基于Kalman滤波的量程自适应超声波测距  

Range Adaptive Strategy for Ultrasonic Distance Measurement Based on Kalman Filter

作　　者：王军政[1] 陈超[1] 汪正军[1] 沈伟[1] 

机构地区：[1]北京理工大学自动化学院,北京100081

出　　处：《北京理工大学学报》2011年第3期283-288,共6页Transactions of Beijing Institute of Technology

基　　金：北京市产学研科研基金资助项目(1010013020105)

摘　　要：针对移动式机器人障碍物探测时,超声波测距存在大量程与小盲区之间的矛盾及测量周期长的问题.设计了易于控制的超声波测距系统,采用基于Kalman滤波的量程自适应测量方法.为系统设定多级量程,在实际跟踪测量时,利用Kalman滤波器对目标的状态进行预测,通过预测值与设定阈值的比较进行量程的自适应切换,调整系统的测量参数.实验结果表明,该方法在增大量程的同时减小了盲区,实现了在大动态范围内对目标动态参数的准确估计,同时缩短了平均测量周期,增强了系统的实时性.This paper aims at reducing the cost of measurement period and solving the problem of contradiction between large range and small blind zone in ultrasonic distance measurement,when mobile robot detects the obstacle.A controllable ultrasonic distance measurement system with a multi-range adaptive strategy based on Kalman filter is designed.By using the estimated values from Kalman filtering,the system accomplishes the range adaptation and the measurement parameters of the system are automatically adjusted.The experimental results show that this method has reduced the blind zone and expanded the dynamic measurement range of the system,meanwhile achieved an accurate estimate of the dynamic parameters of the target.Furthermore,the proposed scheme has cut down the average cost of measurement period and enhanced real-time capability.

关 键 词：超声波测距 KALMAN滤波 量程自适应 

分 类 号：TB551[理学—物理]