With the rapid development of wireless communication and mobile positioning technologies, Location-Based Services (LBS) have seen increasing applications across various fields. However, existing research primarily relies on techniques such as generalization and encryption for location privacy protection, facing critical challenges in balancing privacy protection and service quality. To solve this issue, this paper proposes a Flexible Screening and Noise Addition (FSNA) model designed to enhance the flexibility and adaptability of trajectory data privacy protection. The FSNA model identifies personalized sensitive location points by analyzing user trajectory characteristics, improving the accuracy of sensitive location detection. It further protects correlated location points based on spatiotemporal relationships. Finally, it integrates a flexible noise addition mechanism grounded in differential privacy, enabling adaptive adjustment of noise intensity to achieve dynamic protection of trajectory data. Experiments demonstrate that, compared to other algorithms, the proposed model achieves superior performance in balancing privacy protection and service quality.