一种线运动扰动环境下基于惯性凝固系抗干扰自对准优化算法研究

Research on an Anti-interference Self-alignment Optimization Algorithm Based on the Inertial Fixed Frame under the Linear Motion Disturbance Environment

传统惯性凝固性对准技术可有效隔离角运动干扰环境对捷联惯导自对准精度的影响,但对线运动环境下的抗干扰能力不足。据此,在深入分析线运动干扰对捷联惯导惯性凝固系下自对准精度影响途径之上,对线运动干扰环境划分为速度周期波动、突跳以及速度短期线性漂移。提出采用积分降噪、载体惯性系速度递推拟合与基于带遗忘因子递推最小二乘的速度慢漂提取技术相结合的抗干扰自对准优化算法,并进行了试验验证。试验结果表明,本算法可在5min内实现1.3mil的抗干扰自对准精度。

Traditional inertial fixed alignment technology can effectively isolate the angular motion interference environment from the alignment accuracy of an INS, but the anti-interference ability in the linear motion environment is insufficient. Accordingly, based on the deeply analysis of the linear motion interference influenced the alignment accuracy,divided it into noise wave, jump not expected, and short-term linear drift. An anti-interference self-alignment optimization algorithm which combined with integral noise reduction, vehicle inertial frame speed recursive fitting and with forgetting factor recursive least squares is presented, and a test was carried out. Experimental results show that this algorithm can achieve1.3mil within 5min.