Abstract: Disclosed are techniques for performing object detection and tracking. In some implementations, a process for performing object detection and tracking is provided. The process can include steps for obtaining, at a tracking object, an image comprising a target object, obtaining, at the tracking object, a first set of messages associated with the target object, determining a bounding box for the target object in the image based on the first set of messages associated with the target object, and extracting a sub-image from the image. In some approaches, the process can further include steps for detecting, using an object detection model, a location of the target object within the sub-image. Systems and machine-readable media are also provided.

Abstract: Disclosed are techniques for performing object detection and tracking. In some implementations, a process for performing object detection and tracking is provided. The process can include steps for obtaining, at a tracking object, an image comprising a target object, obtaining, at the tracking object, a first set of messages associated with the target object, determining a bounding box for the target object in the image based on the first set of messages associated with the target object, and extracting a sub-image from the image. In some approaches, the process can further include steps for detecting, using an object detection model, a location of the target object within the sub-image. Systems and machine-readable media are also provided.

Abstract: An electronic device is described. The electronic device includes a memory and a processor in communication with the memory. The memory is configured to store precalibration data for a camera mounted on a vehicle, the precalibration data including a camera height determined relative to a road plane the vehicle is configured to contact during operation. The processor is configured to receive a plurality of images. The processor is also configured to classify one or more features in the plurality of images as road features based on the precalibration data.

Abstract: A method performed by an electronic device is described. The method includes determining a predicted velocity relative to Earth corresponding to a first epoch using a camera and an inertial measurement unit (IMU). The method also includes determining, using a Global Positioning System (GPS) receiver, a GPS velocity relative to Earth. The method further includes determining a difference vector between the predicted velocity and the GPS velocity. The method additionally includes refining a bias estimate and a scale factor estimate of IMU measurements proportional to the difference vector. The method also includes refining a misalignment estimate between the camera and the IMU based on the difference vector. The method further includes providing pose information based on the refined bias estimate, the refined scale factor, and the refined misalignment estimate.

Abstract: A method for visual inertial odometry (VIO)-aided global positioning is described. The method includes updating an extended Kalman filter (EKF) state including a current pose and a sliding window of multiple prior poses. The sliding window includes poses at a number of most recent global positioning system (GPS) time epochs. Updating the EKF includes updating an EKF covariance matrix for the prior poses and the current pose in the EKF state. The method also includes determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose. The method further includes determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix. The method additionally includes using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs.

Abstract: A method performed by an electronic device is described. The method includes determining a predicted velocity relative to Earth corresponding to a first epoch using a camera and an inertial measurement unit (IMU). The method also includes determining, using a Global Positioning System (GPS) receiver, a GPS velocity relative to Earth. The method further includes determining a difference vector between the predicted velocity and the GPS velocity. The method additionally includes refining a bias estimate and a scale factor estimate of IMU measurements proportional to the difference vector. The method also includes refining a misalignment estimate between the camera and the IMU based on the difference vector. The method further includes providing pose information based on the refined bias estimate, the refined scale factor, and the refined misalignment estimate.

Abstract: A method for visual inertial odometry (VIO)-aided global positioning is described. The method includes updating an extended Kalman filter (EKF) state including a current pose and a sliding window of multiple prior poses. The sliding window includes poses at a number of most recent global positioning system (GPS) time epochs. Updating the EKF includes updating an EKF covariance matrix for the prior poses and the current pose in the EKF state. The method also includes determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose. The method further includes determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix. The method additionally includes using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs.

Abstract: An electronic device is described. The electronic device includes a memory and a processor in communication with the memory. The memory is configured to store precalibration data for a camera mounted on a vehicle, the precalibration data including a camera height determined relative to a road plane the vehicle is configured to contact during operation. The processor is configured to receive a plurality of images. The processor is also configured to classify one or more features in the plurality of images as road features based on the precalibration data.

Abstract: A multimedia distribution system is disclosed. The distribution system includes a transmitter unit that distributes content from a content provider to one or more wireless subscriber units. The transmitter unit includes a decoder configured to determine whether a plurality of incoming packets include one or more erasures, a transmitter configured to transmit the packets to a receiving unit, and an error detection code generator configured to generate an error detection code for each of the packets transmitted to the receiver unit, the error detection code being modified for each of the erased packets so that the receiver unit will be able to identify the erased packets.

Abstract: The claimed subject matter relates to analyzing performance of a transmitter. This can be accomplished, for instance, through partitioning a super frame into a plurality of segments, and thereafter estimating and correcting phase with respect to at least one of the plurality of segments. Thereafter, additive noise can be determined with respect to the at least one segment. For instance, the super frame can include multiple OFDM symbols, and the transmitter can be a FLO transmitter.

Abstract: Systems and methodologies are described that facilitate monitoring transmitter performance in a wireless communication environment. A signal analyzer can be used to sample the output of a transmitter and the sampled signal can be propagated to a processor. The processor can generate frequency domain channel estimates for the subcarriers. If the transmitted modulation symbols are unknown, the processor can determine the modulation symbols and use the determined modulation symbols to calculate the channel estimates. The channel estimates can be averaged and used to generate various metrics to evaluate the transmitter performance.

Abstract: Systems and methods are provided for processing forward link only (FLO) signals. A device receives a FLO signal, processes a TDM pilot comprising a TDM Pilot 1, a TDM Pilot 2, a WIC, a LIC, a Transition Pilot Channel, and a Positioning Pilot, from the FLO signal, processes an overhead information symbol (OIS) comprising a wide-area OIS and a local-area OIS, from the FLO signal, processes an FDM pilot comprising a wide-area FDM pilot and a local-area FDM pilot, from the FLO signal; and processes data comprising wide-area data and local-area data, from the FLO signal.

Abstract: Systems and methods are provided for processing forward link only (FLO) messages.

Abstract: A system and method for time diversity uses interleaving. To simplify the operation at both transmitters and receivers, a formula can be used to determine the mapping from slot to interlace at a given OFDM symbol time.

Abstract: The disclosure is directed to a mobile communication device that determines when a performance disruption indicates a loss of synchronization with a broadcast signal and, in response, initiates reacquisition of the signal. Reacquisition techniques may include identifying and decoding only select portions of header information in the broadcast signal. Reacquisition may also be initiated in response to one or more deterministic triggers and during a test mode of operation.

Abstract: The disclosure is directed to a mobile communication device that may receive wireless broadcast signals from a number of different base stations or transmitters. As the location of the device moves relative to the transmitters, one transmitter will likely be identified as the transmitter broadcast the strongest, or highest quality, signal. When that determination is made, the user of the mobile device is presented the opportunity to switch to receiving that transmitters signal. Based on the user's reply, the device may remain with the current transmitter, even though it does not have the strongest signal, or the device may be configured to acquire and start receiving the new transmitter's signal. The measuring of the quality of a transmitter's signal may be based on a composite score that combines a number of individual measurements made over a predetermined period of time.

Abstract: A media access control (MAC) layer controller can manage base layer data and enhancement layer data in a layered modulation system. The MAC layer controller can process both base layer data and enhancement layer data and map the encoded symbols to a layered modulation constellation when both are present. If data for one of the layers terminates, then the MAC layer controller can generate and supply predetermined stuffing data to the layer lacking additional data. The MAC layer controller can send a control signal to the physical layer hardware to cause the hardware to map the layered signals having the stuffing data to a modified signal constellation. The MAC controller can also generate an overhead message that indicates the occurrence of the stuffing data. The receiver can receive the overhead message and can use the information to configure the receiver for the layered modulation constellation or the modified signal constellation.

Abstract: A system and method for modulation diversity uses interleaving. Code bits are placed into groups and are then shuffled within each group.

Abstract: A system and method for frequency diversity uses interleaving. Subcarriers of an interlace are interleaved in a bit reversal fashion and the interlaces are interleaved in the bit reversal fashion.