A formulation for a joint communication and estimation problem is proposed: simultaneous communication over a noisy channel and estimation of certain channel parameters are desired. We are interested in quantifying the tradeoff between the achievable rate and distortion in estimating the channel parameters. Two particular sample channels are considered and achievable rates for these channels are determined. First, the binary symmetric channel is examined; an achievable capacity-distortion tradeoff is derived for both joint and time-orthogonal protocols. For the flat fading, additive, white, Gaussian noise channel, a novel joint communication and estimation scheme using low correlation sequences is presented. It is observed that in most situations, joint communication and estimation performs better than a scheme where communication and estimation are performed individually, furthermore, the gains of joint communication and estimation over individual communication and estimation can be significant as the distortion tolerance increases. Finally, it is observed that even a slight tolerance to errors in the channel parameters close to the theoretical lower bounds yield significant improvements in the rate at which reliable communication is achievable.

Unmanned surface vehicles (USVs) are subjected to external forces such as wind, water currents and waves which make their control challenging. Typical problems in USV control involve navigation, trajectory tracking and station keeping. Station keeping implies dynamic positioning in order to reject disturbances while holding position. This is necessary when sensors need a sufficiently large warm-up and/or dwell time, to ensure that the data collected pertains to the appropriate location where measurements are being made. This poster describes ongoing work on the robotic boat RoboDuck-II in addressing these issues.