We develop a software system to automatically identify aircraft in thermal camera imagery to assist with uplink laser safety for deep space optical communications. Ground terminals often transmit a high-powered laser for use as a beacon to assist spacecraft pointing. The wavelengths for these beacons are not eye safe for humans. Previous missions have used spotters and transponder-based aircraft detection (TBAD) as a warning system. However not all aircraft (e.g., low-flying planes, hang gliders) have transponders. For this reason, we take an image-based approach, utilizing data from multiple thermal cameras aligned with the telescope, for detecting lowflying aircraft as part of a multi-tiered system. We use a Kalman filter-based tracking software, which is capable of detecting and tracking aircraft within 20 km of the ground terminal. At these ranges, smaller aircraft are only 1-2 pixels in extent, and any system sensitive enough to detect and track all possible aircraft will also detect and track non-aircraft such as insects and birds. We develop traditional machine learning and neural network classifiers to separate aircraft from non-aircraft, using key distinguishing features based on track statistics. In addition, we develop convolutional and recurrent neural network models that incorporate the time-series history of the tracks. Since we cannot tolerate missed aircraft, we select a decision threshold that yields a true positive rate of 1 (all aircraft are identified), and compare performance of a variety of machine learning classifiers. We demonstrate use in the field, where we correctly identify all aircraft, with a false positive rate around 50% when classification is made using only the initial 45 frames of a track and a false positive rate less than 20% when full system tracks are used.
The Deep Space Optical Communication (DSOC) project will demonstrate free-space optical communication at almost 3 AU, or 3 orders of magnitude further than any previous attempt. DSOC will utilize the 5m Palomar Hale Telescope to receive the downlink signal, which will couple the downlink light onto an optical table and into a superconducting nanowire single photon detector (SNSPD). The output of the SNSPD is digitized by the Ground Laser Receiver Signal Processing Assembly (GSPA) using a high throughput streaming time to digital converter (TDC). The GSPA is a scalable FPGA-based receiver which demodulates and decodes the DSOC downlink signal through novel signal processing algorithms implemented on Xilinx UltraScale+ FPGAs, as well as Python-based software monitor and control routines. Exploiting the unique TDC-based architecture, the GSPA supports over four orders of magnitude of downlink data rates across multiple orders of magnitude of signal and background powers. In this paper we present an overview of the hardware, firmware and software architectures to implement this system, as well as performance analysis for links ranging from near-Earth to 2.8 AU.
The Optical Communications Telescope Laboratory (OCTL) located on Table Mountain near Wrightwood, CA served as
an alternate ground terminal to the Lunar Laser Communications Demonstration (LLCD), the first free-space laser
communication demonstration from lunar distances. The Lunar Lasercom OCTL Terminal (LLOT) Project utilized the
existing 1m diameter OCTL telescope by retrofitting: (i) a multi-beam 1568 nm laser beacon transmitter; (ii) a tungsten
silicide (WSi) superconducting nanowire single photon detector (SNSPD) receiver for 1550 nm downlink; (iii) a
telescope control system with the functionality required for laser communication operations; and (iv) a secure network
connection to the Lunar Lasercom Operations Center (LLOC) located at the Lincoln Laboratory, Massachusetts Institute
of Technology (LL-MIT). The laser beacon transmitted from Table Mountain was acquired by the Lunar Lasercom
Space Terminal (LLST) on-board the Lunar Atmospheric Dust Environment Explorer (LADEE) spacecraft and a 1550
nm downlink at 39 and 78 Mb/s was returned to LLOT. Link operations were coordinated by LLOC. During October
and November of 2013, twenty successful links were accomplished under diverse conditions. In this paper, a brief
system level description of LLOT along with the concept of operations and selected results are presented.
KEYWORDS: Sensors, Receivers, Signal processing, Signal detection, Statistical analysis, Error analysis, Clocks, Detection and tracking algorithms, Data acquisition, Monte Carlo methods
The Lunar Laser Communications Demonstration Project undertaken by MIT Lincoln Laboratory and NASA’s Goddard
Space Flight Center will demonstrate high-rate laser communications from lunar orbit to the Earth. NASA’s Jet Propulsion
Laboratory is developing a backup ground station supporting a data rate of 39 Mbps that is based on a non-real-time
software post-processing receiver architecture. This approach entails processing sample-rate-limited data without feedback
in the presence high uncertainty in downlink clock characteristics under low signal flux conditions. In this paper we present
a receiver concept that addresses these challenges with descriptions of the photodetector assembly, sample acquisition and
recording platform, and signal processing approach. End-to-end coded simulation and laboratory data analysis results are
presented that validate the receiver conceptual design.
In this work, we study the performance of structured Low-Density Parity-Check (LDPC) Codes together with
bandwidth efficient modulations. We consider protograph-based LDPC codes that facilitate high-speed hardware
implementations and have minimum distances that grow linearly with block sizes. We cover various higherorder
modulations such as 8-PSK, 16-APSK, and 16-QAM. During demodulation, a demapper transforms the
received in-phase and quadrature samples into reliability information that feeds the binary LDPC decoder. We
will compare various low-complexity demappers and provide simulation results for assorted coded-modulation
combinations on the additive white Gaussian noise and independent Rayleigh fading channels.
We present a decoding architecture for high-speed free-space laser communications. This system will be used by NASA's Mars Laser Communication Demonstration (MLCD) project, the first use of high-speed laser communication from deep space. The Error Correction Code (ECC) and modulation techniques for this project have been motivated by an analysis of capacity, and existing designs have been shown to operate within 0.9 dB of the Shannon limit on the nominal operating point. In this paper, we give the algorithmic description and FPGA implementation details that led to the development of a 50 Mbps hardware decoder.
We present the DEVise (data exploration via visualization environment) toolkit designed for visual exploration of stream data. Data of this type are collected continuously from sources such as remote sensors, program traces, and the stock market. A typical application involves looking for correlations, which may not be precisely defined, by experimenting with graphical representations. This includes selectively comparing data from multiple sources, selective viewing by zooming and scrolling at various resolutions, and querying the underlying data from the graphics. DEVise is designed to provide greater support than packages such as AVS or Khoros for this type of application. First, by abandoning the network flow model of AVS and Khoros in favor of a database query model, we are able to incorporate many performance improvements for visualizing large amounts of data. To our knowledge, this is the first attempt to eliminate data size limitations in a visualization package. Second, by structuring the stand-alone graphics module of most existing tools into user accessible components, users can quickly create, destroy, or interconnect the components to generate new visualizations. This flexibility greatly increases the ease with which users can browse their data. Finally, through limited programming, users can query the underlying data through the graphical representation for more information about the records used to generate the graphical representation.
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