Khanh Pham

Multi-Pursuer Multi-Evader Pursuit-Evasion Games with Jamming Confrontation

Existing pursuer-evader (PE) game algorithms do not provide good real-time solutions for situations with the following complexities: (1) multi-pursuer multi-evader, (2) multiple evaders with superior control resources such as higher speeds, and (3) jamming confrontation between pursuers and evaders. This paper introduces a real-time decentralized approach, in which decentralization strategy reduces computational complexity in multi-pursuer multievader situations, cooperative chasing strategy guarantees capture of some superior evaders, and min-max double-sided jamming confrontation provides optimal jamming-estimation strategies under adversarial noisy environments. Extensive simulations confirm the efficiency of this approach.

On-Orbit Identification of Inertia Properties of Spacecraft Using a Robotic Arm

This paper presents a robotics-based method for on-orbit identification of inertia properties of spacecraft. The method makes use of an onboard robotic arm to change the inertia distribution of the spacecraft system. As a result of the inertia redistribution, the velocity of the spacecraft system will change correspondingly. Because the velocity change is measurable and the inertia redistribution of the robotic arm itself is precisely computable, the inertia parameters of the spacecraft body become the only unknown in the momentum equations and, hence, can be identified from the momentum equations of the spacecraft system. To treat the problem as a linear identification problem, it has to be solved in two steps. The first step is to identify the mass and mass center of the spacecraft; and the second step is to identify the inertia tensor of the spacecraft. The advantages of this method are 1) it does not consume fuel because a robotic subsystem is energized by solar power; 2) it requires measuring velocities only, but not accelerations and forces; and 3) it is not affected by internal forces, which are difficult to accurately measure. The paper investigates the sensitivity of the method with respect to different arm/spacecraft mass ratios, arm motion trajectories, and velocity-measurement errors.

Orbital satellite pursuit-evasion game-theoretical control

This paper develops and evaluates a trust-based sensor management game-theoretical control approach for orbital pursuit-evasion for satellite interception and collision avoidance. Using a coupled zero-sum differential pursuit-evasion (PE) game, the pursuer minimizes the satellite interception time and evader tries to maximize interception time for collision avoidance. A trust-based decentralized sensor manager performs sensor-to-target assignment and nonlinear tracking. The interception-avoidance (IA) game approach provides a worst-case solution, which is the robust lower-bound performance case. We divide our IA algorithm into two parts: first, the pursuer will rotate its orbit to the same plane of the evader, and second, the two spacecrafts will play a zero-sum PE game. A two-step setup saves energy during the PE game because rotating a pursuer orbit requires more energy than maneuvering within the orbit plane. For the PE orbital game, an optimum open loop feedback saddle-point equilibrium solution is calculated between the pursuer and evader control structures. Using the open-loop feedback rule, each player calculates their distributed control track state. Numerical simulations demonstrate the performance using the NASA General Mission Analysis Tool (GMAT) simulator.

Comparison of Several Space Target Tracking Filters

In this paper, we present a comparative study of several nonlinear filters, namely, extended Kalman Filter (EKF), unscented KF (UKF), particle filter (PF), and recursive linear minimum mean square error (LMMSE) filter for the problem of satellite trajectory estimation. We evaluate the tracking accuracy of the above filtering algorithms and obtain the posterior Cramer-Rao lower bound (PCRLB) of the tracking error for performance comparison. Based on the simulation results, we provide recommendations on the practical tracking filter selection and guidelines for the design of observer configurations.

Pursuit-evasion orbital game for satellite interception and collision avoidance

This paper develops and evaluates a pursuit-evasion orbital game approach for satellite interception and collision avoidance. Using a coupled zero-sum differential pursuit-evasion game, the pursuer minimizes the satellite interception time, and the evader tries to maximize interception time for collision avoidance. For the satellite interception problem we design an algorithm for pursuer and one for collision avoidance, where the game solution controls the evader satellite. The interception-avoidance (IA) game approach provides a worst-case solution, which is the robust lower-bound performance case. We divide our IA algorithm into two parts: first, the pursuer will rotate its orbit to the same plane of the evader; and second, the two spacecraft will play a zero-sum pursuit-evasion (PE) game. A two-step setup saves energy during the PE game because rotating a pursuer orbit requires more energy than maneuvering within the orbit plane. For the PE orbital game, an optimum open loop feedback saddle-point equilibrium solution is calculated between the pursuer and evader control structures. Using the open-loop feedback control rule, each player will calculate their distributed control track state. Numerical simulations are calculated to demonstrate the performance.

A Holistic Cloud-Enabled Robotics System for Real-Time Video Tracking Application

Future distributed sensor fusion applications will require efficient methods of information management such as Cloud computing. Using a server-based cloud-enabled software architecture would increase performance over hardware constraints (e.g., power, memory, and processors). In this paper, we propose a comprehensive framework for information fusion demonstrated for Cloud Robotics, which possesses user favorable features such as good scalability and elasticity. Robots are connected together to form a networked robotic system that is able to accomplish more computationally intensive tasks. Supported by the emerging Cloud computing technology, cloud-enabled robotic systems (CERS) provide even more powerful capabilities to users, yet keeping the simplicity of a set of distributed robots. Through an experimental study, we evaluate the memory, speed, and processors needed for a video tracking application.

Cooperative aircraft defense from an attacking missile

This paper addresses a three-body pursuit-evasion scenario where an Attacker missile using Pure Pursuit guidance pursues a Target aircraft and a Defender missile launched by a wingman aims at intercepting the Attacker before it reaches the aircraft. An optimal control problem is posed which captures the goal of the Target-Defender team, namely, to maximize the separation between Target and Attacker at the instant of capture of the Attacker by the Defender. The optimal control law provides the heading angles for the Target and the Defender team.

Cooperative space object tracking using space-based optical sensors via consensus-based filters

Cooperative tracking plays a key role in space situation awareness for scenarios with a limited number of observations or poor performance of a single sensor or both. To use the information from multiple networked sensors, both centralized and decentralized fusion algorithms can be used. Compared with centralized fusion algorithms, decentralized fusion algorithms are more robust in terms of communication failure and computational burden. One popular distributed estimation approach is based on the average consensus that asymptotically converges to the estimate by multiple exchanges of neighborhood information. Consensus-based algorithms have become popular in recent years due to the fact that they do not require global knowledge of the network or routing protocols. The main contributions of this paper are an effective space-based object (SBO) measurement model that considers the geometric relation of the Sun, the space object, the SBO sensor, and the Earth; two consensus-based filters, the information-weighted consensus filter (ICF) and the Kalman consensus filter (KCF), are used to track space objects by using multiple SBO sensors; and the cubature rule-embedded ICF (Cub-ICF) and KCF (Cub-KCF) are proposed to improve the accuracy of the ICF and KCF. Three scenarios that contain one or two space objects and four SBOs are used to test proposed algorithms. We also compare the consensus-based space object tracking algorithms with the centralized extended information filter (centralized EIF) and the centralized cubature information filter (centralized Cub-IF). The simulation results indicate that cooperative space object tracking algorithms provide better results than algorithms using a single sensor, the consensus-based tracking algorithms can achieve performance close to that of the centralized algorithms, and the Cub-ICF and Cub-KCF outperform the conventional ICF and KCF for a challenging space object tracking case shown in the paper. The proposed Cub-ICF and Cub-KCF algorithms should facilitate the application of using consensus-based filters for cooperative space object tracking.

Space object tracking with delayed measurements

This paper is concerned with the nonlinear filtering problem for tracking a space object with possibly delayed measurements. In a distributed dynamic sensing environment, due to limited communication bandwidth and long distances between the earth and the satellites, it is possible for sensor reports to be delayed when the tracking filter receives them. Such delays can be complete (the full observation vector is delayed) or partial (part of the observation vector is delayed), and with deterministic or random time lag. We propose an approximate approach to incorporate delayed measurements without reprocessing the old measurements at the tracking filter. We describe the optimal and suboptimal algorithms for filter update with delayed measurements in an orbital trajectory estimation problem without clutter. Then we extend the work to a single object tracking under clutter where probabilistic data association filter (PDAF) is used to replace the recursive linear minimum means square error (LMMSE) filter and delayed measurements with arbitrary lags are be handled without reprocessing the old measurements. Finally, we demonstrate the proposed algorithms in realistic space object tracking scenarios using the NASA General Mission Analysis Tool (GMAT).

Awareness-based game-theoretic space resource management

Over recent decades, the space environment becomes more complex with a significant increase in space debris and a greater density of spacecraft, which poses great difficulties to efficient and reliable space operations. In this paper we present a Hierarchical Sensor Management (HSM) method to space operations by (a) accommodating awareness modeling and updating and (b) collaborative search and tracking space objects. The basic approach is described as follows. Firstly, partition the relevant region of interest into district cells. Second, initialize and model the dynamics of each cell with awareness and object covariance according to prior information. Secondly, explicitly assign sensing resources to objects with user specified requirements. Note that when an object has intelligent response to the sensing event, the sensor assigned to observe an intelligent object may switch from time-to-time between a strong, active signal mode and a passive mode to maximize the total amount of information to be obtained over a multi-step time horizon and avoid risks. Thirdly, if all explicitly specified requirements are satisfied and there are still more sensing resources available, we assign the additional sensing resources to objects without explicitly specified requirements via an information based approach. Finally, sensor scheduling is applied to each sensor-object or sensor-cell pair according to the object type. We demonstrate our method with realistic space resources management scenario using NASAs General Mission Analysis Tool (GMAT) for space object search and track with multiple space borne observers.