A position detection system includes a measurement unit that obtains a measurement value related to transmission and reception of radio waves from when the radio waves are transmitted from one of first and second communication devices to the other one of the first and second communication devices to when the one of the first and second communication devices receives a response to the radio waves to detect a positional relationship of the first and second communication devices. The measurement unit obtains multiple measurement values by performing communication to obtain the measurement value a multiple number of times in which a parameter of the communication is changed.

A position detection system includes a measurement unit that obtains a measurement value related to transmission and reception of radio waves from when the radio waves are transmitted from one of first and second communication devices to the other one of the first and second communication devices to when the one of the first and second communication devices receives a response to the radio waves to detect a positional relationship of the first and second communication devices. The measurement unit obtains multiple measurement values by performing communication to obtain the measurement value a multiple number of times in which a parameter of the communication is changed.

A method of selecting and optimizing a countermeasure for application against a novel, ambiguous, or unresponsive radar threat includes selecting a candidate countermeasure and an initial parameter set and varying at least one of the parameters while the effectiveness of the candidate countermeasure against the radar threat is assessed, for example by a human observer. Embodiments include repeating the process with additional candidate countermeasures. For an unresponsive radar threat, a previously effective countermeasure can be selected as the candidate countermeasure. For an ambiguous radar threat, at least one countermeasure previously verified as effective against a partially matching known threat can be selected as the candidate countermeasure. Correlated parameters can be simultaneously varied. An optimization surface and trajectory formed by a plurality of correlated parameters can be identified by machine intelligence, used to guide the parameter variations, and/or stored for use against the same or similar threats in the future.

A method of selecting and optimizing a countermeasure for application against a novel, ambiguous, or unresponsive radar threat includes selecting a candidate countermeasure and an initial parameter set and varying at least one of the parameters while the effectiveness of the candidate countermeasure against the radar threat is assessed, for example by a human observer. Embodiments include repeating the process with additional candidate countermeasures. For an unresponsive radar threat, a previously effective countermeasure can be selected as the candidate countermeasure. For an ambiguous radar threat, at least one countermeasure previously verified as effective against a partially matching known threat can be selected as the candidate countermeasure. Correlated parameters can be simultaneously varied. An optimization surface and trajectory formed by a plurality of correlated parameters can be identified by machine intelligence, used to guide the parameter variations, and/or stored for use against the same or similar threats in the future.

A waveform shaping unit (220) accumulates beat signals S9, which are beat signals S8 in frame units. A distance calculation unit (252) generates a histogram of range bins using the beat signals S9, and calculates a distance based on a range bin number corresponding to a peak in the histogram as a relative distance of a target object. A velocity calculation unit (253) generates a power spectrum of Doppler bins for each time period or for each range bin using the beat signals S9, generates a difference statistic graph that indicates a statistic of differences between power spectra, and calculates a velocity based on a Doppler bin number corresponding to a peak in the difference statistic graph as a relative velocity of the target object.

A waveform shaping unit (220) accumulates beat signals S9, which are beat signals S8 in frame units. A distance calculation unit (252) generates a histogram of range bins using the beat signals S9, and calculates a distance based on a range bin number corresponding to a peak in the histogram as a relative distance of a target object. A velocity calculation unit (253) generates a power spectrum of Doppler bins for each time period or for each range bin using the beat signals S9, generates a difference statistic graph that indicates a statistic of differences between power spectra, and calculates a velocity based on a Doppler bin number corresponding to a peak in the difference statistic graph as a relative velocity of the target object.

Described herein is a method and apparatus for a multi-beam digital system including a frequency reference device having an output for providing a frequency reference signal; a fanout device connected to the frequency reference device and configured to generate n frequency reference signals from the frequency reference signal output from the frequency reference device, having n outputs configured to output the n frequency reference signals, respectively, where n is a positive integer; n local clock domain devices configured to synchronize the n frequency reference signals and distribute reference and clock signals having deterministic phase and phase/data alignment; and n beamforming devices connected to the n local clock domain devices, respectively, and configured to form a user-definable beam, and having n input configured to receive n radio frequency (RF) signals, and n outputs for transmitting n RF signals.

Embodiments for securing fine timing measurement (FTM) communications are described. FTM communications include FTM frames sent and received from an initiating station (ISTA) and a responding station (RSTA). The RSTA records a plurality of parameters associated with the FTM frames and uses the plurality of parameters to learn and identify a device profile for the ISTA. The device profile is used to determine a behavior filter for the FTM from the ISTA and the RSTA filters FTM traffic according to the behavior filter to prevent malicious attacks in the FTM communications.

Embodiments for securing fine timing measurement (FTM) communications are described. FTM communications include FTM frames sent and received from an initiating station (ISTA) and a responding station (RSTA). The RSTA records a plurality of parameters associated with the FTM frames and uses the plurality of parameters to learn and identify a device profile for the ISTA. The device profile is used to determine a behavior filter for the FTM from the ISTA and the RSTA filters FTM traffic according to the behavior filter to prevent malicious attacks in the FTM communications.

According to one embodiment, a radar apparatus includes a signal processing device that has a first circuit, a second circuit and a transmitter. The first circuit is configured to determine whether or not there is a radio interference based on a radio signal received via an antenna. The second circuit is configured to, when the first circuit determines that there is the radio interference, select a predetermined pulse pattern based on an avoiding function of a wireless communication device having the avoiding function of the radio interference, the predetermined pulse pattern being separately defined from a pulse pattern of transmission processing for operating a radar. The transmitter is configured to transmit from the antenna a radio signal matching the pulse pattern selected by the second circuit.