Development of a resource manager framework for adaptive beamformer selection

Adaptive digital beamforming (DBF) algorithms are designed to mitigate the effects of interference and noise in an radio frequency (RF) environment encountered by modern electronic support (ES) receivers. Traditionally, an ES receiver employs a single adaptive DBF algorithm that is part of the design of the receiver system. If the ES receiver is designed to form multiple independent beams, the same adaptive DBF algorithm is applied in each beam. Traditional receiver design is effective and works when system processing power is limited. Modern computer technology allows improvements over traditional receiver design, where a receiver is able to change the implemented algorithm based upon system usage. This dissertation provides a new ES receiver framework that attempts to make better use of available computing resources by adaptively selecting the most ecient DBF algorithm for each beam that is able to meet system requirements. The framework contains a resource manager (RM) that facilitates adaptive algorithm selection through the use of a look-up-table (LUT). The RM estimates parameters of the RF environment, to include the number of signals present in the environment, whether the signals are wideband or narrowband, and their respective directions-of-arrival (DOAs). The parameters of signal relative bandwidth and the number of signals in the environment are used to select an adaptive DBF algorithm from the LUT. The resource manager also contains a method to detect signals-of-interest (SOIs) in the RF environment and to estimate their respective DOAs for use in adaptive DBF implementation. The SOI detection method also indicates the number of independent simultaneous beams the receiver is required to form.;Implementation of the proposed framework requires the development of the adaptive DBF LUT. Creation of the LUT requires selecting a set of adaptive DBF algorithms, determining their sensitivity to dierent environmental parameters, and choosing the best algorithm for each member of a selected set of RF environments. The RF environment parameters with the highest sensitivity are used to create the set of RF environments. This dissertation focuses on development and characterization of the RM but provides a representative LUT creation for demonstration purposes. Future users of the framework are required to formulate their own LUT. The methods of the RM, however, are designed to be used intact from the research and implemented with a user generated LUT.