In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to be used in the spectrum sensing phase of a Cognitive Radio (CR) communication paradigm for Vehicular Dynamic Spectrum Access (VDSA). It is used to smooth the acquired spectra, which constitute the input for a spectrum sensing algorithm. The sensing phase is necessary, since VDSA is based on an opportunistic approach to the spectral resource, and the opportunities are represented by the user-free spectrum zones, to be detected through the sensing phase. Each filter typology presents peculiarities in terms of its computational cost, de-noising ability and signal shape reconstruction. The SG filtering properties are compared with those of the linear Moving Average (MA) filter, widely used in the CR framework. Important improvements are proposed.
In this paper, a comparison analysis of three different algorithms for the estimation of sine signal parameters in two-channel common frequency situations is presented. The relevance of this situation is clearly understood in multiple applications where the algorithms have been applied. They include impedance measurements, eddy currents testing, laser anemometry and radio receiver testing for example. The three algorithms belong to different categories because they are based on different approaches. The ellipse fit algorithm is a parametric fit based on the XY plot of the samples of both signals. The seven parameter sine fit algorithm is a least-squares algorithm based on the time domain fitting of a single tone sinewave model to the acquired samples. The spectral sinc fit performs a fitting in the frequency domain of the exact model of an acquired sinewave on the acquired spectrum. Multiple simulation situations and real measurements are included in the comparison to demonstrate the weaknesses and strong points of each algorithm.