The present disclosure is of an atmospheric characterization system that has a central processing board that has a first and a second communication interface. Further, the atmospheric characterization system further has a first precision temperature sensor that is communicatively coupled to the central processing board via the first communication interface and positioned a distance from a first side of the processing board, wherein the precision temperature measures a first temperature and transfers data indicative of the first temperature to the central processing board. In addition, the atmospheric characterization system has a second precision temperature sensor that is communicatively coupled to the central processing board via the second communication interface and positioned the distance from a second opposing side of the processing board such that the first precision temperature sensor and the second precision temperature sensor are equidistance from the processing board and a distance between the first precision sensor and the second precision sensor is a predetermined distance, r, and the second precision temperature sensor measures a second temperature and transfers data indicative of the second temperature to the central processing board simultaneously with the transferring of the first temperature. Additionally, the atmospheric characterization system has a processor that receives the first temperature and the second temperature and calculates a value indicative of atmospheric turbulence based upon the first temperature and the second temperature, wherein the value indicative of the atmospheric turbulence is used for designing, modifying, calibrating, or correcting an optical system.

The present disclosure is of an atmospheric characterization system that has a central processing board that has a first and a second communication interface. Further, the atmospheric characterization system further has a first precision temperature sensor that is communicatively coupled to the central processing board via the first communication interface and positioned a distance from a first side of the processing board, wherein the precision temperature measures a first temperature and transfers data indicative of the first temperature to the central processing board. In addition, the atmospheric characterization system has a second precision temperature sensor that is communicatively coupled to the central processing board via the second communication interface and positioned the distance from a second opposing side of the processing board such that the first precision temperature sensor and the second precision temperature sensor are equidistance from the processing board and a distance between the first precision sensor and the second precision sensor is a predetermined distance, r, and the second precision temperature sensor measures a second temperature and transfers data indicative of the second temperature to the central processing board simultaneously with the transferring of the first temperature. Additionally, the atmospheric characterization system has a processor that receives the first temperature and the second temperature and calculates a value indicative of atmospheric turbulence based upon the first temperature and the second temperature, wherein the value indicative of the atmospheric turbulence is used for designing, modifying, calibrating, or correcting an optical system.

A system and a method for tracking a target and for compensating for atmospheric turbulence is described. In an embodiment, the system includes at least two light sources each emitting a light beam to the target; at least two collimators that collimate the light beam of the associated light source; and a reference device to reflect a portion of the light beam exiting from all the collimators. The system also includes: at least two targeting modules to lead the light beam from the light source to reach a predetermined zone of the target; at least two detection modules to receive and detect the portion of the beam reflected by the reference device; a module for determining angle of deviation; a module for determining phase deviation; and an adjustment module for adjusting each of the light sources in order to compensate for atmospheric turbulence.

A system and a method for tracking a target and for compensating for atmospheric turbulence is described. In an embodiment, the system includes at least two light sources each emitting a light beam to the target; at least two collimators that collimate the light beam of the associated light source; and a reference device to reflect a portion of the light beam exiting from all the collimators. The system also includes: at least two targeting modules to lead the light beam from the light source to reach a predetermined zone of the target; at least two detection modules to receive and detect the portion of the beam reflected by the reference device; a module for determining angle of deviation; a module for determining phase deviation; and an adjustment module for adjusting each of the light sources in order to compensate for atmospheric turbulence.

A multi-fiber optical sensor system includes a light source configured to generate light energy, a transmitter fiber configured to receive the light energy from the light source and to project light energy out of a projecting end of the transmitter fiber over a transmitter fiber field of view, and a plurality of receiver fibers. Each of the plurality of receiver fibers has a receiving end aligned proximate and substantially parallel to the projecting end of the transmitter fiber and is configured to receive a received portion of the projected light energy reflected from a target within a receiver field of view. The multi-fiber optical sensor system also includes a lenslet array configured to shape the transmitter fiber field of view and give the transmitter field of view a finite cross-sectional area. The lenslet array has a plurality of lens corresponding to the transmitter fiber and each of the plurality of receiver fibers and is further configured to shape the receiver fiber field of view, tilt the center of the field of view with respect to the axis of the projected light energy for each of the plurality of receiver fibers and give the receiver fiber field of view for each of the plurality of receiver fibers a finite cross-sectional area. The multi-fiber optical sensor system also includes a detector configured to detect the portion of the projected light energy received by each of the plurality of receiver fibers. The receiver fiber field of view for each of the plurality of receiver fibers crosses the transmitter fiber field of view between a first crossing point at a distance R.sub.min from a lens axis and a last crossing point at a distance R.sub.max from the lens axis. There is a center crossing point R.sub.mid at a point where a centerline of the receiver fiber field of view for each of the plurality of receiver fibers crosses a centerline of the transmitter fiber field of view. The range between R.sub.min and R.sub.max for each of the plurality of receiver fibers defines a detection zone such that each of the plurality of receiver fibers has a unique detection zone. Targets include a hard target and/or constituents of a cloud atmosphere.

A multi-fiber optical sensor system includes a light source configured to generate light energy, a transmitter fiber configured to receive the light energy from the light source and to project light energy out of a projecting end of the transmitter fiber over a transmitter fiber field of view, and a plurality of receiver fibers. Each of the plurality of receiver fibers has a receiving end aligned proximate and substantially parallel to the projecting end of the transmitter fiber and is configured to receive a received portion of the projected light energy reflected from a target within a receiver field of view. The multi-fiber optical sensor system also includes a lenslet array configured to shape the transmitter fiber field of view and give the transmitter field of view a finite cross-sectional area. The lenslet array has a plurality of lens corresponding to the transmitter fiber and each of the plurality of receiver fibers and is further configured to shape the receiver fiber field of view, tilt the center of the field of view with respect to the axis of the projected light energy for each of the plurality of receiver fibers and give the receiver fiber field of view for each of the plurality of receiver fibers a finite cross-sectional area. The multi-fiber optical sensor system also includes a detector configured to detect the portion of the projected light energy received by each of the plurality of receiver fibers. The receiver fiber field of view for each of the plurality of receiver fibers crosses the transmitter fiber field of view between a first crossing point at a distance R.sub.min from a lens axis and a last crossing point at a distance R.sub.max from the lens axis. There is a center crossing point R.sub.mid at a point where a centerline of the receiver fiber field of view for each of the plurality of receiver fibers crosses a centerline of the transmitter fiber field of view. The range between R.sub.min and R.sub.max for each of the plurality of receiver fibers defines a detection zone such that each of the plurality of receiver fibers has a unique detection zone. Targets include a hard target and/or constituents of a cloud atmosphere.

An apparatus, method, and computer program product are provided for the improved and automatic prediction of an elevation of an architectural feature of a structure at a particular geographic location. Some example implementations employ predictive, machine-learning modeling to facilitate the use of LiDAR-derived ground-elevation data, additional location context data, and elevation data from comparator locations to extrapolate and otherwise predict the elevation or other position of a given architectural feature of structure.

An apparatus, method, and computer program product are provided for the improved and automatic prediction of an elevation of an architectural feature of a structure at a particular geographic location. Some example implementations employ predictive, machine-learning modeling to facilitate the use of LiDAR-derived ground-elevation data, additional location context data, and elevation data from comparator locations to extrapolate and otherwise predict the elevation or other position of a given architectural feature of structure.

An apparatus, method, and computer program product are provided for the improved and automatic prediction of an elevation of an architectural feature of a structure at a particular geographic location. Some example implementations employ predictive, machine-learning modeling to facilitate the use of LiDAR-derived ground-elevation data, additional location context data, and elevation data from comparator locations to extrapolate and otherwise predict the elevation or other position of a given architectural feature of structure.

An apparatus, method, and computer program product are provided for the improved and automatic prediction of an elevation of an architectural feature of a structure at a particular geographic location. Some example implementations employ predictive, machine-learning modeling to facilitate the use of LiDAR-derived ground-elevation data, additional location context data, and elevation data from comparator locations to extrapolate and otherwise predict the elevation or other position of a given architectural feature of structure.