###### Abstract  
Autonomous navigation (AN) and manoeuvring are increasingly important in distributed satellite systems (DSS) in order to avoid potential collisions with space debris and other resident space objects (BSO). In order to accomplish collision avoidance manoeuvres, tracking and characterization of RSO is crucial. At present, RSO are tracked and catalogued using ground-based observations, but space-based space surveillance (SBSS) represents a valid alternative (or complementary asset) due to its ability to offer enhanced performances in terms of sensor resolution, tracking accuracy, and weather independence. This paper proposes a particle swarm optimization (PSO) algorithm for DSS AN and manoeuvring, specifically addressing RSO tracking and collision avoidance requirements as an integral part of the overall system design. More specifically, a DSS architecture employing hyperspectral sensors for Earth observation is considered, and passive electro-optical sensors are used, in conjunction with suitable mathematical algorithms, to accomplish autonomous RSO tracking and classification. Simulation case studies are performed to investigate the tracking and system collision avoidance capabilities in both space-based and ground-based tracking scenarios. Results corroborate the effectiveness of the proposed AN technique and highlight its potential to supplement either conventional (ground-based) or SBSS tracking methods.  
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Spacecraft operators must become more aware of the potential threats posed by the existing resident space objects (RSO) in order to prevent further collisions in Earth orbit. This includes not only tracking the total objects in space but also continuously estimating the probability of other accidental collisions. Unfortunately, neither of these tasks are trivial and require considerable tracking resources (optical telescopes and radar), computing power, and sophisticated software to calculate numerous satellite-satellite or satellite-debris conjunctions on a daily basis. The above tasks are referred to as'space situational awareness' (SSA) or space domain awareness (SDA). Traditionally, these tasks are accomplished by a network of ground-based observation facilities known as the Space Surveillance Network (SSN), owned and operated by the US Department of Defence (DoD) [3]. Besides this, various other ground-based telescopes and space surveillance systems contribute to SSA. Different SSA systems in current use are briefly described in [4]. Table 1 provides a summary of major ground-based systems and the time frames during which they were introduced. Although these ground-based radars, laser, and telescope systems continue to play a pivotal role in providing situational awareness in the space environment, whether or not these systems can effectively achieve the goal in the future, adapting to the evolving space domain, is still a question. This is due to the following reasons.  
* Most of the ground-based systems are able to perform regional surveillance and then randomly look at other areas.
* They lack persistency in surveillance. In order to achieve true surveillance, it is necessary to monitor objects or regions for extended periods of time.
* Due to space perturbations, there is an on-orbit change in the RSO position. This will decrease the revisit frequency of the RSO within the field of view of the sensors on ground.
* Weather conditions are still a significant concern for ground-based systems. In typical ground-based observation sites, weather restricts visibility more than half the time, with some sites having a visibility of no more than 25% [4].
* For optical sensors on the ground, daylight observations represent a significant challenge because the passage of objects between the Earth and the Sun is almost always difficult to monitor.  
Figure 1: (a) Space environment statistics by ESA; (b) Space debris population estimation by ESA.