To accomplish the task of searching for specific indoor targets with a drone, even when system power consumption and platform weight are constrained, a low-cost, low-power, small-size drone design for autonomous indoor target search is proposed. Firstly, a suitable UAV hardware architecture based on constraints is chosen, and the controller is designed using saturation control. Besides, a simple sensor combination comprising three TF-Luna laser sensors is employed to gather environmental information. In the obstacle avoidance algorithm design, the avoidance logic of the Bug algorithm is referenced, achieving the design of the UAV's autonomous cruising mode. Then, the image acquisition chip is used to obtain real-time image information in the drone's flight direction. The chip integrated with the YOLO-v2 algorithm detects target information in the images. Furthermore, a central region following strategy is employed to achieve real-time tracking of the target. Finally, the simulation and actual flight of the autonomous cruise and target detection tracking tasks were completed at a speed of 1m/s in a 6m x 6m Simulink simulation environment and real-world scenarios.