Digital filtering for data compression in telemetry systems
Renick Bell · University of North Texas Digital Library (University of North Texas) · 1994
There are many obstacles to using data compression in a telemetry system. Non-linear quantization is often too lossy, and the data is too highly structured to make variable-length entropy codes practical. This paper describes a lossless telemetry data compression system that was built using digital FIR filters. The method of compression takes advantage of the fact that the optimal Nyquist sampling rate is rarely achievable due to two factors: (1) Sensor/transducers are not bandlimited to the frequencies of interest, and (2) Accurate, high-order analog filters are not available to perform effective band limiting and prevent aliasing. Real-time digital filtering can enhance the performance of a typical sampling system so that it approaches Nyquist sampling rates, effectively compressing the amount of data and reducing transmission bandwidth. The system that was built reduced the sampling rate of 14 high-frequency vibration channels by a factor of two, and reduced the bandwidth of the-data link from 1.8 Mbps to 1.28 Mbps. The entire circuit uses seven function-specific, digital-filter DSP`s operating in parallel (two 128-tap FIR filters can be implemented on each Motorola DSP56200), one EPROM and a Programmable Logic Device as the controller.