论文部分内容阅读
采样频率限制和回波脉冲展宽是导致数字化激光脉冲测距峰值检测精度低的主要原因。传统的反距离加权插值算法只能解决低采样频率的问题,却无力解决回波脉冲展宽的问题。针对该问题,根据回波时间能量分布模型,从采样得到的峰值位置分别向上升沿和下降沿方向搜索,各自对搜索半径内的采样点按照距离远近赋予不同权重和插值,然后加权平均提取修正后的峰值时刻。该改进算法有效地解决了回波展宽的问题,减小了低采样频率和回波脉冲展宽带来的测量误差,通过实验论证了算法的有效性。
Sampling frequency limits and echo pulse broadening are the main reasons leading to the low accuracy of peak detection of digital laser pulse ranging. The traditional anti-distance weighted interpolation algorithm can only solve the problem of low sampling frequency, but can not solve the problem of echo pulse broadening. To solve this problem, according to the echo time energy distribution model, we search the peak position from the sampling direction to the rising edge and the falling edge separately. Each sampling point within the search radius is given different weights and interpolation according to the distance. Then, the weighted average extraction correction After the peak moment. The improved algorithm effectively solves the problem of echo broadening, reduces the measurement error caused by low sampling frequency and echo pulse broadening, and proves the effectiveness of the algorithm through experiments.