Multi-Edge Slant Target for Non-Localized MTF Measurement

NASA Goddard Space Flight Center has developed a low cost, modular, and flexible space flight laser range finder consisting of optics, electronics, and interfaces for satellite servicing missions (i.e. Restore-L) using customized optics. Built upon previous NASA technologies, the system also consists of a high dynamic range receiver and adjustable laser for a wide range of measurements (i.e. multiples of km to sub-meter).

This NASA-developed eVTOL UAS is a purpose-built, electric, reusable aircraft with rotor/propeller thrust only, designed to fly trajectories with high similarity to those flown by lunar landers. The vehicle has the unique capability to transition into wing borne flight to simulate the cross-range, horizontal approaches of lunar landers. During transition to wing borne flight, the initial transition favors a traditional airplane configuration with the propellers in the front and smaller surfaces in the rear, allowing the vehicle to reach high speeds. However, after achieving wing borne flight, the vehicle can transition to wing borne flight in the opposite (canard) direction. During this mode of operation, the vehicle is controllable, and the propellers can be powered or unpowered. This NASA invention also has the capability to decelerate rapidly during the descent phase (also to simulate lunar lander trajectories). Such rapid deceleration will be required to reduce vehicle velocity in order to turn propellers back on without stalling the blades or catching the propeller vortex. The UAS also has the option of using variable pitch blades which can contribute to the overall controllability of the aircraft and reduce the likelihood of stalling the blades during the deceleration phase. In addition to testing EDL sensors and precision landing payloads, NASA’s innovative eVTOL UAS could be used in applications where fast, precise, and stealthy delivery of payloads to specific ground locations is required, including military applications. This concept of operations could entail deploying the UAS from a larger aircraft.

This suite of technologies includes a method, algorithms, and computer processing techniques to provide for image photometric correction and resolution enhancement at video rates (30 frames per second). This 3D (2D spatial and range) resolution enhancement uses the spatial and range information contained in each image frame, in conjunction with a sequence of overlapping or persistent images, to simultaneously enhance the spatial resolution and range and photometric accuracies. In other words, the technologies allows for generating an elevation (3D) map of a targeted area (e.g., terrain) with much enhanced resolution by blending consecutive camera image frames. The degree of image resolution enhancement increases with the number of acquired frames.

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.

This technology can be applied to most optical frequency domain reflectometry (OFDR) fiber optic strain sensing systems. It is particularly well suited to Armstrong's FOSS technology, which uses efficient algorithms to determine from strain data in real time a variety of critical parameters, including twist and other structural shape deformations, temperature, pressure, liquid level, and operational loads. How It Works This technology enables smart-sensing techniques that adjust parameters as needed in real time so that only the necessary amount of data is acquired—no more, no less. Traditional signal processing in fiber optic strain sensing systems is based on fast Fourier transform (FFT), which has two key limitations. First, FFT requires having analysis sections that are equal in length along the whole fiber. Second, if high resolution is required along one portion of the fiber, FFT processes the whole fiber at that resolution. Armstrong's adaptive spatial resolution innovation makes it possible to efficiently break up the length of the fiber into analysis sections that vary in length. It also allows the user to measure data from only a portion of the fiber. If high resolution is required along one section of fiber, only that portion is processed at high resolution, and the rest of the fiber can be processed at the lower resolution. Why It Is Better To quantify this innovation's advantages, this new adaptive method requires only a small fraction of the calculations needed to provide additional resolution compared to FFT (i.e., thousands versus millions of additional calculations). This innovation provides faster signal processing and precision measurement only where it is needed, saving time and resources. The technology also lends itself well to long-term bandwidth-limited monitoring systems that experience few variations but could be vulnerable as anomalies occur. More importantly, Armstrong's adaptive algorithm enhances safety, because it automatically adjusts the resolution of sensing based on real-time data. For example, when strain on a wing increases during flight, the software automatically increases the resolution on the strained part of the fiber. Similarly, as bridges and wind turbine blades undergo stress during big storms, this algorithm could automatically adjust the spatial resolution to collect more data and quickly identify potentially catastrophic failures. This innovation greatly improves the flexibility of fiber optic strain sensing systems, which provide valuable time and cost savings to a range of applications. For more information about the full portfolio of FOSS technologies, see DRC-TOPS-37 or visit https://technology-afrc.ndc.nasa.gov/featurestory/fiber-optic-sensing