Particle Filtering Based on Improved Whale Algorithm
ZHANG Xiaoli
LIN Shixiong
Abstract：Aiming at the problems of particle impoverishment and loss of diversity in particle filtering algorithm,an improved whale algorithm particle filtering is proposed.By optimizing particles through the improved whale algorithm,each particle repre-sents a humpback whale,simulating the foraging behavior of humpback whales,guiding prior particles to move towards high likeli-hood regions.In the initialization part of the whale algorithm,reverse learning is introduced to select the optimal solution in the ini-tial population,and when updating the position,the random number is changed to a randomly changing function,thereby improving the exploratory ability.In order to improve the diversity of the population,Cauchy mutation method is adopted.Simulation results show that the improved algorithm improves the estimation accuracy of particles and verifies the effectiveness of the improved algo-rithm.
Keywords：particle filterwhale algorithmreverse learningfunction of random variationCauchy variation
Publication Date：2025-06-20
Online Publishing Date：2025-09-23(First online date of this platform, not the publication date of the document)
Pages：7( 1521-1526,1532 )