Abstract
Adaptive sampling is a signal processing technique used in various aerospace applications. Many adaptive algorithms used for instrumentation and telemetry systems process the signal in the frequency domain, which leads to high computational cost and power. ASA-m solves this problem by performing all operations in the time domain. It estimated the subsequent sampling frequency to collect meaningful information based on mean velocity prediction. This novel algorithm is implemented on the Spartan 3E FPGA board to study the device power and hardware utilization for real-time vibration signal datasets. The significant recovery of data with a lesser number of samples and lower hardware utilization for the state of art algorithm ASA-m is brought out in this paper.
Published Version
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