Rocadenbosch Francesc, Reba M Nadzri Md, Sicard Michaël, Comerón Adolfo
Remote Sensing Laboratory (RSLAB), Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Campus Nord, Jordi Girona 1-3, 08034 Barcelona, Spain.
Appl Opt. 2010 Jun 10;49(17):3380-93. doi: 10.1364/AO.49.003380.
We present an analytical formulation to compute the total-backscatter range-dependent error bars from the well-known Klett's elastic-lidar inversion algorithm. A combined error-propagation and statistical formulation approach is used to assess inversion errors in response to the following error sources: observation noise (i.e., signal-to-noise ratio) in the reception channel, the user's uncertainty in the backscatter calibration, and in the (range-dependent) total extinction-to-backscatter ratio provided. The method is validated using a Monte Carlo procedure, where the error bars are computed by inversion of a large population of noisy generated lidar signals, for total optical depths tau < or = 5 and typical user uncertainties, all of which yield a practical tool to compute the sought-after error bars.
我们提出了一种分析公式，用于根据著名的克莱特弹性激光雷达反演算法计算与距离相关的总后向散射误差线。采用误差传播与统计公式相结合的方法，来评估因以下误差源产生的反演误差：接收通道中的观测噪声（即信噪比）、用户在反向散射校准方面的不确定性，以及所提供的（与距离相关的）总消光与后向散射比的不确定性。该方法通过蒙特卡罗程序进行验证，其中误差线是通过对大量生成的噪声激光雷达信号进行反演来计算的，适用于总光学深度τ≤5以及典型的用户不确定性情况，所有这些都产生了一个实用工具来计算所需的误差线。
