A Single-Snapshot Direction-of-Arrival Estimation Method Based on Hyperbolic Tangent Kernel Correlation Entropy

By proposing a single-snapshot direction-of-arrival (DOA) estimation method based on hyperbolic tangent kernel correlation entropy and quantum locust search strategy, the problem of poor robustness of ODA estimation in complex noise environments is solved, achieving efficient and accurate ODA estimation, which is suitable for complex noise environments.

CN115932714BActive Publication Date: 2025-12-02HARBIN ENG UNIV
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Patent Information

Application Number
CN202211467804.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-11-22
Publication Date
2025-12-02
Estimated Expiration
2042-11-22

AI Technical Summary

Technical Problem

Existing single-shot direction-of-arrival (DOA) estimation methods have poor robustness in complex impact noise environments, especially in low signal-to-noise ratio and strong impact noise environments, where it is difficult to achieve effective DOA estimation. Furthermore, they involve large computational loads and have low real-time performance.

Method used

A single-shot direction-of-arrival estimation method based on hyperbolic tangent kernel correlation entropy is adopted. By constructing a low-order matrix of hyperbolic tangent kernel correlation entropy and a steering matrix of uniform linear array, a high-efficiency direction-finding method in complex noise environment is designed by using quantum locust search strategy and Fibonacci operator to fit the signal subspace.

Benefits of technology

It achieves high-precision direction-of-arrival estimation in complex noise environments, reduces computational load, and improves robustness and real-time performance. It is suitable for harsh environments such as impulse noise, low signal-to-noise ratio, and Gaussian noise.

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Abstract

This invention discloses a single-shot direction-of-arrival (DOA) estimation method based on hyperbolic tangent kernel correlation entropy. The method involves establishing a single-shot sampling signal model; constructing a low-order matrix based on hyperbolic tangent kernel correlation entropy; constructing an orthogonal projection matrix to obtain a single-shot weighted signal subspace fitting equation based on hyperbolic tangent kernel correlation entropy; initializing a quantum locust population and setting parameters; calculating the fitness value of the quantum locust's mapped state position and recording the quantum position corresponding to the mapped state position with the largest fitness value; updating the quantum locust's social position and adaptive weight coefficients to generate Fibonacci weights; updating the quantum locust's quantum position and global optimal position using a simulated quantum rotation gate according to the locust and Fibonacci search strategy; calculating the iteration to the maximum number of iterations and outputting the mapped state position of the last generation of globally optimal quantum locusts as the DOA estimation result of the single-shot direction finding. This invention can effectively perform direction finding for both independent and coherent sources under impulsive noise conditions.
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