采用四象限探测器的智能跟踪定位算法

为了提高跟踪定位系统的跟踪精度与响应速度,提出了一种增益可调的快速跟踪定位(GAFT)算法,以实现对目标的快速定位及在信号较弱时的精确定位,该算法首先根据目标在四象限探测器上光斑成像的大小、位置与输出信号间的关系,确定光斑在探测器上的线性变化区间,并在此区间上得到光斑移动与信号变化的对应关系,再实时采集光斑在4个象限上的信号之和,作为目标光斑信号强度,然后计算光斑信号强度的变化率,采用自适应学习的方法得到信号强度的变化趋势,根据该趋势对信号增益进行动态调整,从而提高信号的分辨率和跟踪精度.实验数据表明,GAFT算法在线性工作区间中通过改变光斑半径及调整光斑的信号强度等措施,可以将跟踪精度提高到0.049 7mm.

An Intelligent Tracking Algorithm Using Four-Quadrant Detector

A gain adjustable fast tracking(GAFT) algorithm is proposed to improve the tracking precision and reaction speed in tracking systems.The algorithm can quickly locate the position of the goal,and realize the precise tracking under the weaker signal.The GAFT determines the linear change interval of the goal in the sensor from the relation among the flare imaging size of the goal in four-quadrant detector,location and output signal,Then,the relation between mobile goal and output signal change within the linear change interval can be established.The sum of the four-quadrant detector output signals is real-time counted,and is regarded as a target flare signal strength.The change rate of the flare signal strength is then calculated.Then,the adaptive learning method is used to get the change tendency of the signal,and to realize the dynamic adjustment of signal gain so that the tracking precision can be improved when signal is weaker.Experimental results show that the GAFT increases the tracking precision to 0.0497 mm by changing the radius of goal,adjusting flare of signal intensity and other measures in linear intervals.