Non-line-of-sight (NLOS) imaging is an emerging optical imaging technique used for detecting hidden targets outside the line of sight. Due to multiple diffuse reflections, the signal echoes are weak, and gated single-photon avalanche diode (SPAD) plays a pivotal role in signal detection under low signal-to-noise ratio (SNR) conditions. However, when gated SPAD is used for detecting a target signal, existing methods often depend on prior information to preset the gate width, which cannot fully mitigate non-target signal interference or signal loss. Additionally, these methods encountered some problems such as large data acquisition volumes and lengthy processing times. To address these challenges, an adaptive gating algorithm is proposed in this work based on the principle of maximizing the distance from the vertex of a triangle to its base. The algorithm possesses advantages of the linear variation in scan point positions and the echo information from specific feature points. It can automatically identify echo signals and compute their widths without additional prior information or manual intervention. This method reduces the amount of data collected, improves processing efficiency, and has other benefits. Moreover, a confocal NLOS imaging system based on gated SPAD is developed to validate the proposed algorithm. The work further quantitatively evaluates the enhancement of target signal detection and image quality achieved by gated SPAD, and compares its imaging performance with leading NLOS image reconstruction algorithms. Experimental results demonstrate that the adaptive gating algorithm can effectively identify echo signals, facilitate automatic adjustment of gating parameters, and significantly improve target imaging quality while reducing data acquisition volume and enhancing processing efficiency.