Atomic norm minimization-based dimensionality-reducible two-dimensional out-of-lattice DOA estimation method
A technique of minimization and norm, which is applied in the field of radar communication and array signal processing, can solve problems such as lattice point mismatch and reduce the amount of calculation, and achieve the effect of overcoming poor effect, reducing the amount of calculation, and realizing the decoherence operation
Active Publication Date: 2021-11-19
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Aiming at the above problems, as well as the fact that many algorithms are difficult to simultaneously reduce the amount of calculation, solve the problem of coherent signal estimation, solve the problem of low signal-to-noise ratio estimation and solve the problem of grid point mismatch under the multi-snapshot receiving data model, a new method is proposed. A dimensionality-reducible two-dimensional planar gridless DOA estimation method based on atomic norm minimization, which is a dimensionality-reducible gridless DOA estimation method for two-dimensional planar arrays
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[0029] The specific implementation manner and working principle of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0030] Such as figure 2 As shown, the X axis is perpendicular to the YOZ plane. For a better description, the following definitions are first made:
[0031] Azimuth θ(-90°, 90°): the angle between the projection of the ray on the XOY plane and the X axis (normal);
[0032] Pitch angle ψ(-90°,90°): the angle between the ray and the XOY plane projection;
[0033] Uniform rectangular planar array: The array elements are evenly distributed on the YOZ plane to form a uniform rectangular planar array, with the origin of the coordinates as the reference point, the array element spacing d on the Y axis y and the array element spacing d on the Z axis z They are all half-wavelength, and N array elements are evenly arranged parallel to the Y-axis direction, and M array elements are evenly arranged parallel ...
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The invention discloses an atomic norm minimization-based dimensionality-reducible two-dimensional out-of-lattice DOA estimation method. The method is characterized by: deforming an array receiving data model by utilizing property of a Kronecker product, and dividing two-dimensional joint angle estimation into two one-dimensional DOA estimation problems through dimensionality reduction, so as to reduce the calculation complexity; respectively introducing an atomic norm minimization ANM theory after dimension reduction, establishing an atomic norm minimization problem under multiple snapshots, converting a non-convex problem into a positive semidefinite programming problem, carrying out solving by using a CVX toolbox, and finally realizing estimation of an azimuth angle and a pitch angle through an esprit algorithm. According to the method, DOA estimation of two-dimensional planar arrays with automatic angle matching can be realized, the problem of grid mismatching can be solved, coherence can be solved, a good estimation effect can be obtained under a low signal-to-noise ratio, and the calculated amount is reduced.
Description
technical field [0001] The invention belongs to the technical field of radar communication and array signal processing, in particular to a two-dimensional off-grid DOA estimation method based on atomic norm minimization and dimensionality reduction. Background technique [0002] Direction of Arrival (DOA) estimation is widely used in array signal processing fields such as radar, sonar, and wireless communication. Among them, the classic methods for DOA estimation include the Multiple Signal Classification (MUSIC) algorithm proposed by Schmidt.R.O et al., the Estimation of Signal Parameter by Rotational Subspace (Estimation of Signal Parameter by Rotational Invariant Techniques, ESPRIT) algorithms, but these algorithms are not suitable for angle estimation when signals are coherent. In 2006, Donoho formally proposed the compressed sensing theory, and Malio utov et al. proposed the L1-SVD algorithm on the compressed sensing theory. Cotter et al. proposed an Orthogonal matchi...
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Login to View More IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/00G06F2218/04G06F18/213Y02D30/70
Inventor 谢菊兰阮铭陈杭陈政宇何子述
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA