Steering Mirror assisted laser fine pointing

The current Star Tracker software package is comprised of a Lumenera LW230 monochrome machine-vision camera and a FUJINON HF35SA-1 35mm lens. The star tracker cameras are all connected to and powered by the PC/104 stack via USB 2.0 ports. The software code is written in C++ and is can easily be adapted to other camera and lensing platforms by setting new variables in the software for new focal conditions. In order to identify stars in images, the software contains a star database derived from the 118,218-star Hipparcos catalog [1]. The database contains a list of every star pair within the camera field of view and the angular distance between those pairs. It also contains the inertial position information for each individual star directly from the Hipparcos catalog. In order to keep the star database size small, only stars of magnitude 6.5 or brighter were included. The star tracking process begins when image data is retrieved by the software from the data buffers in the camera. The image is translated into a binary image via a threshold brightness value so that on (bright) pixels are represented by 1s and off (dark) pixels are represented by 0s. The binary image is then searched for blobs, which are just connected groups of on pixels. These blobs represent unidentified stars or other objects such as planets, deep sky objects, other satellites, or noise. The centroids of the blob locations are computed, and a unique pattern recognition algorithm is applied to identify which, if any, stars are represented. During this process, false stars are effectively removed and only repeatedly and uniquely identifiable stars are stored. After stars are identified, another algorithm is applied on their position information to determine the attitude of the satellite. The attitude is computed as a set of Euler angles: right ascension (RA), declination (Dec), and roll. The first two Euler angles are computed by using a linear system that is derived from vector algebra and the information of two identified stars in the image. The roll angle is computed using an iterative method that relies on the information of a single star and the first two Euler angles. [1] ESA, 1997, The Hipparcos and Tycho Catalogues, ESA SP-1200

A new method is described for optical data transmissions from satellites using laser arrays for fine pointing of laser beams that use body pointing. It combines a small lens system and a VCSEL/Photodetector Array in a novel way to provide a fine pointing capability for laser beams that are pointed by body pointing of a CubeSat. As Fig. 1 shows, an incoming laser beam (green or blue, with rightward arrows), transmitted from a ground terminal, enters the lens system, which directs it to an element of the pixel array (gray rectangle). Each element, or pixel, consists of a VCSEL component/photodetector pair. The photodetector detects the incoming beam, and the VCSEL component returns a modulated beam to the lens system (green or blue, with leftward arrows), which sends it to the ground terminal. As the incoming beam changes direction, e.g., from the blue to the green incoming direction, this change is detected by the adjacent photodetector, and the laser paired with that photodetector is turned on to keep the outgoing laser beam on target. The laser beams overlap so that the returning beam continues to point at the ground terminal. The VCSEL component may consist of a single VCSEL or a cluster of VCSELs. Figure 2 shows the propagation of two overlapping laser beams. The system can very accurately point finely focused diffraction-limited laser beams. Also, simultaneous optical multiple access (OMA) is possible from different transceivers within the area covered by the laser array. For this electro-optical system, reaction times to pointing changes and vibrations are on the nanosecond time scale, much faster than mechanical fine pointing systems.

This invention provides a new method for optical data transmissions from satellites using laser arrays for laser beam pointing. The system is simple, static, compact, and provides accurate pointing, acquisition, and tracking (PAT). It combines a lens system and a vertical-cavity surface-emitting laser VCSEL)/Photodetector Array, both mature technologies, in a novel way for PAT. It can improve the PAT system's size, weight, and power (SWaP) in comparison to current systems. Preliminary analysis indicates that this system is applicable to transmissions between satellites in low-Earth orbit (LEO) and ground terminals. Computer simulations using this design have been made for the application of this innovation to a CubeSat in LEO. The computer simulations included modeling the laser source and diffraction effects due to wave optics. The pointing used a diffraction limited lens system and a VCSEL array. These capabilities make it possible to model laser beam propagation over long space communication distances. Laser beam pointing is very challenging for LEO, including science missions. Current architectures use dynamical systems, (i.e., moving parts, e.g., fast-steering mirrors (FSM), and/or gimbals) to turn the laser to point to the ground terminal, and some use vibration isolation platforms as well. This static system has the potential to replace the current dynamic systems and vibration isolation platforms, dependent on studies for the particular application. For these electro-optical systems, reaction times to pointing changes and vibrations are on the nanosecond time scale, much faster than those for mechanical systems. For LEO terminals, slew rates are not a concern with this new system.

Flashpose is the combination of software written in C and FPGA firmware written in VHDL. It is designed to run under the Linux OS environment in an embedded system or within a custom development application on a Linux workstation. The algorithm is based on the classic Iterative Closest Point (ICP) algorithm originally proposed by Besl and McKay. Basically, the algorithm takes in a range image from a three-dimensional imager, filters and thresholds the image, and converts it to a point cloud in the Cartesian coordinate system. It then minimizes the distances between the point cloud and a model of the target at the origin of the Cartesian frame by manipulating point cloud rotation and translation. This procedure is repeated a number of times for a single image until a predefined mean square error metric is met; at this point the process repeats for a new image. The rotation and translation operations performed on the point cloud represent an estimate of relative attitude and position, otherwise known as pose. In addition to 6 degree of freedom (DOF) pose estimation, Flashpose also provides a range and bearing estimate relative to the sensor reference frame. This estimate is based on a simple algorithm that generates a configurable histogram of range information, and analyzes characteristics of the histogram to produce the range and bearing estimate. This can be generated quickly and provides valuable information for seeding the Flashpose ICP algorithm as well as external optical pose algorithms and relative attitude Kalman filters.

State of the art space-based LIDARs typically require a telescope with sufficient area to increase the return signal on the detector to levels above the noise floor of the detectors. Two major drivers of the signal-to-noise ratio (SNR) on the detectors are the laser output energy and the round trip distance traveled by the laser signal. The SNR on the detectors can be increased by increasing the telescope reflector area or by decreasing the system noise. If these techniques are not an option, this method can be used to separate stray light from polarized laser light in the LIDAR system and improve the SNR. The method includes generating a beam of azimuthally polarized or OAM light utilizing an optical transmitter comprising a laser light source. The method includes providing an optical receiver including optical sensors at a focal plane with a photon sieve that produces a ring pattern on the focal plane corresponding to a laser return signal. The ring pattern comprises azimuthally polarized or OAM light that is transmitted by the transmitter and reflected towards the receiver. The photon sieve is utilized to cause stray light that is not polarized to cluster centrally, and away from the ring pattern created by the LIDAR signal. This technology could also be used with space based and terrestrial LIDAR for encrypted line of sight communications. The unique revolution frequencies of the LIDAR make any attempt to intercept the communication pointless for those who don&#39t know the specific mode of the source. The lidar system also has use cases for short range navigation for Urban Air Mobility (UAM) vehicles providing input as to whether there is significant enough clear air turbulence on a given path as to be dangerous to an aerial vehicle.