Kovalev Vladimir A, Newton Jenny, Wold Cyle, Hao Wei Min
Fire Sciences Laboratory, Forest Service, U.S. Department of Agriculture, P.O. Box 8089, Missoula, Montana 59807, USA.
Appl Opt. 2005 Mar 20;44(9):1761-8. doi: 10.1364/ao.44.001761.
We propose a modified algorithm for the gradient method to determine the near-edge smoke plume boundaries using backscatter signals of a scanning lidar. The running derivative of the ratio of the signal standard deviation (STD) to the accumulated sum of the STD is calculated, and the location of the global maximum of this function is found. No empirical criteria are required to determine smoke boundaries; thus the algorithm can be used without a priori selection of threshold values. The modified gradient method is not sensitive to the signal random noise at the far end of the lidar measurement range. Experimental data obtained with the Fire Sciences Laboratory lidar during routine prescribed fires in Montana were used to test the algorithm. Analysis results are presented that demonstrate the robustness of this algorithm.
我们提出了一种梯度方法的改进算法，用于利用扫描激光雷达的后向散射信号确定近边缘烟雾羽流边界。计算信号标准偏差（STD）与STD累积和之比的运行导数，并找到该函数全局最大值的位置。确定烟雾边界无需经验标准；因此该算法无需事先选择阈值即可使用。改进的梯度方法对激光雷达测量范围远端的信号随机噪声不敏感。利用蒙大拿州常规规定燃烧期间火灾科学实验室激光雷达获得的实验数据对该算法进行了测试。给出的分析结果证明了该算法的稳健性。
