Abstract
The traditional algorithm performing direction of arrival (DOA) estimation under the background of strong interference and colored noise has the problems of low estimation accuracy and small measurement targets. Based on the construction of a fourth-order cumulant (FOC) matrix to suppress colored noise, this paper adopts the extended noise subspace (ENS) algorithm and the fixed projection blocking (FPB) algorithm to estimate the DOA of weak targets. Firstly, a FOC matrix of the received signal vector is established to curb the noise component, and the eigenvalue decomposition is performed. Then, two approaches of weak signal DOA estimation are proposed. One approach is to merge the space where the strong interference steering vector lies into the noise subspace to construct an extended noise subspace, and then, the multisignal classification (MUSIC) algorithm is used to obtain the DOA estimation of the weak signal on the basis of the extended noise subspace. Another approach is to build the orthogonal projection matrix of the interference subspace as the interference blocking matrix, and the receiving array signal is preprocessed, and on the basis of it, the eigen decomposition is performed again to obtain the DOA information of the weak signal. Both algorithms make breakthroughs in the aperture limitation of the traditional algorithm, effectively expand the aperture, and promote the accuracy of estimation. The simulation tests the effectiveness of the proposed method.
Highlights
With the increasing intricacy of the electromagnetic environment, radar detection is interference by more and more electromagnetic, making it increasingly difficult for radar to detect targets [1, 2]
When the power of the interference signal is greater than that of the echo signal, the received data is directly used in the estimation of the direction of arrival, and the false peak resulting from strong interference will be regarded as the peak of the source, which will give birth to the misinterpretation of the correct angle [5, 6]
fourthorder cumulant (FOC)-extended noise subspace (ENS) algorithm simulation time is shorter than the FOC-fixed projection blocking (FPB) algorithm in that the fourth-order cumulant-fixed projection blocking (FOC-FPB) algorithm has one more feature decomposition than the FOC-ENS algorithm, which enhances the complexity to a certain extent
Summary
With the increasing intricacy of the electromagnetic environment, radar detection is interference by more and more electromagnetic, making it increasingly difficult for radar to detect targets [1, 2]. E algorithm first constructs an extended noise subspace for strong interferences and noises, and performs conventional DOA estimation. Literature [13, 14] proposed a variety of FOC-based algorithms, which have better angle estimation performance under Gaussian colored noise conditions. Tufail and Ahmed [15] used the FOC and ESPRIT algorithm to propose DOA estimation based on the genetic algorithm (GA) and obtained the multiple invariant cumulant ESPRITalgorithm, which has a better angular resolution, but the problem of excessive complexity remains unsolved. E other method is to construct the orthogonal projection matrix of the strong interference signal subspace as the interference blocking matrix, and the received array signal is preprocessed. This algorithm enjoys higher estimation accuracy under a variety of conditions
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