论文部分内容阅读
对于带不确定噪声方差的多传感器系统,基于极大极小鲁棒估计原理,提出保证估计性能的集中式融合鲁棒稳态Kalman预报器.对于预置的估计精度偏差指标,利用Lagrange乘数法求得相应噪声方差的最大扰动域,使该域中所有可容许的噪声扰动,其实际精度对鲁棒精度的偏差被保证在预置范围内,并给出精度偏差的最大下界和最小上界.应用Lyapunov方程方法证明了保证估计性能能够被满足.仿真分析表明了所得结果的正确性和有效性.
For the multisensor system with uncertain noise variance, a robust converged robust Kalman predictor with guaranteed estimation performance is proposed based on the principle of maximum and minimum robust estimation.For the preset estimation accuracy deviation index, the Lagrange multiplier The maximum perturbation domain of the corresponding noise variance is obtained, and all the allowable noise perturbations in this domain are disturbed. The deviation of the actual accuracy from the robustness accuracy is guaranteed within the preset range, and the maximum lower bound and the minimum of the precision deviation are given The Lyapunov equation method is used to prove that the guaranteed estimation performance can be satisfied.The simulation results show the correctness and validity of the results obtained.