This paper is devoted to understanding traditional relative navigation and models which are used for small satellites. Compare the traditional relative navigations models and approaches which are based on different systems (Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS) , Laser&INS, etc.). These based Technologies are used individually or combined with each other for solving relative navigation problems.  The advantages and disadvantages of models are varied according to usage area, platform type, etc. Different methods and approaches exist besides, need for different estimation and optimization algorithms for adaptation, control, and sensor fusion. All the models are focused on assuming that perfect attitude conditions. Only consider relative navigation and distance perspective. Also, the aim of this article is understanding to the correlation between relative navigation systems and the effectiveness of algorithms use for estimating the states during constellation or formation flight.

This paper devoted the relative navigation of Unmanned Aerial Vehicles(UAVs) which fly within a formation. The concept and the methods of swarm UAVs technology and architecture are explained. Comparison of the relative navigations models and approaches which are based on different systems (Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS), Laser&INS, Vision-Based, etc.). These based Technologies are used individually or combined with each other via sensor integration for solving relative navigation problems.  The advantages and disadvantages of models are varied according to usage area, platform type, environment. Also, the aim of this article is to understand the correlation between relative navigation systems and the effectiveness of algorithms that are used for the relative motion states during constellation or formation flight/movement.

This article is devoted to the analysis of relative satellite vector estimations with extended Kalman filter (EKF) using the target and follower satellite positioning approach obtained by the Newton Raphson method (NRM). In this study, target and follower satellite baseline values were determined as derived simulation data. Position states due to Earth-centered inertial (ECI) reference frame were obtained by Keplerian orbital parameters and Global Positioning System (GPS) receiver. The Pseudo-ranging model was used to determine the position of target and follower satellites. To simulate GPS receiver, random measurement errors were added to the actual distance between the target and follower satellites. With this study, satellite relative state vectors are obtained within the analysis scenario.

This paper devoted the relative navigation of satellites that fly within a formation. The concept and the methods of swarm satellites technology and architecture are explained. The difference between the constellation and the formation architecture of satellites is focused. Analyses of relative motion between satellites are simulated by the mathematic model which used Hill-Clohessy-Wiltshire (H-C-W) equations and Keplerian orbital equations. And the analyses results are showed the drift of all axes according to formation. The control algorithms requirements of the follower satellite are decided according to the drift of all axes. Extended Kalman Filters are used for optimization, estimation, and control stability of non-linear orbital relative motion of satellites. At last, a comparison of relative navigation models is focused.

This paper is devoted to Global Positioning System (GPS) based fault-tolerant satellite orbital states estimation which is used for the Pseudo-ranging model. Many approaches are used for satellite navigation estimates. Besides the GPS is commonly used for determining a satellite’s orbital state vectors by many researchers. The fault-tolerant state estimation models are used for not only space vehicles but only terrestrial, naval vehicles during motion control and localization problem. In this study, the satellite localization was detected via measurement of the actual distance between 4 GPS satellites and target satellite. The Keplerian equations and orbit elements are used for satellite dynamic model J2 orbit perturbation are taken into account within the EKF algorithms. The novel approach to the fault-tolerant estimation of satellite states which is designed according to 2 versions is proposed. One of them is reconfiguration fault-tolerant satellite localization and the other one is adaptively fault-tolerant satellite localization. The Extended Kalman Filter (EKF) is used for the satellite stat vector estimation and detection of GPS measurement errors. The Reconfigurable version and the adaptive version of fault-tolerant localization architecture eliminate the GPS measurement errors during estimating satellite orbital position vectors. Approaches to identify target satellite state vectors can also be used as a fault warning system feedback within the GPS system.

This paper means to comprehend vision-based relative navigation strategies which are utilized for small/microsatellites. Advancements dependent on this technique are utilized separately or joined with one another to deal with relative position issues. The benefits and detriments of vision-based relative navigation models change as indicated by space of utilization and stage type. Various strategies and approaches exist and need distinctive assessment and advanced algorithms for variation, control, and sensor combination. Each of the models centering inside expects those ideal disposition conditions. This paper just spotlights on relative route and distance point of view. Additionally, the point of this article is to comprehend the connection between’s general navigation control frameworks and the adequacy of calculation, which are utilized in assessing the states during gathering or development flight/development.

This paper is committed to the relative navigation of Unmanned Aerial Vehicles (UAVs) flying in formation flight. The concept and methods of swarm UAVs technology and architecture have been explained. The relative state estimation models of unmanned aerial vehicles are based on separate systems such as Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS), Laser&INS, and Vision-based techniques have been compared via various approaches. The sensors are used individually or integrated with each other via sensor integration for solving relative navigation problems. The UAV relative navigation models are varied as stated in the operation area, type of platform, and environment. The aim of this article is to understand the correlation between relative navigation systems and potency of state estimation algorithms as well during formation flight of UAV

This paper is devoted to understanding relative navigation models that are used for space vehicles. The relative navigations models and approaches are based on different systems (Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS), Laser&INS, Vision-Based, etc.) are compared. These models and approaches can be used individually or combined for solving relative navigation problems. The advantages and disadvantages of the models vary according to the usage area, platform type, and environment. Different methods and approaches exist in addition to different estimation and optimization algorithms for adaptation, control, and sensor fusion. Most of the models assume perfect attitude conditions. This study considers satellites’ position estimates according to each other within formation on the Low Earth Orbit (LEO). Also, the aim of this article is to understand the correlation between the relative navigation systems and the effectiveness of the algorithms which are used for estimating states during constellation or formation flight.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce a auctor sem. Suspendisse egestas nulla eget nunc commodo, et blandit ante tristique. Aliquam dignissim nulla tellus, sed pellentesque libero pellentesque et. Donec nec sem mattis, suscipit ligula id, porttitor tortor. Maecenas sed egestas odio, vitae euismod nulla. Duis viverra blandit mi quis rhoncus. Aenean vitae turpis et tortor elementum blandit. dignissim nulla tellus, sed pellentesque libero pellentesque et. Donec nec sem mattis, suscipit ligula id, porttitor tortor. Maecenas sed egestas odio, vitae euismod nulla. Duis viverra blandit mi quis rhoncus. Aenean vitae turpis et tortor elementum blandit

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce a auctor sem. Suspendisse egestas nulla eget nunc commodo, et blandit ante tristique. Aliquam dignissim nulla tellus, sed pellentesque libero pellentesque et. Donec nec sem mattis, suscipit ligula id, porttitor tortor. Maecenas sed egestas odio, vitae euismod nulla. Duis viverra blandit mi quis rhoncus. Aenean vitae turpis et tortor elementum blandit. dignissim nulla tellus, sed pellentesque libero pellentesque et. Donec nec sem mattis, suscipit ligula id, porttitor tortor. Maecenas sed egestas odio, vitae euismod nulla. Duis viverra blandit mi quis rhoncus. Aenean vitae turpis et tortor elementum blandit.