ALBERT

Description: A simple recursive solution for a class of fading memory tracking filters is presented. A fading memory filter provides estimates of filter states based on past measurements, similar to a traditional Kalman filter. Unlike a Kalman filter, an exponentially decaying weight is applied to older measurements, discounting their effect on present state estimates. It is shown that Kalman filters and fading memory filters are closely related solutions to a general least squares estimator problem. Closed form filter transfer functions are derived for a time invariant, steady state, fading memory filter. These can be applied in loop filter implementation of the Deep Space Network (DSN) Advanced Receiver carrier phase locked loop (PLL).

Description: An approach to the design of digital phase locked loops (DPLLs), using estimation theory concepts in the selection of a loop filter, is presented. The key concept is that the DPLL closed-loop transfer function is decomposed into an estimator and a predictor. The estimator provides recursive estimates of phase, frequency, and higher order derivatives, while the predictor compensates for the transport lag inherent in the loop. This decomposition results in a straightforward loop filter design procedure, enabling use of techniques from optimal and sub-optimal estimation theory. A design example for a particular choice of estimator is presented, followed by analysis of the associated bandwidth, gain margin, and steady state errors caused by unmodeled dynamics. This approach is under consideration for the design of the Deep Space Network (DSN) Advanced Receiver Carrier DPLL.

Description: Demonstration results are presented for a high dynamic GPS receiver. The receiver tested is a breadboard unit capable of tracking one simulated satellite signal in pseudorange and range rate. The receiver makes approximate maximum likelihood estimates of pseudorange and range rate each 20 ms, and tracks these observables using a third order filter with a time constant of 0.14 s. Carrier phase is not tracked, which eliminates the typical failure mode of loss of carrier lock associated with PLLs at high dynamics. The receiver tracks with pseudorange lag errors of under 0.06 m when subjected to simulated 50 g turns with 40 g/s peak jerk. Pseudorange errors due to receiver noise alone are approximately 0.6 m rms at a carrier power to noise spectral density ratio of 34 dB-Hz. The tracking threshold SNR is approximately 28 dB-Hz, which provides 12 dB margin relative to the 40 dB-Hz that occurs with minimum specified satellite signal strength, 3.5 dB system noise figure, and 0 dBi antenna gain.

Description: A Viterbi decoder, capable of decoding convolutional codes with constraint lengths up to 15, is under development for the Deep Space Network (DSN). The objective is to complete a prototype of this decoder by late 1990, and demonstrate its performance using the (15, 1/4) encoder in Galileo. The decoder is expected to provide 1 to 2 dB improvement in bit SNR, compared to the present (7, 1/2) code and existing Maximum Likelihood Convolutional Decoder (MCD). The decoder will be fully programmable for any code up to constraint length 15, and code rate 1/2 to 1/6. The decoder architecture and top-level design are described.

Description: The Galileo mission was originally designed to investigate Jupiter and its moons utilizing a high-rate, X-band (8415 MHz) communication downlink with a maximum rate of 134.4 kb/sec. However, following the failure of the high-gain antenna (HGA) to fully deploy, a completely new communication link design was established that is based on Galileo's S-band (2295 MHz), low-gain antenna (LGA). The new link relies on data compression, local and intercontinental arraying of antennas, a (14,1/4) convolutional code, a (255,M) variable-redundancy Reed-Solomon code, decoding feedback, and techniques to reprocess recorded data to greatly reduce data losses during signal acquisition. The combination of these techniques will enable return of significant science data from the mission.

Description: The Validation Demonstration establishes that the high dynamic Global Positioning System (GPS) receiver concept developed at JPL meets the dynamic tracking requirements for range instrumentation of missiles and drones. It was demonstrated that the receiver can track the pseudorange and pseudorange rate of vehicles with acceleration in excess of 100 g and jerk in excess of 100 g/s, dynamics ten times more severe than specified for conventional High Dynamic GPS receivers. These results and analytic extensions to a complete system configuration establish that all range instrumentation requirements can be met. The receiver can be implemented in the 100 cu in volume required by all missiles and drones, and is ideally suited for transdigitizer or translator applications.

Description: Over the years, NASA has supported unmanned space missions, beyond earth orbit, through a Deep Space Mission System (DSMS) that is developed and operated by the Jet Propulsion Laboratory (JPL) and subcontractors. The DSMS capabilities have been incrementally upgraded since its establishment in the late '50s and are delivered primarily through three Deep Space Communications Complexes (DSCC 's) near Goldstone, California, Madrid, Spain, and Canberra, Australia and from facilities at JPL. Traditionally, mission support (tracking, command, telemetry, etc) is assigned on an individual-mission basis, between each mission and a ground-based asset, independent of other missions. As NASA, and its international partners, move toward flying fullconstellations and precision formations, the DSMS is developing plans and technologies to provide the requisite support. The key activities under way are: (1) integrated communications architecture for Mars exploration, including relays on science orbiters and dedicated relay satellites to provide continuous coverage for orbiters, landers and rovers. JPL is developing an architecture, as well as protocols and equipment, required for the cost-effective operations of such an infrastructure. (2) Internet-type protocols that will allow for efficient operations across the deep-space distances, accounting for and accommodating the long round-trip-light-time. JPL is working with the CCSDS to convert these protocols to an international standard and will deploy such protocol, the CCSDS File Delivery Protocol (CFDP), on the Mars Reconnaissance Orbiter (MRO) and on the Deep Impact (01) missions. (3) Techniques to perform cross-navigation between spacecrafi that fly in a loose formation. Typical cases are cross-navigation between missions that approach Mars and missionsthat are at Mars, or the determination of a baseline for missions that fly in an earth-lead- lag configuration. (4) Techniques and devices that allow the precise metrology and controllability of tightformations for precision constellation missions. In this paper we discuss the four classes of constellatiodformation support with emphasis of DSMS current status (technology and implementation) and plans in the first three areas.

Description: The Consultative Committee for Space Data Standards (CCSDS) recommends that space communication links employ a concatenated, error-correcting, channel-coding system in which the inner code is a convolutional (7,1/2) code and the outer code is a (255,223) Reed-Solomon code. The traditional implementation is to perform the node synchronization for the Viterbi decoder and the frame synchronization for the Reed-Solomon decoder as separate, sequential operations. This article discusses a unified synchronization technique that is required for deep space missions that have data rates and signal-to-noise ratios (SNR's) that are extremely low. This technique combines frame synchronization in the bit and symbol domains and traditional accumulated-metric growth techniques to establish a joint frame and node synchronization. A variation on this technique is used for the Galileo spacecraft on its Jupiter-bound mission.

Description: In this paper we discuss the four classes of constellation/formation support with emphasis of DSMS current status (technology and implementation) and plans in each area.