Sparse sensor array design method based on global enhanced whale optimization algorithm

Abstract

The invention discloses a sparse sensor array design method based on a global enhanced whale optimization algorithm. Comprising the steps of performing position decomposition on an array position to determine a search aperture according to the number of array elements, a minimum array element spacing and an array aperture; chaos initialization is carried out in a search aperture range, and a primary population of the whale optimization algorithm is generated; determining and performing optimal individual screening according to a target function; updating the population position to generate a new offspring population; generating a reverse solution of the offspring population by using refraction learning, screening the offspring population and the reverse solution thereof, and searching an optimal individual in an optimal offspring; iterative search is carried out until design conditions are met, an optimal individual is obtained, and therefore the sparse sensor array is obtained. According to the method, a three-step enhanced global search strategy is utilized, the population traverses the search interval, the solution leakage phenomenon is avoided, the phenomenon of falling into a local optimal solution is avoided, the design precision and the array beam performance of the large sparse sensor linear array can be effectively improved, and the method has high engineering application value.

Description

technical field [0001] The invention belongs to a sparse sensor array design method in the field of sparse array design, and particularly relates to a sparse sensor array design method based on a global enhanced whale optimization algorithm. Background technique [0002] Sparse sensor linear arrays are widely used in communication systems, such as radar, sonar, and wireless systems, and are designed to achieve better array performance with fewer sensors. In practical engineering, the design goal is mostly to optimize the position of the array elements to reduce the beam side lobes when the number of array elements and the array aperture are fixed. The placement aperture is determined, the main lobe width of the array is relatively fixed, and the sparse design of the array can reduce the beam peak side lobe level, reduce the influence of interference, and enhance the ability to detect weak targets. Compared with the uniform array commonly used in engineering, the sparse arra...

AI Technical Summary

Problems solved by technology

At present, there are relatively few applications of whale algorithm for array design. Although the existing whale algorithm has shown good performance in array design, its performance will also decline in the design of large arrays.

The main reasons are: 1) With the expansion of the search range, the existing exponential spiral strategy will have too large a step size, resulting in a decrease in search accuracy and prone to premature phenomena

2) The random update strategy cannot effectively jump out of the local optimal solution, and it is easy to fall into the local optimal situation

[0005] To sum up, the existing whale algorithm is rarely used for large sensor arrays, and is prone to performance degradation

The existing spiral search strategy will reduce the search accuracy with the expansion of the array deployment range; at the same time, the existing random update strategy cannot jump out of the local optimal solution

This problem directly affects the performance of the obtained array, resulting in poor performance of the designed array or even failing to meet the engineering requirements

Images