Indoor navigation systems for visually impaired people (VIPs) have seen significant advancements in recent years, leveraging various technologies to enhance spatial awareness and mobility. This chapter provides a comprehensive review of the state-of-the-art in indoor navigation systems for VIPs, focusing on the key components, techniques, and innovative approaches. The review covers a wide range of input technologies, including non-camera-based solutions such as radio-frequency identification (RFID), Bluetooth Low Energy (BLE), and ultrasonic sensors, as well as camera-based systems utilizing RGB-D sensors, time-of-flight (ToF) cameras, and computer vision algorithms. The computational equipment used in these systems, ranging from microcontrollers and minicomputers to smartphones and cloud-based servers, is also discussed. Feedback mechanisms, a crucial aspect of these systems, are explored in depth, covering auditory, tactile, and visual modalities. The chapter highlights recent innovations in the field, such as the integration of artificial intelligence techniques like convolutional neural networks (CNNs) and simultaneous localization and mapping (SLAM), as well as the use of multimodal feedback and personalized user interfaces. The potential of emerging technologies, including 5G networks and edge computing, in enhancing the performance and usability of these systems is also discussed. The review concludes by emphasizing the importance of user-centered design and close collaboration with the VIP community in developing effective and accessible indoor navigation solutions.