携带传感节点高速运动下的运动参数精确测试  

Motion Parameters Accurately Test Under the High Speed Moving Sensor Nodes

作　　者：张大中[1] 

机构地区：[1]中国矿业大学体育学院,江苏徐州221116

出　　处：《科技通报》2014年第11期165-167,172,共4页Bulletin of Science and Technology

摘　　要：传统依据卡曼尔滤波器的运动参数测试算法,受到人体高速运动目标信号模糊以及光电传感器畸变的干扰,测试的结果存在较大的误差问题,存在较大的弊端。提出一种应用光电传感器和优化卡曼尔滤波算法的携带传感节点高速运动参数测量方法,分析了光电传感器检测信号的原理,采用高精密光反射型传感器对携带传感节点运动目标信号进行探测,利用光电传感器探测反射光信号,将携带传感节点运动信号转换为电信号,通过信号调理将电路放大后,采用微控制器完成运动目标信号的采集,通过优化的卡尔曼算法,获取一套递推预测算法,以信号和噪声的状态空间模型为依据,基于前一时刻的预测值和当前时刻的预测值,调整携带传感节点高速运动下人体运动参数变量的预测值,动态调整检测噪声的协方差,对携带传感节点高速运动参数进行准确预测。实验检测结果表明,所提方法可对含传感节点的运动参数进行高效检测,该种算法精度高,可有效的降低高速运动目标的信号模糊和光电传感器畸变等因素产生的误差问题。Traditional algorithm based on kalman filter＆#39;s motion parameters testing, by the high speed moving target signal interference to the distortion of the fuzzy and photoelectric sensor, the results of the test error of the larger problems, there is a big drawbacks. Put forward a kind of application of the photoelectric sensor and the optimization of the kalman filtering algorithm of sensor nodes to carry high speed motion parameters measurement method, the principle of photoelectric sensor detection signal is analyzed, using high precision optical reflective sensor to carry a sensor node moving target signal detection, using photoelectric sensor to detect the reflected light signal, will carry a sensor node movement signal into electrical signal, after amplification circuit for signal disposal, adopt micro controller to complete the moving target signal acquisition, by optimizing the kalman algorithm, to obtain a set of recursive prediction algorithm, based on state space model of signal and noise, based on the previous moment of predicted value and predictive value of the current time, adjust the sensor nodes to carry variables predicted under the high speed movement parameters, dynamic adjustment testing noise covariance, accurate projections for sensor nodes to carry high speed motion parameters. Experimental results show that the proposed method can be to detect contain movement parameters of the sensor nodes efficiently, this algorithm is of high precision, and can effectively reduce the high speed moving target fuzzy and photoelectric sensor signal distortion error of the factors such as the problem.

关 键 词：携带 传感节点 高速运动 运动参数 

分 类 号：TP33[自动化与计算机技术—计算机系统结构]