Study on the application of intelligent optimization algorithm in the optimization of passive positioning network layout

With the development of intelligent optimization algorithms, more and more optimization algorithms are applied to solve the optimization problems in real production and life. In a certain background environment, the positioning accuracy of the multi-station passive positioning system largely depends on the specific distribution of the stations in the system. Therefore, by analyzing the constraint conditions and reasonably establishing the model, the optimization problem of passive positioning network distribution station can be transformed into an optimization problem and solved by intelligent optimization algorithm. The GDOP direction finding cross location algorithm formula was deduced, the analysis is established under the condition of certain multistation disposition optimization model of passive location system is proposed using genetic algorithm and particle swarm optimization (pso), artificial fish algorithm of embattling method for solving optimization problem, through the comparison and analysis it is concluded that the particle swarm algorithm is more suitable for more rapid network cloth station station passive location system.