To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a unifor...
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ISBN:
(纸本)9781457705397
To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a uniform linear array, there exist algorithms for autocalibration which exploit the Toeplitz structure of the unperturbed spatial covariance matrix. In this paper, we develop an autocalibration method for 2-D DOA estimation with a uniform rectangular array, in which we exploit a Toeplitz-block Toeplitz structure. We present a simple algorithm for gain and phase estimation, discuss ambiguity problems and evaluate the performance using simulations.
To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a unifor...
详细信息
ISBN:
(纸本)9781457705380
To maintain the performance of direction-of-arrival (DOA) estimation, an accurate model of the array response is required. In a time-varying sensor environment, this is only possible with autocalibration. For a uniform linear array, there exist algorithms for autocalibration which exploit the Toeplitz structure of the unperturbed spatial covariance matrix. In this paper, we develop an autocalibration method for 2-D DOA estimation with a uniform rectangular array, in which we exploit a Toeplitz-block Toeplitz structure. We present a simple algorithm for gain and phase estimation, discuss ambiguity problems and evaluate the performance using simulations.
Based on the symmetrically distributed array (SDA) structure and the resultant generalised conjugate symmetric property of its optimum weight vector, a transformation matrix is introduced to preprocess the received ar...
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ISBN:
(纸本)9780819486356
Based on the symmetrically distributed array (SDA) structure and the resultant generalised conjugate symmetric property of its optimum weight vector, a transformation matrix is introduced to preprocess the received array data, after which the original complex-valued optimum weight vector is reduced to a real-valued one, so that in the following weight adaptation we can simply remove imaginary part of the weight vector. As a result of this regularization, improved performance is achieved with much lower computational complexity. There is an undetermined phase factor in the transformation matrix and two different cases are studied with beamforming examples provided for each case, supported by simulation results.
In this study, a low complexity two-dimensional direction-of-arrival (2-D DOA) estimation method is proposed with uniform rectangular array (URA) when uncorrelated and coherent signals coexist. By using a new method o...
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In this study, a low complexity two-dimensional direction-of-arrival (2-D DOA) estimation method is proposed with uniform rectangular array (URA) when uncorrelated and coherent signals coexist. By using a new method of modified estimation of signal parameters via rotation invariance techniques (ESPRIT), the DOAs of uncorrelated signals are first estimated. Afterwards, the contributions of uncorrelated signals are eliminated, and then a new Toeplitz matrix without the information of uncorrelated signals is constructed. Using the product of the Toeplitz matrix and its conjugate transpose matrix, the remaining coherent signals can be resolved. With the two-step processing, the proposed method can resolve more signals with low computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method. The Cramer-Rao bound (CRB) for this signal scenario is also derived.
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