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为方便分析散射介质中光传输的规律,文中首先建立散射介质中光传输的基本模型——基于Monte Carlo的Mie散射模型。Mie散射理论是由德国物理学家Gustav Mie于1908年提出的,其主要为解决光传播路径存在尺寸与光波长相当的散射颗粒时,入射光经散射颗粒散射后的散射光场分布[32]。下文以普适的单球模型为例,对Mie散射理论进行介绍。
如图1所示,设一束光强为
${I_0}$ 的自然光入射至半径为$r$ ,相对复折射率为$m = {m_r} - {\text{i}}{m_i}$ (${m_r}$ 、${m_i}$ 分别代表颗粒复折射率的实部与虚部)的各向同性散射颗粒,在距散射体$d$ 处,散射角为$\theta $ (由散射光方向矢量与入射光方向矢量间的夹角确定)的位置,散射光光强$I$ (图1中红色部分)为:公式(1)中散射振幅函数
${S_1}\left( \theta \right)$ 和${S_2}\left( \theta \right)$ 具体形式如下:除此之外,Mie散射理论还给出了消光系数
${k_{{\text{ext}}}}$ 、散射系数${k_{{\text{sca}}}}$ 、吸收系数${k_{{\text{abs}}}}$ 等表征散射前后光场能量变化的参数:式中:无因次直径(
$\alpha = {{{\text{π }}r} \mathord{\left/ {\vphantom {{{\text{π }}r} \lambda }} \right. } \lambda }$ )由粒径$r$ 和入射光波长$\lambda $ 确定;Mie系数中包含的${a_n}$ 和${b_n}$ 是由Ricatti-Bessel函数定义的,与散射颗粒的复折射率$m$ 有关。${\pi _n}$ 与${\tau _n}$ 则用来表征颗粒的散射强度,是关于$\cos \theta $ 的勒让德函数和一阶缔合勒让德函数。Ricatti-Bessel函数一般按无穷级数的形式给出,这给数值计算Mie散射系数带来了一定的困难。不仅如此,公式(2)、(3)中
${a_n}$ 和${b_n}$ 包含的复杂递推关系会导致Mie散射系数在计算时产生剧烈震荡[33]。考虑到Ricatti-Bessel函数会随项数增加快速收敛,因此不断有学者提出Ricatti-Bessel函数适当截断项经验公式[34-35]以及快速计算Mie散射系数的优化方法[36]。文中采用向前递推与向后递推相结合的方式,权衡计算耗时与精度,建立了一套宽范围高精度Mie散射系数的计算方法。部分计算结果如下所示:表1中,计算Mie散射系数的平均用时约为
$41.812\;{\text{ms}}$ 。文中算法相比Dave、Bohren算法的精度更高、适用范围更广,相比Lentz算法的耗时更低。验证了文中算法具备宽范围高精度的Mie散射系数计算能力,为后续散射介质传输模型的建立奠定了基础。Particle Scattering coefficients Dave[37] Bohren[38] Lentz[34] Proposed method α=0.0001 kext 2.3068×10−17 2.3068×10−17 2.306805×10−17 2.306805×10−17 m=1.5 kabs 0 0 0 0 α=5.2182 kext 3.10542 3.10543 3.105425 3.092631 m=1.55 kabs 0 0 0 0 α=100 kext 2.0944 2.0944 2.094388 2.094388 m=1.5 kabs 0 0 0 0 α=1570.7963 kext 2.01294 — 2.012945 2.012945 m=1.342 kabs 0 — 0 0 α=25000 kext 2.00235 — 2.002352 2.002352 m=1.5 kabs 0 — 0 0 α=0.0001 kext 1.9925×10−5 1.99252×10−5 1.99252×10−5 1.99252×10−5 m=1.5-0.1 i kabs 1.9925×10−5 1.99252×10−5 1.99252×10−5 1.99252×10−5 α=5.2182 kext 2.86165 2.86165 2.861651 2.857821 m=1.55-0.1 i kabs 1.1974 1.1974 1.197404 1.197355 α=100 kext 2.0898 2.0898 2.089822 2.089822 m=1.55-0.1 i kabs 0.9577 0.9577 0.957688 0.957688 α=1570.7963 kext 2.01445 — 2.014609 2.014609 m=1.55-0.1 i kabs 0.93354 — 0.910498 0.910498 α=25000 kext 2.00232 — 2.002323 2.002323 m=1.55-0.1 i kabs 0.90641 — 0.906409 0.906409 Table 1. Comparison of Mie scattering coefficients with different methods
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对于大气环境,散射颗粒的浓度大致为0.5~50 mg/L[39]。在此类介质中传输时,绝大多数的光会被多次散射(即散射光),仅有极少的光子未被散射或只被散射了几次(即弹道光与蛇形光)。由于散射传输中存在大量随机且无序的散射事件,仅用单次散射光场分布模型已无法精确描述。基于此,文中选择Monte Carlo方法来模拟散射介质中的光传输过程。如图2所示仿真过程,首先引入光子团的概念,光子团是指:一定数量状态完全相同的光子集合,且该集合内光子传播的行为当且仅当与散射颗粒作用时才会产生差异[40]。基于图1所示的单次散射模型,计算单次反照率(光子团由散射引起的能量损失率)
${\omega _0}$ ,以及散射自由程$l$ 、散射角$\theta $ 、方位角$\;\beta $ 的概率分布[36,41-42],便可利用Monte Carlo方法来模拟散射介质中的光传输过程。Figure 2. Simulation procedure of Mie scattering model for light field transmission based on Monte Carlo[43]
由于穿透激光雷达系统旨在获取散射介质中目标的时空信息,文中对Mie散射模型做出了改进,在散射介质中置入待测目标,并精确统计光子团的飞行时间。过程中需计算光子团与目标的作用坐标,即光子飞行路径所在直线的参数方程与目标法向表面微元的交点,接下来按照光子团入射坐标及方向余弦抽样,光子脉冲抽样,光子自由程抽样,光子团散射角、方位角抽样,最后按照目标碰撞假定、光子团能量、光子团飞行路程累加的流程完成Monte Carlo模拟。
由于该仿真模型中所用抽样的精度依赖于Mie散射系数的计算能力,因而仿真模型同样具有宽范围散射介质模拟、高仿真精度的特点。借此仿真模型,可对不同种类,不同强度的散射介质;不同深度,不同材质的目标;不同范围,不同空间采样率的激光雷达进行探测模拟,并获取目标的强度图、深度图、时间直方图,对后续研究具有显著的指导作用。
Research on penetrating imaging LIDAR based on time-correlated single photon counting (invited)
doi: 10.3788/IRLA20220404
- Received Date: 2021-12-20
- Rev Recd Date: 2022-01-25
- Available Online: 2022-08-31
- Publish Date: 2022-08-31
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Key words:
- LIDAR /
- penetrating imaging /
- Mie scattering /
- TCSPC
Abstract: Light detection and ranging (LIDAR) is a kind of optical sensor with accurate positioning and efficient identification ability that can quickly acquire three-dimensional information of targets. Therefore, LIDAR plays an increasingly important role in military reconnaissance, unmanned driving, space docking and other fields. However, in complex environment such as fog, smoke, sea and so on, scattering effect in light field causes serious degradation of the received signal in traditional LIDAR. Under these environmental conditions, the performance of traditional LIDAR will decrease rapidly, or fail to work. Aiming at the degradation characteristics of received signal in scattering environment, the transmission model of Mie scattering transient light field of Monte Carlo was firstly established. Then, the time-domain distribution law of the transmission light field was simulated by computer software. According to this law, the filtering algorithm of the time-domain signal de-scattering effect was studied. Finally, a kind of penetrating LIDAR based on TCSPC was built in laboratory. Through the imaging experiments in fog simulation environment, the results verify that the penetrating LIDAR method has a good effect on improving the quality of target image reconstruction. This study provides a base for the further applications of LIDAR in complex scattering environment.