This application relates to the field of wireless communications and self-driving/intelligent driving/autonomous driving vehicles, and in particular, to the field of collaborative radars. A first apparatus receives first information from a second apparatus. The first apparatus determines, based on the first information, the priorities of a plurality of time-frequency resources included in a first time-domain range. The first apparatus further selects a first time-frequency resource among the plurality of time-frequency resources. The priority of the first time-frequency resource is the highest among the priorities of the plurality of time-frequency resources. A time-frequency resource with a comparatively high priority is selected to send a radar signal, to reduce a probability of a resource collision, and reduce and/or avoid interference between radars, especially collaborative radars.

A communication system has a phased antenna array configured to communicate via a plurality of beams with a wireless device, such as user equipment (e.g., a smart phone). The plurality of beams defines a field of view of the phased antenna array, the field of view having a plurality of cells and each of the plurality of beams is associated with one of the plurality of cells within the field of view. A processing device detects the wireless device within the field of view and determines a coarse geographic location of the wireless device within the field of view of the wireless device when the wireless device is within the field of view, or within a cell. The system further determines a fine geographic location for the wireless device based on frequency offset (due to Doppler) and signal flight time.

A method of determining a user location comprises: calculating a horizontal velocity and direction of horizontal movement of a mobile device in communication with at least one wireless access point, calculating an observed Doppler shift in a signal transmitted between the mobile device and the at least one wireless access point, calculating an expected Doppler shift in the transmitted signal based on a carrier frequency, the horizontal velocity and direction of horizontal movement, and determining a vertical position of the mobile device based on the expected Doppler shift and the observed Doppler shift. A mobile device, apparatus and positioning system for performing the method are also provided.

A signal processing system is provided. The signal processing system includes a transmission architecture configured to transmit first and second signals, and a receiver architecture including an antenna configured to receive the signals, and a coherent signal fusion processing device communicatively coupled to the antenna. The processing device is configured to generate a broadband analog signal that contains the first and second signals, digitize the broadband analog signal, isolate first and second signals of interest, estimate, relative to a reference template, at least one of a time difference of arrival and a frequency difference of arrival for at least one of the first and second signals of interest, and determine a location of at least one of the transmission architecture and the receiver architecture based on the estimated at least one of a time difference of arrival and a frequency difference of arrival.

A method for improving geolocation accuracy in a passive radar warning receiver, using synchronized data curve-fit and interpolation to asynchronous and noisy receiver and navigation measurements over observation periods that are extended to reduce inaccuracies caused by noise. The present disclosure yields synchronized data samples at intervals short enough that constant-rate equations are valid, even though the actual motions over the observation interval may be more complex and have higher-order dynamics. It reduces noise, synchronizes data samples, and is readily adapted to motions with variable acceleration. The method generates rate samples short enough to satisfy constant rate assumptions, yet fit data over intervals long enough to enhances measurement accuracy by reducing measurement noise.

This disclosure provides systems, methods and apparatuses for classifying traffic flow using a plurality of learning machines arranged in multiple hierarchical levels. A first learning machine may classify a first portion of the input stream as malicious based on a match with first classification rules, and a second learning machine may classify at least part of the first portion of the input stream as malicious based on a match with second classification rules. The at least part of the first portion of the input stream may be classified as malicious based on the matches in the first and second learning machines.

The invention involves using Doppler shift to locate a leak of a signal from an HFC network. The leaked signal includes a component having a nominal frequency. The invention comprises: (a) moving along a drive route in the area of the network; (b) recording a speed at a number of drive-route points along the drive route; (c) at each point, receiving the component at a received frequency; (d) for each point, measuring the received frequency; (e) for each point, determining a measured Doppler shift from a difference between the received and nominal frequencies; (f) estimating a zero Doppler shift and a zero Doppler shift point based on the measured Doppler shifts; and (g) estimating the leak location based on the estimated zero Doppler shift point.

Embodiments provided describe detections of RF leakage test signal emanating from cable plant. In one embodiment a single mobile receive antenna, connected to a complex demodulator mobile receiver, receives a stabilized test signal radiating from the cable plant. The test signal may be a known continuous wave (CW) carrier or other deterministic signal. The received test signal varies in phase as a function of a position of the mobile receive antenna relative to the location of a leakage antenna. The phase variance forms a Doppler shift as the test antenna moves relative to the leakage antenna. The receiver generates multiple in-phase (I) and quadrature (Q) test signal samples over a SPA (synthetic phased array) distance as the test antenna's travels, and the samples are inserted into a Fourier transform. The result of the transform is instantaneous Doppler frequency shift, from which a bearing angle can be computed.

An electronic device may include wireless circuitry that detects the location of external objects. A signal generator may concurrently transmit different radio-frequency ranging signals over two or more transmit antennas. The ranging signals may include waveforms with time-varying frequencies, where each waveform includes frequencies that are non-overlapping with the frequencies of each of the other waveforms at any given time. Antennas may receive reflected versions of the ranging signals and a processor may process the reflected versions of the ranging signals to identify the location of the external objects. This may prevent interference between the ranging signals and may significantly reduce the latency of location detection relative to examples where the ranging signals are transmitted by different transmit antennas in series.

A hybrid method of estimating position of a mobile device which utilizes both received signal power and timing measurements. Received signal power of signals received by the mobile device from a plurality of cells are measured and corresponding received signal power measurements are stored. The method further includes measuring, at the mobile device, times of arrival of signals received from the plurality of cells. A plurality of time difference of arrival (TDOA) measurements are determined from the times of arrival. A power-time hybrid Gaussian maximum likelihood estimator and positioning assistance data for the plurality of cells are used to generate a maximum likelihood estimate of the position of the mobile device by evaluating a joint conditional probability of the received signal power measurements and the plurality of TDOA measurements. Gaussian random variables may be used to represent the received signal power measurements and the TDOA measurements.