In this paper, we introduce a specific kind of doubly reflected backward stochastic differential equations (in short DRBSDEs), defined on probability spaces equipped with general filtration that is essentially non quasi-left continuous, where the barriers are assumed to be predictable processes. We call these equations predictable DRBSDEs. Under a general type of Mokobodzki’s condition, we show the existence of the solution (in consideration of the driver’s nature) through a Picard iteration method and a Banach fixed point theorem. By using an appropriate generalization of Itô’s formula due to Gal’chouk and Lenglart we provide a suitable a priori estimates which immediately implies the uniqueness of the solution.

在本文中，我们介绍了一种特定类型的双反射后向随机微分方程（简称DRBSDE），该方程定义于配备有一般为准准连续性的一般过滤的概率空间，其中障碍被认为是可预测的过程。我们称这些方程为可预测的DRBSDE。在一般类型的Mokobodzki条件下，我们通过Picard迭代方法和Banach不动点定理证明了解决方案的存在（考虑了驾驶员的性质）。通过对Gal'chouk和Lenglart使用Itô公式进行适当的概括，我们提供了适当的先验估计，这立即意味着解决方案的唯一性。