Pini Gurfil

Methods for Sparse Signal Recovery Using Kalman Filtering With Embedded Pseudo-Measurement Norms and Quasi-Norms

We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimization problem. We propose solving this optimization problem by two algorithms that rely on a Kalman filter (KF) endowed with a pseudo-measurement (PM) equation. Compared to a recently-introduced KF-CS method, which involves the implementation of an auxiliary CS optimization algorithm (e.g., the Dantzig selector), our method can be straightforwardly implemented in a stand-alone manner, as it is exclusively based on the well-known KF formulation. In our first algorithm, the PM equation constrains the l 1 norm of the estimated state. In this case, the augmented measurement equation becomes linear, so a regular KF can be used. In our second algorithm, we replace the l 1 norm by a quasi-norm lp , 0 ¿ p < 1. This modification considerably improves the accuracy of the resulting KF algorithm; however, these improved results require an extended KF (EKF) for properly computing the state statistics. A numerical study demonstrates the viability of the new methods.

Relative Motion between Elliptic Orbits: Generalized Boundedness Conditions and Optimal Formationkeeping

Based on the concept of orbital commensurability, necessary and sufficient conditions are presented for bounded relative motion between any two spacecraft flying on elliptic Keplerian orbits. The proposed approach does not involve any simplifying assumptions regarding the relative dynamics but rather treats the general, nonlinear, eccentric relative motion problem. The methodology presented alleviates the difficulty in computing corrections to the linear equations of motion to account for nonlinearities and eccentricities. Instead of dealing with the local relative motion problem, the global relative motion problem is addressed by transforming the orbital resonance requirement into an energy-matching condition. The newly developed setup is then utilized to derive an optimal single-impulse formationkeeping maneuver based on relative state variables. The orbital elements interpretation of the optimal formationkeeping maneuver is also discussed.

Adaptive Neural Control of Deep-Space Formation Flying

A novel nonlinear adaptive neural control methodology is presented for the challenging problem of deep-space spacecraft formation flying. When the framework of the circular restricted three-body problem with the sun and Earth as the primary gravitational bodies is utilized, a nonlinear model is developed that describes the relative formation dynamics. This model is not confined to the vicinity of the Lagrangian libration points but rather constitutes the most general nonlinear formulation. Then, a relative position controller is designed that consists of an approximate dynamic model inversion, linear compensation of the ideal feedback linearized model, and an adaptive neural-network-based element designed to compensate for the model inversion errors. The nominal dynamic inversion includes the gravitational forces, whereas the model inversion errors are assumed to stem from disturbances such as fourth-body gravitational effects and solar radiation pressure. The approach is illustrated by simulations, which confirm that the suggested methodology yields excellent tracking and disturbance rejection, thus, permitting submillimeter formation keeping precision.

Stereovision-Based Estimation of Relative Dynamics Between Noncooperative Satellites: Theory and Experiments

Estimating the relative pose and motion of cooperative satellites using on-board sensors is a challenging problem. When the satellites are noncooperative, the problem becomes even more complicated, as there might be poor a priori information about the motion and structure of the target satellite. In this paper, the mentioned problem is solved by using only visual sensors, which measurements are processed through robust filtering algorithms. Using two cameras mounted on a chaser satellite, the relative state with respect to a target satellite, including the position, attitude, and rotational and translational velocities, is estimated. The new approach employs a stereoscopic vision system for tracking a set of feature points on the target spacecraft. The perspective projection of these points on the two cameras constitutes the observation model of an iterated extended Kalman filter (IEKF) estimation scheme. Using new theoretical results, the information contained in the visual data is quantified using the Fisher information matrix. It is shown that, even in the noncooperative case, there is information that can be extracted pertaining to the relative attitude and target structure. Finally, a method is proposed for rendering the relative motion filtering algorithm robust to uncertainties in the targets inertia tensor. This is accomplished by endowing the IEKF with a maximum a posteriori identification scheme for determining the most probable inertia tensor from several available hypotheses. The performance of the new filtering algorithm is validated by Monte-Carlo simulations. Also a preliminary experimental evaluation is provided.

Nonlinear Modeling of Spacecraft Relative Motion in the Configuration Space

A reduced-input system problem is formed with the objective of preserving system input–output properties. For exogenous inputs, a reduced-order input system H∞ norm is maximized and an analytic solution is given. For control inputs, a reduced-order input system Hankel norm is maximized. Necessary conditions for the Hankel norm maximization are stated and an iterative solution is proposed. Although global convergence cannot be guaranteed, many practical applications have shown the achieved maxima to be very close to a known upper bound.

Finite Time Stability Approach to Proportional Navigation Systems Analysis

The e nite time stability of proportional navigation guidance systems is considered. Assuming planar geometry and linear missile dynamics, a proportional navigation missile ‐target guidance model is e rst formulated. The model exhibitsa feedback cone guration consisting of a lineartime-invariant element and a time-varying gain. The dee nition of e nite timeglobal absolutestability isthen presented. Itisshown that by employing thecirclecriterion, the e nite time stability of the guidance dynamics can be analyzed. An analytic bound for the time of e ight up to which stability can be assured is established. The bound depends on the system parameters and the time of e ight. Less conservative results, as compared to previous works, are obtained. This approach enables not only analysis of the system behavior for given missile dynamics, but more importantly, enables generation of a tool for system design. Illustrative examples are presented showing the effect of the system parameters on the bound. In addition, some design implications, such as the relation to miss distance, are outlined.

Effect of Kinematic Rotation-Translation Coupling on Relative Spacecraft Translational Dynamics

A CCURATEmodeling of the differential translation and rotation between two spacecraft is essential for cooperative distributed space systems, spacecraft formation flying (SFF), rendezvous, and docking. High-fidelity relative motion modeling, as opposed to absolute motion modeling, is particularly important for autonomous missions [1]. Point-mass models for relative spacecraft translational motion have been extensively studied over the past 50 years, since Clohessy and Wiltshire (CW) presented a rendezvous model for a circular reference orbit and a spherical Earth [2]. Following the work of Clohessy and Wiltshire, variants on the point-mass model were developed, such as generalizations to elliptic reference orbits [3–5] and an oblate Earth [6,7]. The growing interest in SFF motivated the research of relative spacecraft motion modeling, yielding more accurate and complete equations and solutions for perturbed relative motion [8–10]. However, most of the works focused on point-mass, 3 degrees-offreedom (DOF) spacecraft. Obviously, performing a space mission that consists of several cooperative space vehicles requires modeling the relative rotational motion in addition to the relative translation, that is, 6-DOF models. Models for the relative motion of 6-DOF spacecraft have gained attention in the literature only in recent years. Among the first to suggest treating the spacecraft relative angular velocity in an SFF control problem were Pan and Kapila [11], who addressed the coupled translational and rotational dynamics of two spacecraft. By defining two body-fixed reference frames, one attached to the leader and the other attached to the follower, it was proposed [11] to use a two-part relative motion model: one that accounts for the relative translational dynamics of the body-fixed coordinate frame origins, and another that captures the relative attitude dynamics of the two body-fixed frames. A similar modeling approach was used for relative motion estimation [1]. In addition, tensorial equations of motion for a formation consisting ofN spacecraft, each modeled as a rigid body, were derived [12]. However, only the absolute equations of motion were developed [12]; a relative version of these equations was not given. Moreover, a clear mathematical relationship between the developed models and the traditional nonlinear point-mass relative motion and CW models was not provided. The coupling between the translational and rotational motion in the aforementioned models [1,11] was induced by gravity torques. The kinematic coupling, which is essentially a projection of the rotational motion about the center of mass (c.m.) onto the relative translational configuration space, was neglected. It is this kinematic coupling that the current paper is concerned with. In general, rigid-body dynamics can be represented as translation of the c.m. and rotation about the c.m. [13]. Thus, spacecraft relative motion must be composed by combining the relative translational and rotational dynamics of arbitrary points on the spacecraft. Whenever one of these points does not coincide with the spacecraft’s c.m., a kinematic coupling between the rotational and translational dynamics of these points is obtained. The purpose of this paper is to quantify the kinematic coupling effect and to show that this effect is key for high-precision modeling of tight SFF, rendezvous, and docking. This effect is also important in vision-based relative attitude and position control, where arbitrary feature points on a target vehicle are to be tracked. Given two rigidbody spacecraft, the model presented herein is formulated in a general manner that describes the motion between any two arbitrary points on the spacecraft. The relative translational motion is then generated by both the spacecraft orbitalmotion and the rotation about the c.m. In addition, this paper provides a CW-like approximation of the relative motion that includes the kinematic coupling. This new approximation is aimed at alleviating an apparent contradiction in linearized relative motion theories: to obtain linear equations of motion, the spacecraft are assumed to operate in close proximity. However, if the spacecraft are close to each other, then they can no longer be treated as point masses, because the spacecraft shape and size affects the relative translation between off-c.m. points. This effect is accentuated as the distances between spacecraft decrease. The remainder of this paper is organized as follows. First, a background on the relative position and attitude dynamics is given. Then, a new coupled relative spacecraft motion model is presented. The newly developed model is then examined in a simulation.

Manifolds and Metrics in the Relative Spacecraft Motion Problem

This paper establishes a methodology for obtaining the general solution to the spacecraft relative motion problem by utilizing the Cartesian configuration space in conjunction with classical orbital elements. The geometry of the relative motion configuration space is analyzed, and the relative motion invariant manifold is determined. Most importantly, the geometric structure of the relative motion problem is used to derive useful metrics for quantification of the minimum, maximum, and mean distance between spacecraft for commensurable and noncommensurable mean motions. A number of analytic solutions as well as useful examples are provided, illustrating the calculated bounds. A few particular cases that yield simple solutions are given. Nomenclature a = semimajor axis E = eccentric anomaly E = follower orbit e = eccentricity F = follower perifocal frame f = true anomaly I = inertial frame i = inclination Jk = Bessel function L = leader-fixed frame M = mean anomaly n = mean motion n0 = fundamental frequency R = leader position vector R = relative motion invariant manifold r = follower position vector W = distance function α = normalized semimajor axis μ = gravitational constant ρ = relative position vector � = right ascension of the ascending node ω = argument of periapsis ω = angular velocity vector |·| = vector norm �·� = signal norm Superscripts � = leader ∗ = relative orbital element

Real-Time Vision-Aided Localization and Navigation Based on Three-View Geometry

A new method for vision-aided navigation based on three-view geometry is presented. The main goal of the proposed method is to provide position estimation in GPS-denied environments for vehicles equipped with a standard inertial navigation system (INS) and a single camera only, without using any a priori information. Images taken along the trajectory are stored and associated with partial navigation data. By using sets of three overlapping images and the concomitant navigation data, constraints relating the motion between the time instances of the three images are developed. These constraints include, in addition to the well-known epipolar constraints, a new constraint related to the three-view geometry of a general scene. The scale ambiguity, inherent to pure computer vision-based motion estimation techniques, is resolved by utilizing the navigation data attached to each image. The developed constraints are fused with an INS using an implicit extended Kalman filter. The new method reduces position errors in all axes to the levels present while the first two images were captured. Navigation errors in other parameters are also reduced, including velocity errors in all axes. Reduced computational resources are required compared with bundle adjustment and simultaneous localization and mapping (SLAM). The proposed method was experimentally validated using real navigation and imagery data. A statistical study based on simulated navigation and synthetic images is presented as well.

Robust guidance for electro-optical missiles

A robust guidance law is presented which renders zero miss distance (ZMD) against deterministically or randomly maneuvering targets for all missile parametric uncertainties. Since the resulting guidance controller is a phase-lead network, it is mainly suitable for systems characterized by moderate glint levels such as electro-optical missiles. The structured uncertainties in missile dynamics are modeled by interval transfer functions. It is first shown that for the nominal case, when the total missile transfer function is positive real, ZMD can be obtained. When uncertainties are considered, the problem becomes design of a guidance controller which renders a family of transfer functions positive real. A new algorithm for the design of such controllers is proposed. An example illustrating a typical design procedure for a nonlinear real-life missile model is given, showing the simplicity and effectiveness of the proposed robust guidance. The main conclusion of this work is that the newly developed guidance law performs well against highly maneuvering targets and may be a suitable alternative to optimal guidance laws in low-glint systems.