Thesis - Open Access
Master of Science (MS)
In telemetry systems, the limited power available from the RF transmitter imposes a constraint on the data transmission rate. For example, a spacecraft’s ability to communicate with a ground receiving station decreases with the square of the distance, and electrical power to operate the system increases with the data transmission rate. To solve this problem, considerable attention has been devoted toward improving the efficiency of telemetry systems by selecting advantageous coding, modulation and reconstruction techniques. One technique which is used to achieve this goal is to design a telemetry system which transmits only the significant information contained in the source data instead of transmitting all of the data so that the system capacity is maximized while the power requirements and size of the system is minimized. This technique is called data compression. Data compression reduces the bandwidth needed to transmit a given amount of information in a given time or it can reduce the time needed to transmit a given amount of information in a given bandwidth. While basic data compression techniques have been applied for many years in the off-line processing of data and by human analysts in seeking significant changes in data, their application to on-line service and particularly to space vehicles has been quite recent. Such compression must be accomplished without sacrificing the information requirements of the user. The performance enhancement of a basic data acquisition system by incorporation of data compression can be manifested in a variety of ways, depending on the manner in which the data compressor is utilized in the system and the performance desired. As shown in Figure 1-1, the engineer had the option of incorporating the data compression into either the transmitter or the receiver portions of the system. Four basic categories of data handling come under this definition: parameter extraction, adaptive sampling, redundancy reduction and coding. Figure 1-2 shows a schematic classification of data compression techniques by category.
Library of Congress Subject Headings
Number of Pages
South Dakota State University
Chung, Seon J., "An Adaptive Redundancy Reduction Technique" (1970). Electronic Theses and Dissertations. 3769.