This chapter explores single-modal object tracking across four sensing modalities: RGB, thermal infrared, LiDAR, and event cameras. Each modality offers distinct characteristics that influence tracking strategies. RGB-based tracking is the most mature, leveraging rich color information and wide applicability. Thermal infrared tracking excels in low-light conditions and temperature-sensitive applications, while LiDAR provides accurate 3D spatial representations critical for autonomous navigation. Event-based tracking offers high temporal resolution and low latency, ideal for dynamic environments. For each modality, the chapter categorizes mainstream tracking paradigms—such as Siamese networks, correlation filters, one-stream architectures, and motion modeling—and outlines representative algorithms and methods. It also compares their performance across benchmarks and highlights ongoing challenges including occlusion, target deformation, illumination variation, and sensor-specific limitations. The structure of the chapter moves from modality characteristics to technical paradigms, method examples, performance evaluation, and concludes with open problems, providing a comprehensive view of single-modal object tracking. This chapter underscores the importance of modality-specific strategies in advancing robust, efficient tracking systems across diverse real-world applications.