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Robust Vision-Based Pose and Parameter Estimation of Unknown Space Objects in the Cluttered Orbits

Zarei Jalalabadi, Mahboubeh | 2018

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 51286 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Malaek, Mohammad Bagher
  7. Abstract:
  8. To provide a safe environment for space equipments and infrastructures in addition to managing the role of hazardous objects that are known as space debris, the presented thesis describes a new robust technique to estimate the dynamic states and inertial parameters of Uncooperative Space Objects (USO) with uncertain dynamics in the cluttered orbits. The prescribed method is especially effective to capture stray objects, capture and servicing of the satellites, rendezvous and collision avoidance maneuvers, space explorations as well as Actrive Debris Removal (ADR) missions. Such missions call for high degree of precision and reliable estimation methods. The proposed estimation architecture that is an attempt toward this goal, consists of a network of synchronized platforms, i.e., Observer Satellites (OS), each with processing power and transmission capability, that are observing a common Target Space Object (TSO). All OSs are expected to have suitable measuring devices; such as active vision sensor, which provide sensory range image data. Each platform could also independently estimate its objective based on its own observations. The estimates are then transmitted to a fusion center to assimilate the fused estimate that is more accurate than any individual estimates. Many researchers have used active vision sensors for estimating motion pattern of space objects. In this thesis as a specific work, we show exploiting efficient algorithms in processing of range image data, filtering, and fusion of estimates enables the proposed method to be more efficient than the previous ones. We have also proposed a Modified version of Unscented Kalman Filter (M_UKF) to deal with highly nonlinear dynamics of the TSO. Moreover, two new fusion techniques have been developed that are particularlly efficient for space applications. To evaluate the proposed estimation architecture, computer simulations have been conducted on a cubic defunct satellite. Different case studies confirm that exploiting efficient algorithm in the processing range image data, filtering and fusion enables the method to be an appropriate architecture for estimation of unknown and uncooperative space obejcts
  9. Keywords:
  10. Sensor Network ; Estimation ; Nonlinear Filters ; Active Debris Removal Mission ; Track-to-Track Fusion

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