Abstract: A method and system for detecting pulsed communication signals, the method and system includes obtaining a time-frequency representation of a received training data signal, the received training data signal representative of a known/training bitstream associated with a transmitted pulse signal; using a scalogram process to convert the time-frequency representation of the received training data signal into a plurality of training images, and training a deep learning architecture platform with the plurality of training images to generate a classification model representative of a plurality of high bit states and a plurality of low bit states included in the plurality of training images.

Abstract: A system and method involve determining a time difference of arrival between two robust broadcast digital television (DTV) signals received at a mobile receiver and a monitor receiver from at least two DTV transmitters, determining a pseudorange between the mobile receiver and each of the DTV transmitters, and determining a position of the mobile receiver using the determined pseudoranges and the distance between the monitor receiver and the mobile receiver.

Abstract: Embodiments in accordance with the invention provide a state-based channel selection method to improve the rate of successful transmissions for a multi-channel wireless network. Channels are monitored for performance, and, based upon performance, are placed in channel state vectors having increasing levels of desirability. The higher the state vector in which a channel is placed, the more desirable the channel is considered for selection. The channel in the highest state vector is considered for selection first. A channel not in the highest desirable state vector is eligible for selection when a channel is unavailable from higher desirable state vectors. Channels not in the highest desirable state vector, but also not in the lowest undesirable state vector, are monitored for improvement to move into higher desirable state vectors as they improve.