SBIR-STTR Award

To support Navys need for improved detection, tracking, and classification within the Continuous Active Sonar (CAS) functional segment (CASFS) of the AN/SQQ-89A(V)15, ARiA will develop and demonstrate signal- and information-processing algorithms that reduce range uncertainty, recover signal mismatch loss, and improve tracking performance. The Phase I effort will (1) develop algorithms for estimating and compensating for time-varying platform motion within a coherent processing interval, (2) develop features for classification and tracking derived from sparse model-based estimation, and (3) demonstrate that PICASSO algorithms can meet Navys need for improved tracking and classification performance on archived and simulated data representative of the AN/SQQ-89A(V)15 operating at full duty cycle with sub-CPI platform and target motion.

Benefit:
The PICASSO signal and information processing algorithms and software developed in this work will advance the state-of-the-art in tracking and classification for CAS. Phase I efforts will specifically contribute validated new concepts and algorithms for estimating and compensating for sub-CPI motion-induced uncertainty and signal-mismatch loss and physics-based tracking and classification clues that improve track localization and target classification. Results of the Phase I effort will provide a basis for Phase II development of the most promising algorithms into a software library and transition into the tactical system. Signal-processing algorithms in particular may be applied to commercial midfrequency sonar systems used for subbottom profiling, single-beam and multi-beam (swath) bathymetry, and acoustic seafloor characterization.

Keywords:
tracking, tracking, waveforms, Active sonar, Continuous Active Sonar, detection, Doppler, antisubmarine warfare, Clutter Reduction

Renewable energy, specifically photovoltaic, is an attractive technology for man-portable power sources and tactical applications. However, to be effective as a system, it is necessary to have a power manager that can efficiently couple a small solar array (~20W) to a battery such as the BB2590. Power managers are already being fielded with PV sources, but their usefulness has been limited by the design of the power manager. The goal of this topic is to develop a cost-effective, lightweight power manager that displays high efficiencies for low power modules in a user-friendly format that can rapidly charge a BB2590. In addition, given the nature of Li-ion batteries, maximum use of solar input is achieved when multiple batteries are charged in parallel, so a power manager is sought that can charge multiple batteries simultaneously. Other capabilities that will benefit the system are scavenge mode, buck/ boost capability, high-speed maximum point tracking, reduced heat and IR signature, a wide operating temperature range, charging capability in low light (<0.1W input power), and near loss-less power transfer.