Resident Space Objects (RSOs) are anthropogenic entities orbiting Earth, often persisting for extended periods. These objects, which include debris from space launches, orbital missions, and fragmentation events, pose significant threats to operational space assets. The escalating concern over orbital congestion is further driven by recent technological advancements such as launch ride-sharing, the proliferation of small launch vehicles, and the deployment of large-scale satellite constellations. According to statistical data published by the European Space Agency (ESA) in 2023, the space environment is approaching critical congestion levels. The situation is expected to deteriorate as commercial operators like SpaceX and One-Web plan to deploy mega-constellations comprising thousands of satellites. This trend suggests a potential cascade of collision events, commonly called the Kessler syndrome, which could eventually halt space operations. To mitigate collision risks, spacecraft operators must enhance their situational awareness regarding potential threats posed by RSOs. This requires comprehensive tracking of the total number of objects in space and continuous estimation of the probability of accidental collisions. Accurate tracking and characterization of RSOs are essential for implementing effective Collision Avoidance (CA) maneuvers. This capability is vital not only for maintaining the safety and integrity of current space assets but also for enabling future applications such as interplanetary exploration, space tourism, and Point-to-Point Suborbital Transport (PPST). Currently, RSOs are monitored and cataloged using ground-based observational systems. Previous studies have explored the feasibility of utilizing space-borne radars and laser systems for RSO tracking, but challenges related to size and power consumption have prompted a shift toward alternative solutions. Although ground-based sensors offer wider sky coverage and the ability to track debris over multiple passes, they are highly susceptible to atmospheric conditions such as cloud cover, weather changes, and atmospheric turbulence, which degrade tracking accuracy. In contrast, Space-Based Space Surveillance (SBSS) offers a viable solution for RSO tracking, providing superior sensor resolution, tracking accuracy, and independence from weather conditions. While both ground-based and space-based sensors have inherent limitations, integrating them into a hybrid sensor network significantly enhances overall tracking performance. This integrated approach creates a complementary system that improves tracking accuracy, ensures continuous Low Earth Orbit (LEO) coverage, and strengthens the effectiveness of CA capabilities. Such an integrated strategy is critical for maintaining the safety and sustainability of space operations in the increasingly congested LEO environment. This paper proposes a multi-sensor data fusion strategy that employs hybrid sensor networks composed of intelligent Distributed Space Systems (iDSS) and ground-based sensors to achieve seamless, real-time tracking and continuous surveillance of space debris. A verification case study is conducted on a constellation of iDSS designed to perform SBSS for Space Domain Awareness (SDA).