Quantum lookout non-circular direction finding method in impact noise environment

Abstract

The invention provides a quantum lookout non-circular direction finding method in an impact noise environment. The method comprises the steps: building a mathematical model for an array to receive non-circular signals, constructing a low-order real value weighted covariance matrix, and constructing a maximum likelihood direction finding equation through the low-order real value weighted covariance matrix; initializing a quantum lookout group and a quantum belief space, calculating the fitness of quantum positions in the quantum lookout group, and obtaining the optimal quantum position of the whole quantum lookout group; updating quantum specification knowledge, and updating a quantum situation knowledge space according to a lookout mechanism; using a simulation quantum revolving door to achieve the optimization searching process of quantum individuals through a quantum belief space and a quantum lookout mechanism; judging whether the maximum iteration number G is reached or not, if not, enabling g to be equal to g + 1, and returning to the step 3; and otherwise, terminating the iterative loop, and outputting the mapping state of the optimal quantum position in the last generation as a direction finding result. According to the invention, the method has robustness in a low-snapshot and impact noise environment, and breaks through the limitation of the existing non-circular direction finding method.

Description

technical field [0001] The invention relates to a quantum lookout non-circular direction finding method in an impact noise environment, and belongs to the field of array signal processing. Background technique [0002] The binary phase shift keying, amplitude modulation and other signals widely used in communication systems are non-circular signals, and the direction finding of non-circular signals is an important technology in the field of array signal processing, which is widely used in communication, navigation and electronic countermeasures, etc. field. In practical applications, radar and wireless communication systems are faced with increasingly complex electromagnetic environments, which put forward higher requirements for the signal processing capabilities of their receivers, so research on coherent The direction finding method of source non-circular signal has important significance and value. [0003] The direction-finding method for non-circular signals utilizes...

AI Technical Summary

Problems solved by technology

When the classical direction finding method is used for non-circular signal direction finding, the information contained in the signal is not fully utilized, and the performance of the existing typical non-circular direction finding algorithm deteriorates seriously in the environment of impact noise, and even fails. The combination of some anti-shock methods and direction-finding methods cannot effectively solve the direction-finding problem of non-circular signals in harsh noise environments, so it is necessary to design high-performance direction-finding with robustness in low-snapshot and impact-noise environments method

[0004]Using the maximum likelihood principle for non-circular signal direction finding can obtain theoretically excellent performance and can distinguish coherent sources, but multi-dimensional nonlinear optimization is required The problem is to search for the global maximum value. How to obtain the search results quickly and with high precision is the bottleneck problem in the application of the maximum likelihood direction finding method. Using intelligent optimization algorithms to solve it is a potential solution, but the existing intelligent optimization algorithms When applied to the complex engineering problem of non-circular direction finding, there are many defects, such as slow convergence speed, easy to fall into local extremum, etc. Therefore, it is necessary to design a new and efficient solution method for specific engineering problems

[0005] Through the retrieval of prior art documents, it is found that the "based on DOA Estimation Algorithm under Shock Noise Environment Based on the Screened Ratio Principle" reconstructs the correlation matrix of the array signal, and uses the MUSIC algorithm to realize the direction finding, which can suppress the shock noise, but cannot distinguish the coherent source and the direction finding results have quantization errors; Charge P et al. published "A noncircular sources direction finding method using polynomia rooting[J]" in "Signal Processing" (2001,81(6):1765-1770), using the conjugate extended MUSIC (CE-MUSIC) algorithm, It is proposed for non-circular signals. Compared with the MUSIC algorithm, the number of direction-finding signals, resolution and angle-measurement accuracy have been improved, but the CE-MUSIC algorithm cannot measure the direction of coherent signal sources.

[0006]The retrieval results of the existing literature show that the existing non-circular signal direction finding method has a narrow scope of application, high computational complexity, and lacks a Therefore, a new low-order moment is designed and a new maximum likelihood direction-finding method is proposed. Specifically, a low-order real-valued weighted covariance matrix is ​​designed The maximum likelihood direction finding method, and the non-circular direction finding results that can expand the aperture of the non-circular signal array are quickly obtained through the quantum lookout mechanism, and the existing direction finding methods have low accuracy and cannot Technical challenges in quickly obtaining coherent and non-coherent direction finding results

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