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Direction-of-arrival estimation in the presence of gain and phase errors is investigated from the phase retrieval (PR) perspective. In order to remove the influence of phase errors, they are isolated by taking the absolute values of the elements in the compensated covariance matrix. Finally, the formulated nonconvex PR optimization problem is solved by utilizing the feasible point pursuit algorithm...
For GPS (Global Position System) receivers, the nonstationary interferences may result from rapid relative motion between interference and GPS receiver, a change in the number of interferences and impulse interference, etc. The conventional interference suppression algorithms based on covariance matrix are ineffective with nonstationary interferences. By utilizing the sparse representation, a new...
In this paper, a modified Range-Doppler (RD) algorithm with the Keystone Transform and the rank-deficient Capon is proposed for the shorter Synthetic Aperture Radar (SAR) imaging in the high squint mode. With the decrease of the aperture time under the squint mode, the linear range-walk becomes the dominant part of the range migration. The Keystone Transform is well suitable for removal of the range...
For airborne radar, the estimation performance of moving target parameters is greatly affected by the residuals of ground clutter after space-time adaptive processing (STAP). The non-homogeneity of environment, which results in the lack of available secondary data, will make this problem worse. In this paper, a novel method, which utilizes small amount of secondary data, is proposed for getting more...
In this paper, a new spectral estimation method, which is based on the rank-deficient sample covariance matrix, is proposed. The new method applies the amplitude and phase estimation (APES) filter and the Capon weight simultaneously on the data matrix to obtain the complex amplitude estimate of the spectral line of interest. Because the sample covariance matrix is singular, a rank-deficient version...
Employing singular covariance matrix, spectral estimation methods can give high resolution results. In this paper, the original one-dimensional (1-D) spectral estimation method, which is based on singular covariance matrix, is extended to the case of two-dimensional (2-D). With the few snapshots, forward-backward method is utilized to calculate the sample covariance matrix. Owing to the better estimate...
In this paper, two nonparametric amplitude spectral estimators, which belong to the adaptive filtering-based approach, are proposed. In case of only several snapshots available, the filtering data, which is formed by weighting the snapshots with the traditional Fourier weight vector, contains more larger residual term besides the signal term at the frequency of interest. Those residual term dramatically...
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