A system and method for detecting a rotary wing aircraft. A return electromagnetic signal, reflected by a rotary wing aircraft, is received through an electromagnetic signal detection apparatus. The aircraft includes a plurality of propeller blades attached to at least one motor. At least one propeller blade has at least one portion with a reflectivity different from other portions. A first time series data of the return electromagnetic signal is received. A second time series data is determined based on the first time series data and a predefined threshold. A characteristic of the second time series data is used to determine whether it corresponds to the known aircraft.

In some example embodiments, there is provided a tag. The tag may include an antenna configured to receive a first radio frequency signal and to reradiate a second radio frequency signal; and an ultrasonic transducer coupled to the antenna, wherein an ultrasound signal received by the ultrasonic transducer causes a variation of at least one property of the ultrasonic transducer, wherein the variation of the at least one property imparts a modulation onto at least a portion of the first radio frequency signal, and wherein the modulated first radio frequency signal is reradiated by the antenna as the second radio frequency signal. Related system, methods, and articles of manufacture are also disclosed.

A vehicle-interior monitoring apparatus for a vehicle includes a sensor and a determiner. The sensor is configured to output a millimeter radio wave toward a vehicle cabin of the vehicle and detect a millimeter reflection wave from an in-vehicle object including an occupant in the vehicle cabin of the vehicle and baggage in the vehicle cabin of the vehicle. The determiner is configured to determine a type of the in-vehicle object in the vehicle cabin of the vehicle based on a detection level of the millimeter reflection wave detected by the sensor. The determiner is configured to perform a determination, the determination including determining that the in-vehicle object is either one of a child as the occupant or the baggage based on a tendency of a change in the detection level of the millimeter reflection wave detected by the sensor.

Methods and systems for mapping boundaries of a given environment by a processor of a computer system, the method comprising: determining a trajectory of the body in the given environment over the given time period; and determining, based on the trajectory of the body in the given environment, one or more of an outer boundary of the given environment, and an inner boundary of the given environment. Methods and systems for mapping functionalities of a given environment executable by a processor of a computer system, the method comprising determining a pattern of movement of a body in the given environment in a given time period; and determining a functional identity of at least one zone in the given environment based on the pattern of movement of the body to obtain a mapped given environment.

This document describes techniques for fine-motion virtual-reality or augmented-reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or sub-millimeter scale, for user control actions even when those actions are small, fast, or obscured due to darkness or varying light. Further, these techniques enable fine resolution and real-time control, unlike conventional RF-tracking or optical-tracking techniques.

A method and electronic device for radar-based face authentication anti-spoofing for determining access to the electronic device. The electronic device includes a radar transceiver and at least one processor. The at least one processor is configured to transmit, via the transceiver, a first set of signals, generate a channel impulse response (CIR) based on receipt of reflections of the first set of signals, detect a first CIR tap in the CIR, determine a selection of CIR data based on the detected first CIR tap, determine a profile matching metric based on comparison of the selection of CIR data to a set of predetermined reference signals, and determine whether to allow access to the electronic device based on comparison of the profile matching metric to a profile matching threshold.

A first behaviometric user profile for a first user is generated and stored, by detecting a position and velocity of the first user relative to the mobile device based on a received response from a radar transmission while the first user uses the mobile device, the received response over time indicating a position and velocity of the first user. Based on further received responses of additional radar transmissions an additional behavioral pattern of an unknown user is determined. The additional behavioral pattern is then compared to the first behaviometric user profile, and based on the comparison, a measure of similarity between the first behaviometric user profile and the additional behavioral pattern, measuring if the first user and the unknown user are a same user is heuristically determined. As a result of the comparison, operation or access to at least some data stored on the mobile device is prevented.

Embodiments relate to using an active reflected wave detector to classify the state of a person in an environment and optionally respond accordingly. In one embodiment there is provided a computer implemented method of determining a state of a person comprising: receiving an output of an active reflected wave detector; classifying a state of the person as being in a safe supported state based on the output using measurements of reflections associated with the person, wherein said classifying is based at least on: a height metric associated with at least one reflection from the person conveyed in the output of the active reflected wave detector; and a plurality of velocity magnitude measurements of the person corresponding to different times, each of said velocity magnitude measurements determined using the reflections associated with the person conveyed in the output of the active reflected wave detector.

A system and method for predicting mild cognitive impairment (MCI) related diagnosis and prognosis utilizing deep learning. More specifically, the system and method produce predictions of MCI conversions to Alzheimer's/dementia and prognosis related thereof. Using available medical imaging and non-imaging data a diagnosis and prognosis model is a deep learned model trained using transfer learning. An MCI-DAP server may then receive a request from a clinician to process predictions related to a target patient's diagnosis or prognosis. The target patient's medical data is retrieved and used to create a model for the target patient. Then details of the target patient's model and the diagnosis and prognosis model are compared, a prediction is generated, and the prediction is returned to the clinician. As new medical data becomes available it is fed into the respective model to improve accuracy and update predictions.

Low-cost devices and methods for measuring radar transmission and/or reflectance of coated articles, as well as methods for forming coatings on articles are provided. An exemplary low-cost radar transmission and reflection measurement device includes a radar transmitter that emits a radar signal, a radar target to which the radar signal is directed, and a radar receiver that receives the radar signal. Further, the exemplary low-cost device includes a sample holder located between the radar transmitter and the radar target and between the radar target and the radar receiver. The sample holder receives a sample including a coating. The low-cost device also includes a controller connected to the radar transmitter and radar receiver. The controller measures a radar signal loss due to the coating.