Abstract
A low-power analog sensor front-end is described that reduces the energy required to extract environmental sensing spectral features without using Fast Fouriér Transform (FFT) or wavelet transforms. An Analog Harmonic Transform (AHT) allows selection of only the features needed by the back-end, in contrast to the FFT, where all coefficients must be calculated simultaneously. We also show that the FFT coefficients can be easily calculated from the AHT results by a simple back-substitution. The scheme is tailored for low-power, parallel analog implementation in an integrated circuit (IC). Two different applications are tested with an ideal front-end model and compared to existing studies with the same data sets. Results from the military vehicle classification and identification of machine-bearing fault applications shows that the front-end suits a wide range of harmonic signal sources. Analog-related errors are modeled to evaluate the feasibility of and to set design parameters for an IC implementation to maintain good system-level performance. Design of a preliminary transistor-level integrator circuit in a 0.13 μm complementary metal-oxide-silicon (CMOS) integrated circuit process showed the ability to use online self-calibration to reduce fabrication errors to a sufficiently low level. Estimated power dissipation is about three orders of magnitude less than similar vehicle classification systems that use commercially available FFT spectral extraction.
Highlights
IntroductionSensor systems typically operate by transducing some physical quantity (e.g., pressure, velocity, flux) into the electrical domain and applying signal conditioning
Sensor systems typically operate by transducing some physical quantity into the electrical domain and applying signal conditioning
Several low power monitoring schemes use statistical parameters as features, such as signal mean, standard deviation and peak. These parameters are obtained directly from the time domain signal to generate signal features for identification [10], but they are limited in the amount of classification information they contain compared with spectral features
Summary
Sensor systems typically operate by transducing some physical quantity (e.g., pressure, velocity, flux) into the electrical domain and applying signal conditioning. Hardware-oriented architectures and designs utilizing CS concepts have recently been proposed in [12,13,14,15,16] These techniques are targeted at sampling high-frequency communication signals over large bandwidths with the goal of reducing the ADC rate. An Analog Harmonic Transform (AHT) is developed, which extracts feature vectors directly from acquired analog signals These features may be used for signal classification or other back-end processing, either directly or transformed into equivalent Fouriér series coefficients by a simple back-substitution. This transform replaces the typical ADC/FFT with a multi-channel analog projection to extract a signal’s spectral features.
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