Fully Adaptive Radar

Period of Performance: 08/26/2013 - 05/26/2014

$150K

Phase 1 SBIR

Recipient Firm

Black River Systems Co., Inc.
162 Genesee Street
Utica, NY 13502
Principal Investigator

Abstract

ABSTRACT: The challenge set by Fully Adaptive radar tech techniques is how to best optimize all of the possible radar settings all of the possible transmit and receive degrees of freedom to maximize radar performance. The available degrees of freedom, including transmitter parameters such as beamshape and waveform, receiver parameters such as beamformer and coherent processing, and radar timeline parameters such as antenna scan pattern, as well as rapidly changing and competing mode requirements such as surveillance, tracking, SAR, and emerging techniques such as multi-static operation and MIMO waveforms, combine to provide an almost limitless set of parameters that can be varied. Optimal parameter selection can become unclear, and can change rapidly with environmental operating conditions. Black River proposes to address these issues by developing a theoretical optimal performance prediction, to develop an initial set of metrics that can be used to evaluate the environment, and then to formulate an adaptive method to drive parameter selection. We will develop a radar performance model that can be used to evaluate overall system performance in a realistic simulated environment, and which can be used as the basis for further development and evaluation. BENEFIT: An accurate and efficient simulation capability of airborne fully adaptive radar systems will help researchers and developers to streamline and enhance the processes of adaptive radar requirements definition, data collection / validation planning, and development of the environmental assessment and intelligent radar parameter control algorithms. Commercial entities could exploit this tool to identify applications where adaptive radar could cost effectively satisfy system requirements, either with reduced payload (size weight, and power), or enhanced performance. The use of a simulated environment as an algorithm testbed also allow testing real radar parameter control algorithms against optimal ideal performance, which can often be simulated but may not be realizable in an actual system