Method for carrying out low-complexity angle estimation by using co-prime linear array

Abstract

The invention discloses a method for carrying out low-complexity angle estimation by using a co-prime linear array. The method comprises the steps of: firstly, carrying out vectorization processing ona covariance matrix of an array received signal, deleting redundant rows and intercepting a continuous array element part to obtain a received signal of a virtual uniform linear array with an array element interval of half of lambda; then carrying out DFT (Discrete Fourier Transform) on the virtual received signal and finding out positions of K maximum peak values (K represents an information source number), so that initial estimation of a DOA (Direction Of Arrival) can be obtained; and finally, carrying out DFT on the virtual received signal subjected to phase rotation, searching a rotationphase eta in a small range, respectively finding out a rotation phase which enables the K peak values to be shrunk to the maximum, and obtaining accurate estimation of the DOA hereby. According to theinvention, DFT and a DOA estimation problem of the co-prime linear array are combined, the virtual received signal does not need to be subjected to decorrelation processing, a relatively high space freedom degree can be obtained, and meanwhile, the method has low calculation complexity and high estimation accuracy.

Description

technical field [0001] The invention relates to the field of space spectrum estimation, in particular to a method for low-complexity angle estimation using a coprime linear array. Background technique [0002] At present, an array antenna layout called a coprime array has been paid attention to. This array structure breaks through the half-wavelength limitation of the traditional antenna array element spacing, which greatly expands the antenna aperture and improves the performance of angle estimation. . [0003] There are two methods of angle estimation using coprime linear arrays: defuzzification and virtualization. Among them, the defuzzification method can obtain better estimation performance than the uniform linear array, but the method of using two sub-arrays for angle estimation makes the spatial degree of freedom greatly reduced. The virtualization method can obtain a higher degree of spatial freedom than the actual number of array elements, which greatly increases ...

AI Technical Summary

Problems solved by technology

Among them, the defuzzification method can obtain better estimation performance than the uniform linear array, but the method of using two sub-arrays for angle estimation makes the spatial degree of freedom greatly reduced

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