A method for jointly estimating gain-phase error and direction of arrival (DOA) based on an unmanned aerial vehicle (UAV) array includes: equipping each UAV with an antenna, and forming a receive array through a swarm of multiple UAVs to receive source signals; when an observation baseline of the swarm remains unchanged, changing array manifold through movement of the UAVs, and re-sensing the source signals; for each sensed source signals, calculating a covariance matrix, and obtaining a corresponding noise subspace through eigenvalue decomposition; and constructing a quadratic optimization problem based on the noise subspace and array steering vector, constructing a cost function, and implementing joint estimation of the gain-phase error and the DOA through spectrum peak search. The method can jointly estimate the DOA and gain-phase error and calibrate the gain-phase error, thereby improving accuracy of passive positioning.

The systems and methods use Hermetic Transform processing to achieve higher resolution in space, time, and frequency measurements, leading to enhanced object detection, localization, and classification, and can improve several aspects of RADAR, including: phased-array beamforming, Doppler filter processing, pulse compression/replica correlation, and in the creation of higher resolution ambiguity function measurements for both multi-static active and passive RADAR.

The systems and methods use Hermetic Transform processing to achieve higher resolution in space, time, and frequency measurements, leading to enhanced object detection, localization, and classification, and can improve several aspects of RADAR, including: phased-array beamforming, Doppler filter processing, pulse compression/replica correlation, and in the creation of higher resolution ambiguity function measurements for both multi-static active and passive RADAR.

An example method for estimating the angle-of-arrival (AoA) and other parameters of radio frequency (RF) signals that are received by an antenna array comprises: receiving a plurality of radio frequency (RF) signal power measurements by a plurality of antenna elements at a plurality of RF channels; computing, by applying a machine learning model to the plurality of RF signal power measurements, an estimated RF signal parameter value; and outputting the RF signal parameter value.

An example method for estimating the angle-of-arrival (AoA) and other parameters of radio frequency (RF) signals that are received by an antenna array comprises: receiving a plurality of radio frequency (RF) signal power measurements by a plurality of antenna elements at a plurality of RF channels; computing, by applying a machine learning model to the plurality of RF signal power measurements, an estimated RF signal parameter value; and outputting the RF signal parameter value.

Methods and systems for spatial filtering transmitters and receivers capable of simultaneous communication with one or more receivers and transmitters, respectively, the receivers capable of outputting source directions to humans or devices. The methods and systems use spherical wave field partial wave expansion (PWE) models for transmitted and received fields at antennas and for waves generated by contributing sources. The source PWE models have expansion coefficients expressed as functions of directional coordinates of the sources. For spatial filtering receivers a processor uses the output signals from at least one sensor outputting signals consistent with Nyquist criteria representative of the wave field and the source PWE model to determines directional coordinates of sources (wherein the number of floating point operations are reduced) and outputs the directional coordinates and communications to a reporter configured for reporting information to humans. For spatial filtering transmitters a processor uses known receiver directions and source partial wave expansions to generate signals for transducers producing a composite total wave field conveying communications to the specified receivers. The methods and communications reduce the processing required for transmitting and receiving spatially filtered communications.

Methods and systems for spatial filtering transmitters and receivers capable of simultaneous communication with one or more receivers and transmitters, respectively, the receivers capable of outputting source directions to humans or devices. The methods and systems use spherical wave field partial wave expansion (PWE) models for transmitted and received fields at antennas and for waves generated by contributing sources. The source PWE models have expansion coefficients expressed as functions of directional coordinates of the sources. For spatial filtering receivers a processor uses the output signals from at least one sensor outputting signals consistent with Nyquist criteria representative of the wave field and the source PWE model to determines directional coordinates of sources (wherein the number of floating point operations are reduced) and outputs the directional coordinates and communications to a reporter configured for reporting information to humans. For spatial filtering transmitters a processor uses known receiver directions and source partial wave expansions to generate signals for transducers producing a composite total wave field conveying communications to the specified receivers. The methods and communications reduce the processing required for transmitting and receiving spatially filtered communications.

A radar apparatus is provided to receive a transmission wave reflected by a target object by antennas. The radar apparatus includes a signal analysis unit to analyze reception waves, and to obtain amplitudes and phases of the reception waves, at a frequency with which reception strength shows a peak. The radar apparatus also includes a direction detection unit to detect a direction of the target object based on the phases of the reception waves, and an estimated amplitude and phase output unit to output estimated amplitudes and estimated phases of reception waves to be received, assuming that the target object exists in the detected direction. The radar apparatus further includes a comparison unit to compare the amplitude or phase obtained by the signal analysis unit with that output by the estimated amplitude and phase output unit.

A radar apparatus is provided to receive a transmission wave reflected by a target object by antennas. The radar apparatus includes a signal analysis unit to analyze reception waves, and to obtain amplitudes and phases of the reception waves, at a frequency with which reception strength shows a peak. The radar apparatus also includes a direction detection unit to detect a direction of the target object based on the phases of the reception waves, and an estimated amplitude and phase output unit to output estimated amplitudes and estimated phases of reception waves to be received, assuming that the target object exists in the detected direction. The radar apparatus further includes a comparison unit to compare the amplitude or phase obtained by the signal analysis unit with that output by the estimated amplitude and phase output unit.

The present disclosure discloses an intelligent device navigation method and navigation system. The method comprises the following. Construct a plurality of antennas on a network card in the intelligent device into a linear antenna array. By using the linear antenna array, acquire channel state information of a wireless signal, and estimate an angle of arrival (AoA) and a time of flight (ToF) between the wireless signal transmitting device and the intelligent device. Measure inertial parameters of the intelligent device. Perform data fusion of the AoAs, the ToFs and the inertial parameters to estimate a state variable of the intelligent device. Adjust a motion state of the intelligent device with reference to the state variable, thereby achieving autonomous navigation of the intelligent device. The disclosure can estimate the state of the intelligent device by using wireless signals ubiquitous in the surrounding environment in a GPS unreliable environment.