Reconstructing Aliased Frequency Spectra by Using Multiple Sample Rates

Abstract

A novel algorithm is presented that can resolve frequency ambiguity that arises from sampling a set of signals spanning more than a single Nyquist zone. The method uses two samplers, each sampling the same input signal with different (non-integer multiple) sampling rates. The algorithm is able to resolve frequency ambiguity and reconstruct signals with an orthogonal frequency basis spanning multiple Nyquist zones, provided that the aggregate information-bearing bandwidth of the signals is less than half the cumulative data converter sampling rates. This manuscript describes the theoretical background for the algorithm and validates it through measurements performed on a test-board comprising of two 10 bit analog-to-digital converters clocked at two different (non-integer multiple) sample rates. Measurements show that even in the presence of aliasing, an orthogonal signal spanning multiple Nyquist zones can be fully reconstructed.