus, in the second step, we propose a 2-D unitary estimation of parameters via rotation invariance technique (ESPRIT) superresolution ISAR imaging technique to extract isolated scatterers instead of conventional ISAR image. In the last step, we search rotation velocity (RV) and rotate the image by angular shift to find the right RV that makes the two selected images match each other best. Finally, simulated and real ISAR data are provided to demonstrate the effectiveness and correctness of the proposed cross-range scaling algorithm.Index Terms-Inverse synthetic aperture radar (ISAR) crossrange scaling, scattering center extraction, 2-D unitary ESPRIT (U-ESPRIT).

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Section: A Estimation Of the Locations Of The Isolated Scatterersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Cross-Range Scaling Method via Two-Dimensional Unitary ESPRIT Scattering Center Extraction Algorithm

Wang

Zhang

Zhao

2015

IEEE Geosci. Remote Sensing Lett.

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“…That is, the locations of the scattering centres can be determined only within the Fourier resolution cells, thus this method results in relatively low resolution and poor precision. With regard to the latter, multiple signal classification (MUSIC) [9, 10] and estimation of signal parameters via rotational invariance techniques (ESPRITs) [11–14] are the two most popular super resolution algorithms for parameters estimation. The MUSIC algorithm [15] returns the pseudospectrum at all frequency samples; however, it has to involve an exhaustive search for spectral peaks which is time‐consuming.…”

Section: Introductionmentioning

confidence: 99%

Three‐dimensional super resolution ISAR imaging based on 2D unitary ESPRIT scattering centre extraction technique

Zhao

Min

Wang³

et al. 2017

IET Radar, Sonar & Navigation

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“…The 3D DOA estimation problem for one fixed wavelength is hence equivalent to estimating the 2D (spatial) frequency parameters ✓ k [3]. A significant number of methods have been proposed in the literature for this problem, often extending methods for 1D spectral line estimation (such as the ESPRIT method) to the 2D case, see, e.g., [4]- [7]. While they have been successfully used in applications, most methods are affected by at least one of the following conceptual limitations.…”

Section: Introductionmentioning

confidence: 99%

A method for 3D direction of arrival estimation for general arrays using multiple frequencies

Андерссон

Carlsson

Tourneret

et al. 2015

2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

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We develop a novel high-resolution method for the estimation of the direction of incidence of energy emitted by sources in 3D space from wideband measurements collected by a planar array of sensors. We make use of recent generalizations of Kronecker's theorem and formulate the direction of arrival estimation problem as an optimization problem in the space of sequences generating so called "general domain Hankel matrices" of fixed rank. The unequal sampling at different wavelengths is handled by using appropriate interpolation operators. The algorithm is operational for general array geometries (i.e., not restricted to, e.g., rectangular arrays) and for equidistantly as well as unequally spaced receivers. Numerical simulations for different sensor arrays and various signal-to-noise ratios are provided and demonstrate its excellent performance.

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A 2-D robust high-resolution frequency estimation approach

Cited by 8 publications

References 28 publications

Efficient Cross-Range Scaling Method via Two-Dimensional Unitary ESPRIT Scattering Center Extraction Algorithm

Efficient Cross-Range Scaling Method via Two-Dimensional Unitary ESPRIT Scattering Center Extraction Algorithm

Three‐dimensional super resolution ISAR imaging based on 2D unitary ESPRIT scattering centre extraction technique

A method for 3D direction of arrival estimation for general arrays using multiple frequencies

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