针对声波测距系统噪声复杂,淹没在噪声中的回波难以检测的问题,文章利用时间序列分析法对音频测距系统建立了ARMA模型,采用改进的递推最小二乘算法(RELS)实现了ARMA模型系数的实时估计,在ARMA模型的基础上,利用卡尔曼滤波算法对音频测距信号实时补偿,并构建了一种半实物仿真系统.仿真结果表明,该方法具有很好的实时滤波效果,能有效地抑制噪声,提高回波测距仪的精度.%Aiming at the problem of the difficulty to detect complex noise in acoustic ranging system and weak echoes from signal with high noise, the audio ranging system is analyzed by means of time series analysis. The auto regressive Moving Average (ARM A) model is established. The recursive extended least squares ( RELS) algorithm is adopted to realize the real-time estimation of parameters. The Kalman filter is used for compensating for the model error of the audio ranging system. It is concluded from the simulated results that the proposed methods achieve better smoothing effects and more effective inhibitions of the audio signal random noise, and improve the precision of the echo range finder.
展开▼
