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The Modified ESPRIT Method Under Low SNR Condition

Zhengya Zhang

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Abstract

In low SNR,a new multistage wiener filtering(MSWF)suitable for ESPRIT is proposed for the instant problem among direction-of-arrival(DOA) estimation of signals. Firstly,the MSWF is combined with ESPRIT. Then subspace can be acquired through spatially smoothed forward recursion of the multistage wiener filtering,not through the matrix eigenvalue decomposition. In low SNR,the noise subspace leaked to the signal subspace,a discriminated method is proposed to find a more accurate signal subspace. The DOA of singles can be estimated combining with the subspace kind algorithms such as ESPRIT. Because this algorithm has realized the judgment of the real signal subspace,it has higher estimation precision than the traditional algorithm based on MSWF. Especially in low SNR,enhance the practicability of the algorithm. Simulation results verify that the proposed algorithm is effective.

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What this paper is about

In low SNR,a new multistage wiener filtering(MSWF)suitable for ESPRIT is proposed for the instant problem among direction-of-arrival(DOA) estimation of signals. Firstly,the MSWF is combined with ESPRIT. Then subspace can be acquired through spatially smoothed forward recursion of the multistage wiener filtering,not through the matrix eigenvalue decomposition. In low SNR,the noise subspace leaked to the signal subspace,a discriminated method is proposed to find a more accurate signal subspace. The DOA of singles can be estimated combining with the subspace kind algorithms such as ESPRIT. Because this algorithm has realized the judgment of the real signal subspace,it has higher estimation precision than the traditional algorithm based on MSWF. Especially in low SNR,enhance the practicability of the algorithm. Simulation results verify that the proposed algorithm is effective.

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Available abstract

In low SNR,a new multistage wiener filtering(MSWF)suitable for ESPRIT is proposed for the instant problem among direction-of-arrival(DOA) estimation of signals. Firstly,the MSWF is combined with ESPRIT. Then subspace can be acquired through spatially smoothed forward recursion of the multistage wiener filtering,not through the matrix eigenvalue decomposition. In low SNR,the noise subspace leaked to the signal subspace,a discriminated method is proposed to find a more accurate signal subspace. The DOA of singles can be estimated combining with the subspace kind algorithms such as ESPRIT. Because this algorithm has realized the judgment of the real signal subspace,it has higher estimation precision than the traditional algorithm based on MSWF. Especially in low SNR,enhance the practicability of the algorithm. Simulation results verify that the proposed algorithm is effective.

Key concepts: Subspace topology, Signal subspace, Recursion (computer science), Algorithm, Eigenvalues and eigenvectors, Eigendecomposition of a matrix, SIGNAL (programming language), Computer science

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