John Crassidis - Academia.edu (original) (raw)
Papers by John Crassidis
2018 AIAA Guidance, Navigation, and Control Conference
A novel method for nonlinear filtering based on a generalized Gaussian cubature approach is shown... more A novel method for nonlinear filtering based on a generalized Gaussian cubature approach is shown. Specifically, a new point-based nonlinea r filter is developed which is not based on one-dimensional quadrature rules, but rather uses multidimensional cubature rules for Gaussian distributions. Th e new generalized Gaussian cubature filter is not in general limited to odd-order de gre s of accuracy, and provides a wider range of order of accuracy. The method requi s the solution of a set of nonlinear equations for finding optimal cubature poin ts, but these equations are only required to be solved once for each state dimensiona l and order of accuracy. This rule is also extended to anisotropic cases where t order of accuracy is not isotropic in dimension. This method allows for tuning of the cubature rules to develop problem specific rules that are optimal for the given problem. The generalized Gaussian cubature filter is applied to benchmark proble ms in astrodynamics, and it is comp...
A method for relative attitude determination from planar line-of-sight observations is presented.... more A method for relative attitude determination from planar line-of-sight observations is presented. Three vehicles are assumed to be equipped with sensors to provide measurements of the three inter-vehicle line-of-sight vectors. The line-of-sight vectors are further assumed to be always in the same plane. This information is combined with all the available measurements to find an optimal relative attitude estimation solution. Covariance analysis is provided to help gain insight on the statistical properties of the attitude errors of the solution.
In this paper the validity of neglecting the relative effect of the gravitational force of the Ea... more In this paper the validity of neglecting the relative effect of the gravitational force of the Earth on a formation of spacecraft is studied. This relative effect is treated as an unknown disturbance acting on the system and all control laws are designed using a linear model that neglects this effect. A previously designed simple linear feedback controller is tested under different conditions using the linear model and the full nonlinear model that includes the gravitational force. All tests are carried out in the presence of saturation limits. The results show that the linear controller exhibits oscillations in the transient response and poor robustness under certain conditions. It also exhibits a high saturation tendency, thereby leading to increased fuel consumption. This controller also causes a high rise in the velocity errors at ordinary values of the gains. Based on the behavior of this controller, new controllers are proposed that overcome these drawbacks without any need fo...
This paper describes a path toward the development of theory for using a low noise high frame rat... more This paper describes a path toward the development of theory for using a low noise high frame rate camera as a star tracker for spacecraft attitude estimation. The benefit of using a low noise high frame rate camera is that s ar data can be sampled at a faster rate while allowing one to measure very di m stars, increasing the number of stars available for attitude estimation. The d evelopment of a noise model is discussed and an algorithm to process raw data is sho wn. An attitude estimation method is discussed and simulated data is shown. A simulated star tracker for attitude estimation is shown and attitude estim ation results are shown.
This paper addresses the attitude determination and control problem for the University at Buffalo... more This paper addresses the attitude determination and control problem for the University at Buffalo’s GLADOS mission. The main objective of the mission is to collect multi-band photometric data of resident space objects to improve space situational awareness. The team plans to use two optical payloads, a wide-field camera and a spectrometer, to achieve this goal. The attitude control system uses feedback from the wide-field camera in order to track targets and allow the collection of spectral data. The development of this novel approach which is suitable for low-cost small satellites is presented. A numerical simulation of a modeled mission including environmental disturbances, reaction wheel limitations, and sensor errors and delays is outlined. Results of this simulation are then presented. The ability of this approach to effectively track targets within the narrow field-of-view of the spectrometer is demonstrated.
2009 12th International Conference on Information Fusion, 2009
The main objective of this work is to model and exploit available maritime contextual information... more The main objective of this work is to model and exploit available maritime contextual information to provide a hypothesis on suspicious vessel maneuvers. This concept involves utilizing the L1 tracking to perform L2/L3 data fusion, i.e. refinement and assessment for situations and threats. A new context-based tracker known as the ConTracker is developed. The purpose of the ConTracker is to incorporate the contextual information into a traditional α - β tracker in such a way so that it provides a repeller or an attractor characteristics to a specific region of interest. Any behavior of the vessel that is inconsistent with the repeller or the attractor characteristics of the current vessel location would be classified as suspicious. Such an inconsistent vessel behavior would be directly indicated by a high measurement residual which may be used to estimate an accurate process noise covariance using a multiple-model adaptive estimator. Based on the rate of change of the estimated proce...
A new spacecraft attitude estimation approach based on the Unscented Filter is derived. For nonli... more A new spacecraft attitude estimation approach based on the Unscented Filter is derived. For nonlinear systems the Unscented Filter uses a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard Extended Kalman Filter, leading to faster convergence from inaccurate initial conditions in attitude estimation problems. The filter formulation is based on standard attitude-vector measurements using a gyro-based model for attitude propagation. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is derived from the local attitude error, which guarantees that quaternion normalization is maintained in the filter. Simulation results indicate that the Unscented Filter is more robust than the Extended Kalman Filter under realistic initial attitude-error conditions. ...
This paper presents a method to determine the shape of a space object while simultaneously recove... more This paper presents a method to determine the shape of a space object while simultaneously recovering the observed space object’s inertial orientation. This paper employs an Adaptive Hamiltonian Markov Chain Monte Carlo estimation approach, which uses light curve data to infer the space object’s orientation, shape, and surface parameters. This method is shown to work well for relatively high dimensions and non-Gaussian distributions of the light curve inversion problem.
A method for space event characterization using the framework of conceptual spaces will be illust... more A method for space event characterization using the framework of conceptual spaces will be illustrated in this paper. The focus of this paper is on estimating the likelihood of a collisions between space objects. We hope to develop an approach for anticipatory decision support for space operators so that preventative actions can be taken based on the assessment of relative risk. The conceptual spaces approach will draw on fusion of both hard and soft data into a single decision framework. The fusion-bases approach presented in this paper for decision support extends the conceptual spaces framework with a set of ontologies by drawing on the space domain ontologies, a large system of ontologies designed to support aspects of space situational awareness. This framework is coupled with a mathematical optimization approach, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundatio...
Proceedings of the 16th International Conference on Information Fusion, 2013
Astrometric and photometric data fusion for the purposes of simultaneous position, velocity, atti... more Astrometric and photometric data fusion for the purposes of simultaneous position, velocity, attitude, and angular rate estimation has been demonstrated in the past. This state estimation is extended to include the various surface parameters associated with the bidirectional reflectance distribution function (BRDF). Additionally, a physically consistent BRDF and radiation pressure model is utilized thus enabling an accurate physical link between the observed photometric brightness and the attitudinal dynamics and ultimately the orbital dynamics. An example scenario is then presented where the model is an uncontrolled High Area to Mass Ratio (HAMR) object in geosynchronous Earth orbit and the position, velocity, attitude, angular rates, and surface parameters are estimated simultaneously.
A study is conducted with the goal of utilizing estimation techniques on measurements obtained fr... more A study is conducted with the goal of utilizing estimation techniques on measurements obtained from various onboard resources such as a Sun sensor, a magnetometer and a commercial GPS unit in order to approximate the true trajectory of the vehicle in realtime and minimize the error associated with the process. This carries significant relevance to the field of orbit determination, where a small mission could operate a relatively cheap system for tracking purposes. This paper models a GPS sensor to become available only 5 minutes each day, which approximates a worst-case scenario where sparse pseudorange data is only possible due to suboptimal operating conditions for commercial GPS receivers taken to the space environment. Using a dynamic propagation model, which includes effects of Earth’s gravity, J2 zonal harmonics, and atmospheric drag, a sequential filtering method is used in order to estimate the states (position and velocity) of the vehicle with respect to time. This study de...
This paper presents a method to determine the shape of a space obje t in orbit while simultaneous... more This paper presents a method to determine the shape of a space obje t in orbit while simultaneously recovering the observed space object ’s inertial orientation and trajectory. This work studies a shape estimation approa ch b sed on octant triangulation applied to light curve and angles data fusion . The filter employs the Unscented estimation approach, reducing passively-co llected electro-optical data to infer the unknown state vector comprised of the space object inertial-tobody orientation, position and their respective temporal r ates. Recovering these characteristics and trajectories with sufficient accuracy is shown in this paper. The performance of this strategy is demonstrated via simulated sc narios.
17th International Conference on Information Fusion (FUSION), 2014
The sparse grid quadrature filter is a point-based Gaussian filter in which expectations of nonli... more The sparse grid quadrature filter is a point-based Gaussian filter in which expectations of nonlinear functions of Gaussian random vectors are computed using the sparse grid quadrature. The sparse grid quadrature can be considered a generalization of the Unscented Transform in that the Unscented Transform is equivalent to the level-2 sparse grid quadrature. A novel extension of the sparse grid quadrature filter is presented that directly transforms the points in time update and measurement update to eliminate repeated covariance decomposition based point generation and to relax the Gaussian assumption inherent in the sparse grid quadrature filter as well as the sigma-point filters. A tracking example is presented to demonstrate the performance of the novel filter.
In this paper a relative attitude determination solution of a formation of two vehicles with mult... more In this paper a relative attitude determination solution of a formation of two vehicles with multiple constraints is shown. The solution for th e relative attitude between the two vehicles is obtained only using line-of-sight measurements between them and common (unknown) objects observed by both vehicles . The constraints used in the solution are formed from triangles on the vector o bservations. Multiple constraints are used for each object and the solution is cast into a Wahba problem formulation. Simulation runs are shown that study the perfo rmance of the new approach.
This works investigates the problem of estimating the scaled inertia parameters of a space object... more This works investigates the problem of estimating the scaled inertia parameters of a space object using photometric and astrometric data. The inertia matrix is parameterized in terms of the relative scaled inertias and the orientation of the principal components because the system is not completely observable. A Unscented Kalman Filter (UKF) is presented that processes the lightcurve (single band photometric) and angles (astrometric) data to estimate the orientation, rotational rates, position, and velocity of the space object (SO) along with the scaled inertia parameters.
The overall goal of the approach developed in this paper is to estimate the likelihood of a given... more The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile space based adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to this data fusion framework. The first is the challenge involved in handling multiple complex terminologies, which is addressed by drawing on a set of Space Domain Ontologies. Another challenge is the complex combinatorics involved when considering all possible feature combinations. This can be mitigated by using integer linear programming optimization that is outlined by the Complex Conceptual Spaces Single Observation mathematical model framework. A third challen...
In this paper, a real-time predictive filter is derived for nonlinear systems. This provides a me... more In this paper, a real-time predictive filter is derived for nonlinear systems. This provides a method of determining optimal state estimates in the presence of significant error in the assumed (nominal) model. The new real-time nonlinear filter determines (i.e., “predicts”) the optimal model error trajectory so that the measurement-minus-estimate covariance statistically matches the known measurement-minus-truth covariance. The optimal model error is found by using a one-time step ahead control approach. Also, since the continuous model is used to determine state estimates, the filter avoids discrete state jumps, as opposed to the extended Kalman filter. Introduction Many linear control systems require full state knowledge (such as the LQR). But most systems have sensors which cannot measure all states (e.g., spacecraft sensors measure body positions which must be converted to an attitude for control purposes). An essential feature of most control systems involves an algorithm which...
Multiple hypothesis testing using an underlying Unscented Kalman Filter (UKF) to estimate state p... more Multiple hypothesis testing using an underlying Unscented Kalman Filter (UKF) to estimate state parameters has been previously demonstrated where the state includes the attitude, angular rate, position, velocity, and surface parameters of the space object. This algorithm is extended to include multiple components, and multiple bandpasses. An example scenario is presented where the models are proxy geostationary Earth orbit (GEO) satellites with different bus configurations (e.g. cylinder vs. rectangular prism) and in different controlled states (e.g. nadir-tracking vs. inertial).
ArXiv, 2021
This work provides a theoretical framework for the pose estimation problem using total least squa... more This work provides a theoretical framework for the pose estimation problem using total least squares for vector observations from landmark features. First, the optimization framework is formulated for the pose estimation problem with observation vectors extracted from point cloud features. Then, error-covariance expressions are derived. The attitude and position solutions obtained via the derived optimization framework are proven to reach the bounds defined by the Cramér-Rao lower bound under the small angle approximation of attitude errors. The measurement data for the simulation of this problem is provided through a series of vector observation scans, and a fully populated observation noise-covariance matrix is assumed as the weight in the cost function to cover for the most general case of the sensor uncertainty. Here, previous derivations are expanded for the pose estimation problem to include more generic cases of correlations in the errors than previously cases involving an is...
2018 AIAA Guidance, Navigation, and Control Conference
A novel method for nonlinear filtering based on a generalized Gaussian cubature approach is shown... more A novel method for nonlinear filtering based on a generalized Gaussian cubature approach is shown. Specifically, a new point-based nonlinea r filter is developed which is not based on one-dimensional quadrature rules, but rather uses multidimensional cubature rules for Gaussian distributions. Th e new generalized Gaussian cubature filter is not in general limited to odd-order de gre s of accuracy, and provides a wider range of order of accuracy. The method requi s the solution of a set of nonlinear equations for finding optimal cubature poin ts, but these equations are only required to be solved once for each state dimensiona l and order of accuracy. This rule is also extended to anisotropic cases where t order of accuracy is not isotropic in dimension. This method allows for tuning of the cubature rules to develop problem specific rules that are optimal for the given problem. The generalized Gaussian cubature filter is applied to benchmark proble ms in astrodynamics, and it is comp...
A method for relative attitude determination from planar line-of-sight observations is presented.... more A method for relative attitude determination from planar line-of-sight observations is presented. Three vehicles are assumed to be equipped with sensors to provide measurements of the three inter-vehicle line-of-sight vectors. The line-of-sight vectors are further assumed to be always in the same plane. This information is combined with all the available measurements to find an optimal relative attitude estimation solution. Covariance analysis is provided to help gain insight on the statistical properties of the attitude errors of the solution.
In this paper the validity of neglecting the relative effect of the gravitational force of the Ea... more In this paper the validity of neglecting the relative effect of the gravitational force of the Earth on a formation of spacecraft is studied. This relative effect is treated as an unknown disturbance acting on the system and all control laws are designed using a linear model that neglects this effect. A previously designed simple linear feedback controller is tested under different conditions using the linear model and the full nonlinear model that includes the gravitational force. All tests are carried out in the presence of saturation limits. The results show that the linear controller exhibits oscillations in the transient response and poor robustness under certain conditions. It also exhibits a high saturation tendency, thereby leading to increased fuel consumption. This controller also causes a high rise in the velocity errors at ordinary values of the gains. Based on the behavior of this controller, new controllers are proposed that overcome these drawbacks without any need fo...
This paper describes a path toward the development of theory for using a low noise high frame rat... more This paper describes a path toward the development of theory for using a low noise high frame rate camera as a star tracker for spacecraft attitude estimation. The benefit of using a low noise high frame rate camera is that s ar data can be sampled at a faster rate while allowing one to measure very di m stars, increasing the number of stars available for attitude estimation. The d evelopment of a noise model is discussed and an algorithm to process raw data is sho wn. An attitude estimation method is discussed and simulated data is shown. A simulated star tracker for attitude estimation is shown and attitude estim ation results are shown.
This paper addresses the attitude determination and control problem for the University at Buffalo... more This paper addresses the attitude determination and control problem for the University at Buffalo’s GLADOS mission. The main objective of the mission is to collect multi-band photometric data of resident space objects to improve space situational awareness. The team plans to use two optical payloads, a wide-field camera and a spectrometer, to achieve this goal. The attitude control system uses feedback from the wide-field camera in order to track targets and allow the collection of spectral data. The development of this novel approach which is suitable for low-cost small satellites is presented. A numerical simulation of a modeled mission including environmental disturbances, reaction wheel limitations, and sensor errors and delays is outlined. Results of this simulation are then presented. The ability of this approach to effectively track targets within the narrow field-of-view of the spectrometer is demonstrated.
2009 12th International Conference on Information Fusion, 2009
The main objective of this work is to model and exploit available maritime contextual information... more The main objective of this work is to model and exploit available maritime contextual information to provide a hypothesis on suspicious vessel maneuvers. This concept involves utilizing the L1 tracking to perform L2/L3 data fusion, i.e. refinement and assessment for situations and threats. A new context-based tracker known as the ConTracker is developed. The purpose of the ConTracker is to incorporate the contextual information into a traditional α - β tracker in such a way so that it provides a repeller or an attractor characteristics to a specific region of interest. Any behavior of the vessel that is inconsistent with the repeller or the attractor characteristics of the current vessel location would be classified as suspicious. Such an inconsistent vessel behavior would be directly indicated by a high measurement residual which may be used to estimate an accurate process noise covariance using a multiple-model adaptive estimator. Based on the rate of change of the estimated proce...
A new spacecraft attitude estimation approach based on the Unscented Filter is derived. For nonli... more A new spacecraft attitude estimation approach based on the Unscented Filter is derived. For nonlinear systems the Unscented Filter uses a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard Extended Kalman Filter, leading to faster convergence from inaccurate initial conditions in attitude estimation problems. The filter formulation is based on standard attitude-vector measurements using a gyro-based model for attitude propagation. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is derived from the local attitude error, which guarantees that quaternion normalization is maintained in the filter. Simulation results indicate that the Unscented Filter is more robust than the Extended Kalman Filter under realistic initial attitude-error conditions. ...
This paper presents a method to determine the shape of a space object while simultaneously recove... more This paper presents a method to determine the shape of a space object while simultaneously recovering the observed space object’s inertial orientation. This paper employs an Adaptive Hamiltonian Markov Chain Monte Carlo estimation approach, which uses light curve data to infer the space object’s orientation, shape, and surface parameters. This method is shown to work well for relatively high dimensions and non-Gaussian distributions of the light curve inversion problem.
A method for space event characterization using the framework of conceptual spaces will be illust... more A method for space event characterization using the framework of conceptual spaces will be illustrated in this paper. The focus of this paper is on estimating the likelihood of a collisions between space objects. We hope to develop an approach for anticipatory decision support for space operators so that preventative actions can be taken based on the assessment of relative risk. The conceptual spaces approach will draw on fusion of both hard and soft data into a single decision framework. The fusion-bases approach presented in this paper for decision support extends the conceptual spaces framework with a set of ontologies by drawing on the space domain ontologies, a large system of ontologies designed to support aspects of space situational awareness. This framework is coupled with a mathematical optimization approach, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundatio...
Proceedings of the 16th International Conference on Information Fusion, 2013
Astrometric and photometric data fusion for the purposes of simultaneous position, velocity, atti... more Astrometric and photometric data fusion for the purposes of simultaneous position, velocity, attitude, and angular rate estimation has been demonstrated in the past. This state estimation is extended to include the various surface parameters associated with the bidirectional reflectance distribution function (BRDF). Additionally, a physically consistent BRDF and radiation pressure model is utilized thus enabling an accurate physical link between the observed photometric brightness and the attitudinal dynamics and ultimately the orbital dynamics. An example scenario is then presented where the model is an uncontrolled High Area to Mass Ratio (HAMR) object in geosynchronous Earth orbit and the position, velocity, attitude, angular rates, and surface parameters are estimated simultaneously.
A study is conducted with the goal of utilizing estimation techniques on measurements obtained fr... more A study is conducted with the goal of utilizing estimation techniques on measurements obtained from various onboard resources such as a Sun sensor, a magnetometer and a commercial GPS unit in order to approximate the true trajectory of the vehicle in realtime and minimize the error associated with the process. This carries significant relevance to the field of orbit determination, where a small mission could operate a relatively cheap system for tracking purposes. This paper models a GPS sensor to become available only 5 minutes each day, which approximates a worst-case scenario where sparse pseudorange data is only possible due to suboptimal operating conditions for commercial GPS receivers taken to the space environment. Using a dynamic propagation model, which includes effects of Earth’s gravity, J2 zonal harmonics, and atmospheric drag, a sequential filtering method is used in order to estimate the states (position and velocity) of the vehicle with respect to time. This study de...
This paper presents a method to determine the shape of a space obje t in orbit while simultaneous... more This paper presents a method to determine the shape of a space obje t in orbit while simultaneously recovering the observed space object ’s inertial orientation and trajectory. This work studies a shape estimation approa ch b sed on octant triangulation applied to light curve and angles data fusion . The filter employs the Unscented estimation approach, reducing passively-co llected electro-optical data to infer the unknown state vector comprised of the space object inertial-tobody orientation, position and their respective temporal r ates. Recovering these characteristics and trajectories with sufficient accuracy is shown in this paper. The performance of this strategy is demonstrated via simulated sc narios.
17th International Conference on Information Fusion (FUSION), 2014
The sparse grid quadrature filter is a point-based Gaussian filter in which expectations of nonli... more The sparse grid quadrature filter is a point-based Gaussian filter in which expectations of nonlinear functions of Gaussian random vectors are computed using the sparse grid quadrature. The sparse grid quadrature can be considered a generalization of the Unscented Transform in that the Unscented Transform is equivalent to the level-2 sparse grid quadrature. A novel extension of the sparse grid quadrature filter is presented that directly transforms the points in time update and measurement update to eliminate repeated covariance decomposition based point generation and to relax the Gaussian assumption inherent in the sparse grid quadrature filter as well as the sigma-point filters. A tracking example is presented to demonstrate the performance of the novel filter.
In this paper a relative attitude determination solution of a formation of two vehicles with mult... more In this paper a relative attitude determination solution of a formation of two vehicles with multiple constraints is shown. The solution for th e relative attitude between the two vehicles is obtained only using line-of-sight measurements between them and common (unknown) objects observed by both vehicles . The constraints used in the solution are formed from triangles on the vector o bservations. Multiple constraints are used for each object and the solution is cast into a Wahba problem formulation. Simulation runs are shown that study the perfo rmance of the new approach.
This works investigates the problem of estimating the scaled inertia parameters of a space object... more This works investigates the problem of estimating the scaled inertia parameters of a space object using photometric and astrometric data. The inertia matrix is parameterized in terms of the relative scaled inertias and the orientation of the principal components because the system is not completely observable. A Unscented Kalman Filter (UKF) is presented that processes the lightcurve (single band photometric) and angles (astrometric) data to estimate the orientation, rotational rates, position, and velocity of the space object (SO) along with the scaled inertia parameters.
The overall goal of the approach developed in this paper is to estimate the likelihood of a given... more The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile space based adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to this data fusion framework. The first is the challenge involved in handling multiple complex terminologies, which is addressed by drawing on a set of Space Domain Ontologies. Another challenge is the complex combinatorics involved when considering all possible feature combinations. This can be mitigated by using integer linear programming optimization that is outlined by the Complex Conceptual Spaces Single Observation mathematical model framework. A third challen...
In this paper, a real-time predictive filter is derived for nonlinear systems. This provides a me... more In this paper, a real-time predictive filter is derived for nonlinear systems. This provides a method of determining optimal state estimates in the presence of significant error in the assumed (nominal) model. The new real-time nonlinear filter determines (i.e., “predicts”) the optimal model error trajectory so that the measurement-minus-estimate covariance statistically matches the known measurement-minus-truth covariance. The optimal model error is found by using a one-time step ahead control approach. Also, since the continuous model is used to determine state estimates, the filter avoids discrete state jumps, as opposed to the extended Kalman filter. Introduction Many linear control systems require full state knowledge (such as the LQR). But most systems have sensors which cannot measure all states (e.g., spacecraft sensors measure body positions which must be converted to an attitude for control purposes). An essential feature of most control systems involves an algorithm which...
Multiple hypothesis testing using an underlying Unscented Kalman Filter (UKF) to estimate state p... more Multiple hypothesis testing using an underlying Unscented Kalman Filter (UKF) to estimate state parameters has been previously demonstrated where the state includes the attitude, angular rate, position, velocity, and surface parameters of the space object. This algorithm is extended to include multiple components, and multiple bandpasses. An example scenario is presented where the models are proxy geostationary Earth orbit (GEO) satellites with different bus configurations (e.g. cylinder vs. rectangular prism) and in different controlled states (e.g. nadir-tracking vs. inertial).
ArXiv, 2021
This work provides a theoretical framework for the pose estimation problem using total least squa... more This work provides a theoretical framework for the pose estimation problem using total least squares for vector observations from landmark features. First, the optimization framework is formulated for the pose estimation problem with observation vectors extracted from point cloud features. Then, error-covariance expressions are derived. The attitude and position solutions obtained via the derived optimization framework are proven to reach the bounds defined by the Cramér-Rao lower bound under the small angle approximation of attitude errors. The measurement data for the simulation of this problem is provided through a series of vector observation scans, and a fully populated observation noise-covariance matrix is assumed as the weight in the cost function to cover for the most general case of the sensor uncertainty. Here, previous derivations are expanded for the pose estimation problem to include more generic cases of correlations in the errors than previously cases involving an is...