Analysis And Research On Station Distribution Optimization Of Passive Location

With passive location in different fields such as aviation, aerospace and electronicwarfare has been widely used, its performance also become a growing concern. Underthe condition of observed parameters unchanged, the target location accuracy is knownto be affected by the relative geometry relationship between observation station andtarget. In this dissertation, under the background of direction finding cross location andtime difference location, respectively using differential evolution algorithm and particleswarm optimization algorithm for station distribution optimization carry out a detailedsimulation analysis, which verifies the effectiveness of the method and the optimalsensor placement is given.First of all, the basic principle, the basic localization algorithm and GDOP analysisof direction finding cross location and time difference location are introduced. Secondly,the optimization problem is expounded. The mathematical description of optimizationproblems and the solutions for general optimization problem are given. Combined withpassive location and the optimization problem, regarded the average accuracy as theobjective function, the mathematic model of optimize embattle is created. Furthermore,according to the optimized embattle model, using differential evolution algorithm foroptimal embattle carry out a detailed simulation analysis, which verifies theeffectiveness of the algorithm and the optimal sensor placement is given. Finally,particle swarm optimization algorithm is introduced, which is used for optimal embattleto carry out a detailed simulation analysis, which also verifies the effectiveness of thealgorithm. Comparing the algorithm with differential evolution algorithm, analyze theadvantages and disadvantages of both.