In this paper, a robust multiuser detection algorithm based on hybrid whale optimization is proposed to solve the problem of high bit error rate of multiuser detection under impulse noise environment. Firstly, the improved whale optimization algorithm based on the non-linear control strategy is used to accelerate the convergence of the iteration process of the optimization algorithm. Then, the adaptive differential evolution algorithm is used to enrich the individual information of the population and enhance the global convergence of the optimization algorithm. At the same time, the individual information with good fitness is saved in a set to ensure the reliability of the optimization direction of the next iteration, and finally, a fast resolution to the position of the optimal solution is achieved. The simulation results show that the multi-user detector based on the proposed algorithm has fewer iterations and lower bit error rate than the multi-user detector based on genetic algorithm, differential evolution algorithm and whale optimization algorithm.