Fully automatic telemetry data processor

Satellite Telemetry Automatic Reduction System /STARS 2/, a fully automatic computer-controlled telemetry data processor, maximizes data recovery, reduces turnaround time, increases flexibility, and improves operational efficiency. The system incorporates a CDC 3200 computer as its central element

DSN acquisition of Magellan high-rate telemetry data

The Magellan Project levied the stringent requirement of a 98 percent high-rate telemetry data capture rate on the Deep Space Network (DSN) during the Magellan Prime Mapping Mission. To meet this requirement, the DSN undertook extensive development of the DSN Telemetry System, as well as extensive DSN operation planning and test and training. In actuality, the DSN substantially exceeded the requirement by achieving a Prime Mapping Mission high-rate telemetry data capture rate of 99.14 percent. This article details the DSN telemetry system development, and DSN operations planning and test and training. In addition, the actual high-rate telemetry data outages are comprehensively presented and analyzed

The RSZ BASIC programming language manual

The RSZ BASIC interactive language is described. The RSZ BASIC interpreter is resident in the Telemetry Data Processor, a system dedicated to the processing and displaying of PCM telemetry data. A series of working examples teaches the fundamentals of RSZ BASIC and shows how to construct, edit, and manage storage of programs

Telemetry word forming unit

Telemetry data unit to form multibit words for use between demodulator and compute

Digital computer processing of PFM telemetry data

Error probability in digital computer processing of PFM telemetry dat

Telemetry synchronizer

A telemetry data synchronizer is reported for achieving phase lock and synchronization of an input signal having a pseudorandom sequence

Generalizing the first-difference correlated random walk for marine animal movement data

Animal telemetry data are often analysed with discrete time movement models assuming rotation in the movement. These models are defined with equidistant distant time steps. However, telemetry data from marine animals are observed irregularly. To account for irregular data, a time-irregularised first-difference correlated random walk model with drift is introduced. The model generalizes the commonly used first-difference correlated random walk with regular time steps by allowing irregular time steps, including a drift term, and by allowing different autocorrelation in the two coordinates. The model is applied to data from a ringed seal collected through the Argos satellite system, and is compared to related movement models through simulations. Accounting for irregular data in the movement model results in accurate parameter estimates and reconstruction of movement paths. Measured by distance, the introduced model can provide more accurate movement paths than the regular time counterpart. Extracting accurate movement paths from uncertain telemetry data is important for evaluating space use patterns for marine animals, which in turn is crucial for management. Further, handling irregular data directly in the movement model allows efficient simultaneous analysis of several animals