A user dynamic clustering and power alloction scheme is proposed for maximizing the sum rate in a downlink communication system employing non-orthogonal multiple access （NOMA） with unmanned aerial vehicles （UAVs） assistance. Considering the user quality of service and UAV position constraints， an optimization problem is formulated to maximize the sum rate.Due to the non-convexity of the objective function，the original problem is decoupled into three sub-problems to enhance system performance： UAV position deployment and user association， user dynamic clustering， and power allocation to improve system performance. Firstly， a UAV position deployment and user association scheme are designed based on the K-means algorithm， the objective is to minimize path loss， determining the optimal deployment position of the UAV with the simultaneous selection of the optimal user group to be served. Secondly， the multi-density stream clustering （MDSC） algorithm is improved， and a static and dynamic clustering scheme for users under a single UAV is proposed. The static clustering scheme can adaptively balance the number of clusters and the number of cluster users， and obtain a large difference in user channel gain within the cluster. The dynamic clustering scheme formulates an instant update strategy for user mobility attributes.Finally， by applying fractional programming （FP） and quadratic transformation， an auxiliary variable is introduced to transform the original non-convex problem into a convex problem. The auxiliary variable and power allocation are alternately optimized to obtain a suboptimal solution for the original non-convex problem. The simulation results show that compared with other algorithms， the clustering scheme in this paper can obtain larger intra-cluster channel difference and smaller standard deviation of the number of users in the cluster， and the performance of the user system is also significantly improved.