Mechanisms for selecting beam direction for a radio communications device are provided. A method is performed by the radio communications device. The method includes obtaining radio channel estimates of a radio channel on which radio waves have been transmitted between the radio communications device and another radio communications device at an angle of arrival and departure. The method includes determining a Doppler shift from the radio channel estimates. The method includes estimating at least one of the angle of arrival and departure of the radio waves based on the Doppler shift. The method includes selecting a beam direction for a signal to be transmitted between the radio communications device and this another radio communications device over the radio channel according to the estimated angle of arrival or departure.

Disclosed examples include a radar system that operates in a first mode and a second mode. In the first mode, the system detects the presence of an object within a threshold range. In response to detection of the presence of the object, the system transitions to the second mode, and the system generates range data, velocity data, and angle data of the object in the second mode. When the object is no longer detected within the threshold range, the system transitions back to the first mode.

Disclosed examples include a radar system that operates in a first mode and a second mode. In the first mode, the system detects the presence of an object within a threshold range. In response to detection of the presence of the object, the system transitions to the second mode, and the system generates range data, velocity data, and angle data of the object in the second mode. When the object is no longer detected within the threshold range, the system transitions back to the first mode.

In various examples, a radar system includes a logic circuit with an array for processing radar reflection signals. In a specific example, a method includes generating output data indicative of the reflection signals' amplitudes, and discerning angle-of-arrival information for the output data for the output data by correlating the output data with an iteratively-refined estimate of a sparse spectrum support vector (“support vector”). The approach may include: assessing at least one most probable spectrum support vector from among a plurality of most probable spectrum support vectors modeled as random values in a matrix drawn from a long-tail distribution that is controlled as a function of a scaling parameter; and update a set of parameters including a covariance estimate, the scaling parameter, and a noise variance parameter which is being associated with a measurement error for said at least one most probable spectrum support vector from a previous iteration.

The reconfigurable radio direction finder system and method uses a reconfigurable antenna to electronically cycle through a plurality of different antenna configurations to determine a signal direction. Specifically, the reconfigurable antenna is cycled through N different antenna configurations, where N is an integer greater than one, where each antenna configuration has a pointing direction associated therewith defined by an elevation angle θ.sub.n of an n-th antenna configuration, where n is an integer between 1 and N, and an azimuthal angle φ.sub.n of the n-th antenna configuration. A received signal strength of the radio signal is measured for each of the antenna configurations as a power output of the n-th antenna configuration, P.sub.n. A spherical weighted directional mean vector (X.sub.DF, Y.sub.DF, Z.sub.DF) is then estimated for the radio signal as $X_{\mathrm{DF}}=\frac{1}{N}\underset{n=1}{\overset{N}{.Math.}}{P}_n\cos \left({\varphi }_n\right)\sin \left({\theta }_n\right),Y_{\mathrm{DF}}=\frac{1}{N}\underset{}{\overset{}{.Math.}}$

The reconfigurable radio direction finder system and method uses a reconfigurable antenna to electronically cycle through a plurality of different antenna configurations to determine a signal direction. Specifically, the reconfigurable antenna is cycled through N different antenna configurations, where N is an integer greater than one, where each antenna configuration has a pointing direction associated therewith defined by an elevation angle θ.sub.n of an n-th antenna configuration, where n is an integer between 1 and N, and an azimuthal angle φ.sub.n of the n-th antenna configuration. A received signal strength of the radio signal is measured for each of the antenna configurations as a power output of the n-th antenna configuration, P.sub.n. A spherical weighted directional mean vector (X.sub.DF, Y.sub.DF, Z.sub.DF) is then estimated for the radio signal as $X_{\mathrm{DF}}=\frac{1}{N}\underset{n=1}{\overset{N}{.Math.}}{P}_n\cos \left({\varphi }_n\right)\sin \left({\theta }_n\right),Y_{\mathrm{DF}}=\frac{1}{N}\underset{}{\overset{}{.Math.}}$

A method of identifying and classifying social complex behaviors among a group of model organisms, comprising implanting at least one RFID transponder in each model organism in said group of model organisms; enclosing said group of model organisms in a monitored space divided into RFID monitored segments; RFID tracking a position of each model organism by reading said at least one RFID transponder in each model organism over a period of time; capturing a sequence of images of each model organism over said period of time; and calculating at least one spatiotemporal model of each model organism based on time synchronization of said RFID tracked position of said model organism with said sequence of images.

A method of identifying and classifying social complex behaviors among a group of model organisms, comprising implanting at least one RFID transponder in each model organism in said group of model organisms; enclosing said group of model organisms in a monitored space divided into RFID monitored segments; RFID tracking a position of each model organism by reading said at least one RFID transponder in each model organism over a period of time; capturing a sequence of images of each model organism over said period of time; and calculating at least one spatiotemporal model of each model organism based on time synchronization of said RFID tracked position of said model organism with said sequence of images.

In one embodiment, a process obtains a first compensated directional reading from a first directional sensor of a directionally sensitive system, and obtains a second compensated directional reading from a second directional sensor of the directionally sensitive system. The process may then determine, a difference between the first compensated directional reading and the second compensated directional reading, and declares, in response to the difference being greater than an acceptable threshold, an inaccurate directional reading. As such, the process may then prevent performance of a directionally sensitive action by the directionally sensitive system in response to an inaccurate directional reading.

In one embodiment, a process obtains a first compensated directional reading from a first directional sensor of a directionally sensitive system, and obtains a second compensated directional reading from a second directional sensor of the directionally sensitive system. The process may then determine, a difference between the first compensated directional reading and the second compensated directional reading, and declares, in response to the difference being greater than an acceptable threshold, an inaccurate directional reading. As such, the process may then prevent performance of a directionally sensitive action by the directionally sensitive system in response to an inaccurate directional reading.