基于拟合优化的多传感器测距误差残差补偿修正算法设计

Design of Residual Error Compensation and Correction Algorithm for Multi￣Sensor Ranging Based on Fitting Optimization

在复杂环境下,多传感器协同测距过程,受信号强弱、传感器性能、光照的影响,测距过程存在一定误差。为解决上述问题,提出一种多传感器测距误差补偿算法。该算法首先利用小波变换将多传感器信号分解成低频和高频信号,并对高频信号采取阈值量化处理。将处理后的高频信号与低频信号重构,完成信号降噪。其次采用坐标投影法构建误差模型,并在模型中采用带有拟合优化的残差补偿法修正误差。最后将灰度重心算法与电荷耦合原理结合消除光斑,完成多传感器测距误差补偿。实验结果显示:这种算法的残差平均值在0.37附近波动、标准差平均值为0.42、信号采集误差平均值小于1 Hz,能够实现多传感器测距误差的准确补偿。

In a complex environment,the multi-sensor collaborative ranging process is affected by signal strength,sensor performance,and illumination,and there is a certain error in the ranging process.To solve the above problems,a multi-sensor ranging error compensa-tion algorithm is proposed.Firstly,the multi-sensor signal is decomposed into low-frequency and high-frequency signals by wavelet transform,and the high-frequency signal is subjected to threshold quantization processing.The processed high-frequency signal and low-frequency signal are reconstructed to complete signal noise reduction.Secondly,the coordinate projection method is used to construct the error model,and the residual error compensation method with fitting optimization is used in the model to correct the error.Finally,the gray-scale centroid algorithm and the charge-coupled principle are combined to eliminate the light spot and complete the multi-sensor ranging error compensation.The experimental results show that the average residual error of this algorithm fluctuates around 0.37,the average standard deviation is 0.42,and the average value of the signal acquisition error is less than 1 Hz,which can achieve accurate compensation of multi-sensor ranging errors.