Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for signal detection using machine learning models. In some implementations, a method includes obtaining communications data comprising one or more radio signals; providing the communications data to a first machine learning model that is trained to detect frequency bands that likely include radio signals; obtaining information representing one or more frequency bands that correspond to likely radio signals in the communications data as an output of the first machine learning processing the communications data; providing at least a portion of the communications data corresponding to the one of the one or more frequency bands to a second machine learning model that is trained to detect one or more features of radio signals; and obtaining a signal classification as an output of the second machine learning model generated by processing the portion of the communications data provided to the machine learning model.

Abstract: A radio-frequency (RF) receiver includes: at least n antennas, where n is an integer greater than two; m processing channels configured to receive and process n RF signals from the at least n antennas, where m is an integer greater than one and less than n; a controller configured to cause a first processing channel of the m processing channels to receive, at different corresponding times, a plurality of RF signals of the n RF signals; an indexing module configured to receive outputs from the m processing channels, and generate one or more representations of the n RF signals based on the outputs; and a spatial estimation module configured to receive the one or more representations, execute a machine learning model based on the one or more representations, and determine, based on an output of the machine learning model, a spatial estimate for an emitter of the n RF signals.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for positioning a radio signal receiver at a first location within a three dimensional space; positioning a transmitter at a second location within the three dimensional space; transmitting a transmission signal from the transmitter to the radio signal receiver; processing, using a machine-learning network, one or more parameters of the transmission signal received at the radio signal receiver; in response to the processing, obtaining, from the machine-learning network, a prediction corresponding to a direction of arrival of the transmission signal transmitted by the transmitter; computing an error term by comparing the prediction to a set of ground truths; and updating the machine-learning network based on the error term.

Abstract: A radio-frequency (RF) receiver includes: at least n antennas, where n is an integer greater than two; m processing channels configured to receive and process n RF signals from the at least n antennas, where m is an integer greater than one and less than n; a controller configured to cause a first processing channel of the m processing channels to receive, at different corresponding times, a plurality of RF signals of the n RF signals; an indexing module configured to receive outputs from the m processing channels, and generate one or more representations of the n RF signals based on the outputs; and a spatial estimation module configured to receive the one or more representations, execute a machine learning model based on the one or more representations, and determine, based on an output of the machine learning model, a spatial estimate for an emitter of the n RF signals.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for positioning a radio signal receiver at a first location within a three dimensional space; positioning a transmitter at a second location within the three dimensional space; transmitting a transmission signal from the transmitter to the radio signal receiver; processing, using a machine-learning network, one or more parameters of the transmission signal received at the radio signal receiver; in response to the processing, obtaining, from the machine-learning network, a prediction corresponding to a direction of arrival of the transmission signal transmitted by the transmitter; computing an error term by comparing the prediction to a set of ground truths; and updating the machine-learning network based on the error term.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for positioning a radio signal receiver at a first location within a three dimensional space; positioning a transmitter at a second location within the three dimensional space; transmitting a transmission signal from the transmitter to the radio signal receiver; processing, using a machine-learning network, one or more parameters of the transmission signal received at the radio signal receiver; in response to the processing, obtaining, from the machine-learning network, a prediction corresponding to a direction of arrival of the transmission signal transmitted by the transmitter; computing an error term by comparing the prediction to a set of ground truths; and updating the machine-learning network based on the error term.