Unmanned aerial vehicles (UAVs) have become indispensable in search and r operations during emergencies such as natural disasters and maritime accidents, owing to their extended visual range and operational flexibility. However, images of ground targets captured by UAVs often suffer from false detections and missed detections due to suboptimal image quality and target occlusion. While improving target detection algorithms is a common solution, this paper emphasizes the influence of UAV flight trajectories on detection accuracy. Specifically, it addresses the trade-off between achieving a wide field of view at high altitudes and obtaining high-resolution images at low altitudes. By analyzing image data collected through circular and oblique descending trajectories, we investigate the effects of flight altitude and viewing angles on detection accuracy and develop a mathematical model to describe the distribution of detection accuracy. To mitigate the probabilities of false negatives and false positives during detection, we propose an optimized flight trajectory planning method termed the V-Circular. This approach involves the UAV descending obliquely toward a potential target, conducting circular flights at the lowest altitude to capture high-quality images from multiple viewing angles, and then ascending obliquely to rejoin its original path. The V-Circular method not only enhances image quality and detection accuracy but also improves recognition rate stability. Simulation results reveal that, compared to conventional flight paths, the V-Circular significantly increases target detection accuracy, shortens search and rescue time, and optimizes UAV energy efficiency. These advantages are particularly pronounced in missions demanding high precision. Consequently, the V-Circular presents an innovative solution for enhancing UAV search-and-rescue performance in complex environments.