脉冲式激光测距传感器温度补偿研究

Research on temperature compensation of pulsed laser ranging sensor

雪崩光电二极管作为脉冲式激光测距传感器的激光接收器件,在工作过程中容易受到温度影响,导致噪声和倍增因子波动,测距结果误差大。为解决以上问题,文中提出一种全新的温度补偿方式。首先对不同温度下传感器测距范围内输出的测距数据进行卡尔曼滤波,然后通过建立BP神经网络模型得到滤波数据、环境温度和实际距离三者间的映射关系,并利用遗传算法迭代取得最优解。在实际测量过程中,传感器的工作环境温度和经过卡尔曼滤波后的传感器测距输出作为神经网络模型输入,输出得到距离期望值。与通过改变雪崩光电二极管偏置电压进行温度补偿相比,该方法简单可靠,在不改变硬件系统的情况下能够有效提升测量稳定性和精度,将测量误差控制在0.606%以内,具有很好的实用价值。

The avalanche photodiode,as the laser receiving device of the pulsed laser ranging sensor,is easily affected by temperature during the working process,resulting in the fluctuation of noise and multiplication factor,and large ranging error.To solve the above problems,a new temperature compensation method is proposed.First,Kalman filtering is performed on the ranging data output within the sensor ranging range at different temperatures,and then the mapping relationship among the filtered data,the ambient temperature and the actual distance is obtained by establishing a BP neural network model,and the genetic algorithm is used to iteratively obtain the optimal solution.In the actual measurement process,the working environment temperature of the sensor and the sensor ranging output after Kalman filtering are used as the input of the neural network model,and the expected value of the distance is obtained from the output.In comparison with temperature compensation got by changing the avalanche photodiode bias voltage,this method is simple and reliable.It can effectively improve the measurement stability and accuracy without changing the hardware system.It can control the measurement error within 0.606%,and has good practical value.