Robust spectral analyzer for one-dimensional and multi-dimensional data analysis

Abstract

A method of analyzing a spectrum of one-dimensional or multi-dimensional signal X(t) requires a number of steps including deriving coefficients [AN(ω), BN(ω)] of an Lp-norm harmonic regression of tie signal with 0<p≦∞ and pγ2, squaring the coefficients, summing the squared coefficients, and scaling the summed, squared coefficients with a constant c to realize a periodogram of X(t) as LN(ω)=c{[AN(ω)]+[BN(ω)]2}. The method may include receiving the signal X(t), storing the received signal X(t), and outputting the periodogram LN(ω). The method may still further include scanning to maximize the periodogram LN(ω) by identifying its largest peak(s) and comparing the amplitude of the identified largest peak(s) with a threshold to determine if the largest peak(s) is(are) attributable to a presence of a periodic signal. The coefficients are preferable derived from a time series signal X(t), t=1, 2, . . . , N, but may include receiving a continuous-time signal and converting it to the time series signal.

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