Relative Positioning of Unmanned Systems in Denial Environments Based on Guided Optimization
Under satellite denial conditions,unmanned systems composed of multiple nodes such as drones and unmanned surface vehicles can utilize relative positioning methods to determine the absolute geographical locations of all nodes based on inter-node dis-tance information.Due to the high mobility of unmanned system nodes,the distance information between nodes has instantaneous validi-ty,necessitating the implementation of rapid and precise relative positioning solutions.Calculation of rotation matrices is a core step in relative positioning.Traditional methods such as least squares,Newton's method,and genetic algorithms cannot balance both efficiency and accuracy.The guided optimization algorithm based on freedom degree relaxation can guide the initial value of parameter optimiza-tion to the neighborhood of the true value in only one step by relaxing the freedom degree of the rotation matrix.Subsequently,fine opti-mization is performed using iterative methods,enabling short-time and high-precision calculation of rotation matrices.Simulation experi-mental results show that the calculation time of the relative positioning method based on guided optimization is 0.014 s with a positio-ning error of 25.73 m when the ranging error of the unmanned system reaches 5 m.This is comparable to the accuracy of Newton's method but reduces the calculation time by 55.56％.The calculation time is equivalent to the least squares method,but the positioning error is reduced by 39.47％.
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