Estimation and Optimal Configurations for Localization Using Cooperative UAVs

The time-difference of arrival techniques are adapted to locate networked enemy radars using a cooperative team of unmanned aerial vehicles. The team is engaged in deceiving the radars, which limits where they can fly and requires accurate radar positions to be known. Two time-differences of radar pulse arrivals at two vehicle pairs are used to localize one of the radars. An explicit solution for the radar position in polar coordinates is developed. The solution is first used for position estimation given “noisy” measurements, which shows that the vehicle trajectories significantly affect estimation accuracy. Analyzing the explicit solution leads to The Angle Rule, which gives the optimal vehicle configuration for the angle estimate. Analyzing the Fisher Information Matrix leads to The Coordinate Rule, which gives a different optimal configuration for the position estimate. A linearized time-varying model is also formulated and an Extended Kalman Filter applied. This estimation scheme is compared with the earlier one, with the second showing overall improvement in reducing the variance of the estimate.