机械科学与技术2017，Vol.36Issue(7)：1099-1104,6.DOI:10.13433/j.cnki.1003-8728.2017.0719
应用离散粒子群算法的大距离超声信号LMS自适应时延估计
Least Mean Square Time Delay Estimation of Long Distance Ultrasonic Echoes based on Discrete Particle Swarm Optimization Algorithm
摘要
Abstract
In order to meet the need of accuracy and real-time in long distance obstacle detection of tower crane warning system,a new least mean square adaptive time delay estimation (LMSTDE) in ultrasonic echo time delay estimation is proposed,which is based on discrete particle swarm optimization(DPSO) algorithm.The method can reduce computation amount greatly with DPOS and overcome immature constringency in the optimization algorithm with variable step-size LMS and variable acceleration coefficients.The experimental results show that:this method not only keeps the high accuracy and good anti-noise ability of the original algorithm,but also increases the computation speed by 25 times.It can be used in the real time detection of middle and long distance obstacles with higher reliability.关键词
塔式起重机/超声波测距/实时性/自适应时延估计/离散粒子群算法Key words
tower crane/real time/adaptive time delay estimation/discrete particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
王柯渊,谷立臣,寇雪芹,郭佳..应用离散粒子群算法的大距离超声信号LMS自适应时延估计[J].机械科学与技术,2017,36(7):1099-1104,6.基金项目
国家自然科学基金项目(50975218)与陕西省教育厅专项基金项目(2013JK1011)资助 （50975218）
