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NASA NTRS2008

Improved Airborne System for Sensing Wildfires

The Wildfire Airborne Sensing Program (WASP) is engaged in a continuing effort to develop an improved airborne instrumentation system for sensing wildfires. The system could also be used for other aerial-imaging applications, including mapping and military surveillance. Unlike prior airborne fire-detection instrumentation systems, the WASP system would not be based on custom-made multispectral line scanners and associated custom- made complex optomechanical servomechanisms, sensors, readout circuitry, and packaging. Instead, the WASP system would be based on commercial off-the-shelf (COTS) equipment that would include (1) three or four electronic cameras (one for each of three or four wavelength bands) instead of a multispectral line scanner; (2) all associated drive and readout electronics; (3) a camera-pointing gimbal; (4) an inertial measurement unit (IMU) and a Global Positioning System (GPS) receiver for measuring the position, velocity, and orientation of the aircraft; and (5) a data-acquisition subsystem. It would be necessary to custom-develop an integrated sensor optical-bench assembly, a sensor-management subsystem, and software. The use of mostly COTS equipment is intended to reduce development time and cost, relative to those of prior systems.

McKeown, Donald↗

NASA NTRS2008

Autonomous Flight Safety System - Phase III

The Autonomous Flight Safety System (AFSS) is a joint KSC and Wallops Flight Facility project that uses tracking and attitude data from onboard Global Positioning System (GPS) and inertial measurement unit (IMU) sensors and configurable rule-based algorithms to make flight termination decisions. AFSS objectives are to increase launch capabilities by permitting launches from locations without range safety infrastructure, reduce costs by eliminating some downrange tracking and communication assets, and reduce the reaction time for flight termination decisions.

Source record↗

NASA NTRS2009

GPS/MEMS IMU/Microprocessor Board for Navigation

A miniaturized instrumentation package comprising a (1) Global Positioning System (GPS) receiver, (2) an inertial measurement unit (IMU) consisting largely of surface-micromachined sensors of the microelectromechanical systems (MEMS) type, and (3) a microprocessor, all residing on a single circuit board, is part of the navigation system of a compact robotic spacecraft intended to be released from a larger spacecraft [e.g., the International Space Station (ISS)] for exterior visual inspection of the larger spacecraft. Variants of the package may also be useful in terrestrial collision-detection and -avoidance applications. The navigation solution obtained by integrating the IMU outputs is fed back to a correlator in the GPS receiver to aid in tracking GPS signals. The raw GPS and IMU data are blended in a Kalman filter to obtain an optimal navigation solution, which can be supplemented by range and velocity data obtained by use of (l) a stereoscopic pair of electronic cameras aboard the robotic spacecraft and/or (2) a laser dynamic range imager aboard the ISS. The novelty of the package lies mostly in those aspects of the design of the MEMS IMU that pertain to controlling mechanical resonances and stabilizing scale factors and biases.

Gender, Thomas K.↗

NASA NTRS2009

Alignment Jig for the Precise Measurement of THz Radiation

Javadi, Hamid H.↗

NASA NTRS2009

Mars Entry Atmospheric Data System Modelling and Algorithm Development

The Mars Entry Atmospheric Data System (MEADS) is being developed as part of the Mars Science Laboratory (MSL), Entry, Descent, and Landing Instrumentation (MEDLI) project. The MEADS project involves installing an array of seven pressure transducers linked to ports on the MSL forebody to record the surface pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the total pressure, dynamic pressure, Mach number, angle of attack, and angle of sideslip. Secondary objectives are to estimate atmospheric winds by coupling the pressure measurements with the on-board Inertial Measurement Unit (IMU) data. This paper provides details of the algorithm development, MEADS system performance based on calibration, and uncertainty analysis for the aerodynamic and atmospheric quantities of interest. The work presented here is part of the MEDLI performance pre-flight validation and will culminate with processing flight data after Mars entry in 2012.

Karlgaard, Christopher D.↗

NASA NTRS2009

Apollo 13 Guidance, Navigation, and Control Challenges

Combustion and rupture of a liquid oxygen tank during the Apollo 13 mission provides lessons and insights for future spacecraft designers and operations personnel who may never, during their careers, have participated in saving a vehicle and crew during a spacecraft emergency. Guidance, Navigation, and Control (GNC) challenges were the reestablishment of attitude control after the oxygen tank incident, re-establishment of a free return trajectory, resolution of a ground tracking conflict between the LM and the Saturn V S-IVB stage, Inertial Measurement Unit (IMU) alignments, maneuvering to burn attitudes, attitude control during burns, and performing manual GNC tasks with most vehicle systems powered down. Debris illuminated by the Sun and gaseous venting from the Service Module (SM) complicated crew attempts to identify stars and prevented execution of nominal IMU alignment procedures. Sightings on the Sun, Moon, and Earth were used instead. Near continuous communications with Mission Control enabled the crew to quickly perform time critical procedures. Overcoming these challenges required the modification of existing contingency procedures.

Goodman, John L.↗

NASA NTRS2009

Port-O-Sim Object Simulation Application

Port-O-Sim is a software application that supports engineering modeling and simulation of launch-range systems and subsystems, as well as the vehicles that operate on them. It is flexible, distributed, object-oriented, and realtime. A scripting language is used to configure an array of simulation objects and link them together. The script is contained in a text file, but executed and controlled using a graphical user interface. A set of modules is defined, each with input variables, output variables, and settings. These engineering models can be either linked to each other or run as standalone. The settings can be modified during execution. Since 2001, this application has been used for pre-mission failure mode training for many Range Safety Scenarios. It contains range asset link analysis, develops look-angle data, supports sky-screen site selection, drives GPS (Global Positioning System) and IMU (Inertial Measurement Unit) simulators, and can support conceptual design efforts for multiple flight programs with its capacity for rapid six-degrees-of-freedom model development. Due to the assembly of various object types into one application, the application is applicable across a wide variety of launch range problem domains.

Lanzi, Raymond J.↗

NASA NTRS2010

A Comparison Between Orion Automated and Space Shuttle Rendezvous Techniques

The Orion spacecraft will replace the space shuttle and will be the first human spacecraft since the Apollo program to leave low earth orbit. This vehicle will serve as the cornerstone of a complete space transportation system with a myriad of mission requirements necessitating rendezvous to multiple vehicles in earth orbit, around the moon and eventually beyond . These goals will require a complex and robust vehicle that is, significantly different from both the space shuttle and the command module of the Apollo program. Historically, orbit operations have been accomplished with heavy reliance on ground support and manual crew reconfiguration and monitoring. One major difference with Orion is that automation will be incorporated as a key element of the man-vehicle system. The automated system will consist of software devoted to transitioning between events based on a master timeline. This effectively adds a layer of high level sequencing that moves control of the vehicle from one phase to the next. This type of automated control is not entirely new to spacecraft since the shuttle uses a version of this during ascent and entry operations. During shuttle orbit operations however many of the software modes and hardware switches must be manually configured through the use of printed procedures and instructions voiced from the ground. The goal of the automation scheme on Orion is to extend high level automation to all flight phases. The move towards automation represents a large shift from current space shuttle operations, and so these new systems will be adopted gradually via various safeguards. These include features such as authority-to-proceed, manual down modes, and functional inhibits. This paper describes the contrast between the manual and ground approach of the space shuttle and the proposed automation of the Orion vehicle. I will introduce typical orbit operations that are common to all rendezvous missions and go on to describe the current Orion automation architecture and contrast it with shuttle rendezvous techniques and circumstances. The shuttle rendezvous profile is timed to take approximately 3 days from orbit insertion to docking at the International Space Station (ISS). This process can be divided into 3 phases: far-field, mid-field and proximity operations. The far-field stage is characterized as the most quiescent phase. The spacecraft is usually too far to navigate using relative sensors and uses the Inertial Measurement Units (IMU s) to numerically solve for its position. The maneuvers are infrequent, roughly twice per day, and are larger than other burns in the profile. The shuttle uses this opportunity to take extensive ground based radar updates and keep high fidelity orbit states on the ground. This state is then periodically uplinked to the shuttle computers. The targeting solutions for burn maneuvers are also computed on the ground and uplinked. During the burn the crew is responsible for setting the shuttle attitude and configuring the propulsion system for ignition. Again this entire process is manually driven by both crew and ground activity. The only automatic processes that occur are associated with the real-time execution of the burn. The Orion automated functionality will seek to relieve the workload of both the crew and ground during this phase

Ruiz, Jose O,↗

NASA NTRS2010

Configurable Multi-Purpose Processor

Advancements in technology have allowed the miniaturization of systems used in aerospace vehicles. This technology is driven by the need for next-generation systems that provide reliable, responsive, and cost-effective range operations while providing increased capabilities such as simultaneous mission support, increased launch trajectories, improved launch, and landing opportunities, etc. Leveraging the newest technologies, the command and telemetry processor (CTP) concept provides for a compact, flexible, and integrated solution for flight command and telemetry systems and range systems. The CTP is a relatively small circuit board that serves as a processing platform for high dynamic, high vibration environments. The CTP can be reconfigured and reprogrammed, allowing it to be adapted for many different applications. The design is centered around a configurable field-programmable gate array (FPGA) device that contains numerous logic cells that can be used to implement traditional integrated circuits. The FPGA contains two PowerPC processors running the Vx-Works real-time operating system and are used to execute software programs specific to each application. The CTP was designed and developed specifically to provide telemetry functions; namely, the command processing, telemetry processing, and GPS metric tracking of a flight vehicle. However, it can be used as a general-purpose processor board to perform numerous functions implemented in either hardware or software using the FPGA s processors and/or logic cells. Functionally, the CTP was designed for range safety applications where it would ultimately become part of a vehicle s flight termination system. Consequently, the major functions of the CTP are to perform the forward link command processing, GPS metric tracking, return link telemetry data processing, error detection and correction, data encryption/ decryption, and initiate flight termination action commands. Also, the CTP had to be designed to survive and operate in a launch environment. Additionally, the CTP was designed to interface with the WFF (Wallops Flight Facility) custom-designed transceiver board which is used in the Low Cost TDRSS Transceiver (LCT2) also developed by WFF. The LCT2 s transceiver board demodulates commands received from the ground via the forward link and sends them to the CTP, where they are processed. The CTP inputs and processes data from the inertial measurement unit (IMU) and the GPS receiver board, generates status data, and then sends the data to the transceiver board where it is modulated and sent to the ground via the return link. Overall, the CTP has combined processing with the ability to interface to a GPS receiver, an IMU, and a pulse code modulation (PCM) communication link, while providing the capability to support common interfaces including Ethernet and serial interfaces boarding a relatively small-sized, lightweight package.

Valencia, J. Emilio↗

NASA NTRS2010

Demonstration of an Aerocapture GN and C System Through Hardware-in-the-Loop Simulations

Aerocapture is an orbit insertion maneuver in which a spacecraft flies through a planetary atmosphere one time using drag force to decelerate and effect a hyperbolic to elliptical orbit change. Aerocapture employs a feedback Guidance, Navigation, and Control (GN&C) system to deliver the spacecraft into a precise postatmospheric orbit despite the uncertainties inherent in planetary atmosphere knowledge, entry targeting and aerodynamic predictions. Only small amounts of propellant are required for attitude control and orbit adjustments, thereby providing mass savings of hundreds to thousands of kilograms over conventional all-propulsive techniques. The Analytic Predictor Corrector (APC) guidance algorithm has been developed to steer the vehicle through the aerocapture maneuver using bank angle control. Through funding provided by NASA's In-Space Propulsion Technology Program, the operation of an aerocapture GN&C system has been demonstrated in high-fidelity simulations that include real-time hardware in the loop, thus increasing the Technology Readiness Level (TRL) of aerocapture GN&C. First, a non-real-time (NRT), 6-DOF trajectory simulation was developed for the aerocapture trajectory. The simulation included vehicle dynamics, gravity model, atmosphere model, aerodynamics model, inertial measurement unit (IMU) model, attitude control thruster torque models, and GN&C algorithms (including the APC aerocapture guidance). The simulation used the vehicle and mission parameters from the ST-9 mission. A 2000 case Monte Carlo simulation was performed and results show an aerocapture success rate of greater than 99.7%, greater than 95% of total delta-V required for orbit insertion is provided by aerodynamic drag, and post-aerocapture orbit plane wedge angle error is less than 0.5 deg (3-sigma). Then a real-time (RT), 6-DOF simulation for the aerocapture trajectory was developed which demonstrated the guidance software executing on a flight-like computer, interfacing with a simulated IMU and simulated thrusters, with vehicle dynamics provided by an external simulator. Five cases from the NRT simulations were run in the RT simulation environment. The results compare well to those of the NRT simulation thus verifying the RT simulation configuration. The results of the above described simulations show the aerocapture maneuver using the APC algorithm can be accomplished reliably and the algorithm is now at TRL-6. Flight validation is the next step for aerocapture technology development.

Masciarelli, James↗

NASA NTRS2011

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

Busnardo, David M.↗

NASA NTRS2011

Assessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module

Orion Crew Module (CM) touchdown detection is critical to activating the post-landing sequence that safe?s the Reaction Control Jets (RCS), ensures that the vehicle remains upright, and establishes communication with recovery forces. In order to accommodate safe landing of an unmanned vehicle or incapacitated crew, an onboard automated detection system is required. An Orion-specific touchdown detection algorithm was developed and evaluated to differentiate landing events from in-flight events. The proposed method will be used to initiate post-landing cutting of the parachute riser lines, to prevent CM rollover, and to terminate RCS jet firing prior to submersion. The RCS jets continue to fire until touchdown to maintain proper CM orientation with respect to the flight path and to limit impact loads, but have potentially hazardous consequences if submerged while firing. The time available after impact to cut risers and initiate the CM Up-righting System (CMUS) is measured in minutes, whereas the time from touchdown to RCS jet submersion is a function of descent velocity, sea state conditions, and is often less than one second. Evaluation of the detection algorithms was performed for in-flight events (e.g. descent under chutes) using hi-fidelity rigid body analyses in the Decelerator Systems Simulation (DSS), whereas water impacts were simulated using a rigid finite element model of the Orion CM in LS-DYNA. Two touchdown detection algorithms were evaluated with various thresholds: Acceleration magnitude spike detection, and Accumulated velocity changed (over a given time window) spike detection. Data for both detection methods is acquired from an onboard Inertial Measurement Unit (IMU) sensor. The detection algorithms were tested with analytically generated in-flight and landing IMU data simulations. The acceleration spike detection proved to be faster while maintaining desired safety margin. Time to RCS jet submersion was predicted analytically across a series of simulated Orion landing conditions. This paper details the touchdown detection method chosen and the analysis used to support the decision.

Gay, Robert S.↗

NASA NTRS2011

Functional Data Analysis of Spaceflight-Induced Changes in Coordination and Phase in Head Pitch Acceleration During Treadmill Walking

Astronauts returning from spaceflight experience neurovestibular disturbances during head movements and attempt to mitigate them by limiting head motion. Analyses to date of the head movements made during walking have concentrated on amplitude and variability measures extracted from ensemble averages of individual gait cycles. Phase shifts within each gait cycle can be determined by functional data analysis through the computation of time-warping functions. Large, localized variations in the timing of peaks in head kinematics may indicate changes in coordination. The purpose of this study was to determine timing changes in head pitch acceleration of astronauts during treadmill walking before and after flight. Six astronauts (5M/1F; age = 43.5+/-6.4yr) participated in the study. Subjects walked at 1.8 m/sec (4 mph) on a motorized treadmill while reading optotypes displayed on a computer screen 4 m in front of their eyes. Three-dimensional motion of the subject s head was recorded with an Inertial Measurement Unit (IMU) device. Data were recorded twice before flight and four times after landing. The head pitch acceleration was calculated by taking the time derivative of the pitch velocity data from the IMU. Data for each session with each subject were time-normalized into gait cycles, then registered to align significant features and create a mean curve. The mean curves of each postflight session for each subject were re-registered based on their preflight mean curve to create time-warping functions. The root mean squares (RMS) of these warping functions were calculated to assess the deviation of head pitch acceleration mean curves in each postflight session from the preflight mean curve. After landing, most crewmembers exhibited localized shifts within their head pitch acceleration regimes, with the greatest deviations in RMS occurring on landing day or 1 day after landing. These results show that the alteration of head pitch coordination due to spaceflight may be assessed using an analysis of time-warping functions.

Miller, Christopher↗

NASA NTRS2011

Measurement of CPAS Main Parachute Rate of Descent

The Crew Exploration Vehicle Parachute Assembly System (CPAS) is being designed to land the Orion Crew Module (CM) at a safe rate of descent at splashdown. Flight test performance must be measured to a high degree of accuracy to ensure this requirement is met with the most efficient design possible. Although the design includes three CPAS Main parachutes, the requirement is that the system must not exceed 33 ft/s under two Main parachutes, should one of the Main parachutes fail. Therefore, several tests were conducted with clusters of two Mains. All of the steady-state rate of descent data are normalized to standard sea level conditions and checked against the limit. As the Orion design gains weight, the system is approaching this limit to within measurement precision. Parachute "breathing," cluster interactions, and atmospheric anomalies can cause the rate of descent to vary widely and lead to challenges in characterizing parachute terminal performance. An early test had contradictory rate of descent results from optical trajectory and Differential Global Positioning Systems (DGPS). A thorough analysis of the data sources and error propagation was conducted to determine the uncertainty in the trajectory. It was discovered that the Time Space Position Information (TSPI) from the optical tracking provided accurate position data. However, the velocity from TPSI must be computed via numerical differentiation, which is prone to large error. DGPS obtains position through pseudo-range calculations from multiple satellites and velocity through Doppler shift of the carrier frequency. Because the velocity from DGPS is a direct measurement, it is more accurate than TSPI velocity. To remedy the situation, a commercial off-the-shelf product that combines GPS and an Inertial Measurement Unit (IMU) was purchased to significantly improve rate of descent measurements. This had the added benefit of solving GPS dropouts during aircraft extraction. Statistical probability distributions for CPAS Main parachute rate of descent and drag coefficient were computed and plotted. Using test data, a terminal rate of descent at splashdown can be estimated as a function of canopy loading.

Ray, Eric S.↗

NASA NTRS2011

Miniaturized Airborne Imaging Central Server System

In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and data organization, fast aerial imaging applications, including the real time LWIR image mosaic for Google Earth, have been realized for NASA fs LWIR QWIP instrument. MAICSS is a significant improvement and miniaturization of current multisensor technologies. Structurally, it has a complete modular and solid-state design. Without rotating hard drives and other moving parts, it is operational at high altitudes and survivable in high-vibration environments. It is assembled from a suite of miniaturized, precision-machined, standardized, and stackable interchangeable embedded instrument modules. These stackable modules can be bolted together with the interconnection wires inside for the maximal simplicity and portability. Multiple modules are electronically interconnected as stacked. Alternatively, these dedicated modules can be flexibly distributed to fit the space constraints of a flying vehicle. As a flexibly configurable system, MAICSS can be tailored to interface a variety of multisensor packages. For example, with a 1,024x1,024 pixel LWIR and a 8,984x6,732 pixel EO payload, the complete MAICSS volume is approximately 7x9x11 in. (=18x23x28 cm), with a weight of 25 lb (=11.4 kg).

Sun, Xiuhong↗

NASA NTRS2006

IMU/GPS System Provides Position and Attitude Data

A special navigation system is being developed to provide high-quality information on the position and attitude of a moving platform (an aircraft or spacecraft), for use in pointing and stabilization of a hyperspectral remote-sensing system carried aboard the platform. The system also serves to enable synchronization and interpretation of readouts of all onboard sensors. The heart of the system is a commercially available unit, small enough to be held in one hand, that contains an integral combination of an inertial measurement unit (IMU) of the microelectromechanical systems (MEMS) type, Global Positioning System (GPS) receivers, a differential GPS subsystem, and ancillary data-processing subsystems. The system utilizes GPS carrier-phase measurements to generate time data plus highly accurate and continuous data on the position, attitude, rotation, and acceleration of the platform. Relative to prior navigation systems based on IMU and GPS subsystems, this system is smaller, is less expensive, and performs better. Optionally, the system can easily be connected to a laptop computer for demonstration and evaluation. In addition to airborne and spaceborne remote-sensing applications, there are numerous potential terrestrial sensing, measurement, and navigation applications in diverse endeavors that include forestry, environmental monitoring, agriculture, mining, and robotics.

Lin, Ching Fang↗

NASA NTRS2005

Path Following with Slip Compensation for a Mars Rover

A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation. The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path.

Helmick, Daniel↗

NASA NTRS2011

Kalman Orbit Optimized Loop Tracking

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Young, Lawrence E.↗