A critical study of a self-calibrating direction-finding method for arrays

Hung, Eric K.

doi:10.1109/78.275633

Cited by 54 publications

(35 citation statements)

References 3 publications

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“…Nevertheless, these algorithms are usually carried out iteratively, which induces the convergence problem. Also, some self-calibration algorithms do not give unique solutions [16]. In contrast to the first type, the second type requires calibration sources with prior knowledge [17,18].…”

Section: Introductionmentioning

confidence: 99%

A subspace‐based channel calibration algorithm for geosynchronous satellite‐airborne bistatic multi‐channel radars

Zhang

Qiu

et al. 2014

IET Radar, Sonar & Navigation

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Ground moving target indication based on geosynchronous (GEO) satellite-airborne (SA) bistatic radar can keep a certain area under continuous surveillance, and thus has important military application values. However, a channel error will affect the clutter suppression performance of the bistatic multi-channel moving target indication radar. And it is found that the channel calibration algorithm used in the long sequence monostatic side-looking synthetic aperture radar, is not applicable to the long sequence translational variant bistatic radar. An improved subspace-based channel calibration algorithm is proposed in this study to deal with channel errors of the GEO SA bistatic multi-channel radar. The algorithm utilises the clutter as calibrated sources, and estimates channel error parameters by minimising the projections of the calibrated sources onto the noise subspace. As the channel errors are estimated from the data, the proposed algorithm does not need any extra calibration sources. Also, the proposed algorithm does not have the limitation of the traditional array self-calibration algorithms, which may have non-unique estimations under the condition of linear arrays. Besides, it avoids finding the inversion of large-size matrix and calculating with any iteration, and hence it is efficient. Moreover, the proposed algorithm can estimate channel errors that vary with azimuth. Simulations are performed to validate the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

A subspace‐based channel calibration algorithm for geosynchronous satellite‐airborne bistatic multi‐channel radars

Zhang

Qiu

et al. 2014

IET Radar, Sonar & Navigation

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“…Online methods can also be found in the literature [68][69][70][71][72][73][74][75][76][77][78] and are also known as autocalibration, selfcalibration, or blind-calibration methods. These methods estimate the coupling matrix on a continuous basis during the operation of the antenna system using signals in the environment and have the practical advantage of adapting to a changing electromagnetic environment, which is a difficult problem when the antenna system is located near potential scatterers.…”

Section: Introductionmentioning

confidence: 99%

Unifying the Theory of Mutual Coupling Compensation in Antenna Arrays

Henault

Antar

2015

IEEE Antennas Propag. Mag.

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The limitations of current mutual coupling compensation methods in antenna arrays are thoroughly reviewed. The theory of mutual coupling compensation is unified in such a way that efficient methods can be employed for calibrating both transmit and receive systems having arbitrary geometries. The theory leads to methods that can evaluate mutual coupling using either theoretical or experimental means. Reciprocity is studied through the careful comparison of receive and transmit analytical formulations. Examples involving various applications are presented for the validation of the theory. This theory has numerous applications and contributes to the areas of antenna theory, mutual coupling analysis, complex structure modeling, and antenna measurements.

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“…However, such an assumption is often far from reality, as the steering vector in real systems may be distorted by impairments such as mutual coupling, array gain/phase uncertainties [4], and sensor position perturbation [5]. Since the presence of mutual coupling would lead to considerable deteriorations in direction finding of conventional high-resolution direction-of-arrival (DOA) estimation algorithms, mutual coupling calibration has received extensive attention over the last decades [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…The classical mutual coupling auto-calibration method proposed by Friedlander and Weiss [11] and a more recent one proposed by Sellone and Serra [12] are able to estimate DOAs and mutual coupling coefficients using an iterative procedure. However, since a large number of unknown parameters are involved in these two methods, their high computational complexities may be prohibitive for real-time applications and the convergence may not be guaranteed [13,14].…”

Section: Introductionmentioning

confidence: 99%