To enhance the precision and stability of unmanned aerial vehicle(UAV)attitude solution,a particle swarm optimization(PSO)-based cascaded complementary filtering(PCCF)attitude solution method is proposed.This method designs a novel structure of cascaded filtering,consisting of a nonlinear complementary filter for gyroscope bias correction and a linear filter for attitude angle estimation.The PSO algorithm is employed to adaptively compute the gain parameters of the cascaded complementary filtering structure,avoiding the issues of manual adjustment or empirical methods prone to fall into local optimal solution.Experimental results demonstrate that compared to traditional filtering methods,the proposed method can obtain more accurate and reliable attitude information,the static attitude estimation error is less than 0.1°,and the dynamic attitude estimation error range is±1°,meeting the requirements of precise navigation and stable flight for UAV.
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