MAX REVIEW

1. MAX REVIEW Cooperative Navigation in GPS Denied Environments 19 April 2013 Control Automation Branch, Aerospace Systems Directorate Air Force Research Laboratory

2. Overview Long-term Objective: Design control strategies such that a team of UAVs can navigate from one location to another in GPS denied environments. Why? “Further key emphasis must be placed on research to support increased freedom of operations in contested or denied environments…” (from TH) • Approach: Teaming and cooperation • Information acquisition (main purpose) • Reduced cost • Improved robustness • Research: • What information is needed? • How to obtain it? • Any optimality? • Our Expertise Portfolio: • Cooperative control • Stochastic control • Optimal control • Decentralized control The basic idea is to have a team of UAVs maintain a desired rigid formation and rotate around some designated UAV (on top of a UGS) until one UAV in the team connects to a subsequent UGS. UAV Autonomous Control in Denied Environments.

3. Steps and Tasks Note: We pay the price of “teaming and cooperation” to get “information”. cost benefit • 2-UAV navigation (a basic scenario) Navigation of two UAVs from one location to next • Cooperative estimation Estimation of inter-UAV distances • Structure estimation Estimation of the formation of the team • Structure maneuver A match between the current formation and the desired formation • Structure rotation Rotation of the formation CW or CCW • Synthesis A closed-loop point of view

4. Circumnavigation Circumnavigation is one fundamental research problem. Objective: Develop control algorithms such that a UAV can orbit around some unknown static target at some desired distance. : Target UAV: blue triangle : current distance from UAV to Target at time : desired stable distance : actual stable distance : bearing angle : (constant) velocity of the UAV

5. UAV Dynamics & Control Algorithm • UAV Dynamics • Control Algorithm • Range & Range Rate are needed for control algorithm • Assume a known, fixed velocity

6. Algorithm Motivation • The (desired) rate of change for • UAV heads toward tangent on desired orbit • Rate of change of given the UAV’s current heading Control Algorithm revisited

7. Result Note: A proof of the theorem can be found in a recent paper submitted to CDC13.

8. Ongoing Research What if is unavailable?

9. Challenges Q1: Under what conditions the stability can be guaranteed if the change rate of is replaced by ? Q2: Any other options besides the linear filter? • When using the linear filter, the challenges in the stability analysis are: • Properties for the closed-loop system when the change rate of is available do not necessarily hold • Nonlinear system dynamics • Limited information in the controller design due to the GPS denied environments

10. Additional Questions • Consideration of uncertainties: • Wind • Measurement noises • Latency • Loss of package • Other types of measurements: • Heading (e.g., magnetometer) • Bearing (e.g., VOR type of concept) Note: Additional measurements can be useful in two ways • Flexibility in the controller design • Improved performance by information fusion techniques (e.g., Kalman Filtering)