Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving raw GPS measurements from each GPS satellite in view of the UAV, the raw GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A data receiver includes a vibration sensor to sample data from vibrations in an incoming signal at a predetermined sampling rate, and a microcontroller, coupled to the vibration sensor, to control the sampling rate through an inter-integrated circuit (I2C) protocol or the like. A memory card, coupled to the microcontroller, stores the data with a serial peripheral interface (SPI) protocol or the like.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving raw GPS measurements from each GPS satellite in view of the UAV, the raw GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A data receiver includes a vibration sensor to sample data from vibrations in an incoming signal at a predetermined sampling rate, and a microcontroller, coupled to the vibration sensor, to control the sampling rate through an inter-integrated circuit (I2C) protocol or the like. A memory card, coupled to the microcontroller, stores the data with a serial peripheral interface (SPI) protocol or the like.

Abstract: A data transmitter includes a vibration motor and a switch to regulate voltage from a direct-current (DC) power supply to the vibration motor. A microcontroller generates a pulse width modulation signal with which to drive the switch and regulate the voltage to the vibration motor in a sinusoidal manner, to generate data as symbols from vibrations that form a series of bits from the vibration motor. The microcontroller may also cancel and jam a sound of vibration (SoV) created by the vibration motor. A data receiver includes a vibration sensor to sample data from vibrations in an incoming signal at a predetermined sampling rate, and a microcontroller, coupled to the vibration sensor, to control the sampling rate through an inter-integrated circuit (I2C) protocol or the like. A memory card, coupled to the microcontroller, stores the data with a serial peripheral interface (SPI) protocol or the like.

Abstract: A data transmitter includes a vibration motor and a switch to regulate voltage from a direct-current (DC) power supply to the vibration motor. A microcontroller generates a pulse width modulation signal with which to drive the switch and regulate the voltage to the vibration motor in a sinusoidal manner, to generate data as symbols from vibrations that form a series of bits from the vibration motor. The microcontroller may also cancel and jam a sound of vibration (SoV) created by the vibration motor. A data receiver includes a vibration sensor to sample data from vibrations in an incoming signal at a predetermined sampling rate, and a microcontroller, coupled to the vibration sensor, to control the sampling rate through an inter-integrated circuit (I2C) protocol or the like. A memory card, coupled to the microcontroller, stores the data with a serial peripheral interface (SPI) protocol or the like.