A Direction of Arrival Estimation Method Based on Quantum Particle Swarm

Abstract

The invention discloses a DOA (Direction of Arrival) estimation method based on a quantum-behaved particle swarm; the method comprises the steps: establishing an array signal model and setting relevant parameters of an array; establishing maximum likelihood estimation according to the array signal data; then performing initialization, calculating a fitness function for each particle, updating the speed and position of the quantum-behaved particle swarm; judging whether the maximum iteration times is obtained; and finally, outputting the vector estimated value of information message incidence angles and calculating the mean square error of incidence direction angles. The quantum behaviors of the particles are utilized in the optimization process; the DOA estimation method overcomes the disadvantage that the standard particle swarm algorithm is easy to fall into the partial minimum value; the standard particle swarm algorithm is high in estimation precision and has better effect for solving the DOA estimation problem; and a new solving idea is provided to the high-resolution DOA estimation.

Description

technical field [0001] The invention relates to the field of array signal processing and intelligent technology, in particular to a direction-of-arrival estimation technology based on quantum particle swarms. Background technique [0002] At present, array-based DOA estimation mainly includes traditional methods, subspace methods, maximum likelihood methods and MUSIC algorithms. The traditional method requires more array elements to ensure high resolution, which limits its application; the subspace method makes full use of the spatial structure of the received data, decomposes the data into signal subspace and noise subspace, and its performance is better than the traditional method ; The maximum likelihood method has better robustness, and can obtain better performance even when the SNR is low, but it requires a huge amount of calculation, which limits its application in engineering; the MUSIC algorithm exists Difficulty in searching for multidimensional spectral peaks. ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the nonlinear complex optimization problem in the existing DOA estimation algorithm, and propose a DOA estimation method based on quantum particle swarms. The quantum behavior of particles is used in the optimization process, and the search particles synthesize Cooperative switching between individual local extremum and global extremum, giving full play to the cooperative search mechanism among search particles, has the ability of efficient search and global search, in order to achieve the best direction of arrival effect

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