Aiming at the problem that single attribute cooperative node selection algorithm in spatial cooperative transmission cannot balance the reliability and the survival time of the system, a Subjective and Objective Weighting Based Multi-attribute Cooperative Node Selection (SOW-CNS) algorithm was proposed by introducing Multiple Attribute Decision Making (MADM), and considering three attributes such as channel fading level, residual energy of the cooperative nodes and packet loss rate were considered to complement multi-attribute evaluation of spatial cooperative nodes. Firstly, according to the influence of shadow fading, a two-state wireless channel model was established, including the shadow free Loo channel fading model and the shadow Corazza channel fading model. Secondly, considering the channel fading level, the residual energy of cooperative nodes and the system packet loss rate, the multi-attribute decision making strategy based on subjective and objective weighting was introduced, and the subjective attribute weight vector and objective attribute weight vector of spatial cooperative nodes were established by using Analytic Hierarchy Process (AHP) and information entropy method. Then the maximum entropy principle, the deviation and the maximum method were used to calculate the subjective and objective attribute weight vectors. Finally, the evaluation value of each potential node was calculated by using the subjective and objective attributes weight vector and the attribute value of each node, and then the best cooperative node was selected to participate in the cooperative transmission of spatial information. Simulation results show that SOW-CNS algorithm detain lower system packet loss rate, and longer system Survival time compared with traditional Best Quality based Cooperative Node Selection (BQ-CNS) algorithm, Energy Fairness based Cooperative Node Selection (EF-CNS) algorithm and Random based Cooperative Node Selection (R-CNS) algorithm.