Abstract: The present disclosure relates to systems and methods that facilitate active sensor systems. An example method includes receiving information indicative of an operating context of a vehicle, wherein at least one Light Detection and Ranging (LIDAR) sensor or at least one radar sensor are coupled to the vehicle. The method also includes selecting, from a plurality of sensor power configurations, a desired sensor power configuration based on the operating context of the vehicle. The method further includes causing at least one of: the at least one LIDAR sensor to emit light pulses according to the desired sensor power configuration or the at least one radar sensor to emit radar energy according to the desired sensor power configuration.

Abstract: In an example method, a vehicle configured to operate in an autonomous mode could have a radar system used to aid in vehicle guidance. The method could include transmitting at least two signal pulses. The method further includes, for each transmitted signal pulse, receiving a reflection signal associated with reflection of the respective transmitted signal pulse. Each reflection signal may be received when the apparatus is in a different respective location. Additionally, the method includes processing the received reflection signals to determine target information relating to one or more targets in an environment of the vehicle. Also, the method includes correlating the target information with at least one object of a predetermined map of the environment of the vehicle to provide correlated target information. Yet further, the method includes storing the correlated target information for the at least one object in an electronic database.

Abstract: Example embodiments described herein involve determining three dimensional data representative of an environment for an autonomous vehicle using radar. An example embodiment involves receiving radar reflection signals at a radar unit coupled to a vehicle and determining an azimuth angle and a distance for surfaces in the environment causing the radar reflection signals. The embodiment further involves determining an elevation angle for the surfaces causing the radar reflection signals based on phase information of the radar reflection signals and controlling the vehicle based at least in part on the azimuth angle, the distance, and the elevation angle for the surfaces causing the plurality of radar reflection signals. In some instances, the radar unit is configured to receive radar reflection signals using a staggered linear array with one or multiple radiating elements offset in the array.

Abstract: A target estimator that properly conditions measurement variates in the case of a series of sensor measurements collected against a target, a system model that captures visible and hidden stochastic information including but not limited to target state, target identity, and sensor measurements and that marginalizes measurement failure and a dynamic mixed quadrature expression facilitating real-time implementation of the estimator are presented.

Abstract: The present application describes a method including transmitting at least two radar signals by a radar unit of a vehicle, where a first signal is transmitted from a first location and a second signal is transmitted from a second location. The method also includes receiving a respective reflection signal associated with each of the transmitted signals. Additionally, the method includes determining, by a processor, at least one stationary object that caused a reflection. Further, the method includes based on the determined stationary object, determining, by the processor, an offset for the radar unit. The method yet further includes operating the radar unit based on the determined offset. Furthermore, the method includes controlling an autonomous vehicle based on the radar unit being operated with the determined offset.

Abstract: Examples relating to vehicle velocity calculation using radar technology are described. An example method performed by a computing system may involve, while a vehicle is moving on a road, receiving, from two or more radar sensors mounted at different locations on the vehicle, radar data representative of an environment of the vehicle. The method may involve, based on the data, detecting at least one scatterer in the environment. The method may involve making a determination of a likelihood that the at least one scatterer is stationary with respect to the vehicle. The method may involve, based on the determination being that the likelihood is at least equal to a predefined confidence threshold, calculating a velocity of the vehicle based on the data from the sensors. The calculated velocity may include an angular and linear velocity. Further, the method may involve controlling the vehicle based on the calculated velocity.

Abstract: Examples relating to vehicle motion detection using radar technology are described. An example method may involve a computing system receiving, from a radar sensor mounted on an autonomous vehicle, radar data representative of an environment of the vehicle. The method may involve the computing system, based on the radar data, detecting at least one scatterer present in the environment. The method may involve the computing system making a determination of a likelihood that the at least one scatterer is stationary with respect to the vehicle. The method may involve the computing system, based on the determination being that the likelihood is at least equal to a predefined confidence threshold, determining an indication that the vehicle is stationary. And the method may involve the computing system controlling movement of the vehicle based on the determined indication.

Abstract: The present application describes a method including transmitting at least two radar signals by a radar unit of a vehicle, where a first signal is transmitted from a first location and a second signal is transmitted from a second location. The method also includes receiving a respective reflection signal associated with each of the transmitted signals. Additionally, the method includes determining, by a processor, at least one stationary object that caused a reflection. Further, the method includes based on the determined stationary object, determining, by the processor, an offset for the radar unit. The method yet further includes operating the radar unit based on the determined offset. Furthermore, the method includes controlling an autonomous vehicle based on the radar unit being operated with the determined offset.

Abstract: A radar system includes a split-block assembly unit comprising a first portion and second portion, where the first portion and the second portion form a seam. The radar system further includes a plurality of ports located on a bottom side of the second portion opposite the seam. Additionally, the radar system includes a plurality of radiating elements located on a top side of the first portion opposite the seam. The plurality of radiating elements is arranged in a plurality of arrays. The plurality of arrays includes a set of multiple-input multiple-output (MIMO) transmission arrays, a set of synthetic aperture radar (SAR) transmission arrays, and at least one reception array. Further, the radar system includes a set of waveguides configured to couple each array to a port.

Abstract: Disclosed herein are embodiments that relate to crossing target dynamics for a radar system. In one aspect, the present application describes a method for use with a radar system. The method includes transmitting at least one signal pulse. The method also includes receiving a signal associated with reflection of the at least one transmitted signal pulse. Further, the method may also include processing the received signal to determine a cross-range rate. The processing may include determining a Doppler bandwidth based on the received signal. Additionally, the processing may include determining a range based on the received signal. Yet further, the processing may include determining a cross-range extent based on the received signal. Additionally, the processing may include determining the cross-range rate for the target object based on the determined Doppler bandwidth, range, and cross-range extent. An autonomous vehicle may be controlled based on the determined cross-range rate.

Abstract: Systems and methods are described that relate to generating an object grid for a vehicular radar system. The method includes transmitting a radar signal over a 360-degree azimuth. The method also includes receiving one or more reflection signals respectively associated with reflection of the transmitted radar signal by one or more objects. The method further includes determining, for each object, a respective measured angle, a respective measured distance, and a respective measured velocity. Additionally, the method includes determining a first object grid based on the one or more objects. The first object grid comprises a plurality angles that together cover the 360-degree azimuth and, for each angle that corresponds to a measured angle of a given object, the first grid associates the angle with the measured distance and measured velocity of the given object. Yet further, the method includes controlling an autonomous vehicle based on the first object grid.

Abstract: Disclosed herein are embodiments that relate to phase coded linear frequency modulation for a radar system. Embodiments include transmitting at least one signal pulse with a binary phase shift keying (BPSK) encoding. The method also includes receiving a signal associated with reflection of the at least one transmitted signal pulse. The received signal may include at least two channels. Further, the method may also include processing the received signal to determine target information. The processing may include performing a despread operation that provides a phase offset based on a filtering range. Additionally, the processing may include performing a reconstruction operation that comprises creating a virtual spatial channel based on combining the two received channels. Yet further, the processing may include determining the target information based on the virtual spatial channel. An autonomous vehicle may be controlled based on the determined target information.

Abstract: The present application describes a method including transmitting at least two radar signals by a radar unit of a vehicle, where a first signal is transmitted from a first location and a second signal is transmitted from a second location. The method also includes receiving a respective reflection signal associated with each of the transmitted signals. Additionally, the method includes determining, by a processor, at least one stationary object that caused a reflection. Further, the method includes based on the determined stationary object, determining, by the processor, an offset for the radar unit. The method yet further includes operating the radar unit based on the determined offset. Furthermore, the method includes controlling an autonomous vehicle based on the radar unit being operated with the determined offset.

Abstract: A target estimator that properly conditions measurement variates in the case of a series of sensor measurements collected against a target, a system model that captures visible and hidden stochastic information including but not limited to target state, target identity, and sensor measurements and that marginalizes measurement failure and a dynamic mixed quadrature expression facilitating real-time implementation of the estimator are presented.

Abstract: A method for target identification includes receiving, at one or more processors, a number of measurements of a target, each measurement from the number of measurements being observed at a predetermined time (zk), a number of target types (T), each one of the number of measurements, each one the number of target type and each one of one or more hidden states, each hidden state (xk) being characterized at the predetermined time, being correlated to one another, providing, using the one or more processors, a first conditional probability distribution, a conditional probability of a target type given a number of measurements, defined inductively, and obtaining an estimate of the target type from the first conditional probability. Systems that implement the method are also disclosed.

Abstract: The present invention relates to bodysuits for use as personal protective equipment comprising a torso portion comprising a front side; a back side including a sealable port through which a wearer can enter and exit the bodysuit when donning or doffing the bodysuit, respectively; a waist region; a neck opening; a pair of upper limb openings; and a pair of lower limb openings; two arm portions each extending from one of the upper limb opening; and two leg portions each extending from one of the lower limb opening and methods for the removal of such body suits.

Abstract: A method for target identification includes receiving, at one or more processors, a number of measurements of a target, each measurement from the number of measurements being observed at a predetermined time (zk), a number of target types (T), each one of the number of measurements, each one the number of target type and each one of one or more hidden states, each hidden state (xk) being characterized at the predetermined time, being correlated to one another, providing, using the one or more processors, a first conditional probability distribution, a conditional probability of a target type given a number of measurements, defined inductively, and obtaining an estimate of the target type from the first conditional probability. Systems that implement the method are also disclosed.

Abstract: A system and method for discrimination and identification of a target including: receiving a radar return signal including target information and clutter information; determining a two-fold forward or forward-backward data matrix from the received signal, using a multi-dimensional folding (MDF) process; computing singular values of the two-fold forward or forward-backward data matrix; using the computed singular values to determine a noise power level of the radar return signal; determining the number of scatterers in the radar return signal according to a predetermined threshold value above the noise power; estimating complex Doppler and azimuth frequencies of each scatterer from the determined number of scatterers using the MDF process; determining dispersive scatterers and non-dispersive scatterers using the estimated Doppler and azimuth complex frequencies of each scatterer; and distinguishing the target information from the clutter information, according to the determined dispersive scatterers and non-di

Abstract: A system and method for discrimination and identification of a target including: receiving a radar return signal including target information and clutter information; determining a two-fold forward or forward-backward data matrix from the received signal, using a multi-dimensional folding (MDF) process; computing singular values of the two-fold forward or forward-backward data matrix; using the computed singular values to determine a noise power level of the radar return signal; determining the number of scatterers in the radar return signal according to a predetermined threshold value above the noise power; estimating complex Doppler and azimuth frequencies of each scatterer from the determined number of scatterers using the MDF process; determining dispersive scatterers and non-dispersive scatterers using the estimated Doppler and azimuth complex frequencies of each scatterer; and distinguishing the target information from the clutter information, according to the determined dispersive scatterers and non-di

Abstract: Methods, systems, and apparatuses for video broadcast production are disclosed. A method for video broadcast production may be implemented by a computing device. A video stream is captured. An external date is inserted at a point of interest in the video stream. The external data facilitates display of content from an external source at the point of interest in the video stream. An encoded video stream including the external data inserted at the point of interest in the video stream is generated.