Research opportunities exist in physics and phenomenology-based adaptive signal processing methods for enhanced radar target detection and estimation, tracking, and classification involving closed loop radar operation. The onerous challenges of harsh environments, difficult targets, and a rapidly shrinking electromagnetic spectrum necessitate a systematic treatment for developing closed-loop radar operation. The concept of fully adaptive radar (FAR) seeks to exploit all available degrees-of-freedom on transmit and receive in order to maximize target detection, tracking, and classification performance. This area has received increased interest in recent times and builds on a rich history of prior research. Of key importance is the concept of closed loop radar operation via feedback. Specifically feedback from the receiver and tracker to the transmitter for guiding the next illumination to better concurrently detect, and track targets of interest in computationally demanding and training data starved scenarios is required. A first step is the development of the feedback signal from the receiver and tracker to the transmitter through prescribed metrics such as mean squared error, entropy, or mutual information. The next step is to develop analytical and computer simulation methods for determining the detection, tracking, and classification performance with respect to single and multiple radar waveforms. Furthermore, due the large number of degrees of freedom, the number of unknown nuisance parameters incurs a substantial increase. Consequently the curse of dimensionality prevails. Novel approaches for overcoming this issue are of considerable interest. Concepts of machine learning can be brought to bear in a powerful manner in this context. Relevant performance metrics include the tracking error and computational cost. Extension of this approach to handle distributed and MIMO radar performance must be undertaken. Performance validation for both single and distributed radar needs to be analyzed using simulated and measured data sets.

 

key words

Fully adaptive radar; Closed-loop radar operation; Concurrent detection; Tracking and classification; Feedback control design; Performance benchmarking and validation;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral and Senior applicants